From 79c7f2dc1143bbc15793bd87bd82064fa6cd692b Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Sat, 17 Jun 2023 16:37:06 -0400 Subject: [PATCH 01/28] [minor] draw in measure --- torchquantum/measurement.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/torchquantum/measurement.py b/torchquantum/measurement.py index 1fa8cf20..3a3722f5 100644 --- a/torchquantum/measurement.py +++ b/torchquantum/measurement.py @@ -12,6 +12,7 @@ from torchquantum.functional import mat_dict from torchquantum.operators import op_name_dict from copy import deepcopy +import matplotlib.pyplot as plt __all__ = [ "find_observable_groups", @@ -32,7 +33,7 @@ def gen_bitstrings(n_wires): return ["{:0{}b}".format(k, n_wires) for k in range(2**n_wires)] -def measure(qdev, n_shots=1024): +def measure(qdev, n_shots=1024, draw_id=None): """Measure the target state and obtain classical bitstream distribution Args: q_state: input tq.QuantumDevice @@ -58,12 +59,12 @@ def measure(qdev, n_shots=1024): distri = OrderedDict(sorted(distri.items())) distri_all.append(distri) - # if draw_id is not None: - # plt.bar(distri_all[draw_id].keys(), distri_all[draw_id].values()) - # plt.xticks(rotation="vertical") - # plt.xlabel("bitstring [qubit0, qubit1, ..., qubitN]") - # plt.title("distribution of measured bitstrings") - # plt.show() + if draw_id is not None: + plt.bar(distri_all[draw_id].keys(), distri_all[draw_id].values()) + plt.xticks(rotation="vertical") + plt.xlabel("bitstring [qubit0, qubit1, ..., qubitN]") + plt.title("distribution of measured bitstrings") + plt.show() return distri_all From baf4b33177f51ad33095a21fe6f2a376ed07d184 Mon Sep 17 00:00:00 2001 From: Jinglei Cheng Date: Sun, 18 Jun 2023 10:42:51 -0400 Subject: [PATCH 02/28] Tutorials for ISCA 2023, initial version --- torchquantum/pulse/ISCA_tutorial_pulse.ipynb | 111 ++ torchquantum/pulse/MESolver_example.ipynb | 293 ++++ torchquantum/pulse/SESolver_example.ipynb | 443 ++++++ .../pulse/Two_qubit_simple_example.ipynb | 234 +++ torchquantum/pulse/__init__.py | 4 + torchquantum/pulse/hardware/__init__.py | 1 + torchquantum/pulse/hardware/hardware.py | 11 + torchquantum/pulse/mesolve/__init__.py | 1 + torchquantum/pulse/mesolve/mesolve.py | 67 + torchquantum/pulse/sec2_pulse.ipynb | 1270 +++++++++++++++++ torchquantum/pulse/sesolve/__init__.py | 1 + torchquantum/pulse/sesolve/sesolve.py | 52 + torchquantum/pulse/single_qubit_demo.py | 27 + torchquantum/pulse/solver.py | 18 + torchquantum/pulse/templates/draft.py | 32 + torchquantum/pulse/templates/pulse.py | 145 ++ torchquantum/pulse/templates/pulse_utils.py | 228 +++ .../pulse/templates/simplest_draft.py | 70 + torchquantum/pulse/utils.py | 97 ++ 19 files changed, 3105 insertions(+) create mode 100644 torchquantum/pulse/ISCA_tutorial_pulse.ipynb create mode 100644 torchquantum/pulse/MESolver_example.ipynb create mode 100644 torchquantum/pulse/SESolver_example.ipynb create mode 100644 torchquantum/pulse/Two_qubit_simple_example.ipynb create mode 100644 torchquantum/pulse/__init__.py create mode 100644 torchquantum/pulse/hardware/__init__.py create mode 100644 torchquantum/pulse/hardware/hardware.py create mode 100644 torchquantum/pulse/mesolve/__init__.py create mode 100644 torchquantum/pulse/mesolve/mesolve.py create mode 100644 torchquantum/pulse/sec2_pulse.ipynb create mode 100644 torchquantum/pulse/sesolve/__init__.py create mode 100644 torchquantum/pulse/sesolve/sesolve.py create mode 100644 torchquantum/pulse/single_qubit_demo.py create mode 100644 torchquantum/pulse/solver.py create mode 100644 torchquantum/pulse/templates/draft.py create mode 100644 torchquantum/pulse/templates/pulse.py create mode 100644 torchquantum/pulse/templates/pulse_utils.py create mode 100644 torchquantum/pulse/templates/simplest_draft.py create mode 100644 torchquantum/pulse/utils.py diff --git a/torchquantum/pulse/ISCA_tutorial_pulse.ipynb b/torchquantum/pulse/ISCA_tutorial_pulse.ipynb new file mode 100644 index 00000000..b0e619e6 --- /dev/null +++ b/torchquantum/pulse/ISCA_tutorial_pulse.ipynb @@ -0,0 +1,111 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a7f89f62", + "metadata": {}, + "source": [ + "# Examples of quantum pulses in TorchQuantum\n", + "\n", + "Author: Jinglei Cheng, 2023\n", + "\n", + "### Introduction\n", + "\n", + "This notebook can be devided into three parts:\n", + "1. Example of qubit dynamics with Schrödinger equation solver\n", + "2. Example of qubit dynamics with Lindblad master equation solver\n", + "3. Example of quantum optimal control\n", + "\n", + "### Setup\n", + "\n", + "First, we install the TorchQuantum and import the required functions, etc." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ec7d5088", + "metadata": {}, + "outputs": [], + "source": [ + "!git clone https://github.com/mit-han-lab/torchquantum.git\n", + "%cd /content/torchquantum\n", + "!pip install --editable . 1>/dev/null" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "5f13eb79", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "import numpy as np\n", + "import torchquantum as tq\n", + "from torchquantum.pulse import *\n", + "import matplotlib.pyplot as plt\n", + "from utils import *\n", + "from qutip import Bloch" + ] + }, + { + "cell_type": "markdown", + "id": "a9a2e056", + "metadata": {}, + "source": [ + "# 1. Schordinger equation solver for singe qubit dynamics" + ] + }, + { + "cell_type": "markdown", + "id": "e6f3e433", + "metadata": {}, + "source": [ + "Lamor precession is the precession of the magnetic moment of an object in an external magnetic field.\n", + "A good example is the \n", + "\n", + "\n", + "We define an initial state psi0 as the starting point of the time evolution.\n", + "The Hamiltonian of the system is: $H = $" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "47404173", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d9a1cfe", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/torchquantum/pulse/MESolver_example.ipynb b/torchquantum/pulse/MESolver_example.ipynb new file mode 100644 index 00000000..224a2ccf --- /dev/null +++ b/torchquantum/pulse/MESolver_example.ipynb @@ -0,0 +1,293 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "290ddd1c", + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import torch\n", + "import torchquantum as tq\n", + "from torchquantum.pulse import sigmax, sigmay, sigmaz, sigmaminus, sesolve, InitialState, mesolve\n", + "import matplotlib.pyplot as plt\n", + "from utils import *\n", + "from qutip import Bloch" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "f50d8c13", + "metadata": {}, + "outputs": [], + "source": [ + "n_dt = 160\n", + "dt = 0.22 # ns" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "id": "ed3f5bcd", + "metadata": {}, + "outputs": [], + "source": [ + "rho0 = InitialDensity(n_qubit = 1, state = [1])\n", + "pulse = Schedule(0.3 * np.ones((n_dt,1)))\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "id": "5079dd29", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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MLMpCXqZDtc9ZWsUr4/tU+wwitfCL8WYXZ6d0hsSprIxHXbgtEvqHRypmFWXBm5G62TOnwqMuuxtIjBAJSIwYkI9Urhfh8NPT4TYf/KGIqp9FpIa9cTGypFK9qEjs/XMAAPXdfvT7w6p+FpEauDjgRaZqwcXIgeZ+DIeiqn4WIQ4kRgzITqUmQF2nUuJ1odTrgsyAjxv7Vf0sIjV8rIiRHFU/JyfDgWn5GQCAT5r7VP0sIjXsjvsNNVM0AFCR60ZRthMRmeGTpj5VP4sQBxIjBiMUkXGoJTbdcHmVupERAMoME6ob0T9RmeHTpphoXKyyGAGgFDh/0kRCVe8EI1F80hz777RC5YiqJEnU4kucBokRg3G0fQChqAyv247KPLfqn8dPUXsb+lT/LGJqHO8YxFAoigyHFbOKslX/PH6DL51+9c/+Zh9CERn5mQ5UxyNaarI83jpMnXgEh8SIwfg0frpZVO6FJEmqf54SGaHhZ7qHp2gWlXthtahvG7xb51OKjOievfF6kaVVuWnxGyOLWMlvEACJEcPBxciC8tSPch6LBWVe2K0SugZDdDGaztkXj1CoXS/CWVjuhSQBLf0BdA4E0/KZxOTgfkPtwmbO/FIP7FYJff4w+Q0CAIkRw7F/RGQkHbjsVswviw8/o1Y9XbMvnkpLlxjJctowozALAPApFbHqmv3KISY9fsNhsyipwgMtdIMvQWLEUIQiMg63DgBInxgBgKXxzY3qRvTLcCiKI+0x20hH8SqHT2Klbiv94g9FUBsfdragLD0RVQBYGI/eHmwh2yBIjBgKXrzqcdlQlad+ERpnYVz4HGqlE45e2d/Sj6jMUJjtRKnXlbbPPSduGzwNQOiPQ60DYAwoynaiKDt9trEgHlHdT5ERAiRGDAUPtS5MU/EqZ378qvGDrT4qRtMpI+eLpNM2zolHYT5p6iPb0CkH4pGJdEZFRn7eAYqMECAxYig+TXO9CGdmURbsVgkDgQgVo+kUPutjsYr30YzF/FIPbJZYgXNrP93SqkcONMciEzxSkS7mlXogSUC7L0gFzgSJESMxMjKSTkYWox2kVI0u4Sm0+Wk+/brsVswujtkGzRvRJ/tbuN9Ir21kOm2oKcgEQNERgsSIYQhHZRxqixUopluMAIlN7iDlf3VHIBxVChTnlaZ3wwFGFLHSvBHdEYrIOBovbE53ZGTkZ1JHDUFixCAcax9EKCIj22nDtDQWr3JG1o0Q+uJ4xyCiMoPXbUeJJ30Fihw+/Gw/FbHqjmMdAwhHGTwuGypy1Z/YfCoL6BBDxCExYhD2jxh2ZknDdM1TociIfuEpmnml2WktXuXwaMyReOSO0A8j60W0sI2FSkcNCVWzQ2LEIGhVvMrhG05z3zBdGa8zDsVnz2iRogGg1Ix0DATRMxTSZA3E2GjVScPhn3uy2w9fgPyGmSExYhAOtGhTvMrxuu1KmJdSNfpCiYyUaLPhZDltyqWNh9vINvQEr9XQym/kZjpQFp97c4iiqqaGxIgBYIzhaPsgAGCuRhsOQHUjeoQxpggArSIjQMIuKVWjH6IyU/5WtYqMAIkR9DT8zNyQGDEALf0BDAYjsFkkpVVOC3jdCE1i1Q/tviB6/WFYJGBWcZZm65hbEkvV8OsKCO2p7x6CPxSFy27B9ELtbIOGnxEAiRFDcCR+8p1emAmHTbv/pEpkhE44uoELw+mFWXDZrZqtg0dGDreTGNEL/O90bokHVg2K3jm8vZf8hrkhMWIAjrTFUjRzNEzRAInIyLGOAYQisqZrIWIc0kGKBgDmxCMjR9sGIMs0Fl4P8PkiPGqlFfzzazuHEImS3zArJEYMAHcqczQMwwNAeY4bHpcN4SjD8Y5BTddCxEh00mi74VTnZ8Bps2A4HEVDj1/TtRAxuN+YVaytbZTnuOG2WxGKyqjvJtswKyRGDMDheFHgbI2diiRJygmcilj1gdadNByb1aLUrBymIlZdcCxe9D5b40OMxSIptnGM0nimhcSI4ESiMk50aN9Jw+EhV3Iq2hMIR1HbGbMNrdM0wIi6EWrv1ZxAOIr67tgVAXM0PsQAUO624l2BhPkgMSI49d1+hKIy3HarJuOcT2Vm3LEdozSN5hxrH4TMgNwMO4o9Tq2XowhVau/VnhOdMdvwuu0ozNbeNuaUxCIjR+kQY1pIjAjOESVFk6XJGPhTmVUUD7d2kFPRGl68OrfEo8mo71NJREbINrRmZIpGD7bB61ZIjJgXEiOCc4QXr2pcEc/hdSuNPcPwhyIar8bcHNOZbfB11HcPYTgU1Xg15ob7Da3rzDh8HXVdQ9SJZ1JIjAjOUZ0Ur3LyMh3Iz3QAAE50DGm8GnPDU2Uzi7QtUOQUZjuRn+kAY3QC1ppjOhMjZV4Xspw2RGSm1LIQ5oLEiODoLTICJCZ9UqpGW3h79SydiBEAmFtKdSN6gBeKajmVdySSlOioIdswJyRGBGZURbyexAhVxmuOPxRBU+8wAP1ERgBgTnH8jhqKjGiGPxRRZr3ooZOGM7uIOvHMDIkRgTneMQgW75YozNK+Ip7DTzjHKTKiGbWdMZGal+lAvo5sgwujE50kVLWCR8zydWYb3G/QIcackBgRmJHDzvRQEc/hkRFq79UOniKbqeEFaGMxozB2kSNN6NUOvaVoOMqVARQZMSWTEiObN29GdXU1XC4XVq5ciZ07d57x9Y888gjmzJkDt9uNyspK3H333QgEApNaMJHgqA7rRYCEk2vo8VPXhEbwzX6mzjYcHhlp7hsm29CIxPUR+vIbvJi2vnsIgTDZhtlIWow8++yzWL9+PTZu3Ig9e/Zg8eLFWLNmDTo6OsZ8/e9//3t8+9vfxsaNG3Ho0CE88cQTePbZZ/Gd73xnyos3Oyd0WKAIxMK/uRl2MEbheK3gcyT0FhnJz3IqtlHbRbahBXq5k+ZUirKd8LhskFkizUiYh6TFyMMPP4zbbrsNa9euxfz587FlyxZkZGTgySefHPP177//Pi688EJ86UtfQnV1NS6//HLceOONZ42mEGeHb/QzdLbhxCrjeaqGQq5acLxTn6F4IGGvlKrRhsTAM32JEUmSKFVjYpISI6FQCLt378bq1asTb2CxYPXq1dixY8eYv3PBBRdg9+7diviora3Fa6+9hs9//vNTWDYRjCRuP52hs8gIMGISKxWjpZ1QRMbJ+O2neuqk4ShFrCRG0s5AIIzmvliXldYX5I0FTWI1L7ZkXtzV1YVoNIri4uJR3y8uLsbhw4fH/J0vfelL6OrqwkUXXQTGGCKRCL7+9a+fMU0TDAYRDAaV/+/z0cVap3Ky2w+ZAVlOG4p0cLfEqSTGwtOGk27qu4cQlRmynDaUeFxaL+c0uBg5Tim8tHMinv4oyHIiJ8Oh8WpOZzb5DdOiejfN9u3b8cADD+DXv/419uzZgxdeeAGvvvoqfvjDH477O5s2bYLX61W+Kisr1V6mcNQqKZpMXXXScHgImGYGpB8ejZpRpI97R06Fp2loQm/6Gek39Mj0uG3UklA1HUmJkYKCAlitVrS3t4/6fnt7O0pKSsb8nfvuuw8333wzvvrVr2LRokW47rrr8MADD2DTpk2Q5bHvINiwYQP6+/uVr8bGxmSWaQr4CUdv9SKcmSM6aqgyPr0onTR6tY346beuawiRKN1Dkk54YageU7sAMD0ukhp6/GQbJiMpMeJwOLB8+XJs27ZN+Z4sy9i2bRtWrVo15u/4/X5YLKM/xmq1AgAYY2P+jtPphMfjGfVFjIbn2/XqVAqznPC67ZCpoybt8KJhPRavAkBZjhtOmwWhqIzG+JRYIj3wv8XpBfqMjJR53XDZLQhHGdmGyUg6TbN+/Xo8/vjjePrpp3Ho0CHcfvvtGBoawtq1awEAt9xyCzZs2KC8/uqrr8ajjz6KZ555BnV1ddi6dSvuu+8+XH311YooIZLnhM7DrZIkKSdgatNLL3qPjFgtkhKOpyLW9FKr84iqxSKhpoBSNWYkqQJWALjhhhvQ2dmJ+++/H21tbViyZAlef/11pai1oaFhVCTke9/7HiRJwve+9z00NzejsLAQV199NX70ox+l7ilMBmNM92kaAKgpyMTuk72o6yIxki6iMkNt/N9br5ERIJaqOdTqw/HOQaxG8dl/gZgyUZmhLn6X1XSdHmKA2NoOtfpQ2zmEy+ZpvRoiXSQtRgBg3bp1WLdu3Zg/2759++gPsNmwceNGbNy4cTIfRYxBx0AQg8EIrBYJVfkZWi9nXLjDoxNO+mjs8SMUkeGwWVCRq1/boLHw6aelbzhmG1ad20Y8hUTpXXNBd9MICA9tV+VlwGnTb6qL56UpMpI++OY+vSATVov+Omk4dGFe+uH/1tUFGbq2jURHDfkNM0FiREBOdPEUjX5DrcBopzJesTKRWuq79Z++A0bMGukYJNtIE3xzn16gb9vgtkvXBZgLEiMConTS6HzDqcrLgCQBA8EIugZDWi/HFPB6kRqddktwqvMzYZGAgUAEnQPBs/8CMWX45q7nehEAqImvr2swhP7hsMarMQd6OBCQGBEQvd5JcyouuxUVuW4AVDeSLuo6xRAjLrsVlXmxugWaxJoe+JC56Tr3G1lOG4o9sanS5DfSwz9u2YFL//MtfFTfo9kaSIwIiBJu1fkJB4DSpkd1I+mB/zvXCGAbyiRWqg1ICzwyovf0LpBIJVHdSHo43jGI+m4/spyT6mlJCSRGBMMfiigXXek9MgIkilhrSYyozlAwgjZfAIB+h1qNpDo/tsZ6sg3VGQxG0O6LpcP0HhkBEgctKnBWn96hRDqM/01qAYkRweAnhbxMB3Iz9XfR1akk2ntpw1EbXryam2HX5SVop8KjNyRG1KdOuSDPAa/brvFqzs4M6qhJG/ygWOp1we3QrjuTxIhg6H3y6qko4VaqjFedOkGKVzk18VMYH8RFqIdSvKrzThqOcoghv6E6/DCgZVQEIDEiHMJtOPziq266+EptEsWrYmw41QWxAlayDfVRJjYXieE3eGSkvtuPqKx9p4eR0UudGYkRwVBUrCBipNTjgstuQUSmi6/UhjsVEQqbgdilaA5bzDZ4HRShDrWdYkVGynJithGKyGgmv6EqPDJZQ5ERIhnqu/0AtDeciWKxSEr4r45CrqoiyowRTsw2YtER6rZSlxMCdeABscsUuY87QX5DVfRywCUxIhi8SFFrw0kGKkZLD6Kl8IDEWkmMqIcsM2XDEaGThsNTSnSzs3owxnTjN0iMCESfP4Q+v/YtWMlSQ+29qqOX9rxk4aKaOmrUo2MgiOFwFDaLhMr4EEIR4HZ8Mh4NJlJP50AQ/lAUFik2MVtLSIwIBFewJR5tW7CShW7vVR8u9Mo0bs9LlkRHDW04asH9RkWuGzarOC5fEarUbaUaCdvIgMOmrW2IY5mE8kc5LV+/13+PBYXi1UcvFfHJkrANEqpqcVLA1C4wYigeiRHVqNNJvQhAYkQo6rrixas6MJxk4Hnqdl8Qg8GIxqsxJnwzF802+Hqbe4cRilB7rxrwoneR0ncAlOJmsg314J00epjYTGJEIPRS9ZwsXrcdefFpsQ0UjleFRBGaOAWKAFCY7USmwwqZAQ09ZBtqwP2GaBHVwmwnMuK20dhLtqEGfDZRtQ5sg8SIQCidNIKdcICEIzxJIVdVUC5PFEyoSpKkiGtK46mDiB14QMw2pilFrGQbaqAn2yAxIgh6asGaDNPildr1FBlJObLMdOVUkoU6atSDMaZ0o4h4iOEn9vou8hupJuY3Yv+uehiGR2JEEHr9YQwEYvUWWrdgTQY64ahHmy+AQFiGzSKhQqDWTQ6P5tAdNamHt/VaBbUN6qhRj5b+WC2O3SqhLMel9XJIjIhCnU5uVpws/B4Sciqph598K3LdsAvUuslRJvTSULyUUz+irVdM26CIqlrwaFNVXoYuWr61XwExIfRys+JkmUYDjFTjpNLyLaZt8HZkEqqpp15w2+DrphRe6lHupNFJapfEiCCIXBMAJERUa38AgXBU49UYi5PxLhTRuiU4NSNsYzhEtpFKEm29gtpG3N819fqpvTfFJDpp9LGnkBgRhETxqphOJTfDjmyXDQC1cKYa0SMjuZkOeN12ABQdSTWiR1SLsp1w2S2QGehm5xSjtwMuiRFBED3cKkmJ23sp5JpaeOprmoCFzZxqpfWbhGoqUSIjgh5iyG+ox0mdjYogMSIAjDGl2Egv+b3JMI02nJQzqnVT0A0HAKriDrGhhzacVBGzDbEPMQCNhVeDqMzQ2BOLNOklvUtiRAC6h0IYDEYg6eBmxalATiX19IywjYpccW2DR3VIqKaOkTeyVopsGwVkG6mmzRdAKBobB1Dq1b6tFyAxIgT1yo2sbrjs4rX1cigyknp4GL7U4xLaNqritkH1RKmD20Z5rlvzG1mngtL6TWmalMEjZnq6yVkfqyDOCN+8RY6KADTASA14WkPkMDxAkRE1EL14lVNNAxNTDr8jTE9+g8SIAIjeusnh62/pG0YwQi2cqYDXEoluG1yoNvcNIxylFs5UkCh6F902Yutv7CXbSBV63FNIjAhAQ9ypVOnIcCZDYVbiFs6mXmrTSwUNPfo74UwG3sIZlRmayTZSgsh30oykONsFp41sI5U06DDaTmJEAJQNJ09sp0K3cKYeo5x+JUlSHONJqhtJCbzGQnSharEk2nvp/qLUcFKH6V0SIwLAxYieVOxkoVs4U0si9yu+bVTFxXYDbThThjGm+A1Rp6+OhEeFm0ioTpmR4wD05DdIjOicwWAEXYMhAOKnaYDEM1BkZOoMBMLoHorZhp5OOJOFuq1SR68/jMFg7JbvSgMcYvhBjLqtpk6fTm+AJzGic/jJNyfDrozMFpnErBFyKlOFb9oFWQ5kOW0ar2bqKGKENpwpwzftYo9T6JZvTmWuGwCJkVTAU7t6sw0SIzpHad3UkYKdCtMoMpIyjNLyzVFOvyRUp4wyeVXwOjNOYg4NFbBOFb3WIJIY0TlKvYgBwvBAIp3Q1DuMqMw0Xo3Y8CI00bslONXKSHg/GCPbmAqNcb9hhBQNkBCqjWQbU0Y5xOgs7U9iROckTr9ujVeSGko8LtitEiIyQ2s/nXKmwskufTqVyVKe64bVImE4HEXnQFDr5QiNHgsUpwK/6mAwGEGvP6zxasRGrxdrkhjROXoNqU0Wq0VCeU5MWDVSyHVKGC0yYrdaUJYTuyeDaoqmhpE68ADAZbei2OMEQHUjU0VJ/evs0lUSIzpHryG1qVA5IuRKTB4j2gYX3VRTNDUS6V3j2AZ11KQGiowQSROJymju09c1z6mAnMrUCYSjaPMFAOjPqUwFujBv6oy0DaNERgA6xKSC4VAUHfEUqN72FBIjOqalL4CozOCwWVCcrY9rnlOB4lR6yalMlua+YTAGZDqsyMt0aL2clEEX5k2dpt6EbeQbyDaqSIxMGS7yPS4bcjL0ZRskRnQMrwmoysuAxSJpvJrUQZGRqdMwoltCkoxjGzRrZOo0GtQ2yG9MncT1EfqqFwFIjOgao82R4NAJZ+o0GqxAkcOdJI2EnzwnDXJf0amQGJk6DTquMyMxomOMVhHP4WmarsEQ/KGIxqsREz3eupkK+PP0+sPwBaiFczLwwWBGsw3uN1r6hhGOyhqvRkz0vKeQGNExRroEbSRetx0eV2x8ObX3Tg4jdksAQKbTptQ5UORscvDWTaMMSuQUZjnhtFkgs5ggIZKH1+mRGCGSgufNjSZGAOqamCoNBpuwOZIKJY1HG85k0PPpdypYLJJi7+Q3JodST5SrP9sgMaJTGGNK3rzKIAPPRkJ1I5OHMWbYmhGAbGMqMMZGDEo0rm2QGEkeWWZo6o0J/EodTvQmMaJTeoZCGApFIUlARa7+DGeqcGVOTiV5ev1hxTb4NFsjwW9opdbv5OkcCCIQlmGRgDID2gaJkcnTORhEMKJf2yAxolOUK8CzXbq65jlV0ACjycNto8RDtkGMhttGWY4bDpvx3Du3jSZK4SUN/3sq9bpht+rPNvS3IgIA0KjjcFoqUELxdPpNGiPXiwCJqBn/GyAmjlHHAXAoMjJ5uK/V655CYkSn6LnQKBWMLESjK8GTw8j1IgBdFz8VjFq8yiExMnl4Qbhe9xQSIzqlKa5iKwzqVMpz3JAkIBCW0TlI18Ung1FnjHBKc1ywSEAwIqNzgGwjGQwfNYuf6vuHw+j30xyaZGjUuW2QGNEpCRWrz5DaVHHYLCjzxgsVKf+bFEY//dqtFpR6qYh1Mhg9apbhsKEgywmAbCNZKE1DTIqE4RjTqQCJLiEqVEwOo59+AQrHTxYz+A2+mZJtJAelaYikicpMmTBoZKdCG07yhCIyWvuNOe57JHzDoajZxAmEo2j3xdJaRo2oAuQ3JkM4mvAbet1TSIzokDZfAOEog90qocTj0no5qkHDrZKnpW8YMgPcdisKsvR1BXgqUTpqyDYmTHP8AJPhsCIv07i2QWIkebjfcNosKIynufTGpMTI5s2bUV1dDZfLhZUrV2Lnzp1nfH1fXx/uuOMOlJaWwul0Yvbs2XjttdcmtWAz0DhiVoDVYpwrwE+FRjsnz8h6ESNdD38qdF1A8ozswDOybdAcmuThEcaKXDcsOt1TbMn+wrPPPov169djy5YtWLlyJR555BGsWbMGR44cQVFR0WmvD4VC+NznPoeioiI8//zzKC8vx8mTJ5GTk5OK9RsSo7f1csipJI8Z6kUAoCJu+000a2TCGH02EYciqskjQi1R0mLk4Ycfxm233Ya1a9cCALZs2YJXX30VTz75JL797W+f9vonn3wSPT09eP/992G32wEA1dXVU1u1wTGbU2n1BRCKyIacGJlqEu15xrYN/nyt/cNkGxOkKW4bFQY/xHC/0dQ7jKjMDB09ThUiHHCT+gsPhULYvXs3Vq9enXgDiwWrV6/Gjh07xvydl19+GatWrcIdd9yB4uJiLFy4EA888ACi0ei4nxMMBuHz+UZ9mQmzOJWCLAfcdisYS+S7iTNj9LZeTmGWEy47XRefDCKcflNBsccFh9WCiMyUokzizIhwwE1KjHR1dSEajaK4uHjU94uLi9HW1jbm79TW1uL5559HNBrFa6+9hvvuuw8PPfQQ/t//+3/jfs6mTZvg9XqVr8rKymSWKTxmcSqSJFGbXpI0CHDCSQWSJI0YC0+2MRGMPpuIY7VIylgA8hsTw3CRkckgyzKKiorw2GOPYfny5bjhhhvw3e9+F1u2bBn3dzZs2ID+/n7lq7GxUe1l6gqzOBWA8r/Jogy1ytevU0kViZoiOv1OBLMcYgCqN0uWJgFsI6makYKCAlitVrS3t4/6fnt7O0pKSsb8ndLSUtjtdlitidtF582bh7a2NoRCITgcp7egOZ1OOJ36bD9Sm2AkivaBAAB9G06qqKAWzgnTPxyGLxABkBgYZ2Qq6fQ7YQYCYfTFx6ObwW9Qe+/EGQpG0DUYAqBv20gqMuJwOLB8+XJs27ZN+Z4sy9i2bRtWrVo15u9ceOGFOH78OGRZVr539OhRlJaWjilEzE5z7zBYfI5EvoFnBXDIqUwcfropyHIgw5F07blwKKdfStOcFR49ys2wI8tpBtvgQpWiZmeDd6R5XDZ43XaNVzM+Sadp1q9fj8cffxxPP/00Dh06hNtvvx1DQ0NKd80tt9yCDRs2KK+//fbb0dPTgzvvvBNHjx7Fq6++igceeAB33HFH6p7CQIwsNDLyrABOFW04EyYxK0C/p5tUwsVIEwnVs2KmFA1Ah5hk0PsFeZykJfQNN9yAzs5O3H///Whra8OSJUvw+uuvK0WtDQ0NsFgSGqeyshJvvPEG7r77bpxzzjkoLy/HnXfeiXvvvTd1T2EgjH7R1akow626yamcDeUmZxOkaIBEsR1tOGdHhALFVEI1IxNHEao6t41JxfPWrVuHdevWjfmz7du3n/a9VatW4YMPPpjMR5mORpO09XL4xuoLRNDvD8Obod8wotaIcsJJFTwU3+sPYzAYMUX6YbLwUHyFjls3Uwn/G+gZCpFtnAWlIULntkGThHSG2cKtdCX4xFFSeCYRqtkuO3Lj4pROwGfGbJERD9nGhBFlTyExojPM1NbLqaJZIxPCLNNXR0L3F00MUTacVEJ1IxNDFKFKYkRnmNGp0IZzdhhjSihe704llVBtwNlhjJnyEEO2cXZitiHGnkJiREeYbVYAhwafnZ2uwRCGw1FIUuw2Z7NQSRfmnZXuoYRtlJtIjFBk5Oz0+sMYCsWuXtF74TuJER1htlkBHIqMnB0eMSv1uEx1aRxPSZFQHR/+b1Oc7YLTZj3Lq40DiZGzw22jKNsJl13ftmEeryYAZkzRAInTL20446N0WZnUNmjDGR8RLkFTAxIjZ0ekPYXEiI4QpdAo1fBZI819sSvBidNRWjd1HmpNNSOvi2eMbGMszOo3EkPxhiGT3xgTkWqJSIzoCLPNCuCUeFywWyWEowxtvoDWy9ElTYIMLko1ZTluSBIwHI4q92sQo1GG4Qlw+k0lpV4XrBYJoaiMjoGg1svRJRQZISaFWU84VouE8nhRJk1iHZvE4CJz2YbDZkGpxwWAwvHjIdLpN5XYrBaUemO2QTOKxkakPYXEiI4QScWmGroU7cwkRjqba8MBRoTjyTbGxNR+g+rNzogyDkAA2yAxohPMOiuAoxSjUWTkNKIyQ0ufOE4l1dA8ifEh2+DdVtT6fSpRmSXSuwKk/kmM6ASzzgrgUGRkfNp8AYSjDHarhOJ4ysJMUEfN+Iy0jRIT2wb5jdNpj9uGzSKh1Kv/PYXEiE4w66wADoVbx4f/m5TnuGG1SBqvJv1U5dPpdzy4bZSZ1jbIb4yHaLZBYkQnmHVWAEcJt9KkzdMQZZyzWtDpd3xEKlBUgwqa0Dsuou0pJEZ0gtmdCn/uzoEgAuGoxqvRF43KjBGT2kZchLX0DSMclTVejb4QbcNJNfy5W/uHEYqQbYxEtD2FxIhOMOusAE7OiBH41DUxmiY+fdWEtUQAUJjlhMNmgcyA1j6aQzOShG2Y028UZjnhssdsgxfyEjFE67IiMaITeD68ShDDSTWSJI3omiCnMhLRnEqqsVgkpcOMUjWjMbttSJKkCDGyjdE0CTabiMSITmjoMe8cCQ5/duqaGI0yK8DMtkH3kIyJmccBcBShSoeYUYi2p5AY0QFmnxXAoXkSpxOMRJUR+aa2Deq2Oo1gJIr2AbINGgtwOiLaBokRHdDaP4yIbN45EhwKxZ9OS18AjAFuuxX5mQ6tl6MZVcqGQ6dfTnPvMNkGSKiOhYi2QWJEB/DwolnnSHCoZuR0Em29bkiSmW2Dh+Jpw+GM7KQh2yChOhIRbYPEiA4wexEah8Ktp9No0tt6TyUxT4JsgyNa66ZaKLZBQlVBRNsgMaIDzN6ex+GtqwOBCPr9YY1Xow/MelvvqfDn7xoMwR+KaLwafUCHmBj8+buHQhgKkm0AYtoGiREdYPbBRZwMhw0FWU4AFB3h8H8Hs84Y4XjddnhcfA4NheOBROsm2QbZxqmIaBskRnSAiCE1taDagNFQ1CwBdVuNRsTTr1qQbYyGt/WKNLeKxIgOIKeSgG5oHQ1FzRJQ18Ro6BCTgO4vGo2IewqJEY0JhKNo9wUBiDOcRk0SlfHkVIaCEfQMhQCI5VTUgromEgwGI+iN11WRUB0ZUSXbGAiE0afYhjh+g8SIxjTHh51lOKzIE6QfXE0Sp19yKjz/HcuJ2zVejfZUUGREgf8b5GTYkU22QZ14I+C+M3fEfV8iQGJEY0aGWkXpB1cTcioJRs4YISgyMhJK0YyGUngJREzRACRGNIdqAkZTqcyTGIYsM41Xoy00Y2Q0lSPmSTBmdtsgvzES/u/Q1DtMtiGoUCUxojHULTGa0hwXLBIQisjoHAxqvRxNoRkjo+F/IwPBCPqHzT2HRtQNRy24bQwGI0q9hFnh6d0KwYQqiRGNETWkphZ2qwVlOdTeC4yMjIjlVNTC7bAm5tCYvKaIT6KtIL8BAHDZrSjKphlFQMJvitTWC5AY0Ry6Avx0qL03RiNFzU6Duq1ikN84HX6gM7vfaBA0akZiRGO4U63KF8tw1ITa9ADGmBJupbqABFSoGLMNiqiejnLrN/kNAOLZBokRDfGN7AcXTMWqCQ0wAvr8YQzG79mgyEgCiowAPUMh+ENRALGbvokY1IkXu7tpOByFJAFlOS6tl5MUJEY0hJ/u8jIdyBSoH1xtaLRzwqEWZjvhsls1Xo1+oDk0iU6aYg/ZxkgoapbwGyUeF5w2sWyDxIiGUN53bEa26ZkVso2xodMvddKMRwX5DaFtg8SIhlBF/NjwP6TW/mGEo7LGq9EGqgkYG5pDQ7YxHtw2mk1sG6K29QIkRjRFZBWrJoXZTjhtFsgMaOkz5ymHbGNsaA4NRc3Go9TrgtUiIRSV0T4Q0Ho5miBqWy9AYkRTaIri2EiSZPo2PW4bIjoVNbFbLSj1mnsODUVUx8ZmtShFm2atKRK1rRcgMaIpdPodH7O36SkzRkionobZO2rIb4yP2YtYRU7hkRjRCJH7wdOBmQsVozJDM0VGxsXMHTVRmSk3fVNE9XTMPBYgEpXR0hdLT4loGyRGNELkfvB0YOYTTrsvgFBUhs0iKSkJIoGZW7/bfQGEo4xsYxzMPDCxtT+AqMzgsFpQnC3enkJiRCNE7gdPB2a+Lp5vsuW5blgtksar0R9mTtNw2yjLIdsYCzNHVBPXR7hhEdA2SIxoBOV9z0zFiOvizUaDwBXx6cDMaRoqej8zZvYbIteLACRGNEPkfvB0wP+guodCGIqPRTcLfMOhMfBjw23DjHNo6BBzZrhIa/UFEIqYyzZEP8SQGNEIcipnxuu2w+u2AzBfyFXkWQHpoDDLCUd8Dk1rn7nmSYh++lWbwiwnXHYLmAlnFDX0iB01IzGiEVzFTqPbesfFrMVoilAV1KmojcUioSLXnHUjTT08aka2MRaSJCkRRbPZhuiHGBIjGqEMpxHUcNKBWTtqRA+3pgOz2gZFRs6OWWcUNQq+p5AY0YBwVFZCiLThjI8ZK+MD4Sg6BmJjzimFNz5m7KgJRqJo88XnSJBtjEuVCf3GUDCC7qEQABIjRBK09gUgM8Bps6Awy6n1cnSLGU84fNR3ttOGnAy7xqvRL2bsqGnpC4AxwG23oiDLofVydIsZr5Lgwisnww6PS0y/QWJEA0amaETsB08X/O6NJhOdcPjmWpGXAUki2xgPM0bNGkbUEpFtjI8Z23sbusVP7ZIY0QCqCZgYI+sCGDPHleAJ26ACxTNhxshIwjYyNV6JvjHjwESRL8jjkBjRABIjE4N3DAyFouiJ50ONDrV8Twy+4XQNBjEcimq8mvQgerdEuuBRsx4TzSgSvXgVIDGiCUYwnHTgsltR7InV1JjllKMIVWr5PiNetx3ZThsA86TxEqF4ipqdCY/LfDOKGg1wsSaJEQ2gyMjEMVsLpzLumyIjZ0SSJKWmyCwbDgnViWO2GUUNBphNNCkxsnnzZlRXV8PlcmHlypXYuXPnhH7vmWeegSRJuPbaayfzsYaBxMjEMVOhImOMomZJYKZuq5G2QX7j7JjpEGMU20hajDz77LNYv349Nm7ciD179mDx4sVYs2YNOjo6zvh79fX1+I//+A9cfPHFk16sEej3h9E/HAZAUxQngpk2nD5/GIPxHDfZxtlRhKoJNpw+fxgDim2Iu+GkCzMdYjoHgghGZFik2G3OopK0GHn44Ydx2223Ye3atZg/fz62bNmCjIwMPPnkk+P+TjQaxU033YTvf//7mD59+pQWLDr8j6Mgy4HMeM6bGB8ztffyiFmxxwmX3arxavRPpYlGwp8k20gKMx1iuN8o9bpht4pbeZHUykOhEHbv3o3Vq1cn3sBiwerVq7Fjx45xf+8HP/gBioqK8JWvfGVCnxMMBuHz+UZ9GQUaA58cZgq3KqO+6eQ7ISoVoWqeDUfkMHw6MeMhRnTbSEqMdHV1IRqNori4eNT3i4uL0dbWNubvvPfee3jiiSfw+OOPT/hzNm3aBK/Xq3xVVlYms0xdY4TcXjrhxXrNfcOIysaeNWIUp5IuzJSmaaQZI0lhphlFPPojut9QNaYzMDCAm2++GY8//jgKCgom/HsbNmxAf3+/8tXY2KjiKtMLbTjJUeJxwW6VEI4y5V4OozJy+ipxdnhdjS8QUeqwjIoRJmymk5Ezinr9BrcNA3TSAEBSRQsFBQWwWq1ob28f9f329naUlJSc9voTJ06gvr4eV199tfI9WZZjH2yz4ciRI5gxY8Zpv+d0OuF0GvPOFkrTJIfVIqEsx42T3X409vhRLnCB1tmgqFlyZDhsKMhyoGswhMYeP7zlXq2XpBqJtl7j2n8qcdmtKMp2omMgiMYeP/IyjXuXj1E68JKKjDgcDixfvhzbtm1TvifLMrZt24ZVq1ad9vq5c+fi008/xb59+5Sva665Bp/97Gexb98+Q6VfJgptOMljlrqRRM0IbTgTpcIktkER1eQxS0cNfz7RbSPpdo7169fj1ltvxYoVK3DeeefhkUcewdDQENauXQsAuOWWW1BeXo5NmzbB5XJh4cKFo34/JycHAE77vhmIykwpthPdcNKJGe6aiMoMzdw2aKjVhKnKy8C+xj5DbzihiIzW/vgwPPIbE6Yy143dJ3sN3VETCEeV9LXotpG0GLnhhhvQ2dmJ+++/H21tbViyZAlef/11pai1oaEBFou47UVq0to/jIjM4LBaUOxxab0cYTDDLZyjbCObbGOicFFv5OviW/qGITPAZbegMMuY6Ws1MENkpLlvGIwBGQ4r8gVPRU1q0MW6deuwbt26MX+2ffv2M/7uU089NZmPNATcYZbnumG10BXgE8UMToXbRkWuGxayjQmTECPGPf2eHJGikSSyjYlihvRuo4Fsg0IYacQohUbpxgwDjJqok2ZS8L+lhu4hjVeiHg3U1jspzDCHplE5xIjvN0iMpJGEU6ECxWTgp982XwCBsDGviyfbmBy8vqap17hzaKjofXLwWrOmXr9hbcNIhc0kRtJIg0GG06SbvEwHMhyxEdjNfcY85dD01clR4nHBYbUgIjOlyNNoJGaMkFBNhlKvGzZLbEZRu0FnFCUGnolvGyRG0gidcCaHJEmGz/8a6YSTTqwWSRlwZdQi1sSMEbKNZOAzigDj+w0jpP5JjKQRqhmZPEZv7+UnHLKN5DHyWHijXA+vFUb2G0azDRIjaWIwGEH3UAgAbTiTwcjtvf5QBF2DQQBkG5OBO+KT3cazjT5/GAPBCABjFCmmGyNHVPuHjWUbJEbSBP9jyM2ww+Oya7wa8TByey+v9ve4bPC6yTaSZVq+cWeN8Gcq9jjhsls1Xo14VBp4Dg1/psJsJ9wO8W2DxEiaMFJuTwuM3N6rFChSTcCkMHKahmqJpgYXqicN2PptNNsgMZImqF5kalQZ+PRLnTRTw8hTWGnGyNSYFv93M+JQPBIjxKQwmuGkG75R9w+H4QsY60pwso2pwQV+r9+AttFNtjEV+CGmazCIoXh9hVFQit4NcrEmiZE0QRvO1Mh02pS7FxoMVqjYSNNXp0SWgW0j0dZrjA0n3XjdduRkxOqwjBY5M1q0ncRImiAxMnWq8o3ZNWGk9jyt4LZhtLoR8htTx6jdVkazDRIjaUCWmXL3iFEMRwumcafSY5xiNMbYiJoROv1OFiPWjYQisjJV1iinXy1I2IZx/EYkKqMlPo3aKIXvJEbSQMdAEKGoDKtFQqmXroefLFX58WI0A51wuodC8IeikKTYbc7E5DCiGGnpG4bMAJfdgsIsp9bLERYjtn639gcQkRkcVguKs42xp5AYSQP8j6A8xw2blf7JJ0u1AdM0/FlKPS44beLPCtAKI86TGBmGF/16eC3hHTVG8huJ23rdsFiMYRu0M6YBo+X2tMKIJxweOp6WT62bU2GawcUIMXmMKFSV1K6BbIPESBpIDDyjMPxU4LMWWvqHEYxENV5NaqjvitnGNIPkfbWC582be4cRicoaryY10IyR1DDNwLZhpD2FxEgaMFoLllYUZDmQ4bCCscQIddHhToUiI1OjONsFh9WCiMzQ2m+M6+ITM0aMs+FoQYnHBYctZhstfQaxDQM2RJAYSQMUbk0NkiSNaNMzRmV8fTdP05BtTAWLRVJOiUYJxydmjJBtTAWLRVI61QxnGwbaU0iMpAEjGo5WTDNYESs//ZIYmTrV8ehSvQGEqtGuh9caHnk0yliAk93GqzUjMaIyw6EoOgdi18OTU5k6ilMxgBgZCITRPRQCYCynohVGso0+v7Guh9capfXbELYRQp8/du2BkQ4xJEZUhlc9Z9P18CnBSPMk+KZZkOVAltOm8WrEp7ogZhv1XeKffrl9F3uccNmp5XuqGGkKK3+GomwnMhzG8RskRlTm5IiLrmhWwNSpVk6/4m84J+kStJRipA2HUrupRUnvGuAQw9OQ1QaLppIYUZmTBjUcreBOpbF3GLLMNF7N1OD5a7KN1FA9oi5AdNugtt7Uoswo6h4CY2LbxkmD1pmRGFEZRcUWGMtwtKLU64LNIiEUkdHmE7tN72QXdUukkvJcN6wWCYGwjI54nZaoNFDULKXwupuhUBQ98TotUUnsKcYSqiRGVCYx1MpYhqMVNqsFFfE2PdHD8RQZSS32EbYhekdNoq2XZoykApfdihJP7A4X0VM1FBkhJgV3ijUGU7FaolyYJ3ibnlIzYjCnoiXTDFJTRDUjqacq3xgzioya+icxoiLBSFS55tloKlZLphmgUDEQjiqTQqfRhpMyjHCZYiAcRUt/zG8YbcPRkho+h6ZLXNsYCITRNRhLMxntEENiREUae2JXgGc6rHQFeAoxQmU8H2iV7bQhL9Oh8WqMgxFmjTT0+MEY2Uaq4TUWIqfwuF3nZzrgcRlrVASJERUZOSWP2npThxFGwo9M0ZBtpA4eGRF5w6nrShQokm2kjhoDzKExar0IQGJEVerjhkOdNKmFn3BOdvmFbdMz6qwArRkZGRHVNk4atFtCa/i/Z12XuO29RvYbJEZUhCtwIxqOlsQGyAEDwYgyTl006BI0dajMc0OSgEGBbaMuXtNQQ7aRUqbFZ7b4AhH0xsepi4YR76ThkBhRESOrWC1x2a0o88ZbOAUNuSpRM9pwUorTlrANUdN49V0UGVEDtyPR3itqGs/I0XYSIypi5Pye1tSMCLmKSEPcGdKEzdTD/95E7Zow6lArPSD6/UWJW76NZxskRlQiFJHRFL8kj2aMpB7uVEQUI+GojKbeeOumAU84WiPyrJHhUKLlu8aAG47WcF8sohgZDkWVqdNGjKiSGFGJpl4/ZAa47VYUZlNbb6qpKcgCIGa4tal3GBGZwW23ojjbpfVyDEeio0a8yAifyutx2ZCTYazWTT3AU+Z1AtoGrzOL2YbxWr5JjKjEyBQNteelHt6mV9spnhip6xoEEAvDWyxkG6lG5MgIP7HXUFuvKlQLHBkxevqOxIhK1I1wKkTqqRa4hZMLqOlkG6qg1AUIePrlnTRG3XC0pmbE4DPR/IaRO2kAEiOqYXTD0ZrKvAxYLRKGw1G0+8S6oZWEqrrwFs7+4TB6BWvvNeq9I3pBGQsQiAh3e68iVA1YLwKQGFENfiqroQJFVbBbLaiM39BaG097iAKJEXVxO6wo9cZqcWoFC8eTbaiLy25FqaDtvbWdMT83vdCYtkFiRCXqKTKiOonKeLHC8cqGY1Cnoge4w+YOXBSMXhegBxKTWAX1G/HifaNBYkQFRrVukhhRDREvvvKHIkrrJtWMqIeIc2j8oYiScqS2XvUQsYh1IBBGx0DcNgzqN0iMqEBjjx9R3rrpobZeteB/lCJ11PAoTk6G3ZDteXphevz0KKJt5GbY4aW2XtWoUdp7xbONgiwHvG5j2gaJERXgDpDa89SlRsDICNUEpAeeAhMpMkKp3fSgXLQpkN/gdXHTDZqiAUiMqIJiOFQToCo8BdbQHYtEiQCfMUJiRF1mxJ12XfeQQLZBQjUd1BQkrgsQpb135AHXqJAYUQFuODMKjati9UBZjhsOmwWhqIyWvmGtlzMheNEc1YuoS3muGw6rBaGIOLZBbb3poTIvA5b4zc5dg2K09/KuMCMfcEmMqMAJg7dg6QWrRcK0PLHuqElERkioqonVIikX5onS3qucfslvqIrTZkV5fCyAeH7DuLZBYkQFKDKSPqoF65qgUHz6UDpqBGnv5YeYGSRGVIf75hMC2AZjDHV8arOB9xQSIymm3x9Gd3yyH2046jNdIDHSOxRCrz8MgG7rTQfccYsQGekZYRtGLlLUC4oY6dC/GOkYCGIoFIXVIqEqz7h+g8RIijkRD6eVeFzIdNo0Xo3xESkywlsJS70uZDjINtRGJKHKh7OV57jhdlg1Xo3x4Sl0ESIjfI2VubEaOaNi3CfTCK60qV4kPfANRwSnUmeCing9kZjCqn8xoqRoiigqkg4SaRr924ZZUrskRlKMGaqe9cTMuPNu7hvGcCiq8WrOjFmcil7g/87NfcMIhPVtGyeUOjOyjXTAxUhjr1/3tlFrgnoRgMRIyqlVitCMbTh6IT/LidwMOxjT/4V5JEbSS15mYlql3lM1iYgq+Y10UJDlgMdlA2P6H5poFr9BYiTFmEXF6gku/I7rvBiNh+KN7lT0giRJwtxRQ5006UWSJCUldqJD37Zh9Nt6OSRGUkgkKuNkNw21Sjc8VaPn/G9UZkoKbybVBaQNEW7vDUaiaOiJ+Y2ZdIhJGyK094YiMhrjl64avcuKxEgKaeodRigqw2mzoDzHrfVyTIMIbXpNvX6EIjHbqMg1bnue3uCHAj23957s9kNmQLbThsJsulgzXYggRhril65mOIx/6eqkxMjmzZtRXV0Nl8uFlStXYufOneO+9vHHH8fFF1+M3Nxc5ObmYvXq1Wd8vcjUjpiSZ7HQBXnpgkca9JymOdaeqAmwkm2kDWXWiI6jZkq9SFEWXayZRmYI0N47sl7E6LaRtBh59tlnsX79emzcuBF79uzB4sWLsWbNGnR0dIz5+u3bt+PGG2/EW2+9hR07dqCyshKXX345mpubp7x4vZGoF6EUTTrhYqSuS7+Xoh2PO7xZlKJJKyPnSej1UjQetaF6kfQyUqjq1TaOm6iwOWkx8vDDD+O2227D2rVrMX/+fGzZsgUZGRl48sknx3z97373O3zjG9/AkiVLMHfuXPz2t7+FLMvYtm3blBevN07QGHhNKMtxwxm/MK8xnnvXGzwyQvUi6aWmIBNWi4SBQATtvqDWyxkTHhkhv5FepuVnwGaR4A9F0eYLaL2cMTnWMQAAmG0Cv5GUGAmFQti9ezdWr16deAOLBatXr8aOHTsm9B5+vx/hcBh5eXnjviYYDMLn8436EgG6IE8brBZJOTnoNeRKkRFtcNqsyoV53LHrjRM0DkAT7FYLquK2odeOGh4ZmVVsfNtISox0dXUhGo2iuLh41PeLi4vR1tY2ofe49957UVZWNkrQnMqmTZvg9XqVr8rKymSWqRlKmsbgVc96RM91I4wx5fRLkZH0wwUgj07pCcYYDTzTED0XscoyU2x2VnG2xqtRn7R20zz44IN45pln8OKLL8Llco37ug0bNqC/v1/5amxsTOMqJ0fvUAhdg7EwMI10Tj/cketRjLT5AhgMRuLX2tOGk25mxx25HiMjHQNBxTb4KZ1IH3oWI819wxgOR+GwWjDNwBfkcZK6raugoABWqxXt7e2jvt/e3o6SkpIz/u5Pf/pTPPjgg3jzzTdxzjnnnPG1TqcTTqdYbUxH22OOrjzHjSy6IC/tJGaN6M+p8NNNdX6GoS+60iszdRwZ4RGzqrwMOG10QV660XNHDRfP0wszYbMa328k9YQOhwPLly8fVXzKi1FXrVo17u/95Cc/wQ9/+EO8/vrrWLFixeRXq2OOxp3KbBPk9vTIyCmsequMP04pGk2ZVcQjI/qzDZq8qi16nsJqtqL3pOXW+vXr8fjjj+Ppp5/GoUOHcPvtt2NoaAhr164FANxyyy3YsGGD8vof//jHuO+++/Dkk0+iuroabW1taGtrw+Cg/pToVDjaFq96LjF+bk+P1BRkwiIBvkAEnYP66po4xovQisg2tGB6Ycw2+ofD6BzQp21Q8ao28H/3Nl8AvkBY49WMxmx+I2kxcsMNN+CnP/0p7r//fixZsgT79u3D66+/rhS1NjQ0oLW1VXn9o48+ilAohH/8x39EaWmp8vXTn/40dU+hA3iaZrZJDEdvuOxWVObpszKeile1xWW3KrU6x3RWU3QkfoiZQ4cYTfC67SjxxOoXj7Xrq6aIr8cs0fZJFTesW7cO69atG/Nn27dvH/X/6+vrJ/MRQsEYS4gRE1Q965UZhVk42e3H8c5BrJqRr/VyFHjul8SIdswqykJd1xCOtQ/gwpkFWi8HAPkNvTCnJBttvgAOtw1g+bTxR06kE8ZYIjJiEjFi/KqYNNA1GEKvPwxJog1HS5T2Xh2dcLoHg4ptUCheO7hDP6qjyEjnQMw2LOQ3NIVHpXiqXQ+09AfgD0Vht5qnA4/ESArg4bSqvAy4HVQRrxX8dHlER2KEn24qct1kGxrC8+7HddRRw+20uiATLjvZhlbo0W/wiFlNQSbsJuikAUiMpARuOGYpNNIrc+MnnCNtA7rpmlA6aSgqoimJyIh+bEOpF6EUjabo0m+0m6t4FSAxkhJ46HdOCW04WjKzKAsWCej1h9Ghk66JxDhn8zgVPTKjMAuSBPT5w+gaDGm9HAAJMUL1ItoysyhmG73+sG468XidmVnqRQASIynhKDkVXeCyW1FTEMuvHtZJ/vdwW+xeJbqTRltcdiuq8vR1Rw2PqM6lThpNcdmtqI7XZRxt00ca7yhFRohkGVkRbybD0StzSzwAgMOt2l+uyBjDodaYbcwr9Wi8GkIZfqaDuhFZZsqGQ7OJtIenyvjhQUsYY6a6II9DYmSKdAwE4QtEYJHotl49MDL/qzVtvgD6h8OwWiTqltAB3LHrITLS2OuP3TtiM8e9I3qHC8KjOihi5XdZ2SySErExAyRGpgjf9KgiXh/wNr1DOhAjh+LRmRmFZBt6gA+P0oNQ5WuYVZRlintH9M4cpaNG+6jZ4RF7ipnusjLPk6oETV7VFzwdcqJjEOGorOlaeIqGp44IbZlf6gUQ++8iy9p2TXC/QZ00+oAfYo61a28bB1tih5j5JkvtkhiZIjz/bJaRvXqnPMeNTIcVoaiM+i5tx8LzyAjVi+iD6YWxk+ZgMIKm3mFN13KY7rLSFdX5GXBYLfCHoprbxsG435hfZi6/QWJkihxuJ6eiJywWSTepmoQYIdvQA3arRYlEHGzt13QtSmSE/IYusFktyg2+Wg8/O0SRESJZIlFZ6dowm+HomTnxtMgRDSvjA+Eo6uKRGYqM6AcuDHkoXAtCERm1nTHboDSNfkgUv2tnG/5QBHXd5vQbJEamQG3XEIIRGZkOq6mqnvUO33AOt2p3wjnaPgCZAXmZDhRlOzVbBzEafmg4qGHrd13XECIyQ7bLhlKvS7N1EKOZrYMi1sNtA2AMKMp2otBkfoPEyBTY3xwL9c4v88BikTReDcFJzAzQToyMTNFIEtmGXphfFiti1TIywmdZzC4m29ATfIK2ljOKlOJVk9WLACRGpsSBuOEsiDs4Qh/w7pXmvmH4AmFN1kCdNPpkbjxq1tIfQO+QNmPhP22KHWIWmHDD0TPcj5/oHIQ/FNFkDQdNnPYnMTIFDrSQU9Ej3gy7Ev7W6lpw6qTRJx6XXRkLf0ijE/Cn8YjqwnI6xOiJYo8LhdlOyEw726DICJE0jDGKjOgYXoymhVOJjYGnThq9omXdiCwzZcNZRGJEd/D/Jjx6lU6iMlNSeBQZISZMY88wBgIROKwWU90fIAr81PmJBk6lpT8AXyA2zpnGwOsPfurUom7kZI8fA8EInDYLXZ6oQ7jf+LQ5/bZR1zWEQFhGhsOKaSZsiCAxMkl4imZOSTbsNM5ZdygnnOb0i5HDyhj4LDhtNAZeb2gZGeH2OK/UQ2PgdcjCuFDdr4Hf4PY4pyQbVhM2RNBfwyTZT/UiumZxZQ6AWIttuovR+Il7LqVodAmPjBzvGEQgHE3rZ/NNjlI0+mRRRey/y7GOAQyH0msbZh0DzyExMkmUehFyKrqk2ONCUbwYLd3h+I+b+gAA51TkpPVziYlR6nUhJ8OOiJy4qj1d8FoEEiP6pMTjQkGWI1bEmubhZ2YdA88hMTJJEsWr5jQcEeBi4OM01o0wxrCvMfZ5Syppw9EjkiQlUjVpFKqMMSWiSp00+kSSJOW/TbpTNRQZIZKmwxdA50AQFgmYR3MkdMs5Fbwyvi9tn9ncN4yuwSBsFom6rHQMd/jprCk62e2PFb3bqOhdz2jRUdPWH0DXYGxPMet9RSRGJgGPiswozILbQQWKeoWLkXR21Hwcj4rMLc2Gy062oVeWVOUAAPY19qXtM5XiVSp61zULNSh+39vQCyB2r1aGw5a2z9UT9BcxCWjYmRjwNE1t11DaJrHyepHFVC+ia5ZW5QKIzaFJV6Hifhp2JgQ8MnIsjQXOe+OieFlcJJsREiOTgNcEkFPRN3mZDlTkugEA+9MUHeEn7SXxbh5Cn5R5XSj2OBGRWdpOwJ9SJ40QlHpdyM90xIeQpWeC856TscgIF8lmhMRIkjDGsCceUls+zbyGIwo8QvFJGjacSFRW8swkRvSNJElYWhn7++V/z2rCGKPIiCCMLGJNh1ANRWTlc5ZSZISYKHVdQ+gZCsFps1CBogAsUupG+lT/rGMdgxgOR5HltGF6IRUo6h3u+PemQYw09Pjhi09s5lfVE/olUcTap/pnHW7zIRiR4XXbMb3AfJNXOSRGkmRXPJy2uCIHDhv98+mddBaxfhxP0ZxT4TXlBEXRWDaNR0b6wBhT9bN21cf8xoJyD/kNAeCRTe7v1SSRosmBJJnXb9BfRZLsjjuVZZSiEQIebm3qHUb3YFDVz+L1IospRSMEi8q9sFkkdA4E0dw3rOpnfVTfAwA4rzpP1c8hUgNPwdd2DqFLZb+RKF41955CYiRJdsdDuitIjAiBx2XH9MJY6FPtNk5FjFAnjRC47FZl2uXehj5VP2tnXIycS2JECHIzHZgdnwWzK/7fTi247Zm5XgQgMZIUff6QMj6aIiPisLImtgF8WKeeU/GHIjjaHqu8N7tTEYml8SiWmkWsXYNB1HYOAQBWVJPfEAUuHD+qV9c2Gnr8kCSKqJIYSQLusKYXZiIv06HxaoiJsrImHwDwQW23ap/xaVM/ZBa726LY41Ltc4jUwlsp1YyM8JP1nOJs5GSQ3xCF82q4GFHvEMPtblZRFjwuu2qfIwIkRpKAF6EtN3luTzRWTo85lf3N/aoNP/ugNuawqN1bLHie/mCLD8GIOgOudtbF/Ma5NWQbIsEjIwdafBgKqnPzNz/g8jZzM0NiJAl2x6ueKdQqFqVeN6blZ0BmiQLkVPP+iS4AwAUz81V5f0IdKvPcyM90IBSVsb9ZnUvzPqJ6ESEpy3GjPMeNqMxUS+PxtvJl03JUeX+RIDEyQcJRWRn1Tadf8ThfxVTNcCiqhFsvmFGQ8vcn1EOSJKX+68O61NvGYDCiXB/Bw/6EOCipGhXqzQLhqFL0bvZOGoDEyIQ50OJDICwjJ8OO6QU00Eo0zp8RcyofqOBUdp3sQSgqo8zrQnV+Rsrfn1CXi2bGBOR7x7pS/t57TvZCZkBFrhulXnfK359QFx7N2qlC3cjuk70IhGUUZTsxs4j2FBIjE4Qr42VVubDQQCvh4EWs+5v7MZDiupG/HY+dqFfNKDD10CJRuWhWTIzsqu9N+aV5NF9EbM6rSRQ4hyJySt/7nWOdAICLZxWS3wCJkQmz/WgHAODCmRSGF5GyHDeq8jIQlVnKpyruiNeLXEj1IkIyvSAT5TluhKJyylM1O+OHmHMpRSMkMwqzkJfpQHDE/TGp4t2jMb9x8SzaUwASIxNiKBhRnMpn5xRqvBpispwf76r5sDZ1Idf+4bDipKheREwkSVI2hHdTmKoZWRNwLhW9C4kkScqAy1QK1a7BIA62xgqm6YAbg8TIBPjb8S6EowxVeRmoMfFFRqKjxryRD2q7IbPY7JkSL80XEZWLZ8UOGe/GQ+epYMeJbgQjMko8LsygixOFhQvVtw53pOw9/3Y8Jnrnl3pQmO1M2fuKDImRCbD9aMxBfXYO5fZEhs8b+TSFdSM7TsSEzYUUFRGaC2fmQ5KAo+2DaOsPpOQ93zzUDgBYPb+I/IbA/N28YgCxgtOeoVBK3vMdnqKZTX6DQ2LkLDDGsD2uiC+dU6TxaoipUJGbgRmFmYjKDH9N0SmHn3AumEH1IiKTk+HAOfE7hd47PvVUDWMM2w7FbOyy+GZGiEl5jhvzSz2QWWqiI4wxJQJ38UxK+3NIjJyFYx2DaOkPwGmz4PzptOGIzhULSwAAbxxom/J7tfsCONYxCEkC2YYB+IxSNzL1VM2BFh/afAFkOKxYRbYhPKvnxQ6iPNo1FY62D6JjIAinzUIDNEdAYuQscCV8/vR8uB1WjVdDTJUrFpQCAN463IlAeGptnK992gogdtlaLt1VJDwj543IMpvSe209GNu0PjOrEC47+Q3RWT0/Ft1652jnlK8N4GJ35fR8so0RkBg5C9uPJOpFCPFZWO5BeY4bw+Eo3jk6tRPwKx+3AACuXlyWiqURGrO0KheZDiu6h0L4ZIptnPwEfdk8Su0agYVlXhR7nBgKRZV7qCbLW0diB9zPUEvvKEiMnIGBQFgZWkT1IsZAkiSsWRBL1by+f/KpmqZeP/Y09EGSgKsWlaZqeYSGOGwWpVjxpb3Nk36f1v5hHGjxQZKAv5tLfsMIWCwS/m5uzDbePDj5VE1bfwDvx4vePzefaolGQmLkDGw71IGIzFBTkIlqauk1DFcuiomRNw+1T3qq4qufxFI0K2vyUOShll6jcP2ycgDAyx+3IBydnG28GS9cXVaVi/wsats0Cp+bHxOW2w61g7HJpfFe2tcMxmJzZ6bl054yEhIjZ+APOxsAANcuKdd4JUQqWVaVi4IsJ3yByKRnjrzyCaVojMjFMwtQkOVEz1AIbx+ZXBqPn5xXUxeNobhgRgHcdita+gM40JL8Dc+MMbywpwkAcP2yilQvT3hIjIzDic5BfFjXA4sE/PO5ZDhGwmqRcPmC2Ebxl0mkamo7B7G/2QerRcKVCylFYyRsVguuXRITmC/sbUr695t6/UqBIrcxwhi47FZcGq8dfPajxqR//0CLD0fbB+GwWfB5Su2eBomRceDGdumcIrpt04BcodSNtCbdVfPneIrmopkFyKMuGsNxXTxV8+ahDvT7kxuO998fnITMYkPUaOqq8bj5/GkAgP/d0wRfkoMTX9gTq0P63LxieN32lK9NdEiMjEEoIuN/d8dORV88t1Lj1RBqcMGMfFTkutHrD+O5XRM/5TDG8DJ10Ria+aUezC3JRigi49V4+/ZEGA5F8czOmC39ywU1ai2P0JBVM/IxuzgL/lAUz+2aeOQsHJXx8scxMcLrkojRkBgZg60H29E9FEJRtpOq4Q2KzWrB1z4zHQDwm3dqEZlgseLWg+043jGIDIeVwvAGRZIkZcPgOf6J8Kd9zegfDqMi101+w6BIkoRbL6gGADz9fj2iE5xH8+6xTnQNhpCf6cBnZtOYiLEgMTIGvHD1n1ZUwGalfyKj8k/LK5Gf6UBT7/CETsCyzPDw1qMAgLUXVsPjolCrUfnCknJYLRJ2nezFhxMocmaM4an36wEAt66qhtVCd9EYleuWlsPjsqGhx4/tR84+Hp4xhke3nwAAXLOkDHbaU8aE/lVOYW9Dr3I3xRfPrdJ4NYSauB1WrL2wGgDw6PYTZ23Xe/XTVhxuG0C2y4avXTwjDSsktKLY41JStD/488GznoA/qO3B4bYBuO1W/PMKSu0amQyHDTfEbYML0DPx509a8VF9L9x2qxKNJU6HxMgIgpEovvX8JwCA65eWozIvQ+MVEWpz8/nVyHRYcbhtQLmdeSwiURk/ezMWFbnt4unwZlBUxOis/9xsZLtsONDiO2NdUSQq42fxiNl1y8rJNkzALauqIUnAu8e68P6J8S9WDISjePAvhwEAX79kBjVDnIFJiZHNmzejuroaLpcLK1euxM6dO8/4+ueeew5z586Fy+XCokWL8Nprr01qsWqz+a0TONYxiIIsB+77+/laL4dIA94MO760MhYB+9Grh8btnnhpXwtqO4eQm2FXoimEscnPcuLOy2YBAH76f0cwME73xM+3HcPO+h5kOqz4Nzr5moLKvAwlcnbnM/vQORAc83WPvVOL5r5hlHldFBU5C0mLkWeffRbr16/Hxo0bsWfPHixevBhr1qxBR8fYubP3338fN954I77yla9g7969uPbaa3Httddi//79U158KjnU6sOv3zoOAPj+NQvp4jMT8bXPzECxx4njHYP42n/vOu0irA9ru/H9lw8AiJ1usqlWxDTcsqoa0wsz0TUYwo9fP3xaKu+do534VdxvPHD9IpqqaSLu//sFmF2chc6BIO5+dt9pqbwTnYNKrci3Pz+PLlo9C0mLkYcffhi33XYb1q5di/nz52PLli3IyMjAk08+Oebrf/7zn+OKK67APffcg3nz5uGHP/whli1bhl/96ldTXnwqkGWGVz9pxdf+exciMsPl84vx+fi4cMIcFGY78dTa85DltOHDuh6s/+PHSnfNmwfbccuTOzEQjGBlTZ5SSU+YA4fNokRJ/+eDBqx96iN0DgQRlRk+qO3G3c/uA2PAl1ZW4Qs0qdlUuB1WbP7SMrjtVrx3vAs/evUQugaDYIzh+d1NuPqX72E4HMWKabm4+hwacnY2JJbEkP1QKISMjAw8//zzuPbaa5Xv33rrrejr68Of/vSn036nqqoK69evx1133aV8b+PGjXjppZfw8ccfj/k5wWAQwWAi7OXz+VBZWYn+/n54PJ6JLveMMMbw5qEOPLz1KA61xkb7FnuceGXdRXTXiEn52/Eu3PrkTkRkBosEFGQ50T0UQlRmWD2vGL/60lK68tuk/O7Dk/jBKwcRjMjKoLueoRAAYF6pBy9+4wKyDZPy/O4m/Mdzsb1MkoCagkzUdg4BAM6fnodffHGpqfcUn88Hr9d71v07qchIV1cXotEoiotHz1coLi5GW9vYY7Xb2tqSej0AbNq0CV6vV/mqrEx9dXo4yvD/vXwAh1p9yHLacNfqWdi6/hJTG43ZuXBmAR6+YQmynDbIDOiIn4CvX1aOLV9eRpuNiblp5TS8vO4izCnORs9QCD1DIXjddly/rBxP3LqCbMPE/OPyCjxw3SIsKveCMaC2cwhWi4R71szB7756Pu0pE8Sm9QLGYsOGDVi/fr3y/3lkJJU4bBbcs2YODrcN4N8+M51qRAgAwDWLy3DVolJ0DwbR7gtCkoAFZR5IEs2NMDtzSrLxp3UX4s1D7cjLdODc6jyaGUEAiKXpvrSyCq39w/iwtgfzSj2YU5Kt9bKEIikxUlBQAKvVivb29lHfb29vR0nJ2HUWJSUlSb0eAJxOJ5xO9a/evnYp5XiJ07FaJBR5XHSiIU7DZbfi78+hawCIsSn1umlfmSRJyXqHw4Hly5dj27ZtyvdkWca2bduwatWqMX9n1apVo14PAFu3bh339QRBEARBmIuk0zTr16/HrbfeihUrVuC8887DI488gqGhIaxduxYAcMstt6C8vBybNm0CANx555245JJL8NBDD+Gqq67CM888g127duGxxx5L7ZMQBEEQBCEkSYuRG264AZ2dnbj//vvR1taGJUuW4PXXX1eKVBsaGmCxJAIuF1xwAX7/+9/je9/7Hr7zne9g1qxZeOmll7Bw4cLUPQVBEARBEMKSVGuvVky0NYggCIIgCP2gSmsvQRAEQRBEqiExQhAEQRCEppAYIQiCIAhCU0iMEARBEAShKSRGCIIgCILQFBIjBEEQBEFoCokRgiAIgiA0hcQIQRAEQRCaQmKEIAiCIAhNSXocvBbwIbE+n0/jlRAEQRAEMVH4vn22Ye9CiJGBgQEAQGVlpcYrIQiCIAgiWQYGBuD1esf9uRB308iyjJaWFmRnZ0OSpJS9r8/nQ2VlJRobGw175w09o/gY/fkAekajYPRnNPrzAal/RsYYBgYGUFZWNuoS3VMRIjJisVhQUVGh2vt7PB7DGhaHnlF8jP58AD2jUTD6Mxr9+YDUPuOZIiIcKmAlCIIgCEJTSIwQBEEQBKEpphYjTqcTGzduhNPp1HopqkHPKD5Gfz6AntEoGP0Zjf58gHbPKEQBK0EQBEEQxsXUkRGCIAiCILSHxAhBEARBEJpCYoQgCIIgCE0hMUIQBEEQhKaYWoxs3rwZ1dXVcLlcWLlyJXbu3Kn1kibFpk2bcO655yI7OxtFRUW49tprceTIkVGvCQQCuOOOO5Cfn4+srCz8wz/8A9rb2zVa8dR58MEHIUkS7rrrLuV7RnjG5uZmfPnLX0Z+fj7cbjcWLVqEXbt2KT9njOH+++9HaWkp3G43Vq9ejWPHjmm44okTjUZx3333oaamBm63GzNmzMAPf/jDUXdWiPZ877zzDq6++mqUlZVBkiS89NJLo34+kefp6enBTTfdBI/Hg5ycHHzlK1/B4OBgGp/izJzpGcPhMO69914sWrQImZmZKCsrwy233IKWlpZR7yHyM57K17/+dUiShEceeWTU9/X8jBN5vkOHDuGaa66B1+tFZmYmzj33XDQ0NCg/V9u/mlaMPPvss1i/fj02btyIPXv2YPHixVizZg06Ojq0XlrSvP3227jjjjvwwQcfYOvWrQiHw7j88ssxNDSkvObuu+/GK6+8gueeew5vv/02WlpacP3112u46snz0Ucf4Te/+Q3OOeecUd8X/Rl7e3tx4YUXwm634y9/+QsOHjyIhx56CLm5ucprfvKTn+AXv/gFtmzZgg8//BCZmZlYs2YNAoGAhiufGD/+8Y/x6KOP4le/+hUOHTqEH//4x/jJT36CX/7yl8prRHu+oaEhLF68GJs3bx7z5xN5nptuugkHDhzA1q1b8ec//xnvvPMOvva1r6XrEc7KmZ7R7/djz549uO+++7Bnzx688MILOHLkCK655ppRrxP5GUfy4osv4oMPPkBZWdlpP9PzM57t+U6cOIGLLroIc+fOxfbt2/HJJ5/gvvvug8vlUl6jun9lJuW8885jd9xxh/L/o9EoKysrY5s2bdJwVamho6ODAWBvv/02Y4yxvr4+Zrfb2XPPPae85tChQwwA27Fjh1bLnBQDAwNs1qxZbOvWreySSy5hd955J2PMGM947733sosuumjcn8uyzEpKSth//ud/Kt/r6+tjTqeT/eEPf0jHEqfEVVddxf71X/911Peuv/56dtNNNzHGxH8+AOzFF19U/v9EnufgwYMMAPvoo4+U1/zlL39hkiSx5ubmtK19opz6jGOxc+dOBoCdPHmSMWacZ2xqamLl5eVs//79bNq0aexnP/uZ8jORnnGs57vhhhvYl7/85XF/Jx3+1ZSRkVAohN27d2P16tXK9ywWC1avXo0dO3ZouLLU0N/fDwDIy8sDAOzevRvhcHjU886dOxdVVVXCPe8dd9yBq666atSzAMZ4xpdffhkrVqzAP/3TP6GoqAhLly7F448/rvy8rq4ObW1to57R6/Vi5cqVQjzjBRdcgG3btuHo0aMAgI8//hjvvfcerrzySgDiP9+pTOR5duzYgZycHKxYsUJ5zerVq2GxWPDhhx+mfc2poL+/H5IkIScnB4AxnlGWZdx888245557sGDBgtN+LvIzyrKMV199FbNnz8aaNWtQVFSElStXjkrlpMO/mlKMdHV1IRqNori4eNT3i4uL0dbWptGqUoMsy7jrrrtw4YUXYuHChQCAtrY2OBwOxTlwRHveZ555Bnv27MGmTZtO+5kRnrG2thaPPvooZs2ahTfeeAO33347vvnNb+Lpp58GAOU5RLXbb3/72/jiF7+IuXPnwm63Y+nSpbjrrrtw0003ARD/+U5lIs/T1taGoqKiUT+32WzIy8sT8pkDgQDuvfde3Hjjjcola0Z4xh//+Mew2Wz45je/OebPRX7Gjo4ODA4O4sEHH8QVV1yB//u//8N1112H66+/Hm+//TaA9PhXIW7tJSbOHXfcgf379+O9997TeikppbGxEXfeeSe2bt06Ko9pJGRZxooVK/DAAw8AAJYuXYr9+/djy5YtuPXWWzVe3dT54x//iN/97nf4/e9/jwULFmDfvn246667UFZWZojnMzvhcBj//M//DMYYHn30Ua2XkzJ2796Nn//859izZw8kSdJ6OSlHlmUAwBe+8AXcfffdAIAlS5bg/fffx5YtW3DJJZekZR2mjIwUFBTAarWeVgnc3t6OkpISjVY1ddatW4c///nPeOutt1BRUaF8v6SkBKFQCH19faNeL9Lz7t69Gx0dHVi2bBlsNhtsNhvefvtt/OIXv4DNZkNxcbHwz1haWor58+eP+t68efOUinb+HKLa7T333KNERxYtWoSbb74Zd999txLpEv35TmUiz1NSUnJa0XwkEkFPT49Qz8yFyMmTJ7F169ZRV8+L/ozvvvsuOjo6UFVVpfiekydP4t///d9RXV0NQOxnLCgogM1mO6vvUdu/mlKMOBwOLF++HNu2bVO+J8sytm3bhlWrVmm4ssnBGMO6devw4osv4q9//StqampG/Xz58uWw2+2jnvfIkSNoaGgQ5nkvu+wyfPrpp9i3b5/ytWLFCtx0003K/xb9GS+88MLTWrKPHj2KadOmAQBqampQUlIy6hl9Ph8+/PBDIZ7R7/fDYhntcqxWq3IyE/35TmUiz7Nq1Sr09fVh9+7dymv++te/QpZlrFy5Mu1rngxciBw7dgxvvvkm8vPzR/1c9Ge8+eab8cknn4zyPWVlZbjnnnvwxhtvABD7GR0OB84999wz+p607CEpKYMVkGeeeYY5nU721FNPsYMHD7Kvfe1rLCcnh7W1tWm9tKS5/fbbmdfrZdu3b2etra3Kl9/vV17z9a9/nVVVVbG//vWvbNeuXWzVqlVs1apVGq566ozspmFM/GfcuXMns9ls7Ec/+hE7duwY+93vfscyMjLY//zP/yivefDBB1lOTg7705/+xD755BP2hS98gdXU1LDh4WENVz4xbr31VlZeXs7+/Oc/s7q6OvbCCy+wgoIC9q1vfUt5jWjPNzAwwPbu3cv27t3LALCHH36Y7d27V+kkmcjzXHHFFWzp0qXsww8/ZO+99x6bNWsWu/HGG7V6pNM40zOGQiF2zTXXsIqKCrZv375R/icYDCrvIfIzjsWp3TSM6fsZz/Z8L7zwArPb7eyxxx5jx44dY7/85S+Z1Wpl7777rvIeavtX04oRxhj75S9/yaqqqpjD4WDnnXce++CDD7Re0qQAMObXf/3XfymvGR4eZt/4xjdYbm4uy8jIYNdddx1rbW3VbtEp4FQxYoRnfOWVV9jChQuZ0+lkc+fOZY899tion8uyzO677z5WXFzMnE4nu+yyy9iRI0c0Wm1y+Hw+duedd7KqqirmcrnY9OnT2Xe/+91Rm5Zoz/fWW2+N+bd36623MsYm9jzd3d3sxhtvZFlZWczj8bC1a9eygYEBDZ5mbM70jHV1deP6n7feekt5D5GfcSzGEiN6fsaJPN8TTzzBZs6cyVwuF1u8eDF76aWXRr2H2v5VYmzE+EOCIAiCIIg0Y8qaEYIgCIIg9AOJEYIgCIIgNIXECEEQBEEQmkJihCAIgiAITSExQhAEQRCEppAYIQiCIAhCU0iMEARBEAShKSRGCIIgCILQFBIjBEEQBEFoCokRgiAIgiA0hcQIQRAEQRCaQmKEIAiCIAhN+f8BaTQvXNqOoBUAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "L_ops = None\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "id": "744f333f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [dens2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9c9d0b1f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5d45dab", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 123, + "id": "7d6bba1a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "L_ops = 0.2 * sigmaz()\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "id": "b3836bd3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [dens2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "50c713c3", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5c275074", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 125, + "id": "c42a6250", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 125, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "L_ops = 0.1 * sigmaminus() + 0.2 * sigmaz()\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "id": "00e85126", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [dens2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d75196d1", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4d90055a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "64a008a7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/torchquantum/pulse/SESolver_example.ipynb b/torchquantum/pulse/SESolver_example.ipynb new file mode 100644 index 00000000..c85d3944 --- /dev/null +++ b/torchquantum/pulse/SESolver_example.ipynb @@ -0,0 +1,443 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "290ddd1c", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import torch\n", + "import torchquantum as tq\n", + "from torchquantum.pulse import sigmai, sigmax, sigmay, sigmaz, sesolve, InitialState\n", + "import matplotlib.pyplot as plt\n", + "from qutip import Bloch\n", + "from utils import *" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f50d8c13", + "metadata": {}, + "outputs": [], + "source": [ + "n_dt = 160\n", + "dt = 0.22 # ns" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ed3f5bcd", + "metadata": {}, + "outputs": [], + "source": [ + "psi = InitialState(n_qubit = 1, state = [0])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "7d6bba1a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pulse = Schedule(0.1 * np.ones((n_dt,1)))\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "y_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "psi0_t = torch.abs(y_res[0][:,0]).tolist()\n", + "plt.plot([p**2 for p in psi0_t])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f2e92e55", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [sv2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d9805508", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc54e612", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e93d3ab2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import torch.optim as optim\n", + "\n", + "theta = np.pi/3\n", + "n_dt = 10\n", + "target_unitary = torch.tensor([[np.cos(theta/2), -1j*np.sin(theta/2)], [-1j*np.sin(theta/2), np.cos(theta/2)]], dtype=torch.complex64)\n", + "pulse = Schedule((0.2+0.1j) * np.ones((n_dt,1)))\n", + "\n", + "optimizer = optim.Adam(params=[pulse], lr=1e-2)\n", + "\n", + "losses = []\n", + "\n", + "for k in range(100):\n", + " H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + " solver_result = sesolve(psi0 = sigmai(), H = H, n_dt = n_dt, dt = dt)\n", + " unitary = solver_result[0][-1]\n", + " loss = 1 - (torch.trace(unitary @ target_unitary) / target_unitary.shape[0]).abs() ** 2 \\\n", + " + 0.1 * torch.abs(torch.diff(pulse)).sum() + 0.01 * torch.norm(pulse)\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + " losses.append(loss.item())\n", + "plt.xlabel(\"Number of Iterations\")\n", + "plt.ylabel(\"Training Losses\")\n", + "plt.title(\"Training from Default Initialization\")\n", + "plt.plot(losses[:100])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "eff7ede2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([[ 8.6753e-01-3.7338e-05j, 8.1141e-04+4.9739e-01j],\n", + " [-8.1141e-04+4.9739e-01j, 8.6753e-01+3.7338e-05j]],\n", + " grad_fn=)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "unitary" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "5b05b4a6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([[0.8660+0.0000j, 0.0000-0.5000j],\n", + " [0.0000-0.5000j, 0.8660+0.0000j]])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "target_unitary" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "4beeddc4", + "metadata": {}, + "outputs": [], + "source": [ + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "y_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "psi0_t = torch.abs(y_res[0][:,0]).tolist()\n", + "# plt.plot([p**2 for p in psi0_t])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "e6e91d33", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [sv2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5dc6a66e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9c29144f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "6619d6fe", + "metadata": {}, + "outputs": [], + "source": [ + "n_dt = 160\n", + "dt = 0.22 # ns" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "2ac0ee17", + "metadata": {}, + "outputs": [], + "source": [ + "pulse_values = np.arange(1,n_dt+1)/n_dt\n", + "pulse = Schedule(pulse_values)\n", + "# plt.plot(pulse_values)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "434713d8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pulse = Schedule(pulse_values)\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "lin_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "linpsi0_t = torch.abs(lin_res[0][:,0]).tolist()\n", + "plt.plot([p**2 for p in linpsi0_t])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "064b9a94", + "metadata": {}, + "outputs": [], + "source": [ + "# points = [sv2bloch(state) for state in lin_res[0].tolist()]\n", + "# sphere = Bloch()\n", + "# sphere.add_points(np.array(points).T)\n", + "# sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a1df3083", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "aa4e5844", + "metadata": {}, + "outputs": [], + "source": [ + "pulse_values = np.cos(2*np.pi/n_dt*np.arange(1,n_dt+1))/2" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "d0ca6da5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pulse = Schedule(pulse_values)\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "per_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "perpsi0_t = torch.abs(per_res[0][:,0]).tolist()\n", + "plt.plot([p**2 for p in perpsi0_t])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "c07831e4", + "metadata": {}, + "outputs": [], + "source": [ + "# points = [sv2bloch(state) for state in per_res[0].tolist()]\n", + "# sphere = Bloch()\n", + "# sphere.add_points(np.array(points).T)\n", + "# sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "249d6b73", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3947abb1", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/torchquantum/pulse/Two_qubit_simple_example.ipynb b/torchquantum/pulse/Two_qubit_simple_example.ipynb new file mode 100644 index 00000000..d7d87425 --- /dev/null +++ b/torchquantum/pulse/Two_qubit_simple_example.ipynb @@ -0,0 +1,234 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "290ddd1c", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import torch\n", + "import torchquantum as tq\n", + "from torchquantum.pulse import sigmax, sigmay, sigmaz, sigmaminus, sesolve, InitialState, mesolve\n", + "import matplotlib.pyplot as plt\n", + "from utils import *\n", + "from qutip import Bloch" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f50d8c13", + "metadata": {}, + "outputs": [], + "source": [ + "n_dt = 160\n", + "dt = 0.22 # ns" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ed3f5bcd", + "metadata": {}, + "outputs": [], + "source": [ + "rho0 = InitialDensity(n_qubit = 2, state = [0,0])\n", + "# state = [target, control]\n", + "pulse = Schedule(0.1 * np.ones((n_dt,1)))\n", + "H = H_2q_example(pulse = pulse, dt = dt)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "5079dd29", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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GFEqtpMmHWX90wBlHfyyJcCQbBpvXcvI7Tk7G/Nx7yTNiHHvDQ0imZVT5PZhRX17SZ/g8LizIiXxRE/lJjJyEgNettiWnq8+NQw/PyIJp2eZn3YNxdA+Kf4Mlj+Q3O1s4Kc9IToyQZ8QwmHiY0VCOCr+n5M9hQoaaPxrH23khmlJCn4xFuYTynYIaZCRGJoAWo7EciyVx5FhWPJw+CTFS4fdgrtr8bECPoRHHUWqzs+OZ31INSQJCkTh5HA2CiZF5zaV7RQBt/3svFKWuuQbxZucAAODMEioJ81E7sQq6/5EYmYB55KY0FOYVaW8oR01Z6QccoJWaimoZ8M7OXA+DRW2lh2iArHA8ZUq2EodKfI2BtSOYTIgGAGZNqYDP7cJQIq0aDYS+vNWZnatSk1cZTIy83xNFTMDmZyRGJoBipsaihmhKLGnLh5UF7wlTSM0I2Bo4Y5IWHKCF5N6kUI0hsLDyvJaqSX2O1+3Cqc1Z4Uj9lvRHj+RVxpQqP6ZU+aEo2es1RIPEyAQwy2J/XwzxFDXU0hsteXVyFhwAzAlmN973SYwYwt5wdoM7LTi5Aw7QXNLkGdGfZFrGBz1MjEx+XbFQDxlk+qMmrwZKT17Nh63N90Pi7YEkRiYgWO1HXbkXGVlRN2NCP7Tk1dpJf9apwawFF44kMDicmvTnERrReAqdA1k3PfvvPBnIM2Ic+/uGkMooqAp4MK2ubNKfp+bNkRjRnbdy+SJntE4ueZUxJ7c2RTTISIxMgCRJlDdiEP2xpHrAna6DZ6Qq4MXU2uzm+36PeIuRZ5jbt6nKj9rywq83H4/5rdVwSUBPNIFwhJJY9SQ/eVWSJn/A0f5nHFqYevKhT0DzjIgYqiYxUgBkGRgDW4gzGysmVZ2RD7MM9gjopuQZ5vY9VYcQDQCU+zyY05T9LCrx1Re98kUYLG/uyLERROLkcdQTvZJXGSxULaIXn8RIAZBlYAzsgJuvQ1ybcZq6GEmM6Mn7uc1NLzECAHNzh6WIyXY8w/apuTqtq5pyzeP4HvVb0g1ZVrAnlJ2r01v1mSsWQg1F4sKFqkmMFACzMHZ3R4Tt+88j+3qzh9DspsnnIDDmCOym5Jm9Pcwzot9czc6V935AYkRXdutU1psP2wPf7SIvll50DY4gnpLhdUu6JK8CYoeqSYwUwClNlfC4JETiaXQNUnxbL9ghNHtKhW6feZrAbkqeYWGvOTp6Rk7JiVAmSonJ0xONo28oCZekT9UTQ/MOi3XA8cy+3uwdMu0NFfCUcKvyeIiaxEpipAD8Hre6ce6mTqy6wQ6hU3T0jJzSVAlJAo7GknRFvU4MDCfRE83+tzTCM7KvZ4g8jjrBxEJ7YwXKfG7dPlcVIyHa//RCM8b0W1OAuOW9JEYKhJJY9eXoUALHhlOQJGBWo36LscznxvScy1O0xcgrLF+ktSaAKp0SjQGgvbEcLgmIJtLojZJw1AMjQjT5n7cnFEU6I+v62U7FCGMMEDdUTWKkQFjMlKo09IG5KKfWlulqwQFQqzREc1PyCvvveGqzfm5/IOtxZMKR8kb0YY8BSeEAMKO+HGVeNxJpGYf6h3X9bKeiekaa9AtTA+KGqkmMFAhzpe3vi1k8EntglIsSAE7Lta/eI9hi5BVWmaRnJQ2DWYUfUN6ILuzvNWZduVySeoP5QdoDdYHN1SlT9F1XooaqSYwUSP5CpNsrJ49RLkpAOzSpvFcfmLt3jgFzxSqp9pFnZNIoiqIaS7N0TApnzMx95gESI5NmYDiJvqEkAP3nalSoWqA9kMRIgbTVl8PtkjCSyiBM155PGiM9I6fmxUwpMXLyqHfS6BymAfLKe8kzMmmOxpKIxtOQJKiHkZ7Myhlk5B2ePMwYa60JoMLv0f3zTxUwiZXESIF43S51gR/opcU4WYz0jMyaUgG3S0I0nkY4Io6bkkf6hhI4GstacEbMlVre20NrarIwj8XU2jIEvPrmYQGad5j2v8nDvu969ljKh1W9iRSqJjFSBDPJMtCFkWRGvZNGzx4jDL/HjfaGrHAULaOcN5ibt62+DOU+/S045hkJReKIUqvxScFEAtun9EYVI7T/TZoPDMrtYYgYqiYxUgS0GPVhf98QFAWoK/eiodJvyN8QcTHyCAunndqkf4gGAGrKvJhSlf0O7COLe1Ko+SIGi5FQJI5YIm3I33AK+3r07z6dD6soFCn8SWKkCEiM6IOR+SKM9txcHaYyxElxwMCESAbzjlES6+Q40Jf972eUZ6S23If6Cl/ub9EeOBk0z4gxc9XemPUMDwynhLmjhsRIEcwiMaILzAI2IgeBwcI0B4+SGJkMh3L//WY0GCdGqLxXH9i+NNNAkU8G2eSJpzLoyBlJRu2B5T4PmnIex0P9YswViZEiYKVth/uHkaIuhCWzzwTPCDs8Dx0VYyHyCvvv126kGJlC5b2TJSMrqvA2KkwDkBjRg0NHhyErQFXAgykGhakBbc2KYpCRGCmCYFUAZV43MrKiKluieIyspGGwhXjk2AgJxxLJfs+zicYzGvQvFWXMJs/IpOkaGEEyLcPndqE1d2urEZAYmTz5YWpJkgz7O2zNitKkjsRIEbhckpqLQIuxNDKy1pjJSM9IU5UfAa8LGVlB57ERw/6OnekeHEEyk73i3MgDjonSQ0eHkUyTcCwFth/NaMj2QzIK6jUyecwwxgAtb+6gIN5hEiNFQnkjk+PIseyB4/e4MLXOuAPO5ZIwo16sxcgbLF+ENfwziubqACp8WY/jYUHi27zBWosblbzKULuw9tJNy6ViRgI/oHlGDlGYxp5Qr5HJcVBNiDT2gGN/AxBnMfLGQRPyRQBAkiQ1x4eqn0pDS141dq7aGyogSUAknkZ/rhkeURxsXRktHNsFy5sjMVIk1IVwcrDDZnq9sQsREM9NyRuH8oSj0bDuxiQcS8PoHiOMgNeN1pqsR5O8w6XB9kCj19X03Of3DSWFaChIYqRI6LKoydGhihHjDzjyjEwOlvhmtGcE0DZO8oyUhuoZaTTW9Q9oPWfIO1w8gyMpDOT6fhi9B1YHvGjI9YURYQ8kMVIks6gL4aQ4fJSJEePyRRhaaRttmqVglgUHaBszVakVTzylXa9gtOs//2+QQVY87PvdWOkz5IK84xHJICMxUiS15T7UlXsB0CFXCoeYZ8SEA44txI7+YWRkSrYrBkVRTMsZATQxQp6R4jncPwxFAar8HjRW+gz/exSqLh0mRtpM8AwDYhlkJEZKgCyD0lAUxdQwTUtNGXxuF1IZBV0DVN5bDD3RBOIpGW6XZGjVEyNfjFCVRnHs79WSV43sW8HQkvipL0yxHDZx/wPEav5IYqQEWFyWLIPiODacwlAutDWtzvjF6HZJaMuFg0RwU/LEwbzr6L1u47eJ1toyuCQgnpLRG00Y/vfsxAETc3sATYwcPDoMmTyORWG2GGF31IjQhZXESAmo8e1j/E8wT7CF2FwdQMDrNuVviuSm5AkzK2kAwOdxoSVXpUGhmuJg+1C7SXPFhGMyLaNviIRjMRw2OUxDnhGbw6ztI9TZsyjMtgoAsRYjT5iZL8KYQRU1JcFCn2Z4GwHA69aEIxlkxWFmmBrQBGo4ksBwku+CCxIjJcAWPS3E4jA7eQsQy03JE4dMrKRhUBJraTCjaJoJFWqMabk8InZ3ETExGVlR58osMVJb7kNNWbbggvd1RWKkBJhnpGsgjjRdwlYwWlmv+Z6RwyRGisKM23qPp43ESNHIeXcvtZnkGQE0g+wIGWQF0z04grSswOd2IVgdMO3vtqsX5vE9VyRGSiBYFYDXLSEjKwhF4lYPRxjUME2DeRYcW4iH+mOUbFcgiqLgUG7jYp4lM6BeI8XTE00gmclWPbXUmHfAMYOMPCOFc1gNp5UZfhVGPqKEqkmMlIDLJWFqLS3GYrEiZ2RqbRk8LgnxlIweqtIoiP5YEtFEGpJkXh4CQC3hS4F5JlpqAvCYUPXEaKNQddFYEaYG8jwjnK8rEiMl0kYVNUWRTMvoGsy5k01cjB63djswVdQUBtu0WkysegI0MdITTWAkmTHt74oM23+mmdALJh+2himJv3DMrlBjTFcvoeR7/yMxUiJazJQWYyF0DoxAUYAyrxtTKv2m/u02mquiYNa22RZcbbkXVQHPqDEQJ4d5Zs3MFwE08dM1MELdjQvECs8woM1VJ+f7X0li5P7770d7ezsCgQCWLl2Kbdu2nfT1P/zhD3HaaaehrKwMbW1tuO222xCPi51rwSb4CMW3CyJ/IZrRJTIfFlLjfTHyglqdYfIBJ0kSVdQUiVXCMVidzZtLywq6B2ldFYJVYRpNOMa5zpsrWow8+uijWL16NdauXYsdO3ZgwYIFWLFiBXp6esZ8/a9//Wt87Wtfw9q1a7F792788pe/xKOPPoqvf/3rkx68lVCYpjjMbvaTjyocaa4Kgl26ZkYb+OMhMVIczDNidpjGnZc3Rx7HwrDKM9JcHYDbJSGZkdHLcZO6osXIfffdhxtuuAErV67E/PnzsX79epSXl+PBBx8c8/WvvPIKLrjgAnzuc59De3s7LrvsMlx99dUTelN4p62OFmIxmN3sJx92qHbS/TQFoXpGakmM8M6RAetEfhtVPxVMJJ7CseEUAPPnyuN2oTlXSsyzQVaUGEkmk9i+fTuWL1+ufYDLheXLl2PLli1jvuf888/H9u3bVfGxf/9+PP300/j4xz8+7t9JJBKIRCKj/vEGc2GHInEk0pRsNxFajxHzDzg1TENipCA6LUqKBPJ6jXCe+c8D6YyMroFsuNvsnBEgr/EZGWQTwgRbQ4UPlX6P6X9/qgDGc1FipK+vD5lMBsFgcNTPg8EgQqHQmO/53Oc+h29/+9u48MIL4fV6MXv2bFxyySUnDdOsW7cONTU16r+2trZihmkKjZU+lHndUBSge0Ds/Bcz0HqMWLBp5g64roERrmOmPKAoiqVhGmoJXzihSByZXBOtpipzk8IBanxWDFblizCmCWCQGV5Ns3nzZtx999346U9/ih07duCxxx7DU089he985zvjvmfNmjUYHBxU/3V0dBg9zKKRJCnPMqDFeDIURbEsXgoAwSo/3C4JqYxCvUYm4GgsiXhKhiRBvX/ETPLDNIpCwvFksHyRqXVlcJnYRIuhlvdSr6UJsXL/A/Lz5vidq6L8RY2NjXC73QiHw6N+Hg6H0dzcPOZ77rzzTlx77bX44he/CAA488wzEYvF8KUvfQnf+MY34HKdqIf8fj/8fvOVfrG01Zdjb88QNT6bgMGRFIYS2UuazK7QALSYaefACDoHhtFsYqdK0WAVR8GqAHwe8yv/W2vLIElAIi2jbyiJKRZY/KJgVY8RRhsZYwWjlmBbEKYG8vLmOBYjRe02Pp8PixcvxqZNm9SfybKMTZs2YdmyZWO+Z3h4+ATB4XZnGymJbvlQlUZhMNdgY6XP1CZa+YhgGfCAlSEaIHsjbLAqKxa7OHYp84BVJdgMypsrHLaurJqrqbX8h9SKNn1Wr16NDRs24OGHH8bu3btx0003IRaLYeXKlQCA6667DmvWrFFff8UVV+CBBx7AI488ggMHDmDjxo248847ccUVV6iiRFS0lsi0aZ4MpsZbLajOYIiQwMUDbLOaauFctdaSGCmEI2oegjVzRXlzhcO+y1btgdPyKgp5dQIUndZ71VVXobe3F3fddRdCoRAWLlyIZ555Rk1qPXz48ChPyDe/+U1IkoRvfvOb6OzsxJQpU3DFFVfgu9/9rn5PYRHaZVH8qk0eYAvRygNuGvVEKIhO1dq2UoyUYcfhAa6T7XjAas8Iy5vb2zOEjmPDaG8074Zn0VA9jrXWhIhbcn83npLRH0uiweQu2IVQUo3RqlWrsGrVqjF/t3nz5tF/wOPB2rVrsXbt2lL+FNdQS/jC6BrMWk1WekbYXNEBd3LYd9mqME3+36a5OjksV6PNwrmivLmJicRTiMazOXNW7YF+jxvBaj/CkQSOHBvhUozQ3TSTgIVp+oboYq+T0WmxixLIT+AiL9bJ6OTAi8X+NoVpxieRziAUyfUYsahCA6C8uUJg3+O6ci/Kfeb3GGHw3m+JxMgkqKGLvQqCuf4tDdMIEDO1GkVR8sI01h1wrTXaXRrE2HQPxNWLJxsqfJaNg/LmJsbqfBHGVM77wpAYmSTT1MXI5wTzAA85Iy012ZLReErG0VjSsnHwTGQkjWiuBNvaBFa+LTgeyC/rNfviyXwob25iOgesD1MD/N/eS2JkkmguZbLixiKRzqiNxlotSt4CAJ9H61LJ62K0GnbPSUOFD2U+6yrdWEitP5ak8Oc4dHKQ2wNoByzd3Ds+PHiG8/8+rzmOJEYmCZUhnpxQLnk14HWh3kJ3MkAJxxPBQyUNAFQHPOr9HV10yI0JD0nhgNaltyeaQCojWzoWXuHBMwyMDlXzCImRSaJZBuQZGYv85FUr3clAfgIXuZTHgodKGiBbMspEPnmxxqabrSuLuwk3VPjg87igKJrhQYyGl5yR/DANj3lzJEYmSUsNeUZOBgtfWW0VANT4bCJ4qKRhUEXNyWEeIyvuD8rH5ZLUPZAMsrHRxIi1wpF1YY0m0oiMpC0dy1iQGJkkTO2SO3ls1O6rFm+aAP8JXFbDQ/dVRiuJkZPSzUlSJIA8MUJzdTypjKyWYFu9rsp8WuXVEQ69wyRGJgnbDEKDcbqefgx4cVEC/NfZW43V92fkw74vR2iuTkBRFNX4sdrazo6B1tV4hCNxyArgc7vQyEGjMZ69wyRGJkmwyg+XBKQyCvpidD398bBN0+o8BGD0ZXk8xkythpcKDUCbK/KMnMjAcArxVDZZlIcbqJnXk+6nOREWpm6pDcDlsjZnDuDbO0xiZJJ43C40qbeM0mI8nk5O4qWAFjMd4jRmaiWxRBrHhlMA+BAjrVQyPy7aLdh++D3WXzbaQhWF46J6hjkIUwN8e4dJjOgAO2i7OZxgK1EUhZuyNiAbM60r9wKgHJ/jYfH+Kr8H1QGvxaMZ3b+Cwp+j6VbLeq0X+EB+3hwJx+Ph4SqMfFjCM4+VTyRGdKCFY7VpJf2xJOIpGZLEhzsZ4HsxWkm+O5kHglV+uF0SUhkFvUMU/synW62k4WOu1DANCfwTUCvUOPA2Anl9sTicKxIjOtBKpW1jwg64KZy4kwG+F6OVMHFmdakow+N2obk612uERP4o2H8PXuaKramB4RSGkxT+zEfzDPMhHJs5zu8hMaID1BJ5bFhzMV5clIDmoSHPyGi6OLO2AVDjs3Ho5qh3DwBUBbyoYh1zOTzkrISnakJAM5x7onGkOeuYS2JEB5iF0kkLcRSdnG2agDZXtGmOhjfPCECNz8ZDDdNwYm0DlMQ6Fvm3YPMiRhoq/fC4JMgK1DvDeIHEiA5QAuvYdHEWLwWoQdN4sORDng44anw2Nmp+D0fCkbzDJxIZSSOWu+iRF4PM7ZIQrOYzrYDEiA6whdg7lEAyzZfry0q6OLk/Ix9KYB2bEJdhGkoMP56MrHDT0TMf8jieCPveNlT4EPDykTMH5BnPnAlHEiM6kH9ZVDhCi5HBW1kbkHeX0CA1Psunm0Nrm+dukVbRG00gIyvwuCRMqbK+oydjKoVpToC3fBFGM6cGGYkRHZAkiS7MG4Muju7PYLAE1nhKxuBIyuLR8EE0nkI0ka2C4Mozkts0SeBrsETjYHUAbg46ejJa1PJemisGTy3782lVzyq+5orEiE7QzZWjSaZl9OX6Q/B0wAW82mVRvC1Gq2AWUnXAg4pcVQQPMOF4bDiFeCpj8Wj4gJcbYI+HElhPpJvDpHBAW1cUprEpFN8eDbNmfW4X6nOHPy+o5b0RmiuA302zOuBBuS8ba+fNpWwVPIbTgLzKJwp/qrDvLC8NHxm8erFIjOgEdSEcDRMjzTUBSBI/7mSAku2Oh8dSUSAb/mwmj+Moujidq/zw58AwhT8B/jrlMnitKCQxohOam5I2TUA7PHizCgBtMZK1nUXzjPA3V6wLK3mxsvB28RrD73GjsTLrASXvcBbVM1LN17piZ1VPNIEUR43PSIzoBPVEGE2I4wOuhVrCj4JX1z8A8owch3ZJHn9zpfUaoblSFK0Em7d11Vjhh9ctQeGs8RmJEZ1o5TQOZxXdnFoFAHlGjoeJMvJi8Y/W8IzfuSKDDBgcSSGeynodmqr5KcEGAFde47MQRwYZiRGdYNb24EgKsQRdFsXc6nwecCQc82EHPW+ufyDvYi+aKyTSGbVCjWfPCHkcte9rPWcNzxitHObNkRjRieq8y6J4SwyyAp7zEPItOMr85zy/p5o8Iwz238DvcaGu3GvxaE6kleMbYc2G13wRBo/lvSRGdCSoupT5icNZhVbWxp8FxxZiIk2Z/9F4CkM5Tx5vvSuA/DJsOuDy87B4q1AD8vY/miuujTFA8+Tz5HEkMaIjvJZMmU1GVtTEKB4XY37mv9NdymwzqinzotzHT8MzBvv+9NG9Twjn1lSQV2s7Ny7qmKvlYvDobQT49GKRGNGRIC1GANmDIyMrcLskNFbylbzFaKbESAD8W3D1FT743K5c5r+z5yqcmytexUh+F2qnhz+1Sho+50oN03B0VpEY0RGtJwI/E2wF7IALVvm5uj8jH7XxmdPFyACfjZkY+Y3PnC4c8xsJ8girGklS+FPbAzkVjppnhB/PMIkRHaFNMwvvLkogv2SUn8VoBd0c5/YwqNdIFmbkNHF0W28+fo9bvfrB6QaZlt/D57pia6p3iJ/GZyRGdIQ8I1l4rs5gtHAYM7UClt/UyvFcNVNFDQCgJ5LNGeF5XdFcZeH1XhpGQ174k5e0AhIjOtJM1TQA8sva+LQKALplmSGGcKS5AjQjh1fXP0DVT0C2Qi2aq1DjdV25XPzd+0RiREeaKfMfAP9JkQBVPjF4bi/OoFuWs+3F1ZwRjsVIkDwj6jxVBTyo9PNXocZg64qXjrkkRnSkvtwHrzubsOnkzP8Q54l2wOgurE7O/OfdnQxQS3gAiIykkcgZOFM4zRkBKEwD8H0VRj5sXVGYxoa4XBKaqviaYCvg+ZI8Bsv8T6RlREac2b5/KJFWG57x7frPCkcnH3BM4NeVe7lsL85ooTCNEAIfyBeOfKQVkBjRmRaH540oiiLEYgx43ajNtdQOO9SLxQRzpZ9vd7JqwUWz/WucSFiAfBFA68JKxhjfxhgANLG+WJzsfyRGdCbo8FyE/lgSyYwMSYLqJeIVp7uUtQOOX7c/ADRWZvvVZGRFvSjOaahlvZyLEbameEmKtIJuNUzNbx4WkNcxl5O5IjGiM05vicw2ocZKP3wevr9eTQ6fK1GsbbdLQjCXJ+HUQ65HTV7lWzgyb+jgSArxVMbi0ViDKJ6R5prsd4mXkBrfp4WAaDFTh1pwgixEAOoB51wxkutbwbkYAfLL5p3pcRShrBcAqgMelOVyWpzqcRShXB7Qvks9kQQXSfwkRnRGK21z5qbZLcimCWibRdjhwpF31z8wuvrJibDvKO/rKr99v1PnSu1AzflcsTB6MiOjP5a0eDQkRnTH6U1/2EIUwTPS5PCOuaz8nHfXP0D9K0QJqQHODlXHUxkcy93Lw/se6PO41NvLedgDSYzojJYUxIfry2xYFRHvLkpAm6seDhaiFYhibQPUhVWEhmcMJxtkbJ4CXhdqyrwWj2ZieLppnsSIzrDJ5cX1ZTasS6YImyarInHipgloXoagAMIx6OADLp2R0RtlwpG8WDyT3/BMkvi8sTwfnnqNkBjRGZ/HhQYH31wpVFJkboy9DuxfoSiKGqYRwTPiZC/W0VgSspKtKmqo5F+MOLljrkjhNIAvkU9ixACaHdz4JyxIPwQAaMj1r5AVOK5/RX8siVQmK8B4vZI+H+YRCHOS+W8mbE1NyX1feSfo4FysHoFCnwBfIp/EiAE4tfHPcDKNaJy1F+f/gHO7JEypdGZ5L/NgNVb64HXzvw2wzX0klUEk7qz2/Wo4TYA1BeSXYTtrTQFi3MuVD0+hav53IQFRWyI7bDGyA67C50ZVgP/kLWC0xe0kVA8W511yGQGvW00I5MGKM5NwVExru3fIeeFPbV2JIRx5yu8hMWIALQ51U4oWLwWc61IOC2bBAXxZcWYSHhRrXU2pcm77fuHCNBylFJAYMYCgQ7uwavkiYlgFQH4XQusXo5loHT3FmyunerFEEY754U+nharDAiWFA5oX69iw9e37SYwYgFYu5awurKJZBYBz49si9Rhh8NQTwUxCgrn+gTyDzEHratSN5YKsq5oyL/y5O8R6LBb5JEYMwKmlbSKGadgGz+LyTqFHwLlyamdPdkiI4hkBtFC1k+YqMpJGIi0DEMc7nN++3+rwJ4kRA2BWQSSexnDSOZn/olzmlY9qbTtMOKpZ/0LNlTMrn0RcVzzlIpgFC9HUlHkRyF0WKAK85M2RGDGAKr92c6XVri8z0cI0YlgFQN6mGXXOpgloYRpRLDgg/y4h56ypeCqDwZHsXSciiZEmByYbhwXMwwL46TVCYsQAJElypBUnWvIWAARzpa0DHCRwmUUqI+NoTJxOuQxeNk0zYQI/4HWhOuCxeDSFw9aVk4wxEfOwAH7y5koSI/fffz/a29sRCASwdOlSbNu27aSvHxgYwM0334yWlhb4/X6ceuqpePrpp0sasCgwK84puQiKomiWgSC9KwCgusyDgJePBC6z6I0moCiA1y2hrtxn9XAKRq18clD7/vxwmgh3nTCcmGwsYs4cIHCY5tFHH8Xq1auxdu1a7NixAwsWLMCKFSvQ09Mz5uuTySQ+8pGP4ODBg/j973+PPXv2YMOGDZg6deqkB88zTrPiIiNpxFNiJW8BzIvFx2I0C606IwCXAO3FGY2VPrgkICMrqmfH7oh0vUI+jvQMCxqm4WWuihYj9913H2644QasXLkS8+fPx/r161FeXo4HH3xwzNc/+OCD6O/vxxNPPIELLrgA7e3tuPjii7FgwYJJD55n1AZNDkmMZCGa2nKxkrcA51lxPYJumh63C425/hVO8WIJa23nJfGPJJ0R/hR1rpo5McaKEiPJZBLbt2/H8uXLtQ9wubB8+XJs2bJlzPf88Y9/xLJly3DzzTcjGAzijDPOwN13341MZvwvaCKRQCQSGfVPNIIOC9OIGKJhOE2MhATr6JkPL/Fts1AbngkmHPOT+J2yrtSkcMH2wPxmglZeQlmUGOnr60Mmk0EwGBz182AwiFAoNOZ79u/fj9///vfIZDJ4+umnceedd+Lee+/Fv/3bv437d9atW4eamhr1X1tbWzHD5IImhx1wIlZnMJo5cVOahWh3neTDNnqnVD+FBE2KdGISv2idchnsu5VMyzg2nLJsHIZX08iyjKamJvz85z/H4sWLcdVVV+Eb3/gG1q9fP+571qxZg8HBQfVfR0eH0cPUnWAVcyc7ayGKtmkCzmszLtpdJ/moB5zDPCMizpWTkvhlWUFPVLzWBgDg87jQUJFNZLfS41hUrVhjYyPcbjfC4fCon4fDYTQ3N4/5npaWFni9XrjdWh7BvHnzEAqFkEwm4fOdmM3v9/vh94s1ocdzvOtLpEz4UgjnZf2LhtMSWJlXoblGvDXW7DThKLAYcdK9T0djSWRkBZIENa9JJFpry+B2SZY26SzKM+Lz+bB48WJs2rRJ/Zksy9i0aROWLVs25nsuuOACfPDBB5BlWf3Z+++/j5aWljGFiF1gC3EklUE0Yf8urKJmkgPO2jSBvH4IgsW2gfxcLPvPVX65vJAiv8o5YRr2jA0Vfnjd4rXv+uOqC7DtG8uxpL3esjEU/V9t9erV2LBhAx5++GHs3r0bN910E2KxGFauXAkAuO6667BmzRr19TfddBP6+/txyy234P3338dTTz2Fu+++GzfffLN+T8EhZT632qTICS5lLWdEvE0zP5vcygQus1DDNILFtgFnXcAmark8Q2sJb38vVo/A3kYAXHjui27pd9VVV6G3txd33XUXQqEQFi5ciGeeeUZNaj18+DBcLk3jtLW14dlnn8Vtt92Gs846C1OnTsUtt9yCO+64Q7+n4JRgdQCR+BDCkQTmBKusHo6hiHjxGoNt9PGUjEg8jZoyr8UjMo5YIq166kScK+Z563FAHoLI5fJAfvt++wvH0KC43kZeKKm/8KpVq7Bq1aoxf7d58+YTfrZs2TK8+uqrpfwpoQlWB7C3Z8j2bkqRk7cAIOB1o6bMi8GRFMKRuK3FCPsuVvo9qPSL016cwTb7/lgSiXQGfo94h3ShiFwuDzgriV/U5nQ8IV5wSyCYxW33+PbRWBLpXPLWFAGTtwDnXE8vcgk2kPUS+DzOaN8fEjicBvDTv8IMetR7ucRcVzxAYsRAtJbw9t402QHeWOmHR8DkLSDvllGb5yKInBAJjO5f0WNzka96G6vEPODYmnJCEr+ol+TxhJgnhyCoJaM2P+DsYBWowtHmuQgil4oy1ITjQXvPlcidcgGg3OdBVS6J3+6hGtFFPg+QGDGQoEPCNHZI3nJKS3j1kjyBhaNTuhurwlHQMA3gnL4wYRusK6shMWIgTQ4L04icvOWUklH2XRTZgmOi1zFiRNAwDeAM73AqI6NvKAlAXC8WD5AYMRC1mVY0Dlm2bwKXWmMv8EJUGzRRmIZ7WC8H+4uRnHAU2DPihCT+3tye4XVLqC+3byNPoyExYiCssiSVUXBsOGnxaIxDS94S14JTGzTZ2IIDtDCNyGLECe37M7KC3iHxkyKDDvAOq57hqgBcLuubh4kKiRED8XlcaKzMKmU7x0ztYG2zsfcOJZCxqRdLURT1UBBZODrhgDua+x66BL3rhOGElvCUL6IPJEYMpskB8W07LMbGSj9cUtYiPTpkz0Pu2HAKyUyuvTglG3MN8/pMqfLDLbC1rbWEt+9ciXzXE0+QGDEYtaLGpovRLslbbpeEKaoVZ08xol3m5VMbh4kIW1OxZAbReMri0RhD2AaJxkB+5ZM91xQg9iWhPCHujiQIQZsvRjslbzXbPBfBDvkiwOj+FXZdV3aoUAOckcQv8iWhPEFixGBUy8Cm2eR2St6ye/+KHhtZcHYP1diliZYTkvjtUE3IAyRGDEZrCW/vTVPkfBGG3UNqrDmdyKWiDLvfJWQX17/P40JDhb2T+EXvlMsLJEYMRjvg7LkQ7ZS8ZfsDLqp5sUSnyebrKmQj179TvMOiC0erITFiMHbviaC6k21gbTepc2XPAy5sIwvO7sKxxyZhGgBoZhcb2nCuRpIZROLZSwDtIBythMSIwTALrm8ogXSurNJOiH4lfT62D6mx2HaN+HNl95wRuyQbA/kt4e0n8lm+SJnXjepcUjVRGiRGDKahItsnQFGglsDaCfXGXhu4/u1+wKnC0RZzlRVUdvQ4xlMZDAxnS5bt4Bmxc5hGyxfxQ5LETuC3GhIjBuN2SWpGuR0POTslb7GN/9hwCvFUxuLR6Eu2H4x9Eljt3IWVPZPf40J1mfjWdtDGYRp2lxWFaCYPiRETCNq4C6Gdkreqyzzw55qB9drswry+oQQUxR79YAB796/QwmkBW1jb2i3L9lpTQH65PImRyUJixATsej9DfvJW0AbWtiRJqtfAbu5/5sGyQz8YINsmXZKy/Sv6bda/QhX4NginAfZuCa/NlfjGmNWQGDEBu3ZhzU/eqvKL704G8q04e22cdko0BgCv24WGCnuKfDX0aQOBD9g7iV9t22+TubISEiMmYNdmWnZM3mIHAHs2u2CXjp75sKogu62rnijr3WMP4ciS+GUbJvGH1KaP9llXVkFixAS0bHJ7eUbsmLxl15Ba2IaxbbvmItgpKRywdxJ/D4VpdIPEiAkEbdq/wo7JW8zd2mM34WizMA2Q16TOpl4su4RpAHt6hxVF0TpQ22gPtAoSIyZg126RmuufDjjesWWYJq+ixk7YMSnSjt7haCKNkVwLABIjk4fEiAkwq8Bu/StCNrQK2AFgP8+I/bxYdrz3Kd/atlNSpB27G7PrFaoDHpT53BaPRnxIjJhATZkXPhv2rwjbMHkrvwxRUezTv8KWYsSGycaRuD2tbbVjro3mikI0+kJixAQkSbJlzNSOyVusVfpwMoNoIm3xaPRhVD8YG4XUWAKrncI0bE3VlHkR8NrH2rZjmMaOAt9KSIyYhN0y/+3qTi7zaRde2cWlzDbNcp8blTbpBwNowqpvKIlk2h79K7QL8uwjGgF7JvGzTrl2Sgq3EhIjJmG3lvD5yVt2uHgtHy1UYw/hmJ+8apd+MABQX+GD1519nt4hu8yVPV3/9vQM54wxm82VVZAYMQm7dfa0c/JW0GYVNVpjJntZcJIkqULYNuvKpq5/tv8dG04hkbZHEr/d+sFYDYkRk7CbZWBXCw7QPD12ufK8x8ZzpXqxbCIc7ViCDQC15VoSv11uWmb7g91CalZBYsQk7HY/jV0tOEBrM26XTTNk0wMOsKPIt+cBZ8ck/p6I/TpQWwmJEZNgLnK7WNshG4sRu4Vp7FiCzWBerJBthKN9Dzg7JfHLsmJbL5ZVkBgxCS2bXPyFCNjXggPsHKax31yp7fttY23b94DTvMPiz1X/cBJpWYEkAVNs1NrASkiMmARbiEOJNIZs0L9CtQpsVNbL0A44ewhHJ4RpQjY44DKyot3Ya8O5spN3mHlNGyr88LrpGNUD+q9oEpV+j9rjwQ6WgR1bwTPyY9uyLHYX1mw/GPuH1Oywpo7GEsjIClwS0Fjps3o4utNsI++wnT3DVkFixESabJTAZccbexmNlX5IEpCWFfQPJ60ezqSIjKSRyDUEs6M72U7hz/Bg9hkaK/3w2NDatlMuVph6jOiO/b7xHKO2rxZ848x3J9txMXrdLjRU2EM4svBFXbm92osz2AEXTaQREzz8aefQJ2CzMA0zxmw6V1ZAYsRE7FLadnTI3u5kQCvvFX2u7ByiAewV/lTbi9usozHDXl4sdi+XPefKCkiMmEjQJm3G2fjt6k4G7FOGaOeyXkaTTZJY2QHHhLDdsFMSPxOOdp0rK7DnScIpdmkJH7K5OxnIu2VU8LnSeiHYd9O0S2Kk2tXYptZ2pd+DitzVEaKXYrO8FzuLfLMhMWIidsn8V61tm26agHbAiT9X9q16YthlXTkhD8Eu3mE758xZBYkREwnaJIFLS7Szr7Wt5feIvWk6IUyjVmkILkbsnt8D2MM7nEhn0B/LVtmRGNEPEiMmkn8/jaKI27+CuSjtvBDtYm07oWU1E47ih2ns37vCDkn87Hvm87hQW+61eDT2gcSIibA+D8m0jMGRlMWjKZ1w1L73ZzDsI0bs2wqeYQfPSCKdwbHh7J5gb+EofpgmXzRKkmTxaOwDiRETCXjdqMspaaEXoyM8I9nDu28oiVRGtng0pZGRFfQOUc6ICORb2zVl9rW21cRwgUPVdr5ewUpIjJiMHaw4tpHY+YCrK/fB685aPb1RMYXj6H4wdvaMaGEaUcOf+eE0O1vb2lwJvP/Z+GZlKyExYjKil4zGUxkMOMCd7HJJedfTizlXbNOcUuWH22XfA47NUzIjq6EO0Qg5IF8E0PYMUdcU4Iw8LCsgMWIywSqxLQO2EANeF6rLPBaPxlhEt+KcUJ0BZEMbDRXZTsCiinwnlGAD9kjiZwn8dheOZkNixGRET+DK3zTt7E4GxJ+rkEPECKB5HEW1uO188WQ+dkjid4rINxsSIyajNf0Rc9N00gEnen5Pj0Nc/4DWYVZUL5ZTkiIDXrdaDiuqyKcwjTGQGDEZFqYJC5oU6RQLDhC/SsPu7cXz0a6nF3Ndac3p7C8cRW58piiKowwyMyExYjLqATco3kIE8hueOWDTFLyZlhPaizOCgpeMMuHoBGtbZO9wJJ5GPJUt9Scxoi8kRkyGfYF7c2WXouEkq0D0zH8nxba16+nFmytFUZw1V1XidmFlY64OeFCWu/SP0AcSIybTWOmDJGUbUh2NiWdx9zgk6x8QvwybXebliJyR3D1JIgrHaCKN4WQGgDPWlciJ4dq9XPafJ7MhMWIyHrdLbUAlovs/5KDFyA7xaDyN4WTa4tEUh9Mu82qqEveA63GYtS3y/TRaWa/915TZlCRG7r//frS3tyMQCGDp0qXYtm1bQe975JFHIEkSPvnJT5byZ22DqNfT57uTnXDAVQW8qMgdDqIdck5pL85gh0PfUEK49v0s6dYpB5zWEl6sNQU4K/RpNkWLkUcffRSrV6/G2rVrsWPHDixYsAArVqxAT0/PSd938OBB/Ou//isuuuiikgdrF5hlIJpLeXAkhUQ6u9GzfgF2R9SKmh61Zb8zLvNqqPDB45KgKFlBIhJOc/2LnN/jpERjsylajNx333244YYbsHLlSsyfPx/r169HeXk5HnzwwXHfk8lkcM011+Bb3/oWZs2aNakB24EmQWOmTDzVlXsR8NrfnQxopZaiiRFmbTtl08y272dzJda6YhVATQ4owQa072RPVLwkfqe07beCosRIMpnE9u3bsXz5cu0DXC4sX74cW7ZsGfd93/72t9HU1IQvfOELBf2dRCKBSCQy6p+dYHX2olkGTmlZnY+oITWtb4Vz5oqVjIYEK5tXb8GuccYBJ3ISP4VpjKMoMdLX14dMJoNgMDjq58FgEKFQaMz3vPzyy/jlL3+JDRs2FPx31q1bh5qaGvVfW1tbMcPkHlETuMIOTN4SNfNfvVnZIdY2kCfyBes14jSRL3ISv9NCamZiaDVNNBrFtddeiw0bNqCxsbHg961ZswaDg4Pqv46ODgNHaT6iHnBOaVmdj6jlvU6ztoG8XCzBPCNO6t3DENEgS2dk9EadJRzNpKhrVxsbG+F2uxEOh0f9PBwOo7m5+YTX79u3DwcPHsQVV1yh/kyWswmQHo8He/bswezZs094n9/vh99v301UTeASzoJzXrxU3DCN8zZNrbOnWCLfSVcsMIJVAbyNiFBzdTSWhKwAbpekenYI/SjKM+Lz+bB48WJs2rRJ/Zksy9i0aROWLVt2wuvnzp2Lt956C7t27VL/XXnllfjwhz+MXbt22S78UijsMO8bSiKZFqcMURUjDnJRahacOJsm4LykSEDMMI0sK2pzOid5HEVsCc88blMq/XC77F+hZjZFeUYAYPXq1bj++uuxZMkSnHvuufjhD3+IWCyGlStXAgCuu+46TJ06FevWrUMgEMAZZ5wx6v21tbUAcMLPnURduQ9et4RURkHvUAJTa8usHlJBOLGsLb+0V1EUYcpktTCNc+aqWcAE1qOxJNKyAknKJnY6BREvy6NKGmMpWoxcddVV6O3txV133YVQKISFCxfimWeeUZNaDx8+DJeLGruejGwZYgCdAyMIR+LCiBEnxrZZaW8iLWNwJIXacv4PjKFEGrFce/Emh/SDAcTMQ2Bjbaz0w+N2zr4p4lw5MZxmJkWLEQBYtWoVVq1aNebvNm/efNL3PvTQQ6X8SdvRVO1H58CIMOW9qYysNpNy0mL0e9yoK/fi2HAK4UhCCDHCNvgqvwcV/pKWuJCwZONIPI2RZEaI1upO6micj4hJ/E40xszEOVKcM5oFW4x9QwkoCuBxSWio4P9A1hPRurCqJdgOCtEAWfFVrrbvF2OunOr6F7GZoBqmdti6MgsSIxbBDrhuQeLbLA7fVOWHy2HJW2yuRGnfH44684CTJEm8ucodcE5qTgdoxtjRmDhJ/NTwzFhIjFiEcNY2KxV1oFXADnVRQmrqXDmokoYhWi5CaHAEANDisAOuvsIHXy5HRpy5cqbINwsSIxbRIljmv2oVOPKAEyukFnJomAbIv4RNkLlyqOtfkiQEa8QSjk7N7zELEiMWIZo7We2+6rBNExBvrtQbex1UScNoFmyumGfEieuqpTpbRShCqHokmUEkngbgvJCaWZAYsYh8z4ii8H9zpXbxmvMOONGuPHdi91WGaO37mRerxYFiRKSLDZm4LfO6UR1wToWamZAYsQhmCY2kMoiMpC0ezcQ42UUpWhdWZ4dpxHH9xxJp1dp2onBUDTIB5ir/gjxRGh+KBokRiwh43agt9wIQZTE6r/sqgz1z71ACGZlvL5aiKFqYxsFzJYJwZOu+0u9BVcBr8WjMRw1/CuAZUT3DDgx9mgWJEQtpVst7RyweycSw3hVOjJc2VPrhkoCMrODoEN+H3LHhFFKZrGCa4sDLvI5v388zTmzZn4+onhHCGEiMWEizIJdFxRJpRBNZd7ITF6PbJWFKlRihGmZlNlb64PM4b3kf376fZ1jiphO9jYBYdwmFBp2bh2UWztutOIJZBrxnk4fz3MmVDmovno8oXiwn3tabD2vfDwggHB1ubTfnebFkzsOf1PDMeEiMWIgoMdOQgytpGM2CuJSdXJ3BEKUUO+Rwz8iUqmz4My0r6IvxLRydnMBvFiRGLESUmGmPg5NXGS01YvRE6B5wbt8KhijdjbsdnjPidbvQmMtrEsUgo+6rxkFixEKacwecOAvRmZsmIE7H3G7yjGjlvZzPFRNLTp4rEdaVoiiqQebkPdBoSIxYiCjdIrU7GZy7EJvV/B6+c0ZC6gFXZvFIrEPNRYjyva66aV0JEf48NpxCMpO9zM/JoWqjITFiIWwhDgynEE9lLB7N+LC+Fc0OXogtgnixyDOS34WV3zyEZFrG0VyehJPnqlmAvDk2tvoKH/wet8WjsS8kRiykOuBBmTf75RZhMTrZgsuvfOK1f4WiKJQzAjFyRnqicSgK4HO7UF/hs3o4liFCqDrs4CaCZkJixEIkSRKivFe968TBB1x+/4pjw3z2r4gm0oglsx42J4uRZgHEiNay3+/o9uLNuZt7eQ7ThFVjzLmeYTMgMWIxvFtxsuzs9uIMv8eNxsqsBctr3gg74GrKvCj3ObMfDKAdGr3RBNK5WD9vqLk91c7N7QGA5mr+PSMhKus1BRIjFsO7Z+RoLIlURoEk0b0MvOeNUL5IloZKPzwuCbKSvU+IR5x8mWE+IoQ/tRvLnT1XRkNixGK0lsh8WtvMCzCl0g+v29lfl2bOhSP7DjldjLhdkurF6xrgda5IOALH3V4e5/P2cvYdanX4XBmNs08XDuC9tI0txJZaZ7uTgXwrjk/hyOaq2cFlvYzWWr7nqpt69wA47vZyTkU++w7RHmgsJEYshvfSNrYQySoQwTNC1jaDCbJu8oxwD+/9lth6pz3QWEiMWAzvnhFt0ySrgPdukd0Ov3gtH3ZwdHHqGVHvpaG54jpUPZRII5oLH5FnxFhIjFgMW4i8Zv53MaugljZN3jP/Q6oXizZNNaTGoWdElhW6eC0PTeTzl2zM+vZUBZx7Y7lZkBixmMYKvjP/2WIkz0h+HgKfmf9Ov3gtH2bF8pgz0hdLIC0rcEnZm2udjnbLMn9zpRpjtP8ZDokRi3HlZf7zmIuglouSZ0Sdp5FUBpERvjL/893JJEa0w6OLwzUVznkAGqlCDQDf4U/VGKP9z3BoJXBAM6eLMSMrai4LWQbZzH/Wupu3XAQWoiF3chZ2ePQNJZBM8xX+7KYS7FGoycac7X+AJmbJM2w8JEY4gG1KXQN8HXC90QQysgKPSyJ3cg5eq5+o4dloGip88HlcUBT+uhtTOG00rZzuf4DmGaFKGuMhMcIBU3Pxbd4aNDHrP1gdgNvl3Psz8uG1Y243WXCj4PneJ3botlJ1BgAtvycSTyMa5+veJy1MTXNlNCRGOIBXzwirRCBrW4PXMkSaqxPhtUkdc/1PpQMOAFDp96CmLNv4jDvhSH2WTIPECAe0cpr5z8ZD7mQNba742jRZJQLNlQbzEnHncSTPyAnwaJApiqKJfJorwyExwgFsU+rkbtNkPUZoITKaOa18opyRE+HWM0Ji5AR4DFUPjqQwksoAoHVlBiRGOIAtxL6hBOK5Lz8PMGubFqIGrwec1tGTDjhGC4cHXCojqwm11EhQo1WdK37WFfve1Ff4EPC6LR6N/SExwgG15V6U5b7sPFVpqJfk0QGnkn8/DU+Nz+j+jBNp5VA4hiNxyArgc7vQWEEVagwexQiVYJsLiREOkCRJtZJ4XIxkwWkwYTac5OfK8+FkGoMj2SoEyhnRaOGwf4V2C3YALqpQU1H3P46EI/UYMRcSI5ygWgacbJypjIyeaLZTJC1GjTKfduU5LxY3O+Aq/R5UBbwWj4Yf2AHXH0tyE/4ka3tsWjkMqYXIGDMVEiOcoLav5sQzEo7EoeTcyQ25rqNEFpbj03mMj7nqzH1nqFR0NDVlWviTF+9IJyWvjkl+RaEs8xH+7KYwtamQGOEE3mKm+V0iyZ08GlWMcDJXTBRNraNNMx9JktS28N2czFUXCccxCVb54ZKAVEZBHycXhnaRZ8RUSIxwAvvC83LAdQ2QO3k82KHPj2dkGABtmmPRylneCJXLj43H7VIvouQlVE1djc2FxAgnTOXUM0Kb5omwuTrCyVyxA25qbbnFI+GPZs4qaqjHyPjw5B1WFIV695gMiRFOaMnr7MlDyWg3eUbGhbucEQrTjIt6CRsn1raW30Pr6nh4EiNHY0kk0zIkiSrUzILECCewQ384mVHLNK2kiy6IGhd26POwaQKUwHoyVJHPwVxF4ylEc+Xg5Po/Ee32XuuFI0tenVLph9dNx6QZ0H9lTgh43WiszFat8JA30k0XRI0LO/R7ogkk0taWjKYzMkK5jp7TyDNyAjzd3MvGUFPmRYXfY/Fo+IMnzwhLXiVjzDxIjHAET7X2VNY2Ptn20Nml023xXIUicWRkBV63hCmV1NHzeJhA40HgU1nvydF6LVk/V8yTRsaYeZAY4Qheeo0MJ9M4GksCoDyEsZAkiZvy3vyW/VSCfSIsqTcaT1se/uyifJGTwlMX6iO5PCzyNpoHiRGO4MUyYAmR1QEPasqoo+dYtHKSxMrKeilfZGzKfFr488ixYUvHQpU0J4cZY31D1nfM1cQIVaiZBYkRjtAsA2td/7QQJ4YX9z9V0kzM1Nz3+IjFwrGbeoycFJ4uDD2SE/nkGTEPEiMcwUsCF7MgaSGODy9hGqqkmRj2PbZajHRSufxJ4enCUDLIzIfECEfwI0ZoIU4EL11Yj5BnZEI0MWJxmGaQhONEtHIg8qPxFAaGs/lFtK7Mg8QIRzCrIByJI52RLRsHJW9NDEuMtNozQnedTMw0DsI0GVlRQw8UphkfHtr3szVdV+5FJZVgmwaJEY5orPDD53ZBVqD2jrACCtNMDLOYrLxlVFEUCtMUwLRa68M0fUMJpDIK3C4JTVVUgj0ePCSGH+knz7AVkBjhCJdLu2XU0sVIYZoJCVb54XZJSGUU9Fp0y2h/LIl4KutBa6Fy0XHhIUzD1lRzdQAe6ug5LupcDVg5V2SMWQGtCs6YXp8VAIf7rVmM1GOkMDxuF5pzt4xaZXEzr0hTlR9+j9uSMYgA+x5b2WuEDrjCaMvtfx39PBhjNFdmQmKEM5g3osOqA456jBSM1RU1VNZbGOU+DxoqrO01cvho9u8yY4MYm7Z6bU1ZlTdHnmFrIDHCGWwxdljkGaGFWDhWV9RQe/HCsbq8tyMngtpIjJyUYFUAPrcLGVmxLIm1g7xYllCSGLn//vvR3t6OQCCApUuXYtu2beO+dsOGDbjoootQV1eHuro6LF++/KSvdzrTVTelVWKEFmKhaJ4Ra+aKiZFpJEYmxOqKGhZ2Jc/IyXG5JHXv6bDIi0UGmTUULUYeffRRrF69GmvXrsWOHTuwYMECrFixAj09PWO+fvPmzbj66qvx/PPPY8uWLWhra8Nll12Gzs7OSQ/ejrSpYRpaiLxj9cWGFKYpHKuTWFkOBPN8EuMzzUKDLBJPqXlFtK7MpWgxct999+GGG27AypUrMX/+fKxfvx7l5eV48MEHx3z9r371K3z5y1/GwoULMXfuXPziF7+ALMvYtGnTpAdvR5gbNxxJWHI/AyVvFQ4vYRoq650YK8M0qYyM7lzDszYS+RPSxjwjFiSxsrVMPUbMpygxkkwmsX37dixfvlz7AJcLy5cvx5YtWwr6jOHhYaRSKdTX1xc3UoeQvwis2DgpTFM4U2s1a1tRzO81QjkjhWNlmKZrYASyAvg9LkyhHiMTooaqLfBikWfYOooSI319fchkMggGg6N+HgwGEQqFCvqMO+64A62traMEzfEkEglEIpFR/5yCJFkbM6XFWDjT6sogSUAsmVHLoc0ikteympIiJ8bKMI0WoimHJEmm/33RaLOwvQEZY9ZhajXNPffcg0ceeQSPP/44AoHxmzStW7cONTU16r+2tjYTR2k9ViWxxhLUY6QYAl632mvk0FFz54qVijZW+sidXABW9hqh5NXiUPPmLAjTUJjaOooSI42NjXC73QiHw6N+Hg6H0dzcfNL3/sd//Afuuece/OUvf8FZZ5110teuWbMGg4OD6r+Ojo5ihik8bRaJEeb2px4jhWOVcDxEfSuKIr/XiNk5PmpZLx1wBcG+031DCQwn06b+bc0zQuvKbIoSIz6fD4sXLx6VfMqSUZctWzbu+77//e/jO9/5Dp555hksWbJkwr/j9/tRXV096p+TsCqBixZi8cxoyP63Mtszcqg/lvv7Fab+XZGxKlTDPCMUTiuMmnIvqgLW5M2RZ8Q6ig7TrF69Ghs2bMDDDz+M3bt346abbkIsFsPKlSsBANdddx3WrFmjvv573/se7rzzTjz44INob29HKBRCKBTC0NCQfk9hM6Y3WBMzpYVYPEwMMHFgFtTRs3isSmI9QmKkaLRQjVV7IM2V2RQdbL7qqqvQ29uLu+66C6FQCAsXLsQzzzyjJrUePnwYLpemcR544AEkk0n83d/93ajPWbt2Lf7P//k/kxu9TbGq1wgtxOJR7xIy2TNy8CjzjNBcFYpV5b3sagcq6y2c6fXleLc7YqpBRj1GrKWkzLdVq1Zh1apVY/5u8+bNo/7/wYMHS/kTjoaJgWg8jcHhFGrKzcnfoEzy4lHDNCZbcEz8kBgpHCuq1IYSafTnksKp4VnhaNdimCccqceItdDdNBxS5nOr/QjMtAwO9pE7uVhm1GfDNL1R85LtEukMuiPZrq/T6ylnpFCms5DaUfNCaizMUFfuRVWAksILpc2CXiMs74v2P2sgMcIpbSZbcYqiqJv0zEZajIVSU+5VK4/MEo4d/SNQFKDc50Zjpc+Uv2kHZqpiZBiybE6TOkpeLQ0rckZY6LOdksItgcQIp5jd+Kd3KIFYMgOXRBtnsZhdUXM4lyw7nZpoFUVrbQBet4REWlY9S0bTQWKkJPLbG5jV3fhgX06MNJIYsQISI5xidv8KFqJprS2D3+M25W/aBbOTWA9RvkhJeNwu1eJmB4/RHKHk1ZJg+T2xZAbHhs1pUnegjzzDVkJihFO0ihpzErgOqguRrIJi0ZJYzTngNDFCc1UszOo9YJIY0cI0lLxaDAGvG00m581RmMZaSIxwyjQ1m9ychXiAFmLJsCRW88I05BkplXaTk1g7qBV8yZjpHR5OphGOJACQQWYVJEY4hS3EzmMjyJiQbEfx0tIxu0kdO0hnUCVN0TAX/IE+4+dKUZS8VvAkRorFzLw5FqauLfeitpySwq2AxAintNSUwedxIZmR0TVgfKiG4qWlwzwUncdGkM7Ihv4tWVbU0B15RoqHie2DJnhGQpE44ikZHpdETbRKgHko9vcaP1cUorEeEiOc4nZJainiB73Gts7PlvVmLQNajMUTrArA53EhLSvoGjC2SiMUiSOZzh5wLTXj33xNjA37fh8+Omy4x5EdotPry+F101ZbLLOm5MRIn/FXhxygnDnLoRXCMepiNNgyCEcSGEll4HZJVIJYAi6XpIbVjE5iZRbctLoyeOiAK5rW2jL43OZ4HPfnjAi2jonimNVYCSC7/xld3quGqckYswzazThGEyPGWgbMKphWV0YWXImoYsTgJFb1gjzaNEsiK7izIROjQzX7ckbErCmVhv4du8K8FIMjKbWlvlGoYRoKU1sGnTwck28ZGAnFSyfPdJOS7dgdODPIg1Uy7JAzutfIvpwRMZs8IyVR5nNjam1WOO43eK5YQjOFaayDxAjHzG7KiRGDY6bUY2TyaF1Yjd006YK8ycNEt9EVNfvJMzJpzPAOR+Mp9A1ly3qpmtA6SIxwDFuI4UgC0bhxXQgPqPFSOuBKxaxmWsyLRX0rSofNlZHCcSSZQWcuJ2UWHXAlMzsn5PYZ6B1modWGCh+q6TJDyyAxwjHVAS8aK7NdCI085LR4KW2apXJKbtM80BczrLxXlhXV9X9KE1nbpcI8gAcMFCNsvdaUeVFfQX0rSsUMz8gB6rHEBSRGOMfoihpZ1sp6KUxTOlNry1DmdSOVUdS8Dr3pHBhBPCXD53aRZ2QSsBBXR/+wYcKRhVZnT6mgywwngRl5c1RJwwckRjhntsGWQXckjkSubwVLFiOKx+WSVG/F3rAxc7W3JwogK1CprLd0WnMNBVMZ4/rCUL6IPjBj7HD/MFIGCUfmIaOGj9ZCOxrnqDFTg8I0zCpoqy+nA26SzMmJkQ9yokFvmMihEM3kcLkktRrJqFDNPuoxogvN1QGUed1Iy4phlWp0FQYf0OnDOWwz29djjLVNyav6cUqQiRGjPCPZz53TVGXI5zuJdoPLe5lnZDZ5RiaFyyUZHqo+SN2nuYDECOewmOnBozHIBrSvpuQt/WAiYa/RYiRIB9xkmdVoXPhTURT1c6nHyORhoS4j5mpwWGuoRnugtZAY4ZxsV1QJ8ZSMrkH921e/H86GFE4NkrU9WU5p0jwjet97oigKPsjN1RwK00yaObnv+3sh/UNq4UgCsWT2eoXpdLPypJll4IV57+dCqq01AVT6Pbp/PlE4JEY4x+N2qe5DIxYj24znNpMYmSxtddnEyERaRucxfYVj92AcsWQGHpeEGeROnjTs+74nHNX93hNmwbPvAzE5jLww773uCADgNNr/LIdWigCoeSM6uymPDiXQG812HiTPyOTxuF2qFbdX5yRWFqJpb6ygA04HTmmqhEsCBoZT6MmtAb1gyeaUL6IPs6cYV97LjLHTmqt1/2yiOGhXE4BZBi3GPbmFOL2+HBXkotQF5v7XO29kL4VodCXgdat9dfQO1dBtvfrC5uloLInBYX07UbM9cF4LGWNWQ2JEANSYqc5uSs0qoIWoF3OajKmo+UCtpCExohdzc9bwnlBE18+l23r1pcLvQUtNAACwT8c9UFEUVYzQHmg9JEYEgCVGvq9zM609lC+iO0ws6O4ZyX3eKRRO0w12AOntGWFl+BSm0Q+2B+7Rca46B0YQTaThcUlq1SJhHSRGBGBuczVcEtAbTaAnql/HyPfCTIxQvFQvWNntBzomRiqKQmEaA2BiRM8D7lgsqV6QN5dc/7oxvzW7R73TNajbZ7J5P6WpkvKwOIBmQADKfG7V5ftOlz4uZVlW8D65KHVnRkMFPC4JsWQG3YP6CMfeaAKReBouie4P0hPmEdzbM6TbHTXv5qozpteX0w2wOjK/hYkR/UJqFKbmCxIjgnB6zjJ4V6fFeLh/GCOpDHweF3Vf1RGv26UKBr1CNexzZjRUIOB16/KZBNBWV45ynxvJtKzeXD1Z3u7MWu5nTCVvo56c3loDAHivO6pbDx8SI3xBYkQQTtfZTckW4pymSrqTRme0C/P0cf+zz6E7afTF5ZJ0b37GLHd2eBL6MLOxAmVeN0ZSGRzQKYmVJS7PozA1F9ApJAhsc9PLTUlZ5MYxR0041kmM9NAFeUYxN6hv3ggzFliOA6EPbpeklt/qsQcm0hm16on2QD4gMSIIzDNy6OgwIvHJ19rvCZNVYBRnTM0KxzeP6OPFeou5/sna1h09K2qGk2nszzU8O53EiO7oaZDt64khIyuoCmhlw4S1kBgRhNpyH6bWlgHQJ2/kvW7yjBjFwrZaAFnPyHAyPanPiqcy2J1LilzQRmJEb+bqWFGzuzsCRQGaqvxoqqIDTm/0DFXnG2OSJE3684jJQ2JEILTytsmJkXgqoybsUY8R/WmqDqC5OgBZAd7unNxcvdsdQSqjoLFSE6OEfjAxfrh/GLHE5ISjli9CXhEjyPeMTLZsnowx/iAxIhB6WQZ7w0OQFaCu3IspVX49hkYcB/NivNExMKnPYe9fMK2WLDgDaKj0o7EyuwYmm+PzTiclrxrJqc2V8LgkDAyn0DXJsnmqpOEPEiMCwTa5yYZpdufdVEkHnDEsyIVqdh0ZmNTnqGIk93mE/uiVGPlOd9ZIIM+IMfg9bjWJ+53O0g0yRVHwXq6ShjzD/EBiRCDYJre3ZwjxVKbkz3n9UD8AYGFbnS7jIk5k4bRaADp4RnJJsCRGjGPR9Ow62H7oWMmfkUzLat4JS2Am9EePJNbOgRGEIwl4XBJVPXEEiRGBaKkJoK7ci4ysTMql/PrB7KZ77kwSI0ZxxrQaSBJw5NgI+oZKu6J+YDiJA7nqjAXT6IAzinPas+vgtYP9JX/G3p4oUhkF1QEPptVRbo9RnK5D3hyb59On1qDcR7eV8wKJEYGQJGnSlkHfUEItP1w8vV63sRGjqQ541YvSSvWOsNLg9oZy1Jb79BoacRyLptfBlROO3YMjJX0GW4/zW6k6w0jmq52oSw/TvJYzxs6ZQcYYT5AYEQxmGbxdYsz09ZxVcFqwCjXldHeGkSyYZKhmV+59CylEYyiVfo96yDGvYbGwPC7qBWMsbJ66BuPojyVL+ozXDmT3wHNmkjHGEyRGBIPlDpS6aapWAYVoDGdhrqJmV4nNzyh51TyWzMgeTK+XGKpheVhnUjjNUKoDXjWJdduBo0W//1gsqXY0XkKeEa4gMSIYy2Y1QJKAPeEoeiLFl7exzfacdrIKjIaJiDc6Borui6AoCt7IVeKQGDEeth62lSDy+2NJNUyzbHaDruMiTuTCUxoBAC9/0Ff0e1/PJSnPnlKBhkpqa8ATJEYEo67Cp7qC/7qvuMU4nEzj7dymuYTEiOHMba6Gz+3C4EgKh44OF/XezoER9A0lsxn/LZTxbzRLckms74UiRV+38Mq+PihKtkyUOq8azwU5MfLXD4r3jJAxxi8kRgSELcaX9xa3GHceHkBGVjC1toy6eZqAz+NSY9y7iswbeaMjG9qZ11KNgNet99CI4whWBzC9vhyKAuwossT35b1Zo4BZ7ISxLJ1VD7dLwoG+GI4cK07kbyMxwi0kRgTkojnMTdlblPuflbQxK5AwHhaXfnFvb1Hve/mD7OvPnl6r95CIcWDroph8LEVR8FJOjFwwh8SIGVQHvGqp+ytFeEdGkhk18Z/ECH+QGBGQxTPq4Pe4EI4ksK93qOD3sU2WQjTmcem8IADgufd6kM7IBb1HlhVsfLdn1PsJ4zk3ty6K6Tdy6OgwOgdG4HVLWErVGaZRSt7Iro4BpDIKgtV+tNWTZ5g3SIwISMDrVpU9cxFPRDojY8fhXLMzEiOmcU57HWrLvRgYTqnJcxOxs2MAfUMJVPk9OG8WJUSaBRPpuzoGkEwXJhxfyh2GZ0+vowZaJqLljfRBlgvzDufni1AvGP4gMSIoF84pzjJ448gAhpMZVAc8mJMrjSOMx+N24W9OawIAbHw3XNB72OsumdsEn4eWqFnMnlKB+gofEmlZLdWdiJdz4beLKERjKoum16HM68bRWBJ7CuxGvWV/NqRDIRo+oZ1OUJib8tX9/UgV4P5/fGcnAGD5vCBcLrIKzOQj87Ohlo3vhgvK8fnLu6FR7yPMQZIkfCQXFnsit15ORkZW8Mq+7AF34Zwpho6NGI3P48LSWVlR8dcCDLLQYByv5sTIJafRXPEIiRFBmd9SjbpyL4YSabw5wc2wiXQGf3qjGwDwmcXTTBgdkc+HTp0Cn8eFw/3DeD988hyfD3qGsL83Bq9bok3TAj599lQAwNNvhTCSPPlllG8eGUA0nkZ1wIMz6XI80ykmb+TxnZ2QlWyIekZDhdFDI0qAxIiguFwSzs8txr9M4P7ftLsHgyMptNQEKAfBAir8HlyQa4a1Mef1GA8WojlvVgOqA9Su32zOaa/HtLoyDCXSqodqPJ57L5tkfP7sRrjJ22g6F6je4aMYGB6/NbyiKPifHUcAAJ9ZPNWUsRHFQ2JEYK5c0AoA+M3Ww4gl0uO+7rHcQvzUoqm0aVrER+Y3A5g4b4SJlctObzZ8TMSJuFwSPr0oe2A9tmP8UM1IMoNfbT0MAPj4WS2mjI0YzdzmKsxrqUY8JatzMRZvHBnEBz1DCHhd+PiZNFe8QmJEYD4yL4hZjRWIxNN45LWOMV/TN5TA5j3ZJLtPn00hGqtYPi+bxPrGkcFxb4bticaxM9cc7SNU0msZn8qtk5f29o575cLvtnegP5bEtLoyfPwMEo5WIEkSvvShmQCAh145iER67LDa/2zPGmMfPb0ZVeRt5BYSIwLjckn44kWzAAAPvnxgzETWP+zqQlpWsKCtVr1gijCfpuoAzsk11frP/9075mvuf+4DKEr2lt7mGmorbhUzGytw9vRayEp2/RxPOiNjw0v7AQA3XDQLHjdto1bxt2e1oqUmgN5oAn/YeeJcJdIZ/PGN7M8pX45vaBUJzqfPnorGSh86B0bw1Jvdo34nywp+n7MKPnM2xUqt5qsfnQsAeOS1DrXnC+OtI4P4f68eyr5uxWmmj40YDfMi/n77EWSO62Px57dD6OgfQV25F/+wpM2K4RE5vG4X/umCrHfk5y/tP6HnCMuXa64O4PzZVH7NMyRGBCfgdeMfz28HAPzsxf1q6aiiKLj76d3Y3R2Bz+PCFWe1WjhKAsgmR/5dzjq784m31Y6sGVnBN554C7ICfGJhq5qYTFjH357VgoDXhT3hKL71p3dGrav1L+wDAFx/fjvKfHRvkNV89tw2VPk9+KBnCJvf71F/fqAvhrv+8A6ArNFG+XJ8Q2LEBnz+vBko97mxuzuC2x7dhc6BEax/YT9+8fIBAMC6T52JugqfxaMkAOBrH5uL6oAH73RF8MuXD6AnEsd//fUA3jwyiKqAB9+4fJ7VQyQA1Jb7cO/fL4QkAf93yyH8dPM+dA+O4Pbfv4l3uiIIeF24blm71cMkAFQFvPjc0ukAgDWPvYUndnaie3AEn//FVvQNJTCvpRo3XjLb4lESE1GSGLn//vvR3t6OQCCApUuXYtu2bSd9/e9+9zvMnTsXgUAAZ555Jp5++umSBkuMTW25D7ctPxUA8MSuLnz4Pzbje8+8BwD4xsfnUayUIxor/bg9F65Z9+f3cO7dm/BvT+0GANy+4jS6gp4jLj+rBWv/dj4A4N+f3YOL/32zGvb857+Zg3oS+NzwxYtmYUZDOcKRBG59dBcu+ffN6BwYwczGCvzffzqXyuQFoGgx8uijj2L16tVYu3YtduzYgQULFmDFihXo6ekZ8/WvvPIKrr76anzhC1/Azp078clPfhKf/OQn8fbbb0968ITGDR+ahT+uugBLZ9ar92rcePFs3PChWRaPjDiez507HX8ztwkelwTmOb5oTiOuWTrD2oERJ/CPF8zEl3NWdTIt49z2evzPTctw84dPsXhkRD5Tqvx49tYP4fYVp6Hc50YiLaO5OoD/94VzMaXKb/XwiAKQlGLuoAewdOlSnHPOOfjJT34CAJBlGW1tbfjnf/5nfO1rXzvh9VdddRVisRiefPJJ9WfnnXceFi5ciPXr1xf0NyORCGpqajA4OIjq6upihus4FEXBi3v7cHQogU8tmkoXQgmAoig0TxyjKAr+sKsLDZU+XHhKI80V5/RE4vjTm924bH4QbfXlVg/H8RR6fhd1zWQymcT27duxZs0a9WculwvLly/Hli1bxnzPli1bsHr16lE/W7FiBZ544olx/04ikUAikVD/fyQSKWaYjkaSJFx8KrURFwk63PhGkiR8chFVo4lCU3UAX7hwptXDIIqkqDBNX18fMpkMgsHRDZmCwSBCobFbJ4dCoaJeDwDr1q1DTU2N+q+tjcrnCIIgCMKucFlNs2bNGgwODqr/OjrG7i5KEARBEIT4FBWmaWxshNvtRjg8+n6NcDiM5uaxWyI3NzcX9XoA8Pv98Psp6YggCIIgnEBRnhGfz4fFixdj06ZN6s9kWcamTZuwbNmyMd+zbNmyUa8HgI0bN477eoIgCIIgnEVRnhEAWL16Na6//nosWbIE5557Ln74wx8iFoth5cqVAIDrrrsOU6dOxbp16wAAt9xyCy6++GLce++9uPzyy/HII4/g9ddfx89//nN9n4QgCIIgCCEpWoxcddVV6O3txV133YVQKISFCxfimWeeUZNUDx8+DJdLc7icf/75+PWvf41vfvOb+PrXv445c+bgiSeewBlnnKHfUxAEQRAEISxF9xmxAuozQhAEQRDiUej5zWU1DUEQBEEQzoHECEEQBEEQlkJihCAIgiAISyExQhAEQRCEpZAYIQiCIAjCUkiMEARBEARhKUX3GbECVn1Mt/cSBEEQhDiwc3uiLiJCiJFoNAoAdHsvQRAEQQhINBpFTU3NuL8XoumZLMvo6upCVVUVJEnS7XMjkQja2trQ0dFh22Zq9IziY/fnA+gZ7YLdn9Huzwfo/4yKoiAajaK1tXVUd/bjEcIz4nK5MG3aNMM+v7q62rZfLAY9o/jY/fkAeka7YPdntPvzAfo+48k8IgxKYCUIgiAIwlJIjBAEQRAEYSmOFiN+vx9r166F3++3eiiGQc8oPnZ/PoCe0S7Y/Rnt/nyAdc8oRAIrQRAEQRD2xdGeEYIgCIIgrIfECEEQBEEQlkJihCAIgiAISyExQhAEQRCEpThajNx///1ob29HIBDA0qVLsW3bNquHVBLr1q3DOeecg6qqKjQ1NeGTn/wk9uzZM+o18XgcN998MxoaGlBZWYnPfOYzCIfDFo148txzzz2QJAm33nqr+jM7PGNnZyc+//nPo6GhAWVlZTjzzDPx+uuvq79XFAV33XUXWlpaUFZWhuXLl2Pv3r0WjrhwMpkM7rzzTsycORNlZWWYPXs2vvOd74y6s0K053vxxRdxxRVXoLW1FZIk4Yknnhj1+0Kep7+/H9dccw2qq6tRW1uLL3zhCxgaGjLxKU7OyZ4xlUrhjjvuwJlnnomKigq0trbiuuuuQ1dX16jPEPkZj+fGG2+EJEn44Q9/OOrnPD9jIc+3e/duXHnllaipqUFFRQXOOeccHD58WP290furY8XIo48+itWrV2Pt2rXYsWMHFixYgBUrVqCnp8fqoRXNCy+8gJtvvhmvvvoqNm7ciFQqhcsuuwyxWEx9zW233YY//elP+N3vfocXXngBXV1d+PSnP23hqEvntddew89+9jOcddZZo34u+jMeO3YMF1xwAbxeL/785z/j3Xffxb333ou6ujr1Nd///vfxox/9COvXr8fWrVtRUVGBFStWIB6PWzjywvje976HBx54AD/5yU+we/dufO9738P3v/99/PjHP1ZfI9rzxWIxLFiwAPfff/+Yvy/kea655hq888472LhxI5588km8+OKL+NKXvmTWI0zIyZ5xeHgYO3bswJ133okdO3bgsccew549e3DllVeOep3Iz5jP448/jldffRWtra0n/I7nZ5zo+fbt24cLL7wQc+fOxebNm/Hmm2/izjvvRCAQUF9j+P6qOJRzzz1Xufnmm9X/n8lklNbWVmXdunUWjkofenp6FADKCy+8oCiKogwMDCher1f53e9+p75m9+7dCgBly5YtVg2zJKLRqDJnzhxl48aNysUXX6zccsstiqLY4xnvuOMO5cILLxz397IsK83Nzcq///u/qz8bGBhQ/H6/8pvf/MaMIU6Kyy+/XPmnf/qnUT/79Kc/rVxzzTWKooj/fACUxx9/XP3/hTzPu+++qwBQXnvtNfU1f/7znxVJkpTOzk7Txl4oxz/jWGzbtk0BoBw6dEhRFPs845EjR5SpU6cqb7/9tjJjxgzlBz/4gfo7kZ5xrOe76qqrlM9//vPjvseM/dWRnpFkMont27dj+fLl6s9cLheWL1+OLVu2WDgyfRgcHAQA1NfXAwC2b9+OVCo16nnnzp2L6dOnC/e8N998My6//PJRzwLY4xn/+Mc/YsmSJfj7v/97NDU1YdGiRdiwYYP6+wMHDiAUCo16xpqaGixdulSIZzz//POxadMmvP/++wCAN954Ay+//DI+9rGPARD/+Y6nkOfZsmULamtrsWTJEvU1y5cvh8vlwtatW00fsx4MDg5CkiTU1tYCsMczyrKMa6+9FrfffjtOP/30E34v8jPKsoynnnoKp556KlasWIGmpiYsXbp0VCjHjP3VkWKkr68PmUwGwWBw1M+DwSBCoZBFo9IHWZZx66234oILLsAZZ5wBAAiFQvD5fOrmwBDteR955BHs2LED69atO+F3dnjG/fv344EHHsCcOXPw7LPP4qabbsJXvvIVPPzwwwCgPoeo39uvfe1r+OxnP4u5c+fC6/Vi0aJFuPXWW3HNNdcAEP/5jqeQ5wmFQmhqahr1e4/Hg/r6eiGfOR6P44477sDVV1+tXrJmh2f83ve+B4/Hg6985Stj/l7kZ+zp6cHQ0BDuuecefPSjH8Vf/vIXfOpTn8KnP/1pvPDCCwDM2V+FuLWXKJybb74Zb7/9Nl5++WWrh6IrHR0duOWWW7Bx48ZRcUw7IcsylixZgrvvvhsAsGjRIrz99ttYv349rr/+eotHN3l++9vf4le/+hV+/etf4/TTT8euXbtw6623orW11RbP53RSqRT+4R/+AYqi4IEHHrB6OLqxfft2/Od//id27NgBSZKsHo7uyLIMAPjEJz6B2267DQCwcOFCvPLKK1i/fj0uvvhiU8bhSM9IY2Mj3G73CZnA4XAYzc3NFo1q8qxatQpPPvkknn/+eUybNk39eXNzM5LJJAYGBka9XqTn3b59O3p6enD22WfD4/HA4/HghRdewI9+9CN4PB4Eg0Hhn7GlpQXz588f9bN58+apGe3sOUT93t5+++2qd+TMM8/Etddei9tuu031dIn+fMdTyPM0NzefkDSfTqfR398v1DMzIXLo0CFs3Lhx1NXzoj/jSy+9hJ6eHkyfPl3dew4dOoR/+Zd/QXt7OwCxn7GxsREej2fCvcfo/dWRYsTn82Hx4sXYtGmT+jNZlrFp0yYsW7bMwpGVhqIoWLVqFR5//HE899xzmDlz5qjfL168GF6vd9Tz7tmzB4cPHxbmeS+99FK89dZb2LVrl/pvyZIluOaaa9T/LfozXnDBBSeUZL///vuYMWMGAGDmzJlobm4e9YyRSARbt24V4hmHh4fhco3ectxut2qZif58x1PI8yxbtgwDAwPYvn27+prnnnsOsixj6dKlpo+5FJgQ2bt3L/73f/8XDQ0No34v+jNee+21ePPNN0ftPa2trbj99tvx7LPPAhD7GX0+H84555yT7j2mnCG6pMEKyCOPPKL4/X7loYceUt59913lS1/6klJbW6uEQiGrh1Y0N910k1JTU6Ns3rxZ6e7uVv8NDw+rr7nxxhuV6dOnK88995zy+uuvK8uWLVOWLVtm4agnT341jaKI/4zbtm1TPB6P8t3vflfZu3ev8qtf/UopLy9X/vu//1t9zT333KPU1tYqf/jDH5Q333xT+cQnPqHMnDlTGRkZsXDkhXH99dcrU6dOVZ588knlwIEDymOPPaY0NjYqX/3qV9XXiPZ80WhU2blzp7Jz504FgHLfffcpO3fuVCtJCnmej370o8qiRYuUrVu3Ki+//LIyZ84c5eqrr7bqkU7gZM+YTCaVK6+8Upk2bZqya9euUftPIpFQP0PkZxyL46tpFIXvZ5zo+R577DHF6/UqP//5z5W9e/cqP/7xjxW326289NJL6mcYvb86VowoiqL8+Mc/VqZPn674fD7l3HPPVV599VWrh1QSAMb891//9V/qa0ZGRpQvf/nLSl1dnVJeXq586lOfUrq7u60btA4cL0bs8Ix/+tOflDPOOEPx+/3K3LlzlZ///Oejfi/LsnLnnXcqwWBQ8fv9yqWXXqrs2bPHotEWRyQSUW655RZl+vTpSiAQUGbNmqV84xvfGHVoifZ8zz///Jhr7/rrr1cUpbDnOXr0qHL11VcrlZWVSnV1tbJy5UolGo1a8DRjc7JnPHDgwLj7z/PPP69+hsjPOBZjiRGen7GQ5/vlL3+pnHLKKUogEFAWLFigPPHEE6M+w+j9VVKUvPaHBEEQBEEQJuPInBGCIAiCIPiBxAhBEARBEJZCYoQgCIIgCEshMUIQBEEQhKWQGCEIgiAIwlJIjBAEQRAEYSkkRgiCIAiCsBQSIwRBEARBWAqJEYIgCIIgLIXECEEQBEEQlkJihCAIgiAISyExQhAEQRCEpfz/KOxlxOtosEgAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "L_ops = None\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "e5d45dab", + "metadata": {}, + "outputs": [], + "source": [ + "rho0 = InitialDensity(n_qubit = 2, state = [0,1])\n", + "# state = [target, control]" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "50c713c3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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a6UTcu9+6h2omy6RhYKbW4XwJg5qXD/f9IhMfHFiYpj+b076GzCsVdfL0ScgIm6tHhvMoa+5n68+6BwKmQp8IE6aphiEjATBlRPf0XhaiWdjVdJJxioGFpHQ/gRyuTHg2nokwp81VTA5rrhb0T3PSAqJjYp2sxghDJhn3qnfqHqrZMzBxjRGGntY0knELtgP0a/4MMxXgzZOQkZ5W189mO9DezzbdfGVz9ehoIXJd1MPAkJEAolL4bNcRv1vvZPCVEb2JFyMYs9smDtEA8DYt3ePQh4amJyNRMbH6mTQTb9BAdHwjrPrqRJlvgFtDhpFtnedrqWzjYCUsvKRn4vsaj1neXNZ5vtq2461NkymZzSk/o2aP5s8wDxgyEoBfEl7fCQ8EzasTL26AryTo7qNgE37OlGQkGqa4vmnCNECge6/mysj+QXdxniiThmFxN2uYp/dC7ldfnWq+6n94ODZagOMAMQuY1TL5fGXPd5/Ga9PAqBtmilluv6HJwIiX7h4vHjBkJABWhfXg4LjW8UrWJXIy8yrgG1h1nvCA7wOZShmZHZEwzXSGOAA4JdC3RWdM5xkBAsqIxrVGxgtl775OVGOEgZ2gda41wubfrNY04hOYkhm8w4PG87V/yL32ntY0EvHJt1lDRnwYMhLAnLYMknELJdvROstkquqrDPMDnhGdideR4alNYkDQwKr3hO+rIUzTE4HFzbYdj0xN5hkBgMWz3J/prIywWhQdTUl0Nk9+go5Ceu+Rii9isqw3Bo+MaHxQYips7xQqJmDISBCGjAQQj1ne4qezifXQNOY/wJ0E8ZiFsu1oPRG8ME375AscC+GM5EsYzZekXBdv2LbjLXDzpiIjrf5Yc8WylGvjjYGRPAplGzFrauIVhTDNGxXz6lSqCBCN/jRHavB3Af491zms2lcrGanM1yPGwGrIyInwfSN6LnDjhTJGC+4m1DPFpI/HLPRWfn5QUxVorFDCSIVcTLXAtaYTaE65WUW6hmoGRvMoVWLQU50s2zMJpCqysK4kk3UdntfRhOQUEjcL0xwcGkehpGfKK6sxsmQKFROIRq2RWskIOzzonOl32AupTj1Wo4z4MGTkBHjpvZqaWFk6XCoRQ1s6MeV751VOW7r6RtgEziSnHqtlWdqbWNk9mt02dQzasvxsBF1TI6dL62XoaU2hORWH4+jrpejz1K6px7ogCmGaOpURncOqnjIyRfgYgPZzlScMGTkBrJjSfk2lX/ZQ97SkJi0CxqC7Q/9wwC8y3Vh1N7HWkknDwNz7up62ajGvAi7xYuoIUxh0w9ERt2PrVBkXgH9wyOZK2vZYqtczorMywgqe9U4RZgSMMhKEISMnQPf0Xm9xm+b0AfhkRNf03sNehcPpx6p7FdZaMmkYmG9kYETP1uQsRDqdMhJ8j67P8NFRP+tiKrSmE2jPuOqfrmM9UoO/C/Dn6tB4UVvfU80G1lafjOje1qBRGDJyAvwwjebKyDSLGxCowqrp4sYax023uAHw/DG6h2lqUUZ0l35ZyGWqGiMMrGHgsVE9iRc7PMyaRhkBfBOrriGpgeHalJH2TAKZpLs1aTtfs7XNVzZX8yUbw5qa63nBkJETsJD5KDRNeT1aWZRnTdDV9UR4pjhNDayHa0jrZWCERfswzTTeAsAnorpKv7WGaQC3ZgXgb+q6galXUxUBY9DdN1KrZ8SyLG8T79fQN5Irlr1+SdORkUwyjraK4qXrfOUFQ0ZOQFdlE3ccYHBMvwWOPdC1hGnYxnZI03TBWhc3QP8qrH4p+OnHyvwHOiojjuPUbGAFfNLNwh06wbYdHPPCNLUrIzrO1/FC2Tv51zJf52jsG2Hh43QihvamqZMIAOMbYTBk5AQk4zF0NCUB6Cn9MmWkljDNfOZaH9azG2gtfWkYdDewek232mtQRjQO0wyNFzFWSU2fXwsZadU3TDM4XgQTX7tqUjL1VUbYs5hJxtA6TZYf4CsKOnq8+od9f9d0xnqg2jcyk2HIyATwT1v6LXAsLlvLSaunNY1EzO0GquMmzRaq+gys+o3TcRxPGZmq4BnDbI0NrGzOtaUTk3acDoJ5RrQca2WD7mxOTllPhYGFVXX0jAQPDrVs0Ky5pY5+NnbN06X1MhhlxIUhIxNAZ1NcPQbWWMyvv6Fj+ftaSsEzsHHqWIU1O17CeCWroKZsGo0Xt+OVOdddA5kGfK/FMQ3DNL5fpLaxep4RjefqdOZVBp3703iZNDXMVSBARjRUMnnCkJEJ0KWxMuIZWGtczNlpS7d0wWLZ9sZaSzaNzlVYWdy8szlZk1qgc0l4dk+7pujTEkQwTKNbaiTzucyqcYNmpHtgWL91yasxUoOKCejdn8YPqdY2VqOMuDBkZAKwk8oxzaTfUtnG8bHaPSOAn96rmymOZU/EYxa6a9y4dDWxMtWqlrReoFISPqFnSXhPGalRLWDvK5YdZHN6KV61Fjxj6GpxvWzjxTLGC3qRzHrM5kCgP82wXnMVAPpYwbMa56vxjLgwZGQCsAXuuGbZNMfGCnAcIGbVfrJkk1431zqrMdLTmkJsinbkQehqYu2vo+AZUCkJ36qnifXYWH1kJJOMe4ZI3cKqzDNSS1ov4Kp7ybj7rOu2NvlhmtqeYea36BvKaad41VrwjMEoIy4MGZkA3ZqGaZh8292SQrzGDZqRFt0WN7/6am0THtC3CuuhOgqeMehaEp6pkbWSkeB7j2pGvAbqDKlaluXNV92IV73KCAu95ks2suN6KV6hyYhmzy9vGDIyAfw4tF4PRz3mVYbuivTLivToAr/gWe1j1bUKa72LG6BvSfh6lRHAn6+6HR48ZaSu+arn4aFez0gmGUdXs7s26aTaOo4T8IzUR0aOjuS1LLTJC4aMTIDuFj2rOtba5yKITk1PWvWUgmfQtQprPf2GGHQtCc+ew1p9QEAgFV+3+cruax3ES1dlZKBOZQTQ0+OVHS8hV3RrNtW6Ns1qSSNmAbaj333lCUNGJsAsTVN7WZimVtkX8E9aulWb9esW1B+m0WlxA3zVip0Ua4GuJeGZgbWWImAMfiq+XmMdaEQZ0Whtchyn7jANoGf33noz34CKCb9Fz/nKE4aMTICgFKqTeWoghDLCNjjdiFeYxY35S3QrfMYk+VpNyYC+JeHDhWkqSqZmz3A9TfIYWEbNMY3CqtnxEgqVCs+1Zg4BfghWpw36SIjwMWB8I4AhIxNC13TBMMoI2+CyuZJWJeHDeEZ0DdMcr2w8nXUoI0wx0o6MhDCw6himyRX9Xi09NWbTAH74Sidl5MiIqxZ0NCWRTtSmFgB6qkCD4+61dtZxcABMRg1gyMiEyCTjaKkUyNJJMQhjYGV9eAC3V4YuOFJHKXgGHauwOo7jhdDCKSP6PL+5YhmjlfoZYQysOs1Vdq2JmFVTMzUGFr46plFYtZ4eUkF0VMj3cY1UoOMhQqqAqTUCGDIyKbo1XOCYgbXWkssAkAg0BtTFN+I4jidnzqkjw6Q1nUC6UgxMl/s6nC+hVHHY10VGNDxpsXBUPGahPVP7Bs3i7TqpQMEQTS29Whh0VAvqLQXPwJ73oXF9xjpYZwVhBqOMGDIyKbq9nhf6TIQwYRog6BvR4wRyfKyIYtndoOuJQQP+IqFLKvNg5Z6kEzE0pWqXuHUsCX8ssJDXs0HraDhn/q5aC54x6JhNE8bfBfjrko7KSEe9yojxjBgyMhm6vQ1aj4fDcZxQqb2AL/3qUruALW6dzfXFoNnvAPqMNYx5FdCzJPzxCvGqtXEcg479acKYVwH9yDRQf40Rhk4NCzIyz0h4ZUSfzCHeMGRkEni1RjQ5gWTHS55aEHaB00X6ZeGkempRMHghKU38MR4ZqXODDpaE1+W0xcg0yxipFSx0UbIdbap1Hg3h7wKC2TT6EK+wygg7OOhEvMKk4QPGMwIYMjIpvNOWJgZAtuG0ZRJ1qwV+SXg9Jj0jEvVKoUAgDq3JaSvs4gYETKyaLHCMDNcbukgn4mir9Kc5qomS6XXXrpNkMuJVKNkY06RZXqOekcGxAmxNKpOyw4PJpqkfhoxMgm7N4tDspFXvhAf8jU4XA+sQS3Vtqn+D7tQsDh02TAPoVxLe84zUqYwAvuFcFyUzTMEzAGhKxrUzYQ+EqCAM+Cqm7cBLg6aOwZBrE1u3s7kS8iU9SCZvGDIyCXRrljcQMgYNBNIFNRlr2Fz+4O/oIv2GqTHCoFtJ+GMNhN+6Nas1EtYzYlmWdv1pmApZ7wadScbRVKliqstBaTBkWLUtkwDrbTqkSQiZNwwZmQS6OfTDmlcBDcM0zLHegDIyqEm6YJgaIwy6lYRnBtZ6aowwzPI8XnqM1Z+vIQ4PmmXUsM01DKHu0sg3YttO6LHGYpa3ng1pMFYRMGRkEugWpmG+gDBkhHXu1eWkNdjA4tbZpM/iBjSmjOhWDMw3sIYhI3p5vDxlpE5/DKBX595CyfYK2XU2hVcydRhrNlcEs7aEGatu5nreMGRkEszSrM7IkQbCNDpNeKBRz4hejQEbUUYYgdFF9vVTe+vfoGdp5BlxHCd0mAYIhlXp31f27FmWG4qoFzpl1LBrbEnFvbT6etDhmevpj1UEDBmZBMwQN14sY1wD13rYVEFAv6qOjXlG9Dp9NGLq9E9aetzXY2Phx6qTx2s47zeOC6WMMBO2BmNl1VPbM0nEYrUXsmPo0uigFDaThqHTKCMGEyHIbnWIQx8P0e2UIXiCLmuQQjfYQOhCp5MWEEztDSP7snLa9MfqOI63uYZ5hhkJ16FIIVNFWlLxuqrqMujUn6YRv0jw93SYr95cDUGmAWjXloM3DBmZBJZlaWVi9SZ9iNAF2+hsB8hqsHH5ZCS8+U+X2gWNpPZ2aOSPyebC9eBh0Cmb5mjItF4GnZTMsKmuDJ0alR3wlJEQfhHAH6sOa7AIGDIyBdiiqIP0y8hIe4hJn4zHvKJROsihgyFTBYHq2gUjBdq1C/KlslfYqhHPyHCuRF7xYoS/JRVHJlm/WqBTmKaRNHxAr2waRkbCrEuAXpl+jSi2gAnTGDIyBXSqwtpIuiugT3+aKnd+iEmfScaRSbqP/SBxAyC7p7GQ5r/gszCcoz1WtrF2h9yg/TANfcWrEVMyoFc2jZ/5FlYtSFV9DmU0el/bNVIyRcCQkSmgS3pvrlhGvuQa4sKUSAcCHTKJb9DV7vzGTlvUjZ1BQ1wY818yHkNzihWNon1fPb9IyIWcxenLtoMsceLFnuHQBwdPGaE9TqCx8DGgV3Xo4w20bgD0Il4iYMjIFOjWxCjGYowxC2hN1X+CBvyJQH2sQXd+PMQGDfibAHXplxHDsLIv4G8C1E2sftZQODKSTsQ99Yh6+ftGyQhblwY1aJbHqq+GHatOXbbZNXY0mE1Dfa6KgiEjU0CXQkpBv0iYEzRQvcBRRqNxWaDaxEoZjcq+QED6Jb7AHWsgG4zBa4JIXPFqxN8F+M9+yXbI92xppECh+3uVuaqRChReGWEVWGk/v6JgyMgU6PZKTNN+OBo9aQH+RKAu/Tbqzgf0KQbWqOwL6DPWYw2GaQD/+ac+1kbnayYZ98Jv1DNqGvayVZ6H4XwJxUptFqpoJPMNMBVYQ5GRO+64A0uWLEEmk8GqVavw5JNPTvn+22+/HW9+85vR1NSERYsW4YYbbkAulwt1wTLhe0Zo1y5oNC4L+JsAebWALeQNbFqdmvhjGi2iBOizQTdqYAX0GSuPw4MuGTVDDRpY2wPGber3tdGwakcgtZe6CVsE6iYj9957LzZs2ICNGzdix44dWLZsGdauXYvDhw9P+P4f/OAH+MIXvoCNGzfixRdfxHe/+13ce++9+Ju/+ZuGL140ujSp1tlo+hwAdGpi1m0krZehUxMD6yCH0AWreUBd+m3UwAoA7U3uxpUdpx26yObc62uEjOiSUdMo8UrEYx4hIX9QavDwECw7QD38JgJ1k5HbbrsNV199NdatW4ezzz4bmzdvRnNzM+66664J3//YY4/h4osvxp//+Z9jyZIleNe73oXLLrtsWjWFAjo0KULD46TlKyN6jJWLqZP4WI9xMLB2aBKmOdqggRXQRxnJ8lBGNOlP42/QjY+V8toULDkQNqyaTsTRVKmxQ31tEoG6yEihUMD27duxZs0a/wNiMaxZswbbtm2b8Hfe+ta3Yvv27R752LVrFx544AH82Z/92aTfk8/nkc1mq/6pQHuGkZESadc6H9m34hkhf/rg5xmhfqrkYWDVpQoruxezGiAj7ZqQET6HB/r9aWzb4RJCZr9LOfuNqawxy983wkAXj5cI1JUHOjAwgHK5jN7e3qrXe3t78dJLL034O3/+53+OgYEBvO1tb4PjOCiVSvj0pz89ZZhm06ZN+PKXv1zPpQkBWywKZRu5oh2qj4QMcCEjumTTcPGM6JHP7xviGlBGNNmgeWRJ+YcHumN1HIfrfKV8eBgplMCsDw2FkDVolhc06obNaGS/f2goRz6ELALCs2m2bt2Kr33ta/iXf/kX7NixAz/5yU9w//334ytf+cqkv3PjjTdiaGjI+7dv3z7RlzkhmlNxr5YF5UJKXGTfQNllyioQF8+IJmGaRnrwMOjg0LcDhcoa2bR0IF6jhbJXmp9HWJWyMsLmVyYZC1Xin0GHwmfsPjQyVwF9lEwRqEsZ6enpQTweR39/f9Xr/f39mDt37oS/c9NNN+GKK67AJz/5SQDAeeedh9HRUXzqU5/CF7/4RcRiJ/OhdDqNdDpcEymesCwLHU1JHBstYGi8iN72jOpLmhCDHMgIO5G6FSxLDX2WSPDwjOhS+r7RVEFAj+ZbI4USGP9tROLWgYywa0vFY15bgjDo0sBw7odUG9ugOzXwszVaT4WhU5OkCRGoazakUimsWLECW7Zs8V6zbRtbtmzB6tWrJ/ydsbGxkwhHPO6yZMoncAbm5Ka8mPPYoHWpXcBDzg9WOqSaQheMt0c9TMPmVjrR2AmaqSosW4UihrzMtwQsK7yc36VD6GK8cfNq8PdJe0Y4HBwAn7hR3m9Eoe7a4Rs2bMBVV12FlStX4qKLLsLtt9+O0dFRrFu3DgBw5ZVXYsGCBdi0aRMA4JJLLsFtt92G5cuXY9WqVXjttddw00034ZJLLvFICWXoYIprtKIjQ1dzCmOFcRwfK2AJWnhcGnewSd/RwGmLZZiwFDqKKlA2V/Ti7Y1Iv2xxo3yqZKm4jT6/7D5SXsh5zVU21mHKxIvjugQQD9NwOCQB/tpEeayiUDcZufTSS3HkyBHcfPPN6OvrwwUXXIAHH3zQM7Xu3bu3Sgn50pe+BMuy8KUvfQkHDhzA7Nmzcckll+CrX/0qv1EIhLfAEfaM8DDEAW6zsQOD42RPWyyEBDQ26dMJVwUaK5QxOFYgSUbY4taSiiOVCC/ns7GNF8vIl8pIJ+gdALxNK0Rn4iB0UIF4zVW/pgrdsfLIfAP0yH7zChQ2GJIynpE6sX79eqxfv37Cn23durX6CxIJbNy4ERs3bgzzVcrBYtiUzY7cyIhniqM51uDC2+hYO5uSFTJSxCmzGr0y/vD8Ig2kugJAWyYBywIcx31O5rTRIyM8zKuAT2ZG8iWUyjYScXrdLniYzYFA5pAGykjjYRr66t4Qh9YNwMxO7aU3W4mBehw6VyyjUHJ7NjR+2qKtAjFTV2s6gWSDG00H8fReXjHoWMwin/LKbYMO/D7V8AU/ZcT9fUa8KMIPqTZ6SKKvFnjKSIOHBy+sSnSuioQhI9OAyaFUmSqboPGYhdZ0YzJ3sMgbRfBa3AD66YKN9rkIgrr0y4h+I5k0AJCMx9BSMWFTna+M6Df6DLcFQlojREuHN9qXhkEHsy6PppZAINRIdK6KhCEj04C6KS4Yb2/EnQ8E4tDElREeG3Qn8dMWj7ReBurSr290bIxMu59BW93jpYwk4zEv+43u4YHPWJmpM1+ykSuWG74uERjk5BmhPldFwpCRaeDHZmk+HLxOH4A/1mGqY/VOHzw2aNqnLV6hi+BnUF3gsh6hjv5YeZERgP7axOvw0JZOIFEpPkl1vvIoOQAEixTSHKdIGDIyDain9vJKnwt+Bt2TViVMw0MZ0SV0wUEtoB+m4bhBz6j5SjujZoiTMmJZlp9RQ9Bc7ziON7caNZyztS1XpKsCiYIhI9Ogg/gGzfekpUmYhsNYqcuh7B60zQC1gFedEYC+70mEMkL1vvpN8hpXMn1CTU8xGCuUUaiYiBv1jLSlE14LEqr3VRQMGZkGbIOm+mDwNHVSj7fzkkLdz6AepuFj6gQ0IF4mTBMK5Ocrpwqs7mfQzTJh9zQZt9DUQAVhwG9BEvzcmQJDRqYB9aJnvreAg/nPK31P+1TJ46RFPUwz7NXe4Bemobq4ZWfSWEUomQTna65YRq5YKTnAgYywsVL0sw0HssEaTSIA6IdVRcGQkWnATh/DuZLXbZMSZpQhjqdnpHLSIrtpcUp3BWhL3ADnDZpwRpjjODNGGWHjjFlAa4pflhTF+jF+SLXxcQL056soGDIyDYKbwQjBiSBkcRsvkmxiyNMz0kW8xDTboHkscKyPz0wiXhTHOl4so1h25xVffwy9sQbXpViscbWgjXDD0mFOFYQZqIdVRcGQkWmQSsS8OCDFh4Nn6IItbrYDjBboObmHPM9I42Nty/gnLYrEi+cCR3mDLpVtr2gXz7FS3LTY3z8es7zibI3AV4HoHZIGOc5VgHb5exYm46WMdBKeryJhyEgNoCz98kwVzCRjSMbdUwzF2CzPomfsnpZtB+PEUuhs28FwfmYYWIOyO4/FXBe1gIe3gPJYWYiBl1rQRjiE7B0cOMxVwHhGDKYA5ZPlIMcwjWVZZFMjecfbm5JxL4WO2lhHCiUwsYZPmMZ/fqmpQGxzaUnFG+43BPh+IopzlT1nvLpEU/aM8AypAv7hgaZnhK8y4vfNohlCFgVDRmoA5RMIT/MfQHeBGy2UPQMxL+LVRtShzxbcVCKGTIOpgoCvjBTLDsaIhd941hgBaB8ceKqYAO2aKlmOKiYQUEYI3tcsZ2XED9PQu68iYchIDaC6wFWpBdwmPU2jGCMMybiFdILPY0s1e4hn3Q3AVYFY+I3aMzzEeaxBbwE1FYinsgfQDh97nhFuxIuwMuJ5RniHaYwyYnACqKoFQXc+twWO6AbNFqHWdOMNARk84kVsgfPJCB/Z1y2kRDOjhmeNEcCfB2XbIWfC5k5GCKsFLMTAa6yUPSO8n2HKHi+RMGSkBlBVRtj1JDi584FgvwtaG/Qwx/LoDO2BjBpK8GLQnBZywC+KR80UxzvMmEnGkKp4T6jOVx4FCgH/kDRaKKNUKUdOBUPcw290lZHhnChlhNbzKxqGjNQAqpUOgy26eakFVE9bvE1iwc+iNlbfnc9vrFQJNe94u2VZZBvI8SZewblAbZPmnWHip+ITNGFzVjL9Am+0nl/RMGSkBlAN0/CWfQG6Yx0RQkaIKiOcjY5AsOIsrTg0bwNr8LOoES/e8zUZj6G5oohSm6/DnOcr5RpIvFXbtoA/hhrxEglDRmoA9cWN60JO1CjGWwoFgumCtO6rX5E0+srIEOdTJUB/rFwPD0QzanhXJc0kY0h4qfi07qs3XzmF39gaV7Idr7/PTIAhIzWAauhiJikj3ukjzV8ZoTpWXhK3+1k0Q41ZzpsWMNPmK82MGt5VSd3w28yYry2pOFgFfWoHJZEwZKQGUD1p8Y5BA5RPWvzDNFRVIBGhi2DMnRJEhKSozlfeaczBz6JGvMQYzunN10LJ9tQLnr6n1jTNTD+RMGSkBlDtASHipOWnu86ExY3mQs67C2jwsygt5ADfJnkMVPvTCAmrElQLgmnVIjxelO5rkNy3CvGz0RmraBgyUgOon7SEhGmIjVWEMkJ1gx4WsEH7ISlaY/U3aI6KF9HDgxglk174LdjdnKuSSTC9NxuofxTn0J2YgeraJBKGjNQAtkG7khwdJ7eY0AXNTYs1juNrYCWaTcO5iBIQXNxokUwRGzTFw0OuWEa+5Mr5vKolAzSVEXYtqUQM6QSf+kcA0JamN9ZhASomQPO+ioYhIzWgNZUAK+NBSTEQmWGSJdZUjU16vlIozZAUe8Z43leqJy3edUYAmmSE3dOY5a4nvEAxJDUsIBsMIKqMjPNXMd3PozdW0TBkpAbEYoFutoQ2LhEbdHsgrWx8hqhA1Ca8CB+FF4PO03l+86Wyb/6LeDZN0C8S4yjnU1QyRWSDATQ9IyJUTMB4RgymAHvYKJ22RvL8N+jmVNyLfVKKQ4s4bbG/20i+5HUEVg3HcQI1GqKdOcSeL8vim7JNUhkRQDCBaiWTCkRUSwZoEy+eKqb7efTmq2gYMlIjfDmUzsMhYoO2LCuwcdFZ4ERM+uBnjRCZ9Lmi7TU/FKKMEKrqyE6VrekEX7WAIBkZDoyVJygrtqI2aEpj9cM0vJURQ0YMJgGb9DQXOEFyKJFJ7ziOEBUolYghk3SnAJWxsuuIxyyv1DcPsL9bmVD4TYR5Nfh5VO4pIEbFBILZb3Q2LREhVYCm4Vwc8aL3DIuGISM1gtoCJ2qDBuh17s2XfLWA98mS2qQPuvN5NT8EqsNvVBZzcaEL9/NyRRv5Eg3iJcJsDlBXRsSoBRRDUvw9I0YZMZgEnjJCpK1z1QYtLDZLY6zsOiwLaOGYiQDQ81IMCXLnB6s6Ugm/iagxAlQTVir3VVwKKL0NWjTxovL8AsEChYJIJqH7KhqGjNQIaj0gghs0z1RBgN5EYIsbb28BQM+hL6L6KoMfc6exQfut1/ku5PFYkHjRGKuIrtOA/7cbLZRRLNNoqibKwErt+QXEpfYaZcRgUlAzsLLFrTXFf4OmVsFSREVSBmqTXuxYacXcGfHi7RkB6BV5C1bq5Inghk/lvopK7e1ooqeMiAtJ0UvFFw1DRmoENYe+pxYIOEFTU0ZEnSqBoCmOxlizgkIXAMENWkBDQAYvbZvIBj0ioIIwACTiMbRUjM5U5qswA2uGnhfI94yYomeNwpCRGhGsSUEBosyrAL1SxKLSIoFAbw8ik15UDBqgt8CJ6GLLQK3rqYgChQzU5quoZ7iVsAokTBkhlIovGoaM1AiWPkvlVCkqpQygt0GLOmkB9ExxIsM01MYqqnolQK+CpagS6e5n0gohixorRS+QKN8TxVR80TBkpEZQ8xaIikEDlE2d0feMyAnTEBvrDLivYpVMWuZ6kQclSum9tu2XV+BNvKhWwhYJQ0ZqBDUntwwfBZWxilRGqNUZEVV7A6BnYB0WFG8H6I6Vd4FCgJ7HS46Sqf6+jhZKYF0keD/DFFPxRcOQkRpBTeIWO+Erk4DI4ibK/AfQ6wTqd+wVmdpL477K8AKNEMlGEDpfCXlGSmUbYwU3rBD1Z5gdHJJxC+kE/62UWlajaBgyUiPYJMiXbBRK6vP5hXpGCC1ugDiTGAC0pamdKv3urrxBTS0QGbqgFqaRYsImIOcHDf4i1yYKh8JgCjPPaskMbcR8iqJhyEiNCC4iFDJqvIVcxOIWqKlCwcktNkxDa9MSG6ahE28HxN5XSkbHQslGvnKAEWJMJnR4YH/vTDKGlAC1oI0Q8WLXIOL5DX4uhWdYBgwZqRGJeMxrXEaBqYqtM+J+ZqHsL6IqIUfipjHhZYRpKCxuZdsJyPniVCAKG3Tw8CJivlIiXkPj4hRbgFa4XKSKCdBTMkXDkJE6QGnSDwv0UbSkEmBFXSmcor0wjQDzH6UYNOA/W2KqktKp6hgsRiYmI4zQXK08W8EMCZ6gtGmJPDgEP5fC4UFk6wYgWBdI/XyVAUNG6gCljUukjyIWyOcnMVYJBd4KJRs5xfn8hZLt1RQQU2eE0AZdIUTphCg5n9IJWuwG3Upo0xLpZQNohqREzFWA1n4jA4aM1AGSJxABp0ogWP6ezliFSNypBJj3TPV9DW4mIsZKqaqjrBM0BX9XsNGjCFAcq4jibgA1z4i4OjkArf1GBgwZqQOUpF+/zojYiUBjgRM36WMxy+t6rPpkGdy0xMj5dKo6ikzXdj+X0FwVPVZK4WPhoYuZo3hRKzsgGoaM1AFaE0FcrwvAX+BUNxorlm3kiq6JVtykp3EC8cqjCxpn0LOgeqwiU10Bf+MfK5RRKqs1YYveoGkdHMSGLigZzrPSDKzq9xsZMGSkDlDpBFq2HYwKLCwU/FzVE2FYsNERoBObFdnFFqBV1VFWmAZQv0nL9IwoD78J9HcFP1f18wv4hGgmmHVlwJCROuAt5IoXt+rCQmIXONULOSN+zak4EnExjyuVEtOi1QKAzgIn2keRjMeQScaqvksV/JpAYkNSxbKjPBU/Kym1l0KWn/GM8IUhI3WAimzGvj8VjyGdiAv5DiqbVlbmBq14gRN9qnQ/m8YCJ9pHEfxs5YqX4JAq8zwB6u+rcB9F4JBk22pVIFnKiOr9RhYMGakDVDZokWW0GVhDL9UhKdGLW/Cz6SzkIjdoGgucaB9F8LNVP8Mim1oC1an4qpVMkR22AT+EaTtuozqVEF30rJ3IIUkWDBmpA/Q2LRkbNJVNS9wGTaXfBdu0RJ2gATq1RkRv0ACdLBPRISmA0nwVe1/TiRiScdeErfpQKL4cvG9MVu0FkgFDRuoAtTCNyE2LSu0CmcRL9eImRy2g8gzL2KBpVJxlc0iUtwDw/46qVSDRz7BlWWSeYdYRWnTRM1cFUpuKLwOGjNQBKqdKv+CZDDmfRkhK5ELeTsRbILL5IQOV+yqynQEDmbFKDEmpJ9Ti5yuF8Fuw5IAoQt2UjCPhpeJHP1RjyEgd8GQzIhNepDLCPCOqM4fkZJjQMHXK9YyoHqs8dU/9WCXMVyK1RmSQEQo9wqp6KwlVgdSPVRZCkZE77rgDS5YsQSaTwapVq/Dkk09O+f7BwUFce+21mDdvHtLpNM444ww88MADoS5YJaj0gJhZnhGJYRrFRjE5mUPEVKAZkDk0U4zJxbLfW0nK2qSQeLF72pSMIymo5ABAJ6wqA3U/Mffeey82bNiAzZs3Y9WqVbj99tuxdu1avPzyy5gzZ85J7y8UCvjTP/1TzJkzBz/+8Y+xYMEC7NmzB52dnTyuXyrYJBgtlFG2HSElu2uB6FglQCcGnZ1BaoGcDZrGWEX3VgJobNDB7xdKMgnM12EJagEQUG0V3lfmQxI5ToBWLx7RqPsvedttt+Hqq6/GunXrAACbN2/G/fffj7vuugtf+MIXTnr/XXfdhWPHjuGxxx5DMuk+REuWLGnsqhWhqqpjroSOZnEb5FSQYf6jVghMxgmaisQtNnShfiEHxPdWAmjI+Y7jBHxPUVcL3GdKtFrQTsAzIkOxDX6+aiVTBup6YgqFArZv3441a9b4HxCLYc2aNdi2bduEv/Pzn/8cq1evxrXXXove3l6ce+65+NrXvoZyeXJ3cD6fRzabrfpHAelE3Gt3rvLhkJEWyTbE8aLa3h5y1QIaG7QM8596kin+vlLoJTVWKIPV5hJLvNQfHmRt0K0EnuERCcoeQCfUKAN1kZGBgQGUy2X09vZWvd7b24u+vr4Jf2fXrl348Y9/jHK5jAceeAA33XQTbr31Vvzd3/3dpN+zadMmdHR0eP8WLVpUz2UKBYWMGhmhi6DqolIxkOkZUZ3PL0POp/D85ktlFCoEN+oGVvbd8ZjllacXAQqEOitBxQx+vtJ1KS++/pH7+eqfYVkQnk1j2zbmzJmDb3/721ixYgUuvfRSfPGLX8TmzZsn/Z0bb7wRQ0ND3r99+/aJvsyaQUHSl5GJkErEkE6o7+0ho+gZ2/xV9vaQ0fzQ/Wz1akGVtyAlY6wKT9B5f4O2LHEeMwq9pGQYdQFfBVKpTssIlQM01D1ZqOsv2dPTg3g8jv7+/qrX+/v7MXfu3Al/Z968eUgmk4jH/R4qZ511Fvr6+lAoFJBKpU76nXQ6jXQ6Xc+lSQOFE4iM0IX7+UnkR/IkTpYix9qSSsCyAMdxvy+TFNPvZyoENxFZaoHjOEI3yMkwEljIYwJN4BRO0Flpm5b6E7SX1iuoPDoDhTojskJSFO6rLNSljKRSKaxYsQJbtmzxXrNtG1u2bMHq1asn/J2LL74Yr732GmzbP3G+8sormDdv3oREhDoomOJkZCIANBZzGaetYG8PVSST/Y1dRUocGWJ/x5LteEWbZEO2t4CGv0uOWqB2g5YbpqGwBovPppk5ykjdYZoNGzbgzjvvxPe+9z28+OKLuOaaazA6Oupl11x55ZW48cYbvfdfc801OHbsGK677jq88soruP/++/G1r30N1157Lb9RSAQFZURG6ML9fLVjtW1HngqkuNGYd08FE8yWVBxMjFB1X720SIlkWlWHV9kHBwrht5lwSBqR7BlRXVlXBup+ai699FIcOXIEN998M/r6+nDBBRfgwQcf9Eyte/fuRSzmc5xFixbh17/+NW644Qacf/75WLBgAa677jp8/vOf5zcKifCLRql5OIKpgsJPloo36JFAV07xG1cSGMopO23JyJAC3KqOrekEsrkSsrkS5rQL/boJIU/idueqU+nwKnrjmAiy1AIvw0TpBi0vfAzMFOKlXvGShVB/yfXr12P9+vUT/mzr1q0nvbZ69Wo8/vjjYb6KHFRLhPmSjWLZPeVJK7ijaKzsb5yKx4T7OFSnC8qSfQF3gcvmSupCUt5YxZID1uG1WHYwnFNDRuRt0NUqkEgvzmSQpdiqPiQB8g4PFEKNsmB609QJ1aycbVqWJTYTAVAfh5Z1qgx+h7rQhfjmhwyqCbWs+1rd4VXNWLOyvAVpXwUaK6rp8Corw0T1IQmQ6RlRT7xkwZCROtGu+OHw0npTYjMRAAIbtKTTB6DemCwjXZtBdXVdGd2JGfzFXK0KJFotyCRjyju8svsqi3gVSjbyJUXES0LXacBk0xhMAfWnSplyvmLPiKSFPPgd6sca/Q1aBclUF2qUY9a1LMuvNaJ4bRJZ9h6oXvtUq7ai76unTisuyCgDhozUCdVNmmTFoIPfoU7iljPhAUIqkISxKvfHsBP0DAhJyehLw6A6fOHXjxF7X+MxC80p10MW9fvK7mnZdryOyFGFISN1QvXiJouRu9+hVs6XeYJWndo7Ikn2BdQbAKXeVyIeLzn3VbG6JylMA6hVbR3HkaZQN1el4kc7VGPISJ1QTUZk9KVhIKMWyFjIFZ8qsxI9I6pNnSNSxzpzDg+q56us3jRAMPwmf6y5oo1ypW6N6LWJpeIDhowYnAC/zohqQ5w8OV+1WVfmCVpVDFqJZyTi3gL3OxRnhMkMq6bV3deq+kdSiJe6+8rWJctyiwiKhmp1TxYMGakTwWwaFVUdZUrcqp3cKuLtqlUgOeE31SRThWdE8X2NuAo0ViiD+SujPlbf8yS2+SGDanVPFgwZqRNtGbX5/LLKEAPqY9BSF3IinpF2ieE3ZeqeRLVAtcQ9kpN3X1VWYWV/33jMQpOERpMqPSPDEu8poD6rURYMGakTmWQMcYX5/DKzLoKnShVpZbIqOga/Q7W3QOYGrWpxU+GPUeEFKpZtLwMi6mbdkUC/IRlqgcrGliMSVUzAhGkMJoFb1VGhRChRLWDfUSw7yJfkd3jNKvDHqA5Jybyvyr0FEQ+/Bf++LTLDbyrXJdkbtBJlRN7BAVCv7smCISMhoHKBk1X5D6guN6+SeMnMHFLlBZKZJaWyAutowFsQ9dL3jHQ1JeNIxsUvtSo9XjK9bIDaDVrmgRAwnhGDKcAWURXSr8xUwVjMUirp+/4YeadKoLpbsAzkS2UUKspT1A2s7NSeiFnIJMUvPyor68oMRwW/R81clUtGVGaEyTwQAupVW1kwZCQEKIRpZGSYAIpVIIljzSTjSFVOr7IXuOD3SSEjClWgYA8euZkI6sI00jZohdWhZfso2hX6KGQeCIFAerqi9g2yYMhICCg1ikmU8wF1ceiqKocS5HxA3QmEnSpbUnHPHC0Swc1Rtgoks+5G8HuGc/J7e8g0mwNqs2myEs3mgGIVSNmB0CgjBiegXaVEKFn6VdXvYrxYDlQ5lCz9Sj6ByPTGAEA6oU4Fkk0w2d+0ZDvIFeWasGWW+He/R70/Zib4KGSbdVVnv8mCISMhoOoEXbYdjBbkpQoCQKuimHuwbkGzhCqHgDriJdsQF/wu6SqQ5NBFS1VvD9kkU27WBQvTqMymkaYCKTSwyvfHqPMoyoQhIyGgKg4dJATyZW41aoGsugXsuwAVaoHcTSv4XfJVoMpYJW1awd4eshfzrOQTNLun48UyimXJKpBsf4zCULlvTJateBnPiMEJUFUgiz2MqXgM6YQktWBGbdBq7utIXu6mFfwuVWNVcV9lq3uywzRBZW1U0VhlE6+RvHwvkOxnWGX9GJkwZCQEVMn5ahZyNaY42XFZwCdeqlQgWeWlAXVkJKsgJKVO3ZPr70rGY166tPz7KtfAyu6p7bh9cWRCdkhKZV0gmTBkJARUSYRKvAWK0gVVbNCqekCoUEaUqQWSzbrud6n1x8jKugCC81XRMyxprE3JeKAtR7Sf4VaF4TeZMGQkBFRtWiq9BapCUjLHqsrUmVXpGVF0X1UQL1WEWuZ9bVekAo1IVguCXiBVvifZmUOA/PCbTBgyEgKqyi778qBEOV9x7Y0Z4RlRonipNWHLVAvUEWq5acyAuvkqOz0dgBJjsoqMRpXhN5kwZCQEVIcuZG5a7YpUIJm9WhhUbdAqFnLlXqCZQEYUeryUhRojru6pyGgE1IXfZMKQkRBQVdVRhVqgjnjJlUIB9Qu5LIkbUNe519ugJaoFqrPfoq542bajyPckn2SyccrMaATUhd9kwpCREGCTQHZVR/YgKjF1KpN9ZapAajetmRCSmikbNKAqJFW5rxIJdbClgJqUbXn3VcVcDX6fUUYMqtCSSsBSUNVRRbqruhi03FRBQF2/CyWhC0UlpmUXxwLUeLxU9FZyv0uBWlD5rmTcQjohb0tROVaZczX4fVEuCW/ISAjEYmqqOqpYyD1lpCC3w6tao2P0PSPeQq6IeCkJ00g8QeeKtvTeSoCavlnBEI2sasmAGrVAhWILqO3ILAuGjIREu4I6DUoKRlUmgeMAoxI7vKqY9KrKhqtJd5VPvEplG+NFuZkIwe+Su2m5f9eYBWm9lYCgkqkidCGPYAJqVNusgrkK+GONcn8aQ0ZCQkUcWsWkzyRjSFSKC8kkXiokbvZ3LZRs5Etyqjo6jqNEBVJhYA0+P3KNyfIbyAX70shVC+QfklSEj4HggVDeGiy7xD+DKnO9TBgyEhIqndwyT5WWZSk5gSgpehZYTGVtXGOFMlj0S4XipWLTyiRjSMblewukhlQVbVoqxyrdR6HAMyK7FDyDysaAsmDISEiokLnVTQQVcqh84hWPWWipSOqyNmn2PfGYhaakPDmf/V3HCmWUJJWYVuGNcb9PpYqpZq7KVIH81g2Kxiozc0iZZ0RNVqNMGDISEipSI9WdtuSy8nypjELJ3SCjHocO+kVkyvktAUI7mpcTklJRTwXw5fx8yfaeK9FQtml5xewkhi4UhWnY2iBTBVKRmg6Y1F6DKSC7c6+bKqj4tCVLLQj8TVUtcPLIiJpNK5WIeWmYsjYuVc9vcOOQRajVqUDy/THDisM0IzIVL2WeEVOB1WASyI7h5Us2imXXXCCdlUuOzbLvaUn5nTllQbakr8r8B8hf4FR5C4LhN1ljVZZ1EZirsqpDq8qmUZnaqyqbRnYqvkwYMhISsmOzwQnXmop2HFrVqRIInLYke0ZkVtVlkK14eT4giRlSDLKzTFSYzYPfV7Id5CWHpOSrmDPIM2LKwRtMBtmsPOgtiElWC2TXLlAl5wPyS8KrikEDQZlbbvhNyVi9sKpkxUvyWIPVoWWNVR3xcueqVBN2XlGoXFHFZJkwZCQkZBvFVE149zvl9rtQkUnDILt+jCrPSPA75W3Q6kim7MMDI16yFa9YzPKUU/lKppqQFCDfz6bSMyKzOatMGDISEm2SWzqr3LRk5/Oryhpyv1NubFalZ0RVSEp2Ng2gwJis6AQNKMgI88rBy52vVSZsyeuwqpBU2Xa8KsZRgyEjIaEyTCMbsvtdKA1dyD5BKyResquwqvQCzSxjsuzsN3Vrk/R1WJFC3ZyKg0Xno1prxJCRkJCdTaPU1Ck5JKWqiBIgPzVyZvlj1HlG5BNq9SbsmRFqlGdMVln/yLLUNGeVCUNGQkJ2nRGlEz6taoNWcIKWvJCr9ALJDtOo9YzI9T2pVDJVpWxH3eOlsv4REP2S8IaMhAQ7VcpqqqbUMyI9JKXSWyB7g1boGVEUklLpj5kRJFPifS3bDsYK7voX9ZCUyvpHQPSb5RkyEhItab+PiAzFYCSvUC2QbeqkkDk0A+R8VT4KlWOdCUpmu8RNq0otUKiMyLivqor2MUS9JLwhIyGRiMfQLLGqo1JDnOTeNL63QKE/ZgYYk2dkmEayWhB1zwjzkbmZLfIaPTLI9HhlFYaPAfl1gWTDkJEGIJOpqlUL3O/MFW0UJRQXolGPIvpyvkzZ13EcEmOdSd4CKcqIwnRtQM19VXFPgWBjQOMZMTgBMg1FFLJpADmsXK1Z19+gZRQXopCJIINMV/VWUuktkHiCTidiSCXkL7EyQxcqn9/g98r0jKgeqwnTGJwEmXFolXJ+Mh5DJuk+KnImvTtWNf1a3O+0HXhSuyjQkfPlLeSW5ZYslw2ZRQpV1o5xv1ce8VJZ4h+Q/QyrU2yBQF0gY2A1OBFS5VCFtTcAv7qiDIlQVTMqAMgkY55TXvQCp1rO9z0jMpS9CplOye+tBMiV8+mcoMWP1fNRKGh+CMhV9/yQlJqxtpvUXoPJILMmhcowDSCvaFTZdjCqMFXQsqyA9Cv2vjLznyo5ny1uMrxAKv0iwe8dLZRRtsWG30YUloJ3v1feIUllITtADclUPVajjBicBKkGVoUl0oPfK1MtUO1aFx1+U00wZaanq1/I/b+xrLEqk/MVhN9mQuhCZRIBIL9HmGwYMtIAZLHyoFqg+mQpetKrNv8B8tIFVasFiXgMTUk56emqiVewqZroUCMjseqyLuR5RlT6u9zvlU+81GfTGDJicAJkxSuDBEDVRJBVu0D1pgUEw2+iN2i1cn7wu0X3HVJpwGaQFb5Q1WaewVMLCiXYgkNSypURiTWQRhQTL7/OiPGMGJwAWWEatnim4jFkkvILCwHyenuwsaoy6gKQ5xlRfNICAhlh49FWgYLfLYtkqrqvbLN0HGC0EG1CHVRsRafiqw81mjCNwSSQVYRG9YQH5MUrVXtjAJmbFoUNWs7JksZY5ah7qgl1OhFDQlJGmGolk60TxbKDfCnaJmzZXbZlw5CRBiDLR6GakQPysmkobFrSzLpe4ziFISnJY1UafpNMMlXN1+qMsGjP19ZAzRpp91VVqLzyNx4vllGSUAlbNkKRkTvuuANLlixBJpPBqlWr8OSTT9b0e/fccw8sy8IHPvCBMF9LDjPJW9Aq6VQ5rLhuASDPC0ThvsqqXaA6dAHI67GkWi0A5M1X1f1aYjFLop9N7ViD60QU03vrJiP33nsvNmzYgI0bN2LHjh1YtmwZ1q5di8OHD0/5e2+88Qb+x//4H/jjP/7j0BdLDdIlbgIbtPhsGgLKiKTFTWVxN4aZFZJiZt3ok0xZFWdVhy6C3y1ybVLdWwmoroQdxVBN3WTktttuw9VXX41169bh7LPPxubNm9Hc3Iy77rpr0t8pl8u4/PLL8eUvfxmnnnpqQxdMCbIWcrZBtzep36BFp5VRkPNltWCfWRu0erOurPDbTByrSsO5DD/bWKEMlpik9qAUXd9IXWSkUChg+/btWLNmjf8BsRjWrFmDbdu2Tfp7//N//k/MmTMHn/jEJ8JfKUGwh3KsIDaGp1oedL9blmdEvYFV2kJOwjMiR92jQDJn0lhlEOpqtUD92iRyvrLPjscsrzaPCrRLCr+pQF0r/sDAAMrlMnp7e6te7+3txUsvvTTh7zz66KP47ne/i507d9b8Pfl8Hvl83vvvbDZbz2VKQ1VVx3wJnc0pId9D6wQtJySlNLU3LSeNmYScL6nZI4WxyiqQlfXqUVBQC8TN17FAaX21KpB4ksnS/FvTCViW/N5KDFFulic0m2Z4eBhXXHEF7rzzTvT09NT8e5s2bUJHR4f3b9GiRQKvMjyCVR1FLnDZcQrKiJyqpBSIlzyzrvosKWmF+wjcVxknaMdxSBhYZczXoFrQnFKnFsjwjFDwsgW/P4phmrr+sj09PYjH4+jv7696vb+/H3Pnzj3p/a+//jreeOMNXHLJJd5rtu2GMxKJBF5++WWcdtppJ/3ejTfeiA0bNnj/nc1myRKStkwS+ZG8FImQxknLLS4k6nQwk0JSqutRAPJqb1DwUcgI04wXfbVAqcdLguIVzJBSqRbIyGocIfD8AvJUWxWoSxlJpVJYsWIFtmzZ4r1m2za2bNmC1atXn/T+M888E8899xx27tzp/Xvf+96HP/mTP8HOnTsnJRjpdBrt7e1V/6hCxmJOQeJm312yxRYXoqCMyCou5G/Q6omXyLHatoORAgW1YOZ4C2aiWiByrP6BUN3zC8hTbVWg7qdow4YNuOqqq7By5UpcdNFFuP322zE6Oop169YBAK688kosWLAAmzZtQiaTwbnnnlv1+52dnQBw0uu6QuYCp3Ihb0klYFluielsriisLD2FEzT7blZcKBEXE82kELqQUWdktFCCQyITQfxc9UOqVNQCGYckxRu0hPoxFIz1gAnTVOHSSy/FkSNHcPPNN6Ovrw8XXHABHnzwQc/UunfvXsRiM6ewqwxjJwW1IBaz0JpKYDhfwkiuhDltYr6HwgIXXHBEGZNzxTIKlQysqJe+ZyfWZNzyPFYqICNMQ0ctEF8XiMK6FPx+Gc+w+rHK8e6pQKi/7Pr167F+/foJf7Z169Ypf/fuu+8O85VkIaO4kOo23QytGZeMiBprMFVQpY+CFRfKFW0M58SQkapOzCmVZMR9plh6uggVKKjsqVQLgumuonxPZOaqBBWIgpcNkENGsgQUW0CO4qUKM0fCEAS5YRoak17UaWu0qrCQ2sVcdJZJMBwViymU8yWUmKYQegP8e2o77rMmAuTmqoRDkvq5Kt4zMkIgVO5+f3TDNIaMNAjRm1bZdjzntOqJILp2AZvwiZjllT1WBdEnEAp+EUBOiWkKBmwAyCSD3WzF3FfVvVoY5GTT0HiGZYTfqDzDnoF1pmfTGJwM0e7mINtXPRHEqwW+SUylnA+IP21RaBzHwO5rVvAzrHqsVd1sBStequdqu+cZEVkIjMZYZYSkqIxVVl0gFTBkpEGIrurINq1UPCYsg6VWiC6TTsX8B4gf6zCRxS14DaJDUhTGKloxoOYZyRVtFAW1qqCiAskJSdEg1P4hyXhGDE6A6DojlBZy0f0uPClUYd0NBtHFhfzqqwTGKknxUr1BA0HDudj5qtrUWZURFnGS6ZVIL5RgM9MZZ1AJlcso8KYKhow0CFlGR9UTHhDvGaE0VtEkc4RIDBoQ33wrO17ZoJsIkBHR6h6B1g2AXC+QarWAkVzHcWvaiACVsQb3G8cRQ7xUwZCRBiFe4qaxuAWvQZQyQqEDKEOrLG8BCc+I6PAbHeI1kw4P3lgFSfpUqpKmE0FjsqC1ich9Zd9fth3kiuIqYauAISMNQrST25vwCvtcMIju8ErFse5eg9hNi4ohDpAZulBPMtsFx9z9+ap+rKIlfSrEq8qYLDisqnqszak4WCWAqNUaMWSkQfgVWAWfKgn4KJhEGfUYNCA+tdcvoqT+vsoKXVAg1OJN2IQIdZMcLxAlJVPEfC2VbYwX3bo0qsdqWZYfLo9Yeq8hIw2CbVojeTHmKVIbtCQViMZYxZ60SCkjXmqv6A1a/aYlL3NI/ViZCsTIIE84jkNrvgqshF1VLZlEWDWa6b2GjDSINsHmKYoLuagNmtJYZaWAqm68BcjLCKMQphFdU4WSMsJCRSLGmivaKFUOXxTGKlLxYp+ZTsSQUthbiUFGp3gVUP+X1RzVVR3FTQQKE97zjIxH2yTmXoPYhlQj3gZNYawzJ0wjcqy2HeytpJ54sWsQMV/ZRmhZbkdv1RBZdoCS2gXIqauiAoaMNIigeSrqZER0u3lKk96Py4odKw3PiNj7miV0X0WOdaRQguP1ViIwX5uYusd/rMHGcSp7KzGILDtAKaQKyKk4qwKGjHCAyAWOUsEoJvuOVjq88gbb+Cmku7YLPn1QWuBEVhEu2zQ6MTOIDDWyvx+FaslAUBmJ9roEiFUyKWX5AeJDjapgyAgHyFBGKEncQPRVINHFhbKkPCMCzX+BzyShjAg8VVLbtESSTEpkGhDr8aJSCp5BRpdiFTBkhANEpvdSSp9LxmNoTrknPhGsnFSYpnJPS7aDfImvChT0FlBYzEUa4thzkklSMf+JI16UaowAYg2slA4OgGDFi9BcBcSnp6uC+tUhAmgVWDSKmc+oTASRpjhKBtaWVByscTDvxTzoLaAgc7O/92ihjDLn9PQsOTnfJ168FS+/FLz65xcIzFWB4WM6aoH4UDkFfxcQ6MhsyIjBiRAph1JSRgBxprhcsYxCxYdCYTGvKi7E+b4Ojbl/u3SChrcg+GzxXuAo9aUB/GerWOaveFFTC7y5KiSbho6KCVTXe+INSockQLy5XhUMGeEAUTJ32XYwWmCV/2hMBFGmOLa4UUkVBMSdQDy1gMgGnUrEkK6EUHiTTF8ZoXFPW1IJYYoXpa7TgFhlJEtsg54pGY2A+FR8VTBkhANExaGrzX80JoKoOLQnhaZopAoC4lLo2Em1gwgZAcQ9w1S62DLEYpawtgZZzzNCbK6O8w9JUVNs2wRmDtELNZoKrAaTQBRTZZPAPbmql/OBYIlpvmOldvoAgqa4aKsFQDDUKEbxoqICAeIyaihVEAb8zdN24CmsvEBtvnZ4hyQBVbArBIfK4UFkTRWVMGSEA0SZp/wy2jQmPCBOGfGzS2hMeEBcuuDQOK0wDSCeUFN6hkWdLKlt0JlkDMm4qzLyD6vSuq9MjRoSoAINEaogDJjUXoMpIGohp1ZYCBDpGaGViQCID11Quq/eWHmrQOP0SKYojxc1U6dlWYGqyaKIF42xMtWibDsY46wCZYmpe6LuqWoYMsIBovK+qZnEgGA2jZixUigCxtDhZSPwDtPQ84yw+yqMUBM5VQIyDg/0xsrf40VrbWpKxr0eYUOc5+sQscMDWyPHBFXCVgVDRjjAi7dzPlVSM4kB4rNpKI6V9+JGqXEcg6gW7NTMf0BQBYq2WReoNrHyBLW1ybIsYSFkqp4RABjN81WBVMKQEQ6YKTFoQHw2DaWxdghayGlu0GJO0NSK9gFBJXMGeLwEpfdSXJv8+cpvHc4Vy149GiphGpGp+CphyAgHBGVfnuYpihu0qAqsXnEsQht0h+CTFpXFDQimRnIm1HmKYxUVpiGo7gkqfEatRDrgk0CeSiab+5ZFo4EnQxTTew0Z4QD2YJRtB+NFfrIZ6cWN8wY9REwKBfwNlH+Yhp5nRJSpkyLJ9A2AgjJMCIXfRIRV86UyChW1gEqBN0BMSMpT9tJ06h8Bga7iEcqoMWSEA4J9THgWUqJoYBUVuqCWPgf4Y+VORgiHaWZGai//sZbKdqBaMp37KiKsGvy7UTKcizg8eIekZjr3FBAXalQJQ0Y4INjHhGeWCeXU3lHOTm62WFJSC0TEoN3Po0e8RNTKcRyHZtEzAWQkeEKldHgQUaSQ/d1aUnHECakFIsKqFA8OQDRLwhsywgkipF+KykjwWnhOBGqOdUBcNg21VEFATLPHsUAXYEpj9TKHOErc7O/mFhqjs6wyEsgz049iSBUQM18p1gQCxPYdUgU6s0ZziGCq1NLnACARj6El5Zam5zkRKC5w7FrGi36MvFEE5XxaagF/Qxx7PpJxC5kknaVGhMRN9QQtwnA+OFYAAHQ0p7h9Jg+IUDIpHpKAQAh5zJARgxMghozQSxUEgkYxfmOlSEbaMvw7vAafD0r3VYSBNVh91bLoyPki5irFFGZATMq2P1dpjVWEuZ6ilw3wPSyDAhoDqoIhI5wgIuZOURkB+EuExbLtlXCmREaCHV55Sb/sb9aSiiNBUM7n6QWiWJEUEBNSJTtXhWSY0Ds4AGIM5xSrJQPizPUqQWc11BwilRFqp612zmXSgxOK2mLOe9JTbJIHVBMGXiZsL3RBbKxsPuWKNorciBfRueodHKKtYgJi0phZGIRa+M2QEYNJ4ZERTqa4UkAtoLrA8d6g2zIJUu58gH8qM8W6G4DrBeKuAhENXQTLafNKxR8mSryCBwdeBRnJkhERKhDL8iOW2mvIiMGkaE3zlX6rUwVpTQTetQuoLm4Af+JFMYWZgV0TMyg2Coqp6YBLvJorJmxeSmaWqr+r8rcvcSzISHW++qm9/E3Y1J5hUfWeVMKQEU7gHaYZrMiDzak4Uglat4l37QKqixsgQhmhaYgD+J+2/A2a3n316wLxMibT9Iw0B2qBcJ+vxLJpglVJefmeqK5N/sHBkBGDE9DOORuBTYJOYpMA4K+MUM3lB/iftijWGGHobOZMRgLhN2rgfXjwPCOE+pcAlW62nNcmtgFS26CDITJuihcLqxI7PHQ2uUTQhGkMTgLvOg2DRE8fAH+jGNXTB+AvQrzDNNS8BYBAZYTgWHlnv1GsNMswU8KqyUD4LepjFVEDSTUMGeEE/mGaSmEhYowcCObz8zp90JzwAP/iQv5Ji95YmTLCS/ql2JeGgfd8pVqPAuBf+EyL+cqBUNu2Q9b3FKyBFBV1xJARTuB90sp6YZoZpIwQc6wDItQCuhs070ZjfpiG3n1lzzCvrqeD4+7hoZOgksm78BlVtQDgS7xGCiVUuhmQOzzEYpYXEjRkxKAKbQHzFA+w02knwQ16psi+gLixUlvcgJkVpmEGVt4+CpIeL46Hh2KgnQHF+crzGWZ/r1Qihkwy3vDn8UYHZ4+Xahgywgm8u/YOUt6gOcu+lDdoUWoBNdkX8FU4XmEaqhVYAf6hxiHv8EBPGeE51iChoX1fG3+GKZvNgSDx4pOKrxqGjHACe2ALJRv5UuP5/J5jnaQyMnNkX1FqAeWx8i7wRjFMw9MLVCzbXrHDqCsjXoHCdIJUOwMGnnWB2PNL0bcHRC+jht7TpClaA6cEHqa4IQ08I2OFMpdy2kPjdDdo3v4YynVGPAMrp5OWnzlEcazuvDrOocBblVpA8RnmGGocJKxiAnyrsFLOfAOi17nXkBFOiMcstHCs6jjkGeLoTYQ2zsRLB3f+cL4E2268nDZl6ZenCpQLpBxSXMw7OXY99TZogu0MgECRQo6HJIpzFeAbVtVnrPwqzqqEISMcwXMxp1pYCHDLaTPixVP6pThWdqp3nMaJV65YRp7wBs2zqiP7W1kW0Jqip4x0VZQRHqfKQcJ+EYCzWkB4rgJ8ixRS9ncB0etPY8gIR/CUfilv0AA/6bdUtr0MJIqGuHQijkzSnSaNjjW4QVOr1An4/qR8yUauwT4m7G/Vmk4gRlAtYPOKz1ylq2ICfDv3kl+XvFYVM4d4GTJicBK6Wvg0GnMcx5N+yS9wDUqEwQWSoloA8Jv0bINuI7pBt6YSiHEqpDRMuC8NUB2mabSbLWUVE/Dn1TAPFZNwyQGAc2qvl5pO7+AAmGwagynAKzUyV7S9eDtd6ZdPRg1bNFpScSQJuvMBjmSEuPkvFrO4jZURcqpjZWGaQsluuJst9TANz6Jn5JURjmZd6mPl3UtKNWiu/pqCPRzHGyQjLJshaIqlBl5poNQnPMAvo4ayeZWBHxlxf7+7heZYm1NxJOOuDNTo4cFTMYk+w75npNSwCkS5JhDANz3deEbkwpARjmCnrUbDNMGOvZZFT84HgnHoaKsFAM8wDW3ZF/AbMza6QTMvBlW1wLIsdHBSMofGqHtG3OetULY9A3VYUD88iCBeVMfKk4z8v//+NP7iO0/ghYPZhj8rLAwZ4QhuygjhgmcMwUnfCKhPeIB/mGYmjJXNgS7Cz3CX1xiwscMD5WrJANDC0QtEfazsugplG7liY8RLmzojHMjIU28cw6OvDaBkq+sAbMgIR3RyUkYo97lgaOcUh9aBjPCKQ2eJdgANgj1zjT/D7u93EVVGAH61Rqh7RmIxK7A28SHUVFWgllTcI16Nq7a0TdhsXcoVG89+O05gvhoywhFdnFqw63CC5lW7QCcy0ugJhHq8HeAXcz82SjtMA8AL0zSa3suIF+XDA1ub2H0JC+rz1bKsGbM2taUTYFH8RsY6Xih7KlJXiyEjkQCvOiOU25Ez8OoBoQPx8uXQBtOYiZ+0gEDhM05qgR5hGk4GVtJj5etn02O+hr+vwSwrqh4vXtlvbL9KxtUmTIQiI3fccQeWLFmCTCaDVatW4cknn5z0vXfeeSf++I//GF1dXejq6sKaNWumfL/O8FKteHlGCE94Xv4YHRY3XoWUmGxMtfEWwC9dkILsOx14jXWQeO0NwD/xHmuAjBTLNsYK7gZNe742HlYN/i7FRo8MPMgIU8u6mlNKEybqJiP33nsvNmzYgI0bN2LHjh1YtmwZ1q5di8OHD0/4/q1bt+Kyyy7Dww8/jG3btmHRokV417vehQMHDjR88dTAFt7hfKmhBnJDGpy0ulv4qEA6hS6iXmcE8K+tYbVAgw3aUzIbCF2UbSdAMukSLx4qUPD5j/oGzeZqW5pmvyEGHmP1VUy1z2/dZOS2227D1VdfjXXr1uHss8/G5s2b0dzcjLvuumvC93//+9/HX/3VX+GCCy7AmWeeie985zuwbRtbtmxp+OKpoaMp6cXwGpn01B3rQOCkFfEYNMDPR+EtcIQX8k5OxEsnZaSRkNRwrgiWQUr5GeYxX4e855f2Bu0VZGwgrKrDIQngpIywuaq4JlBdZKRQKGD79u1Ys2aN/wGxGNasWYNt27bV9BljY2MoFovo7u6e9D35fB7ZbLbqnw6IxyxPImwkNku95DIAdDMVKMdHBaK8kPPKpjlOvBAYwId45UtlT84nTUaaGm+Wxw4dLak4Ugm6FrwuDn42HdQugJMy4tUEoj1WHkomlcy3umbPwMAAyuUyent7q17v7e1FX19fTZ/x+c9/HvPnz68iNCdi06ZN6Ojo8P4tWrSonstUCh6nLc/ASlj2bW9Keil0jSxwOpxAgotbI4WUgrFZqvBSQDnIvjHLL0VOEV2e76mBDdoLqdK9p4B/eGgkJKWD2RzgUzHZPyTRfX4Bzp4RhZk0gORsmltuuQX33HMPfvrTnyKTyUz6vhtvvBFDQ0Pev3379km8ysbAIw7tTQTCJ5B4wMl9fJTHpKc7VnZtxbITuo9JvlT2uhPPaklzuzbe4EG8gtVXKTYEZOjgcXCojJXy8wvwMZzrMFcBPqn41EvBM/AIq1LJfKuL9vX09CAej6O/v7/q9f7+fsydO3fK3/1f/+t/4ZZbbsF//dd/4fzzz5/yvel0Guk03QV7KvAwiumQTQO4TPr4WDH0ydK2HW+DpjzW5lQc8ZjlmhXHS2hO1X9aYvc0HrNIqwVs0ypX7k0Yfwsjp9Tl/GCRQsdxQmUS6GA2B/gYznUhIzyI13ENVEyAT1iVir+rLmUklUphxYoVVeZTZkZdvXr1pL/3jW98A1/5ylfw4IMPYuXKleGvVgN4+fwh2zqXbcdrv065iBLQuPQ7nCtpYf5z+5g0dgI5OuJPeMpqQSbpex/CjpWpBd3EF3J2cCiWHc/jUi908VFwVWwJz1UAmOWZdfOhP+No5e/U3Ur7Gead2qsSdYdpNmzYgDvvvBPf+9738OKLL+Kaa67B6Ogo1q1bBwC48sorceONN3rv//rXv46bbroJd911F5YsWYK+vj709fVhZGSE3ygIwQtdhGTlQYZLfdI3WruATaCmJG3zH9D4pGenD8rmVYaOBk1xx4g3yWNoSsaRirvPXdhQja9i0h4rU0ayuRJKIQ3nOvi7AH9TbSRziP3uLMU+iunAo0ih32Fb7Vjr1osvvfRSHDlyBDfffDP6+vpwwQUX4MEHH/RMrXv37kUs5m8s3/rWt1AoFPCRj3yk6nM2btyIv/3bv23s6gmi0UqH7KFqTSeQiNPeoBtVRnQ5aQFBkhlurEeJnD5qQWdTEkeG86GlXyox6OlgWRY6mt2xHh8tYEFnU92f4VdLpj1WVnbAcdw1pqe1/jC4302c9jM8q6JmHOVARlRv0NOBpzKi+hkOFbxev3491q9fP+HPtm7dWvXfb7zxRpiv0BYsVzvsqVIXQxwQrF0Qbqw6kZEetsCNhFvgGGGbRVz2BRo/bR0n4s6vBV0VMhJ2MffS8Ik/w8xwPjhWxPHRQigyoouXrbtiEGdlB5IhDnVHNSEjPMy6Xlh1JmXTzAQ02p9Ghz4XDCzkEHasvuxL19DJ0N1gHJpKXLYWNFom/bgmPgrAP+WHPjxoNF/9WiONhZCpk5HOYNmBkOrIcU3ISKNzNV8qY7Til1IdVjVkhDM6G4y3U2/RHUSjsVldvAUAMKtykgwr/eoSgwYaP21RKaJUCzoarDXiK5n0x9po515dlMxYzPKevTDz1XEc7cI0hZKNXIiyA8Esv3bFWX6GjHBGo5UOdZFCgcbTBY+OuCpDGMlYNhiJCBum8Usu017cgMbVAj9VkP4z3NXgyVJHZSSsn00XMgIElcz6xzqSL6FQMflSrgkEuN5CVpo/zDPsK7ZJpU3yAENGuKOzwTojurjzgcb7XbCNvUcDH0UjixsAHBvR46QFNG6K89Nd6Y+10ZRXHVo3MPDKftOJjIRRRtgcb0rG0ZSKc70u3rAsX9EIs+ccJ6ROGzLCGWxRypdsjIeoXaBLESWg8WyaoxX/hQ6hCxamGRgJ5xk5TsQkVgtYCeyhkLVyqBRRqgWNtG9wHMdXRnQ4PDRwUBorlLzqw9RrbwC+UfxYiPmqi3mVoZFDIStQSKEmkCEjnNGaTiBRkc3ChC/8vjT0yQibBKOFcqh45cAIyzChLYUCwUJKjXlG9NigKw3kQmzQtu14v6dDmKaRkNRIvoSy7Vbt0+Hw0MimxVTMTDKGFuJqAdCYknnMW5foz1UA6Glhfrb6iZevjKh/fg0Z4QzLsgJlputf4IY08oy0B1qJhxkr84zoMOm9k9Zooe6eLY7jeJNeh7E20nMomyuisj+TkH6ngx9WDXFwqDzz6UQMmST9DboRzwhTBGe1pJV7C2pBd0t4w7ku5lWGnjb3OgeGQ5ARQmM1ZEQAuhpZ4DQK01iW1VBGDVsodDCwsslaqvSnqQfD+RKKZXeH1kEZaehUWfmdlhT9qrpAY2EanUKqQGPZb0zF7GmjP1eBxpTMY5q0M2Do8ULIIcI0hPxd9FcLDdFIoybfJKb+4agFYWuNFMu2d7LUwTOSTsTRlna9FPXKoez00ZyKa3GCZhvO0dF83SoQpcWtFvhhmvDKiA5+EaAxzwhTRno0mKsAHwMrBbWgFsziEKah0KbCkBEB8MI0IQyAOlVgBcKfttgGHbP02bi6Q5aZ1s0Qx7KbimWnbt8IlWqOtSKY/VYv8WLzu0MTZaS7gWwandLwgcaUEeaP0cGoC/hhmiPDYZQRk00TaYQ9gZRtv9jObE3k0LC1RgYCqa5xwl1sgwhba4RSXLYWpBNxL13wSJ1xaJ2qrwI+mS7ZjleJslYMalIKniFoTGbG21rhh2n0eIYbMese0yjLD/CVkTCZft7aZMhINNEVMuX16GgetuOqBbpsXGEnvZ/WqwfpAoKmuPomvW7KCOCHao7UucDpVH0VcLNDmLel3vmqm2eEXafj1J8pdWREr/k6K3BIqpd4+WEaPcY6u40ptmHCNJXMNxOmiSY6QnpG2Cl0VmtaG7UgbK2Ro5qlzwEB6TesMqLJBg0As0Oa4nSqvgpUst9CFnljz7AuxCsZj6GtonjVq2R6YRpNFFt2SHKc+v1Auh0ePANrmDANoZIDhowIQJcnh9b3cDAyMluTuCwQrOpY30LupQpqNNawrcl1KgXP4CkjocM0+oy1K2Qq/uHhHAB9QqpAIKxa5zPshWk0eYaT8ZgXaqxXtdWpjxTgr6HjxTJG87Vn+hXLNoYr7zdkJKLoalAZ0Wlx88Ya0tSpy4QHwjv0dSoFzzA7ZMXZQc2UESB8s7zDGs5Xv6t4vSqQXsoI4G/S9ZCRXLGMsYp3SJfDQ0sqjkzS3crr8bOx5z1m+c0xVcKQEQFgabn1Lm4sLqvT4tYV0sDqu/P1mPCAL4ceqze1V7MME8B/BustpMQKpemykANBY3J9Y2V/mzltGe7XJArdIQ4PxbLtkRcdDw/1kBH23mRcfRfbWmFZlrc21ePxCjZlpWALMGREAJgZaGgGKCONe0Y0GmvIbBrd6hYAPkmsVxmhlCpYK3rbXTLRXyfxYsrInHZ9nuEwXcXZ8xuPWSTk/FoRRskMtm3QodIsQ5jeWdRaVBgyIgBeDHq8CLsOJ7eOnpGwtQsGNAzThPaMaElGwmXT6GZgBXzyfzhb+1jHCiWMVOLtczQ6PITp3Ms2uO6WFGIETtC1IkytEd3MqwyzW+s/KA0S87IZMiIAs1pSsCy3bkg9G5eOygh7kHPF+roUH9XRwNrix6DrIZnUTiC1IIxD3+3Bw5rk6TNWpowwQ2otYMSlKRlHa1oPOR8I1ECqo++Q19CSyKZVK8KFafTplxVETyhlhFZDS0NGBCARj3kPR3+29gVOR89ISyqOVNx9jOo5bTEGr5NnhC1uZdtBNlfbYl4s28jm3BO0Tov57EBJ+FqJ13ixjELJBqBP7Q0A6G1vbK7qJOeHUUaOarguAeHCNF71VU1qjDDMChFWPU6sJpAhI4Iwl8Wh61ngNFRGLMvyPDK1+kbGCiWMF10VRSdlJJXw6zTUWn8j6FjXpcQ/4C9u9ZSEZypKKhHTSi1gBtTDdXhGmDKiU4gGCNe51+/YS2PTqhV+p+36fRS6jZUdfuvKphk1YZoZASb99tVIRnLFMoYrJ2idyAhQf38aNmHSiRhaUvQbxwVRbxzayy5p1iveHiwJX+tpiz3r8zoyWqkFTBkZHCsiV6wt1MhCOjqZV4FwvaS8GiMaHRyAQMXkOjZoHUOqQDiPF7WQqiEjguBJv0O1kRGmiqQTMa87rC6otz/NQKDplk6bFhCsXVDbpGclmqmcPurB7DpLwh8aGgfgE3Fd0NGU9ErC11rk7bCGab2An+lXT50RHQsUAg0aWDUKHwMBc31dnpHK2kQkpGrIiCD4YZraHg5dY9BA/f1pdCwFz8CIV81hmooyolMpeAbvtFXjBt0fUEZ0gmVZXrilVhMrC9PopmL2VsjTsdEC8qXaVKABDf1dQHUNpFo7Mh/XNEwTpn3DocpBuZfIfDVkRBDqDdPo6Bdh6K43TKNZV8wgelrrG+sxDQueMbBqm7UucGxxm6uZMgIEao2EODzohM7mJNIVFaivRtVWx+qrgL++FMuOZyKfDjqm4QP+wWFovOiZyKcD25vmdzQJu656YMiIIDC2WauBVccaIwz1nqAHNCx4xuAXPqttrKwUvJZhmjrTBdmzPpfISasesLDq4RrnK3ufbgZWy7Iwv9PdfA7VSEa8sKpmGSaZZBzNFU9a7QclPZWRYBXVWsY6Xih7FVjnddKYr4aMCEK96YI6KyPzKw/zgcHxmt6vc5iG1RqpNV2Q+Wh0W9yA+kvC66yMMO9HrVVYj2jqGQH8MBrz+EwF23b8NPw2/Z5hv9bI9Pe1WLa9zDHdlJFYzPLWmFoODwcr974lFSfjUTRkRBDYgnx8rFhTbFZX2RcAFlROWgdrJSOjep60gKBRrDYywjYt3RY3wA9J1WpgZWZtHZWROXUcHopl2yOjumXTAMC8DjZfpx9rNldEqVJnRsdn2O87NP18ZQcHy9KrnQHDrDoyaliIbl5nExmPoiEjghB06NdSZlpvZcRf3GoxikVBGalV9t1fIWjsb6QT6qnqWLYdT1WYRyQGXQ+YwlFLqJH9PeIxS0tjcj3KCBtreyaBdEKvNHygvkw/Nqc7iTSOqxc9dRyU2MGRktnckBFBsCyrrsJnOntG2El4vOjHIaeCrqmCQP1VHQ8cdyf9wi79Nmg/TDP9WI+O5FG2HcQs/bIugPrCqmyu9rTqVTuGgXkEajGw6lpjhIHVGqnFhO1XX9Xv+QXq83ixkKohIzMEbIGrJaNGZ2Ukk4x7i1UtvhFdTWKAr+YcH5u+P02uWPYWBh3JSFAZmW6sbHGb05ZBIq7fslJPNo1ffZXOQl4P5tcRpgnWBNIR9fjZ2MFhQVez0GsSBa8kfA3qnk9G6KxL+q0aGsFL753mBOI4jtaeEcCf9NP5Rmzb8eRQHRc4Vq2wbDsYnKZMOvtbtKTiWpWCZ2CLW8meviQ8I9xUahbUC5YVMzQ+fRVWv+CZfs8v4CsjNYVpmAqkoXkVABZViMX+49OPdd/xMQB6HhyAQEn4GlRbdu/nE8mkAQwZEYq5XjfQqZlqNlfycsN13KCB4Glr6kk/NF5EWWNDXCrhN0Gcbqz7vZMWHZNYPUgnfBI1nfTrGeI0zKQB6qvCqmspeIZ57e5cPT5WnLbTtq9i6jlWRiz2Hxub9r37Ku9ZpKkyUo/H69AgM5vTIV6GjAhErcoIW/zaMwlkkvqZxADUXLuAZdK0ZxLe4q8bTpnlLlZ7jk69wDFpeIGG5lUGL6Nmmg26T+MaI4Dr8arVN3LYC6nqOdb2poRXf2O6ELLuYZpF3b4yMl2okR0eFnXrOV9n1ThXgYAyQmi+6rkbaIJaC5/p7BdhqDU2yyY8pVhlvVhcWeD2TnPaOhBQRnRFrQ24+jRO62WotXuv7vPVsiw/o2aa+TqgceYb4Bo04zELhbI97X31wzR6KyPThWlG8yWvIu08QgclQ0YEorettpOW7n4RoPZaI0xNWNKj54QH/NPWtGRkkGXS6DvW2TWWhO8j6M6vF/UqI7p6RoBArZFplEzdlZFEPOY9k/uPTz5fc8WyZ15epOnhgc3VY6NTm+uZKtKWTqCVSMEzwJARoZjrKSP5KetvHNFc9gWqa41Mhd0DowCAJbNahF+TKJzikZHRKd/HFj+9wzS1lfr3DKyaekaAQBXWaTJqjmhaCj6IWpWRfcfoGR3rBfOA7JuCjLBDVHMqrqWXDXCzExMxC2XbmTL85mXSELunhowIBFuYx4vlKRs16VxjhIGRkf7hHIrlyRs17TnqbuCnaExGFs+aOWEadtqaiow4juOdtnRWRpghdarOvcHMtzkaEy8mzx+aYtPK5oqeMrK0R9/5ykysjFhNhH2BekA6ms0BVwVia9OuI5MflJh5lVqo3JARgcgk/WyEqaRf3WPQgMvKU4kYHGdqw64Xppmlb+iCKSMHBycnXsWy7Z1OFmqsjDBVZ98UxCs7XkKu6P4ddFZGeplnZAplZHCsiGLZVTl1LO7GML8GZWR3ZUOb3ZZGW0a/1HQGFlad6hnWPZOG4dQKadw9MDLpew4SPTgYMiIYtcSh2UlM58UtFvNNcZP5Rkpl25NKl2h80prdlkY6EUPZdiYda99QDrYDpOIxbePtAHDa7FYAwOtHJl/cDmXdv0FXc1LbbDAgWPhsqrnqEpXO5qSW5dEZ5nol4ScfKwup6qyKAH52zFS1RvxMGs3JSGW+7hqYXBnpI1jwDDBkRDhqSe9lkprOoQsgUGtkkmJKh4ZyKJYdpBIxLTu7MliWNW1GTbDGiI4lwxlOne0+k0dHCzg+iUufPds6qyJAMEwzuTLi1RjRWMUEgh6vyTdotqGdNlvvdakWz4juBc8YGHGcKkxz0HhGZiamK3w2ki95WRdn9LZKuy4RmM7E+gbzi3Q3a71BA9PXGolCjREAaEknPEl/MnUkCpk0gB+mmaoK66GIEC92r7K5EkbzE/vZoqKMsGy2Q0M5lCYJq7KiaDpnvgH+vdo9hTJyiGCTPMCQEeGYThl5tX8YgHvS0rFtdRALpqk18sZANBQgYPo4tGde1ZyMAMBpc1yS/NrhSciIV/BM77G2NyWQnqbT9st97nxl4Std0ZZJoq2S1jlZqGZXhXwu7dF7rHPa0khVwqqTjVX3gmcMTMncf3wM+dLEhNqEaWYopit89kqFjJzR2ybtmkRhOun3jQiYVxmmC9McGKyk9Wou+wLAm6YjI6zgmeZqQbAY2GSS/kt9WQDAWfP0n6++b+Tk+eo4TmSUkVjM8kzkE93X0XzJKxSmuzIyuzWN1nQCtgPsnUC1Hc4VMVxRwowyMsPACp9Nlvf9Sr+7wEeJjByaJEzD0np1Nq8yTBem2R8hZYSRkUnDNNlohGkA4Kx57QCAPxwcOulnjuPgxUPDVe/TGfOmaOFweDiPsUIZ8Zjvj9IZC1lZ+AnSe5mS255JaNnQMgjLsjx1ZCITKzs4tGcSaCFU8AwwZEQ42IPxav/IhPFKXxnRWwoF6lFG9CcjiwNhmokK2nmekQgoIywk8do0nhFdO/YGce6CDgDA8weyJ/3syEgex0YLiFnA6XMicHjw0ntPJiPMALmoq0nbHlJBeLVGJlBGvLTeCJAuYGoTKzOvzid4SNL/KSOOU3ta0ZZOYLxYxqsTyNyvVpSR0yOhjLiL23C+hGyuuuV82XY82fCUCIRpmJw7nC/h+Fj1WG3b8RZ43d35gK+M7D8+fpKxs2w73mJOqelWWHhkZAJlhKkiS3pa0JTSN62XYaowza4B5hfR/+AABDJqJgir7jsWjUwahqVT1Bqhal4FDBkRjljMwvmL3AXumX2DVT8bGi96EncUlJHmVAKdza7MeaI60pfNoVC2kYxbJFl5vcgk455H4kTfyJGRPAplG/GYpb2PAnAL2nU2J+E4J5+2Xu4bxmihjNZ0wqtxoDPOme+GX3YPjGLkhCyTlw4xv4j+IRrAT8WfyHDOCp7pbl5lmKrWiGde1dwvwuDVGplIGanca4pmc0NGJGDZwk4AwDP7B6teZ5k08zsyWlc4DMKrNXLCAscyaRZ1NyOueVovw2QmVtaTZm57Bom4/lPMsqxJQzXb9xwDACxf3BmJ+9rTmsa8jgwcB3jxUHWo5qVKJs1Zc/VXMQE/S+r5A0MnNVZj5tVTNa8xwjBVrRH2WlTCNKdOkd77dOVATPHwq/9KqQGWLeoEADy9d7Dq9VciFKJhYCEYJmkzsBojUfCLMHg9ao5WT/oomVcZ3jR74oyap/YcBwCsOKVL+jWJwjnzmW+kOlTDyMmZc6OhjJy/sAPNqTiOjxU9osXgkZGohGkqRKM/mz8p1Mh61kQtTHN0tIChQAi5ULLx1BvufF192iwl1zYVDBmRgAsqZOSV/mGMFXzpl5lX3xyRkxYAvLXykD/yypGq1/dEyLzKMJky8npFHo3K4gZMnlHDFreVp3RLvyZROHeBSzaeC5CRQsn2iNhZ86NBRpLxGN6yxL1v23Yd9V4vlm3vmV4aEWWkqzmJ5orP58Sw1P6IKSMt6YTXhmRXwDfyzP5BjBfL6G5J4QyCBmxDRiSgtz2DeR0Z2E61S5+RkdPn0JPMwuIdb54DANi+53iViZWFaZb0RGPCA74KdCIZeeiFfgDAH51K7/QRFh4ZCSgjh4bGcWBwHPGYhQsWdyq6Mv44t6KM/CEwV18/MoKS7aAtk4iEUZeBnZC3vT7gvbbv2BhKtoOmZNyrSqs7LMvyQjVvBMIXAyN5r6N6lA4PE1Vi3fa6Szj/6NRukhWwDRmRBM83EjCxRqnGCMOi7macOrsFZdvB/33VX+D2eJk00ThpAf5JavfAqJfeu+foKF48lEU8ZmHN2b0qL48rTgs04CpX/AVMFTlrXhtaidUsaAQso+bVw8MYL7iSPgvRnDW3XdsW8xOBKZlP7DrmlR4IFjujuGmFxYWndAIAHny+z3vtgecOAXCNy82p6DzDzMQ6ERlZTfSQZMiIJDDfyM4KGTk2WsDAiFty+nSCZqJG8I4zXHVk68tuqCZfKmPPMeYZiY4yckZvG5pTcfRn83isMtF//Qd3oVu1tBvdLXqX9w9iQVcT0okYCiXbk7WfesM1r0YpRAO4nbZ7WlOwHb/iqmdejUDl1SDOmd+BtkwCw/kS/nDQHatHRiISomH48IULAQD3P3fI68fzH9v3AwA+VPlZVHDqCbVGcsUytu+l6xcBDBmRhmWV9F5GRliIZlF3U6QYOQC8482zAbi+Ecdx8G+P70WuaGNue0b7cstBtKYT+OgKdxH77qO7AQC/qpy63nPuXGXXJQLxmOWdtph3IormVcCV9D0Ta2WD9syrEUnrZYjHLKxa6m5OjFA/s9/1ykTFvMqw4pQuLJnVjLFCGQ8+34fXDg/jmf1DiMcsvP+C+aovjytYFtQLh7Io2w6e3juIQsnG7LY02b5KhoxIwvkLO2FZrnnqyHDer7xK0EjUKC5a2o2mZBx92Rye2nMcdzz8GgDg+jWnRyL9M4i/vHgpLAv4zUuH8djrA17G1LvOiRYZAfxW8r989hBG8iVvg165JFpkBPBNrH+omFiZMnJmhMzmDCxUs23XUTz66gB+8cxBAMDbz5it8rK4w7IsTx35jx378R87DgAA3nHGbPS0plVeGndcsKgLLak4dg+M4s7f7fIMyqtPnUU2zBiKjNxxxx1YsmQJMpkMVq1ahSeffHLK9//oRz/CmWeeiUwmg/POOw8PPPBAqIvVGa3phGdU/bv7X8DXf/USgOgUUAoik4x7UuB1//40jo0WcNrsFnxkRbSkUMCNq7/zTDcs9Zl/3wkAuHBxp/Yt5ifCR1YshGUBP336AD5x9+9hO276MrXunzxwXsU3sm3XUXz1/hdwZDgPy4pW5hsDm6u/330Mn/vxMwCAK/7oFKxcEq3wGwB88MIFAFwV6J4n9wIAPhzBdam7JYWNl5wDALj1P1/GfU+7xItqiAYIQUbuvfdebNiwARs3bsSOHTuwbNkyrF27FocPH57w/Y899hguu+wyfOITn8DTTz+ND3zgA/jABz6A559/vuGL1w3MxPqznQcxWijjwsWd+Pjblqq9KEFgoRrWC+Gza98ciQJgE+HjF7v3kHmA3nPuPJWXIwzvePMcfP3D5wMAnthd8YtEUBUB/Foje46O4c7f7a68Fi2TI8Obe9vQ3ZLCeLGMg0M5LJnVjBv/7EzVlyUEC7uaPSXo+FgR7ZkE3nnWHMVXJQYfXbkQf3p2L4plx8v4o2peBUKQkdtuuw1XX3011q1bh7PPPhubN29Gc3Mz7rrrrgnf/4//+I9497vfjc9+9rM466yz8JWvfAUXXngh/vmf/7nhi9cNqyoPQnsmga9+8Fz8+NNvjZTJMQhmYgVc8+7aCIYtGFafNqtKvn93xPwiQXxs5SJ89YPnev+9MmJ+EYaFXU346IqFOGd+Oy67aDG+8ZHz8f99fJXqyxKCWMzCH53qqiAxC7j1Y8siSboYggrtJcvmI53Qv8/QRLAsC5s+dB56Wt09Zl5HhnRfsLqeuEKhgO3bt+PGG2/0XovFYlizZg22bds24e9s27YNGzZsqHpt7dq1uO+++yb9nnw+j3w+7/13NntyB00d8YEL5qOrOYllizojF6M8EYtnNePcBe34w8EsvvDuM8nGKXnAsixc/cen4q9/9AyWLeyITPGkyXD5qlOQTsTx0At9eN+yBaovRwgsy8Lff3SZ6suQhg8uX4gHnuvDde88Aysilh11It597lxs/NkfMJwvRTJ0HERPaxp//9FluObftuPDFy4kvQ7XRUYGBgZQLpfR21tdP6G3txcvvfTShL/T19c34fv7+vomfD8AbNq0CV/+8pfruTQtkIjH8M6zolN7Yjrc9ZdvwcBwAWdHpGLlVPjQhQuQTsZw/oJO1ZciBR9ZsTDyC/lMwp+e3YuXvvJuZJLRVAmCaE4lcPfHL8KR4RyWL46mshfEn7x5Dp7duBapBO0wOcmru/HGGzE0NOT927dvn+pLMgiBOW2ZGUFEAPck/d/On+/1qzEw0A0zgYgwrDilC++OqLdrIlAnIkCdykhPTw/i8Tj6+/urXu/v78fcuRPHyefOnVvX+wEgnU4jnY52GMPAwMDAwMDARV10KZVKYcWKFdiyZYv3mm3b2LJlC1avXj3h76xevbrq/QDw0EMPTfp+AwMDAwMDg5mFui3TGzZswFVXXYWVK1fioosuwu23347R0VGsW7cOAHDllVdiwYIF2LRpEwDguuuuw9vf/nbceuuteO9734t77rkHTz31FL797W/zHYmBgYGBgYGBlqibjFx66aU4cuQIbr75ZvT19eGCCy7Agw8+6JlU9+7di1jMF1ze+ta34gc/+AG+9KUv4W/+5m9w+umn47777sO555472VcYGBgYGBgYzCBYDms3ShjZbBYdHR0YGhpCe/vMMEQaGBgYGBjojlr3b/oWWwMDAwMDA4NIw5ARAwMDAwMDA6UwZMTAwMDAwMBAKQwZMTAwMDAwMFAKQ0YMDAwMDAwMlMKQEQMDAwMDAwOlMGTEwMDAwMDAQCkMGTEwMDAwMDBQirorsKoAq8uWzWYVX4mBgYGBgYFBrWD79nT1VbUgI8PDwwCARYsWKb4SAwMDAwMDg3oxPDyMjo6OSX+uRTl427Zx8OBBtLW1wbIsbp+bzWaxaNEi7Nu3L7Jl5s0Y9UfUxweYMUYFUR9j1McH8B+j4zgYHh7G/Pnzq/rWnQgtlJFYLIaFCxcK+/z29vbIPlgMZoz6I+rjA8wYo4KojzHq4wP4jnEqRYTBGFgNDAwMDAwMlMKQEQMDAwMDAwOlmNFkJJ1OY+PGjUin06ovRRjMGPVH1McHmDFGBVEfY9THB6gboxYGVgMDAwMDA4PoYkYrIwYGBgYGBgbqYciIgYGBgYGBgVIYMmJgYGBgYGCgFIaMGBgYGBgYGCjFjCYjd9xxB5YsWYJMJoNVq1bhySefVH1JobBp0ya85S1vQVtbG+bMmYMPfOADePnll6vek8vlcO2112LWrFlobW3Fhz/8YfT39yu64sZxyy23wLIsXH/99d5rURjjgQMH8Bd/8ReYNWsWmpqacN555+Gpp57yfu44Dm6++WbMmzcPTU1NWLNmDV599VWFV1w7yuUybrrpJixduhRNTU047bTT8JWvfKWqZ4Vu4/vtb3+LSy65BPPnz4dlWbjvvvuqfl7LeI4dO4bLL78c7e3t6OzsxCc+8QmMjIxIHMXUmGqMxWIRn//853HeeeehpaUF8+fPx5VXXomDBw9WfYbOYzwRn/70p2FZFm6//faq1ymPsZbxvfjii3jf+96Hjo4OtLS04C1veQv27t3r/Vz0+jpjyci9996LDRs2YOPGjdixYweWLVuGtWvX4vDhw6ovrW488sgjuPbaa/H444/joYceQrFYxLve9S6Mjo5677nhhhvwi1/8Aj/60Y/wyCOP4ODBg/jQhz6k8KrD4/e//z3+9//+3zj//POrXtd9jMePH8fFF1+MZDKJX/3qV3jhhRdw6623oqury3vPN77xDfzTP/0TNm/ejCeeeAItLS1Yu3YtcrmcwiuvDV//+tfxrW99C//8z/+MF198EV//+tfxjW98A9/85je99+g2vtHRUSxbtgx33HHHhD+vZTyXX345/vCHP+Chhx7CL3/5S/z2t7/Fpz71KVlDmBZTjXFsbAw7duzATTfdhB07duAnP/kJXn75Zbzvfe+rep/OYwzipz/9KR5//HHMnz//pJ9RHuN043v99dfxtre9DWeeeSa2bt2KZ599FjfddBMymYz3HuHrqzNDcdFFFznXXnut99/lctmZP3++s2nTJoVXxQeHDx92ADiPPPKI4ziOMzg46CSTSedHP/qR954XX3zRAeBs27ZN1WWGwvDwsHP66ac7Dz30kPP2t7/due666xzHicYYP//5zztve9vbJv25bdvO3Llznb//+7/3XhscHHTS6bTz7//+7zIusSG8973vdT7+8Y9XvfahD33Iufzyyx3H0X98AJyf/vSn3n/XMp4XXnjBAeD8/ve/997zq1/9yrEsyzlw4IC0a68VJ45xIjz55JMOAGfPnj2O40RnjPv373cWLFjgPP/8884pp5zi/MM//IP3M53GONH4Lr30Uucv/uIvJv0dGevrjFRGCoUCtm/fjjVr1nivxWIxrFmzBtu2bVN4ZXwwNDQEAOju7gYAbN++HcVisWq8Z555JhYvXqzdeK+99lq8973vrRoLEI0x/vznP8fKlSvx0Y9+FHPmzMHy5ctx5513ej/fvXs3+vr6qsbY0dGBVatWaTHGt771rdiyZQteeeUVAMAzzzyDRx99FO95z3sA6D++E1HLeLZt24bOzk6sXLnSe8+aNWsQi8XwxBNPSL9mHhgaGoJlWejs7AQQjTHato0rrrgCn/3sZ3HOOeec9HOdx2jbNu6//36cccYZWLt2LebMmYNVq1ZVhXJkrK8zkowMDAygXC6jt7e36vXe3l709fUpuio+sG0b119/PS6++GKce+65AIC+vj6kUilvcWDQbbz33HMPduzYgU2bNp30syiMcdeuXfjWt76F008/Hb/+9a9xzTXX4DOf+Qy+973vAYA3Dl2f2y984Qv47//9v+PMM89EMpnE8uXLcf311+Pyyy8HoP/4TkQt4+nr68OcOXOqfp5IJNDd3a3lmHO5HD7/+c/jsssu85qsRWGMX//615FIJPCZz3xmwp/rPMbDhw9jZGQEt9xyC9797nfjP//zP/HBD34QH/rQh/DII48AkLO+atG116B2XHvttXj++efx6KOPqr4Urti3bx+uu+46PPTQQ1VxzCjBtm2sXLkSX/va1wAAy5cvx/PPP4/NmzfjqquuUnx1jeOHP/whvv/97+MHP/gBzjnnHOzcuRPXX3895s+fH4nxzXQUi0V87GMfg+M4+Na3vqX6crhh+/bt+Md//Efs2LEDlmWpvhzusG0bAPD+978fN9xwAwDgggsuwGOPPYbNmzfj7W9/u5TrmJHKSE9PD+Lx+ElO4P7+fsydO1fRVTWO9evX45e//CUefvhhLFy40Ht97ty5KBQKGBwcrHq/TuPdvn07Dh8+jAsvvBCJRAKJRAKPPPII/umf/gmJRAK9vb3aj3HevHk4++yzq14766yzPEc7G4euz+1nP/tZTx0577zzcMUVV+CGG27wlC7dx3ciahnP3LlzTzLNl0olHDt2TKsxMyKyZ88ePPTQQ1Wt53Uf4+9+9zscPnwYixcv9taePXv24K//+q+xZMkSAHqPsaenB4lEYtq1R/T6OiPJSCqVwooVK7BlyxbvNdu2sWXLFqxevVrhlYWD4zhYv349fvrTn+I3v/kNli5dWvXzFStWIJlMVo335Zdfxt69e7UZ7zvf+U4899xz2Llzp/dv5cqVuPzyy73/r/sYL7744pNSsl955RWccsopAIClS5di7ty5VWPMZrN44okntBjj2NgYYrHqJScej3snM93HdyJqGc/q1asxODiI7du3e+/5zW9+A9u2sWrVKunXHAaMiLz66qv4r//6L8yaNavq57qP8YorrsCzzz5btfbMnz8fn/3sZ/HrX/8agN5jTKVSeMtb3jLl2iNlD+Fig9UQ99xzj5NOp527777beeGFF5xPfepTTmdnp9PX16f60urGNddc43R0dDhbt251Dh065P0bGxvz3vPpT3/aWbx4sfOb3/zGeeqpp5zVq1c7q1evVnjVjSOYTeM4+o/xySefdBKJhPPVr37VefXVV53vf//7TnNzs/Nv//Zv3ntuueUWp7Oz0/nZz37mPPvss8773/9+Z+nSpc74+LjCK68NV111lbNgwQLnl7/8pbN7927nJz/5idPT0+N87nOf896j2/iGh4edp59+2nn66acdAM5tt93mPP30014mSS3jefe73+0sX77ceeKJJ5xHH33UOf30053LLrtM1ZBOwlRjLBQKzvve9z5n4cKFzs6dO6vWn3w+732GzmOcCCdm0zgO7TFON76f/OQnTjKZdL797W87r776qvPNb37Ticfjzu9+9zvvM0SvrzOWjDiO43zzm990Fi9e7KRSKeeiiy5yHn/8cdWXFAoAJvz3r//6r957xsfHnb/6q79yurq6nObmZueDH/ygc+jQIXUXzQEnkpEojPEXv/iFc+655zrpdNo588wznW9/+9tVP7dt27npppuc3t5eJ51OO+985zudl19+WdHV1odsNutcd911zuLFi51MJuOceuqpzhe/+MWqTUu38T388MMTzr2rrrrKcZzaxnP06FHnsssuc1pbW5329nZn3bp1zvDwsILRTIypxrh79+5J15+HH37Y+wydxzgRJiIjlMdYy/i++93vOm9605ucTCbjLFu2zLnvvvuqPkP0+mo5TqD8oYGBgYGBgYGBZMxIz4iBgYGBgYEBHRgyYmBgYGBgYKAUhowYGBgYGBgYKIUhIwYGBgYGBgZKYciIgYGBgYGBgVIYMmJgYGBgYGCgFIaMGBgYGBgYGCiFISMGBgYGBgYGSmHIiIGBgYGBgYFSGDJiYGBgYGBgoBSGjBgYGBgYGBgohSEjBgYGBgYGBkrx/wNm6eZtO4GerAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "L_ops = None\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[2].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5c275074", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "c42a6250", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rho0 = InitialDensity(n_qubit = 2, state = [0,0])\n", + "L_ops = 0.1 * (torch.kron(sigmaminus(),sigmai()) + torch.kron(sigmai(),sigmaminus()))\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d75196d1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rho0 = InitialDensity(n_qubit = 2, state = [0,1])\n", + "L_ops = 0.1 * (torch.kron(sigmaminus(),sigmai()) + torch.kron(sigmai(),sigmaminus()))\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[2].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4d90055a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "64a008a7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/torchquantum/pulse/__init__.py b/torchquantum/pulse/__init__.py new file mode 100644 index 00000000..3f785775 --- /dev/null +++ b/torchquantum/pulse/__init__.py @@ -0,0 +1,4 @@ +from .utils import * +from .sesolve import sesolve +from .mesolve import mesolve +# from .smesolve import smesolve diff --git a/torchquantum/pulse/hardware/__init__.py b/torchquantum/pulse/hardware/__init__.py new file mode 100644 index 00000000..d7e1c466 --- /dev/null +++ b/torchquantum/pulse/hardware/__init__.py @@ -0,0 +1 @@ +from .hardware import hardware diff --git a/torchquantum/pulse/hardware/hardware.py b/torchquantum/pulse/hardware/hardware.py new file mode 100644 index 00000000..cd63fd6c --- /dev/null +++ b/torchquantum/pulse/hardware/hardware.py @@ -0,0 +1,11 @@ +import torch +import numpy as np +import torchquantum as tq +import torchdiffeq + + + + +class Hardware(torch.nn.Modele): + def __init__(self,): + diff --git a/torchquantum/pulse/mesolve/__init__.py b/torchquantum/pulse/mesolve/__init__.py new file mode 100644 index 00000000..fe9702cf --- /dev/null +++ b/torchquantum/pulse/mesolve/__init__.py @@ -0,0 +1 @@ +from .mesolve import mesolve diff --git a/torchquantum/pulse/mesolve/mesolve.py b/torchquantum/pulse/mesolve/mesolve.py new file mode 100644 index 00000000..1bc66a0c --- /dev/null +++ b/torchquantum/pulse/mesolve/mesolve.py @@ -0,0 +1,67 @@ +import torch +import math +from ..solver import Solver +from ..utils import * +from torchdiffeq import odeint + +def mesolve( + dens0, + H=None, + n_dt=None, + dt=0.22, + *, + L_ops=None, + exp_ops=None, + options=None, + dtype=None, + device=None +): + if options is None: + options = {} + + if not 'step_size' in options: + options['step_size'] = 0.001 + + t_save = torch.tensor(list(range(n_dt)))*dt + + args = (H, dens0, t_save, exp_ops, options) + + solver = MESolver(*args, L_ops=L_ops) + + solver.run() + + psi_save, exp_save = solver.y_save, solver.exp_save + + return psi_save, exp_save + +def _lindblad_helper(L, rho): + Ldag = torch.conj(L) + return L @ rho @ Ldag - 0.5 * Ldag @ L @ rho - 0.5 * rho @ Ldag @ L + +def lindbladian(H,rho,L_ops): + if L_ops is None: + return -1j * (H @ rho - rho @ H) + + if type(L_ops) is not list: + L_ops = [L_ops] + + _dissipator = [_lindblad_helper(L, rho) for L in L_ops] + dissipator = torch.stack(_dissipator) + return -1j * (H @ rho - rho @ H) + dissipator.sum(0) + +class MESolver(Solver): + + def __init__(self, *args, L_ops): + super().__init__(*args) + self.L_ops = L_ops + + + def f(self, t, y): + h = self.H(t) + return lindbladian(h,y,self.L_ops) + + + def run(self): + # self.y_save = odeint(self.f, self.psi0, self.t_save, method='rk4', options=self.options) + self.y_save = odeint(self.f, self.psi0, self.t_save) + self.exp_save = None diff --git a/torchquantum/pulse/sec2_pulse.ipynb b/torchquantum/pulse/sec2_pulse.ipynb new file mode 100644 index 00000000..7824e914 --- /dev/null +++ b/torchquantum/pulse/sec2_pulse.ipynb @@ -0,0 +1,1270 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "iYVG7W6BghRw", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# **Section2 Use Torchquantum on Pulse Level**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0qvui6fmg7Sv", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Setup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "BgLkdnjhLiK7", + "outputId": "16cd60ff-9852-47aa-aa29-c2bfee9c9cde", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Installing torchquantum...\n", + "fatal: destination path 'torchquantum' already exists and is not an empty directory.\n", + "/content/torchquantum\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "qiskit-nature 0.4.4 requires qiskit-terra>=0.21.0, but you have qiskit-terra 0.18.3 which is incompatible.\u001b[0m\n" + ] + } + ], + "source": [ + "print('Installing torchquantum...')\n", + "!git clone https://github.com/mit-han-lab/torchquantum.git\n", + "%cd /content/torchquantum\n", + "!pip install --editable . 1>/dev/null" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 748 + }, + "id": "Jbhj5196LkpI", + "outputId": "c435d914-49b6-4117-ab4b-26a0670924a2", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Requirement already satisfied: qiskit_nature==0.4.4 in /usr/local/lib/python3.7/dist-packages (0.4.4)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (4.1.1)\n", + "Requirement already satisfied: scipy>=1.4 in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (1.7.3)\n", + "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (1.21.6)\n", + "Collecting qiskit-terra>=0.21.0\n", + " Using cached qiskit_terra-0.21.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.7 MB)\n", + "Requirement already satisfied: scikit-learn>=0.20.0 in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (1.0.2)\n", + "Requirement already satisfied: setuptools>=40.1.0 in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (57.4.0)\n", + "Requirement already satisfied: retworkx>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (0.11.0)\n", + "Requirement already satisfied: psutil>=5 in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (5.4.8)\n", + "Requirement already satisfied: h5py in /usr/local/lib/python3.7/dist-packages (from qiskit_nature==0.4.4) (3.1.0)\n", + "Requirement already satisfied: stevedore>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (3.5.0)\n", + "Requirement already satisfied: shared-memory38 in /usr/local/lib/python3.7/dist-packages (from qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (0.1.2)\n", + "Requirement already satisfied: tweedledum<2.0,>=1.1 in /usr/local/lib/python3.7/dist-packages (from qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (1.1.1)\n", + "Requirement already satisfied: symengine>=0.9 in /usr/local/lib/python3.7/dist-packages (from qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (0.9.2)\n", + "Requirement already satisfied: sympy>=1.3 in /usr/local/lib/python3.7/dist-packages (from qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (1.7.1)\n", + "Requirement already 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/usr/local/lib/python3.7/dist-packages (from stevedore>=3.0.0->qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (5.10.0)\n", + "Requirement already satisfied: importlib-metadata>=1.7.0 in /usr/local/lib/python3.7/dist-packages (from stevedore>=3.0.0->qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (4.12.0)\n", + "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=1.7.0->stevedore>=3.0.0->qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (3.8.1)\n", + "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.7/dist-packages (from sympy>=1.3->qiskit-terra>=0.21.0->qiskit_nature==0.4.4) (1.2.1)\n", + "Requirement already satisfied: cached-property in /usr/local/lib/python3.7/dist-packages (from h5py->qiskit_nature==0.4.4) (1.5.2)\n", + "Installing collected packages: qiskit-terra\n", + " Attempting uninstall: qiskit-terra\n", + " Found existing installation: qiskit-terra 0.18.3\n", + " Uninstalling qiskit-terra-0.18.3:\n", + " Successfully uninstalled qiskit-terra-0.18.3\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "qiskit 0.32.1 requires qiskit-terra==0.18.3, but you have qiskit-terra 0.21.2 which is incompatible.\u001b[0m\n", + "Successfully installed qiskit-terra-0.21.2\n" + ] + }, + { + "data": { + "application/vnd.colab-display-data+json": { + "pip_warning": { + "packages": [ + "qiskit" + ] + } + } + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "!pip install qiskit_nature==0.4.4" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "IYK1GsldLuhq", + "outputId": "c9a72cf2-d2b4-43f1-892f-2d3b249fc7c9", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Collecting qiskit==0.38.0\n", + " Using cached qiskit-0.38.0-py3-none-any.whl\n", + "Collecting qiskit-aer==0.11.0\n", + " Using cached qiskit_aer-0.11.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (19.2 MB)\n", + "Requirement already satisfied: qiskit-terra==0.21.2 in /usr/local/lib/python3.7/dist-packages (from qiskit==0.38.0) (0.21.2)\n", + "Collecting qiskit-ibmq-provider==0.19.2\n", + " Using cached qiskit_ibmq_provider-0.19.2-py3-none-any.whl (240 kB)\n", + "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.7/dist-packages (from qiskit-aer==0.11.0->qiskit==0.38.0) (1.7.3)\n", + "Requirement already satisfied: numpy>=1.16.3 in /usr/local/lib/python3.7/dist-packages (from qiskit-aer==0.11.0->qiskit==0.38.0) (1.21.6)\n", + "Requirement already satisfied: requests>=2.19 in /usr/local/lib/python3.7/dist-packages (from qiskit-ibmq-provider==0.19.2->qiskit==0.38.0) (2.28.1)\n", + "Requirement already satisfied: websockets>=10.0 in /usr/local/lib/python3.7/dist-packages (from 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requests-ntlm>=1.1.0->qiskit-ibmq-provider==0.19.2->qiskit==0.38.0) (38.0.1)\n", + "Requirement already satisfied: ntlm-auth>=1.0.2 in /usr/local/lib/python3.7/dist-packages (from requests-ntlm>=1.1.0->qiskit-ibmq-provider==0.19.2->qiskit==0.38.0) (1.5.0)\n", + "Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.7/dist-packages (from cryptography>=1.3->requests-ntlm>=1.1.0->qiskit-ibmq-provider==0.19.2->qiskit==0.38.0) (1.15.1)\n", + "Requirement already satisfied: pycparser in /usr/local/lib/python3.7/dist-packages (from cffi>=1.12->cryptography>=1.3->requests-ntlm>=1.1.0->qiskit-ibmq-provider==0.19.2->qiskit==0.38.0) (2.21)\n", + "Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from stevedore>=3.0.0->qiskit-terra==0.21.2->qiskit==0.38.0) (5.10.0)\n", + "Requirement already satisfied: importlib-metadata>=1.7.0 in /usr/local/lib/python3.7/dist-packages (from stevedore>=3.0.0->qiskit-terra==0.21.2->qiskit==0.38.0) (4.12.0)\n", + "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=1.7.0->stevedore>=3.0.0->qiskit-terra==0.21.2->qiskit==0.38.0) (3.8.1)\n", + "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.7/dist-packages (from sympy>=1.3->qiskit-terra==0.21.2->qiskit==0.38.0) (1.2.1)\n", + "Installing collected packages: qiskit-ibmq-provider, qiskit-aer, qiskit\n", + " Attempting uninstall: qiskit-ibmq-provider\n", + " Found existing installation: qiskit-ibmq-provider 0.18.1\n", + " Uninstalling qiskit-ibmq-provider-0.18.1:\n", + " Successfully uninstalled qiskit-ibmq-provider-0.18.1\n", + " Attempting uninstall: qiskit-aer\n", + " Found existing installation: qiskit-aer 0.9.1\n", + " Uninstalling qiskit-aer-0.9.1:\n", + " Successfully uninstalled qiskit-aer-0.9.1\n", + " Attempting uninstall: qiskit\n", + " Found existing installation: qiskit 0.32.1\n", + " Uninstalling qiskit-0.32.1:\n", + " Successfully uninstalled qiskit-0.32.1\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "torchquantum 0.1.2 requires qiskit==0.32.1, but you have qiskit 0.38.0 which is incompatible.\u001b[0m\n", + "Successfully installed qiskit-0.38.0 qiskit-aer-0.11.0 qiskit-ibmq-provider-0.19.2\n" + ] + }, + { + "data": { + "application/vnd.colab-display-data+json": { + "pip_warning": { + "packages": [ + "qiskit", + "qiskit_aer" + ] + } + } + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "!pip install qiskit==0.38.0" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 444 + }, + "id": "KNf52acguGpM", + "outputId": "a85550dc-0493-4d9e-e32b-1442d7cb207d", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Collecting matplotlib==3.1.3\n", + " Using cached matplotlib-3.1.3-cp37-cp37m-manylinux1_x86_64.whl (13.1 MB)\n", + "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.1.3) (2.8.2)\n", + "Requirement already satisfied: numpy>=1.11 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.1.3) (1.21.6)\n", + "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.1.3) (3.0.9)\n", + "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.1.3) (0.11.0)\n", + "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.1.3) (1.4.4)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from kiwisolver>=1.0.1->matplotlib==3.1.3) (4.1.1)\n", + "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.1->matplotlib==3.1.3) (1.15.0)\n", + "Installing collected packages: matplotlib\n", + " Attempting uninstall: matplotlib\n", + " Found existing installation: matplotlib 3.5.3\n", + " Uninstalling matplotlib-3.5.3:\n", + " Successfully uninstalled matplotlib-3.5.3\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "torchquantum 0.1.2 requires matplotlib>=3.3.2, but you have matplotlib 3.1.3 which is incompatible.\n", + "torchquantum 0.1.2 requires qiskit==0.32.1, but you have qiskit 0.38.0 which is incompatible.\u001b[0m\n", + "Successfully installed matplotlib-3.1.3\n" + ] + }, + { + "data": { + "application/vnd.colab-display-data+json": { + "pip_warning": { + "packages": [ + "matplotlib", + "mpl_toolkits" + ] + } + } + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "!pip install matplotlib==3.1.3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "syQ7I8rEMI-H", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "from torchquantum.pulse_utils import *\n", + "import torch\n", + "import torch.nn.functional as F\n", + "import torch.optim as optim\n", + "import argparse" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "3KOs5g5ldqE3", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import torchquantum as tq\n", + "import torchquantum.functional as tqf\n", + "import pdb\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k4fF5ASdhqZX", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# **2.1 Quantum Optimal Control**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kjLhsVWGG5u0", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Optimal control can be used to achieve efficient state preparation, state-to-state transfer or some unitary matrix on a quantum system. Current quantum systems can be manipulated in a controlled way, such as the time-varying amplitude of microwave pulses that act on a superconducting circuit.\n", + "\n", + "In the simple example below, QOC is used to achieve a rotation gate, and we use pulses to achieve such target. The pulses are composed of four time steps with different amplitudes. The control Hamiltonian is the Pauli-X. In this gradient-based optimization we will be able to achieve the target unitary with desired accuracy." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "fccmCcyOh1PA", + "outputId": "952bf38a-d1f8-47f6-b8db-2b975c410b5e", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Parameter containing:\n", + "tensor([0.9950, 0.9950, 0.9950, 0.9950], requires_grad=True)\n", + "tensor([[-0.6686+0.0000j, 0.0000+0.7436j],\n", + " [ 0.0000+0.7436j, -0.6686+0.0000j]], grad_fn=)\n", + "Parameter containing:\n", + "tensor([0.9900, 0.9900, 0.9900, 0.9900], requires_grad=True)\n", + "tensor([[-0.6834+0.0000j, 0.0000+0.7300j],\n", + " [ 0.0000+0.7300j, -0.6834+0.0000j]], grad_fn=)\n", + "Parameter containing:\n", + "tensor([0.9850, 0.9850, 0.9850, 0.9850], requires_grad=True)\n", + "tensor([[-0.6979+0.0000j, 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grad_fn=)\n", + "Parameter containing:\n", + "tensor([0.7060, 0.7060, 0.7060, 0.7060], requires_grad=True)\n", + "tensor([[-0.9500+0.0000j, 0.0000-0.3123j],\n", + " [ 0.0000-0.3123j, -0.9500+0.0000j]], grad_fn=)\n", + "Parameter containing:\n", + "tensor([0.7063, 0.7063, 0.7063, 0.7063], requires_grad=True)\n", + "tensor([[-0.9503+0.0000j, 0.0000-0.3112j],\n", + " [ 0.0000-0.3112j, -0.9503+0.0000j]], grad_fn=)\n", + "Parameter containing:\n", + "tensor([0.7066, 0.7066, 0.7066, 0.7066], requires_grad=True)\n", + "tensor([[-0.9507+0.0000j, 0.0000-0.3101j],\n", + " [ 0.0000-0.3101j, -0.9507+0.0000j]], grad_fn=)\n", + "Parameter containing:\n", + "tensor([0.7068, 0.7068, 0.7068, 0.7068], requires_grad=True)\n", + "tensor([[-0.9510+0.0000j, 0.0000-0.3091j],\n", + " [ 0.0000-0.3091j, -0.9510+0.0000j]], grad_fn=)\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "theta = 0.6\n", + "target_unitary = torch.tensor([[np.cos(theta/2), -1j*np.sin(theta/2)], [-1j*np.sin(theta/2), np.cos(theta/2)]], dtype=torch.complex64)\n", + "# The target_unitary is a simple rotation gate with angle = 0.6;\n", + "pulse = tq.QuantumPulseDirect(n_steps=4,\n", + " hamil=[[0, 1], [1, 0]])\n", + "# The pulse has 4 time slots and the drive Hamiltonian is the Pauli-X.\n", + "optimizer = optim.Adam(params=pulse.parameters(), lr=5e-3)\n", + "\n", + "# TODO(jinleic): \n", + "# add Bloch Sphere here\n", + "# add figure for pulse time slots\n", + "# Can we see the learning curve?\n", + "losses = []\n", + "\n", + "for k in range(100):\n", + " # loss = (abs(pulse.get_unitary() - target_unitary)**2).sum()\n", + " loss = 1 - (torch.trace(pulse.get_unitary() @ target_unitary) / target_unitary.shape[0]).abs() ** 2\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + " losses.append(loss.item())\n", + " # print(pulse.pulse_shape.grad)\n", + " # print(loss)\n", + " print(pulse.pulse_shape)\n", + " print(pulse.get_unitary())\n", + "plt.xlabel(\"Number of Iterations\")\n", + "plt.ylabel(\"Training Losses\")\n", + "plt.title(\"Training from Default Initialization\")\n", + "plt.plot(losses[:100])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rkK0N1VaHS_-", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Since the pulses are generated in an iterative way. The initialization of pulses will influence the number of iterations. It would be great if we can choose a better starting point. Intuitively, if pulses are initialized from a \"close\" or \"similar\" target unitary matrix, we will able to reduce the number of iterations. In the following example, we simply show that the pulses are initialized from previous unitary matrix and it can help achieve convergence faster." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HB4WtwxOe6mQ", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# **2.2 Variational Pulse Learning**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DCqFYkPKKNMV", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Varitional pulse control schme is designed to avoid drawbacks of gate level approaches as well as quantum optimal control. We try to find a intermdiate level of pulse control abstraction and post optimization algorithms to improve the pulses and finally achieves better performance on quantum algorithm on NISQ machines." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "opXOGoIvhGNU", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## **Native Pulse Build-up**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dGqKFAf0hZQC", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Set the backend, please note that pulse is hardware dependent, it varying with every calibration and also different with devices." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xmlJ7kRkM0lv", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "backend = FakeJakarta()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wZz_PMfdhoP9", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "SNP is namly a single-qubit native pulse, and TNP is two-qubit native pulse, we use this as a example to build the pulse ansatz for VQE task." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 177 + }, + "id": "HTnB6_GXuhDU", + "outputId": "bdb5ac2c-e0b0-45cd-d9a8-7ac4d4273908", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sched0 = snp(0, backend)\n", + "sched0.draw()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 177 + }, + "id": "wyhu4poTM38D", + "outputId": "dcc716a0-8051-48ab-e7a5-ab5a3744d725", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sched1 = snp(1, backend)\n", + "sched1.draw()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 503 + }, + "id": "puS0a_FWM-Nc", + "outputId": "95ca2a74-00cd-44d9-d5c2-3364ef381865", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sched2 = tnp(0,1,backend)\n", + "sched2.draw()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "m_ZqZASuh813", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "pul_append is a method to combine two schedules." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 266 + }, + "id": "3RX66l2GNCsw", + "outputId": "7f33c770-fca7-44c8-b64e-c250348875ce", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pulse_ansatz = pul_append(sched0, sched1)\n", + "pulse_ansatz.draw()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 503 + }, + "id": "dvQiHIEIRE4s", + "outputId": "cb51438a-ac1a-4bd8-e38f-bce1d4ca6c7a", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pulse_ansatz = pul_append(pulse_ansatz, sched2)\n", + "pulse_ansatz.draw()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HPJYbvz9iG5B", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "In torchquantum, extract_amp can use to get the amplitudes from pulses, you can also choose extract_realamp for only the real part of pulse amplitudes and ignore the imaginary part. We also have extract_phase to get the classical phase from pulses." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "uy5dxMqCNJeg", + "outputId": "3e7636b0-91a2-4a10-9b91-1c773db9c6b1", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0.1007186 0.00833101 0.096837 0.02080554 0.20122114 -1.57079633\n", + " 0.096837 0.02080554 0.11225338 0.01509274 0.7727792 -2.96348159\n", + " 0.20122114 0. 0.11225338 -3.12649991 0.7727792 0.17811106]\n" + ] + } + ], + "source": [ + "parameters_array = extract_amp(pulse_ansatz)\n", + "print(parameters_array)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9F3AQeMnig-h", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## **VQE Model Setup**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BjDLnHUHiozd", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Here we use an example of Hydrogen molecule. And we give a pauli string here based on sto3g basis and with parity mapping as well as two-qubit reduction." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "AQXIa7CtNNbN", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "n_qubit = 2\n", + "pauli_dict = {'II': -1.0523732, 'IZ': 0.39793742, 'ZI': -0.3979374, 'ZZ': -0.0112801, 'XX':0.18093119}" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qjU3El9qi4mg", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "map_amp is a method in torchquantum introduce to map the adjusted amplitude to the pulses then get new pulses and send to quantum machine. observe_generate is a method to genrate the observe-pulses of the hydrogen molecule. run_pulse_sim is use to run the updated pulses in pulse simulator." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "KbrcJ4kiNbPU", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "def vqe(cur_best_w):\n", + " backend = FakeJakarta()\n", + " modified_list = ((cur_best_w[:int(len(cur_best_w)/2)])*np.cos(cur_best_w[int(len(cur_best_w)/2):]) + (cur_best_w[:int(len(cur_best_w)/2)])*np.sin(cur_best_w[int(len(cur_best_w)/2):])*1j)\n", + " modified_list = np.ndarray.tolist(modified_list)\n", + " sched1 = snp(0, backend)\n", + " sched2 = tnp(0,1,backend)\n", + " pulse_ansatz = pul_append(sched1, sched2)\n", + " prepulse = map_amp(pulse_ansatz, modified_list)\n", + " measurement_pulse = observe_genearte(prepulse, backend)\n", + " XX_YY_ZZ_expect = run_pulse_sim(measurement_pulse)\n", + " H_expect = pauli_dict['II'] + pauli_dict['IZ']*XX_YY_ZZ_expect[0] + pauli_dict['ZI']*XX_YY_ZZ_expect[1] + pauli_dict['XX']*XX_YY_ZZ_expect[2] + pauli_dict['ZZ']*XX_YY_ZZ_expect[3]\n", + " return H_expect" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Yq2cVwvFjhuK", + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Note, here we use COBYLA as the optimizer to train the pulse ansatz." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Z5ZG9qg-NcA2", + "outputId": "5af21680-2a17-4463-dac9-aeb7230c3661", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.7/dist-packages/qiskit/compiler/assembler.py:461: RuntimeWarning: Dynamic rep rates are supported on this backend. 'rep_delay' will be used instead of 'rep_time'.\n", + " RuntimeWarning,\n" + ] + } + ], + "source": [ + "vqe_result = minimize(vqe, parameters_array, method='COBYLA', constraints=gen_LC(parameters_array),\n", + " options={'rhobeg': 0.1, 'maxiter': 2, 'disp': True})\n", + "print('The estimated ground state energy from pulse level VQE algorithm is: {}'.format(vqe_result.fun))\n", + "print(\"\\nThe optimal parameter theta is : {} \".format(vqe_result.x))" + ] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "provenance": [], + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/torchquantum/pulse/sesolve/__init__.py b/torchquantum/pulse/sesolve/__init__.py new file mode 100644 index 00000000..c4bb790c --- /dev/null +++ b/torchquantum/pulse/sesolve/__init__.py @@ -0,0 +1 @@ +from .sesolve import sesolve diff --git a/torchquantum/pulse/sesolve/sesolve.py b/torchquantum/pulse/sesolve/sesolve.py new file mode 100644 index 00000000..85377cf9 --- /dev/null +++ b/torchquantum/pulse/sesolve/sesolve.py @@ -0,0 +1,52 @@ +import torch +import math +from ..solver import Solver +from ..utils import * +from torchdiffeq import odeint + +def sesolve( + psi0, + H=None, + n_dt=None, + dt=0.22, + *, + exp_ops=None, + options=None, + dtype=None, + device=None +): + if options is None: + options = {} + + if not 'step_size' in options: + options['step_size'] = 0.001 + + t_save = torch.tensor(list(range(n_dt)))*dt + + args = (H, psi0, t_save, exp_ops, options) + + solver = SESolver(*args) + + solver.run() + + psi_save, exp_save = solver.y_save, solver.exp_save + + return psi_save, exp_save + + + +class SESolver(Solver): + + def __init__(self, *args): + super().__init__(*args) + + + def f(self, t, y): + h = self.H(t) + return -1.j * torch.matmul(h, y) + + + def run(self): + # self.y_save = odeint(self.f, self.psi0, self.t_save, method='rk4', options=self.options) + self.y_save = odeint(self.f, self.psi0, self.t_save) + self.exp_save = None diff --git a/torchquantum/pulse/single_qubit_demo.py b/torchquantum/pulse/single_qubit_demo.py new file mode 100644 index 00000000..06184da9 --- /dev/null +++ b/torchquantum/pulse/single_qubit_demo.py @@ -0,0 +1,27 @@ +import numpy as np +import torch +import torchquantum as tq +from torchquantum.pulse import sigmax, sigmay, sigmaz, sesolve + + +n_dt = 10 +dt = 0.22 + + +initial_value = np.array([1,0]) +initial_state = torch.tensor(initial_value,dtype=torch.complex64) + + +pulse_value = torch.tensor(np.ones((n_dt,1)),dtype=torch.complex64) +pulse = torch.nn.parameter.Parameter(pulse_value) + + +def H(t): + t_ind = (t/dt).long() + return -sigmaz() + sigmax() * pulse[t_ind] + + +result = sesolve(psi0 = initial_state, H = H, n_dt = n_dt, dt = dt) + + +print(result) diff --git a/torchquantum/pulse/solver.py b/torchquantum/pulse/solver.py new file mode 100644 index 00000000..6c9b0b6b --- /dev/null +++ b/torchquantum/pulse/solver.py @@ -0,0 +1,18 @@ +import torch + +class Solver(torch.nn.Module): + def __init__( + self, + H, + psi0, + t_save, + exp_ops, + options + ): + self.H = H + self.psi0 = psi0 + self.t_save = t_save + self.exp_ops = exp_ops + self.options = options + + diff --git a/torchquantum/pulse/templates/draft.py b/torchquantum/pulse/templates/draft.py new file mode 100644 index 00000000..e95d3aad --- /dev/null +++ b/torchquantum/pulse/templates/draft.py @@ -0,0 +1,32 @@ +import os +import argparse +import time +import numpy as np + +import torch +import torch.nn as nn +import torch.optim as optim + + + +class ODEFunc(nn.Module): + + def __init__(self,c_ops): + super(ODEFunc,self).__init__() + + self.c_ops = c_ops + + def forward(self,t,y): + return + +device = torch.device('cpu') + +y0 = torch.tensor([1,0]).to(device) +t = torch.linspace(0., 1., 11).to(device) + + + +c_ops = torch.linspace(0.,1.,11).to(device) + +func = ODEFunc(c_ops).to(device) +res_y = odeint(func,y0,t).to(device) diff --git a/torchquantum/pulse/templates/pulse.py b/torchquantum/pulse/templates/pulse.py new file mode 100644 index 00000000..33543f2d --- /dev/null +++ b/torchquantum/pulse/templates/pulse.py @@ -0,0 +1,145 @@ +import torch +import torch.nn as nn +import numpy as np + +from typing import Union, List, Iterable + + +__all__ = [ + "QuantumPulse", + "QuantumPulseGaussian", + "QuantumPulseDirect", +] + + +class QuantumPulse(nn.Module): + """ + The Quantum Pulse simulator + """ + + def __init__(self): + super().__init__() + pass + + def forward(self): + pass + + +class QuantumPulseDirect(QuantumPulse): + def __init__( + self, + n_steps: int, + hamil, + delta_t: float = 1.0, + initial_shape: List[float] = None, + ): + super().__init__() + self.hamil = torch.tensor(hamil, dtype=torch.complex64) + if initial_shape is not None: + assert len(initial_shape) == n_steps + initial_shape = torch.Tensor(initial_shape) + else: + initial_shape = torch.ones(n_steps) + self.pulse_shape = nn.Parameter(initial_shape) + self.n_steps = n_steps + self.delta_t = delta_t + + def get_unitary(self): + unitary_per_step = [] + for k in range(self.n_steps): + magnitude = self.pulse_shape[k] + unitary = torch.matrix_exp(-1j * self.hamil * magnitude * self.delta_t) + # print(unitary @ unitary.conj().T) + # unitary_mag = (unitary[0]**2).sum().sqrt() + # unitary = unitary_mag / unitary + + unitary_per_step.append(unitary) + + u_overall = None + for k, u in enumerate(unitary_per_step): + if not k: + u_overall = u + else: + u_overall = u_overall @ u + + return u_overall + + def __repr__(self): + return f"QuantumPulse Direct \n shape: {self.pulse_shape}" + + +class QuantumPulseGaussian(QuantumPulse): + """Gaussian Quantum Pulse, will only count +- five sigmas""" + + def __init__( + self, + hamil, + n_steps: int = 100, + delta_t: float = 1.0, + x_min: float = -10, + x_max: float = 10, + initial_params: List[float] = None, + ): + super(QuantumPulseGaussian, self).__init__() + self.hamil = torch.tensor(hamil, dtype=torch.complex64) + self.delta_t = delta_t + # mag, mu, sigma + if initial_params is not None: + assert len(initial_params) == 3 + initial_params = torch.Tensor(initial_params) + else: + initial_params = torch.ones(3) + + self.pulse_params = nn.Parameter(initial_params) + self.n_steps = n_steps + self.delta_x = (x_max - x_min) / n_steps + self.x_list = torch.tensor(np.arange(x_min, x_max, self.delta_x)) + + def get_unitary(self): + self.mag = self.pulse_params[0] + self.mu = self.pulse_params[1] + self.sigma = self.pulse_params[2] + + # delta_x = (10 * self.sigma / self.n_steps).item() + # self.x_list = torch.tensor(np.arange( + # (self.mu - 5 * self.sigma).item(), + # (self.mu + 5 * self.sigma).item(), delta_x)) + + self.pulse_shape = self.mag * torch.exp( + -((self.x_list - self.mu) ** 2) / (2 * self.sigma**2) + ) + + unitary_per_step = [] + for k in range(self.n_steps): + magnitude = self.pulse_shape[k] + unitary = torch.matrix_exp( + -1j * self.hamil * magnitude * self.delta_t * self.delta_x + ) + # print(unitary @ unitary.conj().T) + # unitary_mag = (unitary[0]**2).sum().sqrt() + # unitary = unitary_mag / unitary + + unitary_per_step.append(unitary) + + u_overall = None + for k, u in enumerate(unitary_per_step): + if not k: + u_overall = u + else: + u_overall = u_overall @ u + + return u_overall + + def __repr__(self): + return f"QuantumPulse Guassian \n shape: {self.pulse_shape}" + + +if __name__ == "__main__": + import pdb + + pdb.set_trace() + pulse = QuantumPulseDirect(n_steps=10, hamil=[[0, 1], [1, 0]]) + + print(pulse.get_unitary()) + + print("finish") diff --git a/torchquantum/pulse/templates/pulse_utils.py b/torchquantum/pulse/templates/pulse_utils.py new file mode 100644 index 00000000..bad2a9b5 --- /dev/null +++ b/torchquantum/pulse/templates/pulse_utils.py @@ -0,0 +1,228 @@ +import copy +import sched +import qiskit +import itertools +import numpy as np + +from itertools import repeat +from qiskit.providers import aer +from qiskit.providers.fake_provider import * +from qiskit.circuit import Gate +from qiskit.compiler import assemble +from qiskit import pulse, QuantumCircuit, IBMQ +from qiskit.pulse.instructions import Instruction +from qiskit.pulse.transforms import block_to_schedule +from qiskit_nature.drivers import UnitsType, Molecule +from scipy.optimize import minimize, LinearConstraint +from qiskit_nature.converters.second_quantization import QubitConverter +from qiskit_nature.properties.second_quantization.electronic import ParticleNumber +from qiskit_nature.problems.second_quantization import ElectronicStructureProblem +from typing import List, Tuple, Iterable, Union, Dict, Callable, Set, Optional, Any +from qiskit.pulse import ( + Schedule, + GaussianSquare, + Drag, + Delay, + Play, + ControlChannel, + DriveChannel, +) +from qiskit_nature.mappers.second_quantization import ParityMapper, JordanWignerMapper +from qiskit_nature.transformers.second_quantization.electronic import ( + ActiveSpaceTransformer, +) +from qiskit_nature.drivers.second_quantization import ( + ElectronicStructureDriverType, + ElectronicStructureMoleculeDriver, +) + + +def is_parametric_pulse(t0, *inst: Union["Schedule", Instruction]): + inst = t0[1] + t0 = t0[0] + if isinstance(inst, pulse.Play): + return True + else: + return False + + +def extract_ampreal(pulse_prog): + # extract the real part of pulse amplitude, igonred the imaginary part. + amp_list = list( + map( + lambda x: x[1].pulse.amp, + pulse_prog.filter(is_parametric_pulse).instructions, + ) + ) + amp_list = np.array(amp_list) + ampa_list = np.angle(np.array(amp_list)) + return ampa_list + + +def extract_amp(pulse_prog): + # extract the pulse amplitdue. + amp_list = list( + map( + lambda x: x[1].pulse.amp, + pulse_prog.filter(is_parametric_pulse).instructions, + ) + ) + amp_list = np.array(amp_list) + ampa_list = np.angle(np.array(amp_list)) + ampn_list = np.abs(np.array(amp_list)) + amps_list = [] + for i, j in zip(ampn_list, ampa_list): + amps_list.append(i) + amps_list.append(j) + amps_list = np.array(amps_list) + return amps_list + + +def is_phase_pulse(t0, *inst: Union["Schedule", Instruction]): + inst = t0[1] + t0 = t0[0] + if isinstance(inst, pulse.ShiftPhase): + return True + return False + + +def extract_phase(pulse_prog): + + for _, ShiftPhase in pulse_prog.filter(is_phase_pulse).instructions: + # print(play.pulse.amp) + pass + instructions = pulse_prog.filter(is_phase_pulse).instructions + + phase_list = list( + map( + lambda x: x[1]._operands[0], + pulse_prog.operands[0].filter(is_phase_pulse).instructions, + ) + ) + return phase_list + + +def cir2pul(circuit, backend): + # transform quantum circuit to pulse schedule + with pulse.build(backend) as pulse_prog: + pulse.call(circuit) + return pulse_prog + + +def snp(qubit, backend): + circuit = QuantumCircuit(qubit + 1) + circuit.h(qubit) + sched = cir2pul(circuit, backend) + sched = block_to_schedule(sched) + return sched + + +def tnp(qubit, cqubit, backend): + circuit = QuantumCircuit(cqubit + 1) + circuit.cx(qubit, cqubit) + sched = cir2pul(circuit, backend) + sched = block_to_schedule(sched) + return sched + + +def pul_append(sched1, sched2): + sched = sched1.append(sched2) + return sched + + +def map_amp(pulse_ansatz, modified_list): + sched = Schedule() + for inst, amp in zip( + pulse_ansatz.filter(is_parametric_pulse).instructions, modified_list + ): + inst[1].pulse._amp = amp + for i in pulse_ansatz.instructions: + if is_parametric_pulse(i): + sched += copy.deepcopy(i[1]) + return sched + + +def get_from(d: dict, key: str): + + value = 0 + if key in d: + value = d[key] + return value + + +def run_pulse_sim(measurement_pulse): + measure_result = [] + for measure_pulse in measurement_pulse: + shots = 1024 + pulse_sim = qiskit.providers.aer.PulseSimulator.from_backend(FakeJakarta()) + pul_sim = assemble( + measure_pulse, + backend=pulse_sim, + shots=1024, + meas_level=2, + meas_return="single", + ) + results = pulse_sim.run(pul_sim).result() + + counts = results.get_counts() + expectation_value = ( + (get_from(counts, "00") + get_from(counts, "11")) + - (get_from(counts, "10") + get_from(counts, "01")) + ) / shots + measure_result.append(expectation_value) + return measure_result + + +def gen_LC(parameters_array): + dim_design = int(len(parameters_array)) + Mid = int(len(parameters_array) / 2) + bound = np.ones((dim_design, 2)) * np.array([0, 0.9]) + bound[-Mid:] = bound[-Mid:] * np.pi * 2 + tol = 1e-3 # tolerance for optimization precision. + lb = bound[:, 0] + ub = bound[:, 1] + LC = LinearConstraint(np.eye(dim_design), lb, ub, keep_feasible=False) + return LC + + +def observe_genearte(pulse_ansatz, backend): + qubits = 0, 1 + with pulse.build(backend) as pulse_measurez0: + # z measurement of qubit 0 and 1 + pulse.call(pulse_ansatz) + pulse.barrier(0, 1) + pulse.measure(0) + with pulse.build(backend) as pulse_measurez1: + # z measurement of qubit 0 and 1 + pulse.call(pulse_ansatz) + pulse.barrier(0, 1) + pulse.measure(1) + with pulse.build(backend) as pulse_measurez: + # z measurement of qubit 0 and 1 + pulse.call(pulse_ansatz) + pulse.barrier(0, 1) + pulse.measure(qubits) + with pulse.build(backend) as pulse_measurex: + # x measurement of qubit 0 and 1 + pulse.call(pulse_ansatz) + pulse.barrier(0, 1) + pulse.u2(0, np.pi, 0) + pulse.u2(0, np.pi, 1) + pulse.barrier(0, 1) + pulse.measure(qubits) + + with pulse.build(backend) as pulse_measurey: + # y measurement of qubit 0 and 1 + pulse.call(pulse_ansatz) + pulse.barrier(0, 1) + pulse.u2(np.pi / 2, 0, 0) + pulse.u2(np.pi / 2, 0, 1) + pulse.barrier(0, 1) + pulse.measure(qubits) + measurement_pulse = [ + pulse_measurez0, + pulse_measurez1, + pulse_measurez, + pulse_measurex, + ] + return measurement_pulse diff --git a/torchquantum/pulse/templates/simplest_draft.py b/torchquantum/pulse/templates/simplest_draft.py new file mode 100644 index 00000000..69d3bad3 --- /dev/null +++ b/torchquantum/pulse/templates/simplest_draft.py @@ -0,0 +1,70 @@ +import os +import argparse +import time +import numpy as np + +import torch +import torch.nn as nn +import torch.optim as optim + +import torchquantum as tq + +from torchdiffeq import odeint + + +# class SqaurePulse(Pulse): + + + + +# class Pulse(tq.QuantumModule): +# def __init__(): + + + + + +# class Solver(ABC): +# def __init__( +# self, +# +# +# ): + + +z_value = np.array([[1,0],[0,-1]]) +z = torch.tensor(z_value,dtype=torch.complex64) + +x_value = np.array([[0,1],[1,0]]) +x = torch.tensor(x_value,dtype=torch.complex64) + +y0_value = np.array([1,0]) +y0 = torch.tensor(y0_value,dtype=torch.complex64) + +dt = 0.22 #ns +# test 10 dt first: 2.2ns +# torch.nn.parameter.Parameter +pulse_value = torch.tensor([1,2,3,4,5,5,4,3,2,1]) / 10 #MHz +pulse = torch.nn.parameter.Parameter(pulse_value) +t_list = torch.tensor(list(range(10))) * dt + +assert pulse.size() == t_list.size() + +def H(t): + t_ind = (t/dt).long() + h = z + x * pulse[t_ind] + # print("current ind:",t_ind) + print("current h:",h) + return h + +def f(t, y): + h = H(t) + return -1.j * torch.matmul(h, y) +y_t = odeint(f, y0, t_list) +print("y0:",y0) +print("y_t:",y_t) +print("norm:",torch.norm(y_t,dim=1)) + +# calculate the gradients of pulse segments +# y_t[-1][0].real.backward() +# print(pulse.grad) diff --git a/torchquantum/pulse/utils.py b/torchquantum/pulse/utils.py new file mode 100644 index 00000000..e80465c2 --- /dev/null +++ b/torchquantum/pulse/utils.py @@ -0,0 +1,97 @@ +import numpy as np +import torch +import cmath + +def sigmai(): + i_value = np.array([[1,0],[0,1]]) + return torch.tensor(i_value,dtype=torch.complex64) + +def sigmax(): + x_value = np.array([[0,1],[1,0]]) + return torch.tensor(x_value,dtype=torch.complex64) + +def sigmay(): + y_value = np.array([[0,-1.j],[1.j,0]]) + return torch.tensor(y_value,dtype=torch.complex64) + +def sigmaz(): + z_value = np.array([[1,0],[0,-1]]) + return torch.tensor(z_value,dtype=torch.complex64) + +def sigmaplus(): + p_value = np.array([[0,2],[0,0]]) + return torch.tensor(p_value,dtype=torch.complex64) + +def sigmaminus(): + m_value = np.array([[0,0],[2,0]]) + return torch.tensor(m_value,dtype=torch.complex64) + +def InitialState(n_qubit = 1, state = [0]): + assert len(state) == n_qubit + active_ind = 0 + for element in reversed(state): + assert element==0 or element==1 + active_ind = (active_ind << 1) | element + state_length = 2**n_qubit + initial_value = np.zeros(state_length,dtype=int) + initial_value[active_ind] = 1 + initial_state = torch.tensor(initial_value,dtype=torch.complex64) + return initial_state + +def InitialDensity(n_qubit = 1, state = [0]): + initial_state = InitialState(n_qubit, state) + initial_density = torch.ger(initial_state, torch.conj(initial_state)) + return initial_density + +def H_2q_example(pulse, dt): + def H(t): + t_ind = (t/dt).long() + interaction = -1.548*torch.kron(sigmai(),sigmax())-0.004*torch.kron(sigmai(),sigmay())-0.006*torch.kron(sigmai(),sigmaz()) \ + +5.316*torch.kron(sigmaz(),sigmax())-0.225*torch.kron(sigmaz(),sigmay())-0.340*torch.kron(sigmaz(),sigmaz()) + if t_ind >= len(pulse): + return 0 * interaction + return pulse[t_ind] * interaction + 1.225*torch.kron(sigmaz(),sigmai()) + return H + +def H_qubit_example(n_qubit, pulse, dt): + def H(t): + t_ind = (t/dt).long() + if t_ind >= len(pulse): + return sigmax() * 0 + return sigmax()*pulse[t_ind].real + sigmay()*pulse[t_ind].imag + return H + +def H_larmor_example(n_qubit, pulse, dt): + def H(t): + t_ind = (t/dt).long() + if t_ind>=len(pulse): + return -sigmaz()*0.1 + sigmax() * 0 + return -sigmaz()*0.1 + sigmax()*pulse[t_ind] + return H + +def normalize_state_vector(a, b): + magnitude = cmath.sqrt(a * a.conjugate() + b * b.conjugate()) + alpha = a / magnitude + beta = b / magnitude + return alpha, beta + +def sv2bloch(sv): + a = sv[0] + b = sv[1] + # alpha, beta = normalize_state_vector(a,b) + # Compute x, y, and z coordinates + x = 2 * np.real(b * np.conj(a)) + y = 2 * np.imag(b * np.conj(a)) + z = np.abs(a)**2 - np.abs(b)**2 + return [x, y, z] + +def dens2bloch(rho): + x = np.trace(np.dot(rho, sigmax())) + y = np.trace(np.dot(rho, sigmay())) + z = np.trace(np.dot(rho, sigmaz())) + return [x.real, y.real, z.real] + +def Schedule(pulse_list): + pulse_value = torch.tensor(pulse_list,dtype=torch.complex64) + pulse = torch.nn.parameter.Parameter(pulse_value) + return pulse From e69941b340e74001db3c6e67781dadb2e7f81b16 Mon Sep 17 00:00:00 2001 From: Jinglei Cheng Date: Sun, 18 Jun 2023 12:46:42 -0400 Subject: [PATCH 03/28] Tutorials for ISCA 2023, updated version --- torchquantum/pulse/ISCA_tutorial_pulse.ipynb | 684 ++++++++++++++++++- 1 file changed, 669 insertions(+), 15 deletions(-) diff --git a/torchquantum/pulse/ISCA_tutorial_pulse.ipynb b/torchquantum/pulse/ISCA_tutorial_pulse.ipynb index b0e619e6..ee078fc3 100644 --- a/torchquantum/pulse/ISCA_tutorial_pulse.ipynb +++ b/torchquantum/pulse/ISCA_tutorial_pulse.ipynb @@ -13,8 +13,8 @@ "\n", "This notebook can be devided into three parts:\n", "1. Example of qubit dynamics with Schrödinger equation solver\n", - "2. Example of qubit dynamics with Lindblad master equation solver\n", - "3. Example of quantum optimal control\n", + "2. Example of quantum optimal control with TorchQuantum\n", + "3. Example of qubit dynamics with Lindblad master equation solver\n", "\n", "### Setup\n", "\n", @@ -23,19 +23,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "ec7d5088", "metadata": {}, "outputs": [], "source": [ - "!git clone https://github.com/mit-han-lab/torchquantum.git\n", - "%cd /content/torchquantum\n", - "!pip install --editable . 1>/dev/null" + "# !git clone https://github.com/mit-han-lab/torchquantum.git\n", + "# %cd /content/torchquantum\n", + "# !pip install --editable . 1>/dev/null\n", + "# !pip install qutip\n", + "# !pip install git+https://github.com/rtqichen/torchdiffeq" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "5f13eb79", "metadata": {}, "outputs": [], @@ -54,34 +56,686 @@ "id": "a9a2e056", "metadata": {}, "source": [ - "# 1. Schordinger equation solver for singe qubit dynamics" + "# 1. Schrödinger equation solver for singe qubit dynamics\n", + "\n", + "The Schrödinger equation is $i\\hbar\\frac{{\\partial \\Psi}}{{\\partial t}} = H \\Psi$.\n", + "\n", + "We define an initial state $\\psi_0$ as the starting point of the time evolution.\n", + "\n", + "The Hamiltonian of the system is: $H = -\\frac{\\Omega}{2}V_0s(t)(I\\sigma_x + Q\\sigma_y)$" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "47404173", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Number of time slots and length of each slot:\n", + "n_dt = 160\n", + "dt = 0.22 \n", + "\n", + "# Initialize the state to ground state |0>\n", + "# InitialState and InitialDensity are used to define the initial states\n", + "psi = InitialState(n_qubit = 1, state = [0])\n", + "\n", + "# The pulse is defined as a constant pulse here\n", + "# Schedule() will return a torch.Parameter.parameters variable, \n", + "# which means that we now have access to their gradients\n", + "pulse = Schedule((0.1+0.1j) * np.ones((n_dt,1)))\n", + "\n", + "# Hamiltonian is defined \n", + "# It is a time-dependent Hamiltonian, a function of time.\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "\n", + "# Run the Schrödinger equation solver\n", + "y_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "\n", + "# The results show the evolution of qubit states\n", + "psi0_t = torch.abs(y_res[0][:,0]).tolist()\n", + "\n", + "# Plot the probability of state measured as |0>. (on Z basis)\n", + "plt.plot([p**2 for p in psi0_t])" + ] + }, + { + "cell_type": "markdown", + "id": "2dd98946", + "metadata": {}, + "source": [ + "\n", + "\n", + "## Then we can plot the state on a Bloch Sphere\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "1993b1db", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [sv2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_vectors(points[0])\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.add_vectors(np.array(points[::10]))\n", + "sphere.show()" + ] + }, + { + "cell_type": "markdown", + "id": "5a2c78c4", + "metadata": {}, + "source": [ + "## When the pulse drive is not constant the qubit would evolve at different speeds, as demonstrated here:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c508f463", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pulse_values = np.arange(1,n_dt+1)/n_dt\n", + "pulse = Schedule(pulse_values)\n", + "\n", + "# Here, we have a pulse strength that is linearly increasing.\n", + "plt.plot(pulse_values)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "c47a032e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "lin_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "linpsi0_t = torch.abs(lin_res[0][:,0]).tolist()\n", + "\n", + "#Then we can see that the states are evolving faster with increasing pulse strength\n", + "plt.plot([p**2 for p in linpsi0_t])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c0329c9d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "points = [sv2bloch(state) for state in lin_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_vectors(points[0])\n", + "sphere.add_points(np.array(points).T)\n", + "# sphere.add_vectors(np.array(points[::10]))\n", + "\n", + "# Which can also be seen from the figure, where states are evolving slowly in the beginning\n", + "sphere.show()" ] }, { "cell_type": "markdown", - "id": "e6f3e433", + "id": "9e6b3e3d", "metadata": {}, "source": [ - "Lamor precession is the precession of the magnetic moment of an object in an external magnetic field.\n", - "A good example is the \n", "\n", "\n", - "We define an initial state psi0 as the starting point of the time evolution.\n", - "The Hamiltonian of the system is: $H = $" + "## Another example of the evolution with cosine pulse strength.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f42b5976", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pulse_values = np.cos(2*np.pi/n_dt*np.arange(1,n_dt+1))/2\n", + "pulse = Schedule(pulse_values)\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "per_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "perpsi0_t = torch.abs(per_res[0][:,0]).tolist()\n", + "plt.plot([p**2 for p in perpsi0_t])" ] }, { "cell_type": "code", "execution_count": null, - "id": "47404173", + "id": "5fe09b50", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "45e69c5f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "0a32326c", + "metadata": {}, + "source": [ + "# 2. Optimal control with TorchQuantum\n", + "\n", + "The torch-based solver allows for easy gradients calculation.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "7c619368", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import torch.optim as optim\n", + "\n", + "# The target pulse is composed of 16 segments\n", + "n_dt = 16\n", + "\n", + "# The operation is a simple rotation around the x axis\n", + "theta = np.pi/4\n", + "target_unitary = torch.tensor([[np.cos(theta/2), -1j*np.sin(theta/2)], [-1j*np.sin(theta/2), np.cos(theta/2)]], dtype=torch.complex64)\n", + "\n", + "# Initiliaze the pulse with a constant value\n", + "pulse = Schedule((0.1+0.1j) * np.ones((n_dt,1)))\n", + "\n", + "# Define the optimizer as ADAM\n", + "optimizer = optim.Adam(params=[pulse], lr=1e-2)\n", + "\n", + "losses = []\n", + "\n", + "for k in range(100):\n", + " \n", + " # Obtain the time-dependent Hamiltonian and the results\n", + " H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + " solver_result = sesolve(psi0 = sigmai(), H = H, n_dt = n_dt, dt = dt)\n", + " unitary = solver_result[0][-1]\n", + " \n", + " # Compute the loss, the loss function is composed of fidelity, smoothness penalty and \"weight\" penalty\n", + " loss = 1 - (torch.trace(unitary @ target_unitary) / target_unitary.shape[0]).abs() ** 2 \\\n", + " + 0.1 * torch.abs(torch.diff(pulse)).sum() + 0.01 * torch.norm(pulse)\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + " losses.append(loss.item())\n", + " \n", + "# Draw the convergence curve\n", + "plt.xlabel(\"Number of Iterations\")\n", + "plt.ylabel(\"Training Losses\")\n", + "plt.title(\"Training from Default Initialization\")\n", + "plt.plot(losses[:100])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "f8324405", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Here we demosntrate that the results is close to the target unitary\n", + "\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)\n", + "y_res = sesolve(psi0 = psi, H = H, n_dt = n_dt, dt = dt)\n", + "psi0_t = torch.abs(y_res[0][:,0]).tolist()\n", + "points = [sv2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f25a05a7", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "8a523a7d", + "metadata": {}, + "source": [ + "# 3. Qubit dynamics with Lindblad master equation\n", + "\n", + "\n", + "Lindblad equation: $\\frac{{d\\rho}}{{dt}} = -\\frac{{i}}{{\\hbar}}[H, \\rho] + \\sum_{k}\\left(L_k\\rho L_k^{\\dagger} - \\frac{1}{2}\\{L_k^{\\dagger}L_k, \\rho\\}\\right)$\n", + "\n", + "In this equation, $\\rho$ represents the density operator, $t$ is the time variable, $\\hbar$ is the reduced Planck's constant, $H$ is the Hamiltonian operator, $L_k$ are the Lindblad operators, $\\dagger$ denotes the Hermitian conjugate, $[A, B]$ represents the commutator of operators $A$ and $B$, and $\\{A, B\\}$ represents the anticommutator of operators $A$ and $B$." + ] + }, + { + "cell_type": "markdown", + "id": "9a909a08", + "metadata": {}, + "source": [ + "## First we demosntrate the single-qubit dynamics without noise, we expect to see the same results as in the Schrodinger equation solver" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5422a649", + "metadata": {}, + "outputs": [], + "source": [ + "# First we define the initial Density matrix and the constant pulse\n", + "# All settings are the same with the SESolver\n", + "n_dt = 160\n", + "dt = 0.22 # ns\n", + "rho0 = InitialDensity(n_qubit = 1, state = [0])\n", + "pulse = Schedule((0.1+0.1j) * np.ones((n_dt,1)))\n", + "H = H_qubit_example(n_qubit = 1, pulse = pulse, dt = dt)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0c0c259f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Here, let's first test the Lindblad equation without L operators\n", + "L_ops = None\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "\n", + "# We can see that the curve is exactly the same as the SESolver\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a6640fca", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# The bloch sphere is, of course, the same.\n", + "points = [dens2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_vectors(points[0])\n", + "sphere.add_vectors(np.array(points[::10]))\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4d261675", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "c5b3015e", + "metadata": {}, + "source": [ + "## Then we try to add a dephasing operator $\\sigma_z$" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "bb7cbfaa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# A dephasing L operator\n", + "L_ops = 0.15 * sigmaz()\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "\n", + "# Plot the probability of qubit measured as state |0> (on Z basis)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "de708467", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# The figure demonstrates the change of qubit state\n", + "points = [dens2bloch(state) for state in y_res[0].tolist()]\n", + "sphere = Bloch()\n", + "sphere.add_points(np.array(points).T)\n", + "sphere.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6e7f9b1e", "metadata": {}, "outputs": [], "source": [] }, + { + "cell_type": "markdown", + "id": "8cab24f6", + "metadata": {}, + "source": [ + "## Dynamics of CR pulse on two qubits\n", + "\n", + "The effective Hamiltonian of CR can be expressed in this way:\n", + "$\\hat{H} = \\frac{\\hat{Z}\\otimes\\hat{A}}{2} + \\frac{\\hat{I}\\otimes\\hat{B}}{2}\n", + "=a_x\\hat{Z}\\hat{X} + a_x\\hat{Z}\\hat{Y}+ a_x\\hat{Z}\\hat{Z} + a_x\\hat{I}\\hat{X} + a_x\\hat{I}\\hat{Y} + a_x\\hat{I}\\hat{Z}$" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "a983758e", + "metadata": {}, + "outputs": [], + "source": [ + "# Set the initial state to ground state\n", + "rho0 = InitialDensity(n_qubit = 2, state = [0,0])\n", + "# state = [target, control]\n", + "\n", + "# Set constant Cross Resonance drive\n", + "pulse = Schedule(0.05 * np.ones((n_dt,1)))\n", + "H = H_2q_example(pulse = pulse, dt = dt)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "16aa86b0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# This picture demosntrates the evolution of target state when control qubit's state is set to 0\n", + "L_ops = None\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[0].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "1b485263", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Set control qubit's state to 1, and see how target qubit evolves:\n", + "rho0 = InitialDensity(n_qubit = 2, state = [0,1])\n", + "# state = [target, control]\n", + "y_res = mesolve(dens0 = rho0, H = H, n_dt = n_dt, dt = dt, L_ops = L_ops)\n", + "plt.plot([torch.diag(p)[2].item().real for p in y_res[0]])" + ] + }, + { + "cell_type": "markdown", + "id": "518a29db", + "metadata": {}, + "source": [ + "## The speed of evolution is different\n", + "Then we can use the difference to build controlled gates" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "9d9a1cfe", + "id": "78160fca", "metadata": {}, "outputs": [], "source": [] From 12e5b612af59f860d555e77023de3ae1ef1132fe Mon Sep 17 00:00:00 2001 From: GenericP3rson <41024739+GenericP3rson@users.noreply.github.com> Date: Sat, 1 Jul 2023 09:25:36 -0400 Subject: [PATCH 04/28] [minor] adding missing dependency --- setup.py | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.py b/setup.py index 51f383f9..823d557c 100644 --- a/setup.py +++ b/setup.py @@ -20,6 +20,7 @@ "tqdm>=4.56.0", "setuptools>=52.0.0", "torch>=1.8.0", + "torchdiffeq>=0.2.3", "torchpack>=0.3.0", "qiskit==0.38.0", "matplotlib>=3.3.2", From d71c43efd28e15e733078744ae70694a19ab5568 Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 14 Jul 2023 21:52:11 -0400 Subject: [PATCH 05/28] qubit rotation --- examples/qubit_rotation/README.md | 10 + .../TQ_Qubit_Rotation_Tutorial.ipynb | 988 ++++++++++++++++++ examples/qubit_rotation/qubit_rotation.py | 66 ++ 3 files changed, 1064 insertions(+) create mode 100644 examples/qubit_rotation/README.md create mode 100644 examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb create mode 100644 examples/qubit_rotation/qubit_rotation.py diff --git a/examples/qubit_rotation/README.md b/examples/qubit_rotation/README.md new file mode 100644 index 00000000..1b553fd0 --- /dev/null +++ b/examples/qubit_rotation/README.md @@ -0,0 +1,10 @@ +# Qubit Rotation Tutorial + +Tutorial based off of Pennylane's [Basic Tutorial: qubit rotation](https://pennylane.ai/qml/demos/tutorial_qubit_rotation) + +``` +python3 qubit_rotation.py +``` + +Expected to reach a loss of -1 by epoch 160 + diff --git a/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb b/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb new file mode 100644 index 00000000..64f8ef7a --- /dev/null +++ b/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb @@ -0,0 +1,988 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "gpuType": "T4" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# TorchQuantum Qubit Rotation Tutorial\n", + "\n", + "> Note: This tutorial was adapted from Pennylane's [Basic tutorial: qubit rotation](https://pennylane.ai/qml/demos/tutorial_qubit_rotation) by Josh Izaac.\n", + "\n", + "To see how TorchQuantum allows the easy construction and optimization of quantum functions, let's consider the simple case of qubit rotation.\n", + "\n", + "The task at hand is to optimize two rotation gates in order to flip a single qubit from state |0⟩ to state |1⟩.\n", + "\n" + ], + "metadata": { + "id": "Y6HrDR9HLIgG" + } + }, + { + "cell_type": "markdown", + "source": [ + "## The quantum circuit" + ], + "metadata": { + "id": "Y7jxsrq-TcqC" + } + }, + { + "cell_type": "markdown", + "source": [ + "In the qubit rotation example, we wish to implement the following quantum circuit:\n", + "\n", + "![image.png](data:image/png;base64,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)\n", + "\n", + "Breaking this down step-by-step, we first start with a qubit in the ground state $|0⟩ = [1\\ 0]^T$, and rotate it around the x-axis by applying the gate\n", + "\n", + "$\\begin{split}R_x(\\phi_1) = e^{-i \\phi_1 \\sigma_x /2} =\n", + "\\begin{bmatrix}\n", + "\\cos \\frac{\\phi_1}{2} & -i \\sin \\frac{\\phi_1}{2}\n", + "\\\\\n", + "-i \\sin \\frac{\\phi_1}{2} & \\cos \\frac{\\phi_1}{2}\n", + "\\end{bmatrix},\n", + "\\end{split}$\n", + "\n", + "and then around the y-axis via the gate\n", + "\n", + "$\\begin{split}R_y(\\phi_2) = e^{-i \\phi_2 \\sigma_y/2} =\n", + "\\begin{bmatrix} \\cos \\frac{\\phi_2}{2} & - \\sin \\frac{\\phi_2}{2}\n", + "\\\\\n", + "\\sin \\frac{\\phi_2}{2} & \\cos \\frac{\\phi_2}{2}\n", + "\\end{bmatrix}.\\end{split}$\n", + "\n", + "After these operations the qubit is now in the state\n", + "\n", + "$| \\psi \\rangle = R_y(\\phi_2) R_x(\\phi_1) | 0 \\rangle.$\n", + "\n", + "Finally, we measure the expectation value $⟨ψ∣σ_z∣ψ⟩$ of the Pauli-Z operator\n", + "\n", + "Using the above to calculate the exact expectation value, we find that\n", + "\n", + "$\\begin{split}\\sigma_z =\n", + "\\begin{bmatrix} 1 & 0\n", + "\\\\\n", + "0 & -1\n", + "\\end{bmatrix}.\\end{split}$\n", + "\n", + "Depending on the circuit parameters $ϕ_1$ and $ϕ_2$, the output expectation lies between 1 (if $|ψ⟩ = |0⟩) and -1 (if |ψ⟩ = |1⟩).\n", + "\n", + "$\\langle \\psi \\mid \\sigma_z \\mid \\psi \\rangle\n", + " = \\langle 0 \\mid R_x(\\phi_1)^\\dagger R_y(\\phi_2)^\\dagger \\sigma_z R_y(\\phi_2) R_x(\\phi_1) \\mid 0 \\rangle\n", + " = \\cos(\\phi_1)\\cos(\\phi_2).$\n", + "\n", + "Let's see how we can easily implement and optimize this circuit using TorchQuantum.\n", + "\n" + ], + "metadata": { + "id": "oFuPFpXhTFAR" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Importing TorchQuantum" + ], + "metadata": { + "id": "5sge9dfJTer6" + } + }, + { + "cell_type": "markdown", + "source": [ + "The first thing we need to do is install and import TorchQuantum. To utilize all of TorchQuantum's features, install it from source." + ], + "metadata": { + "id": "4qF2oH1MTmHb" + } + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "omF7GkuHKaPp", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "2c200ab7-f939-4193-d872-01c0f98b3ee6" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Cloning into 'torchquantum'...\n", + "remote: Enumerating objects: 13551, done.\u001b[K\n", + "remote: Counting objects: 100% (1822/1822), done.\u001b[K\n", + "remote: Compressing objects: 100% (758/758), done.\u001b[K\n", + "remote: Total 13551 (delta 1085), reused 1640 (delta 980), pack-reused 11729\u001b[K\n", + "Receiving objects: 100% (13551/13551), 104.07 MiB | 21.17 MiB/s, done.\n", + "Resolving deltas: 100% (7442/7442), done.\n", + "Obtaining file:///content/torchquantum\n", + " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + "Requirement already satisfied: 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symengine-0.10.0 tensorpack-0.11 torchdiffeq-0.2.3 torchpack-0.3.1 torchquantum-0.1.7 tweedledum-1.1.1 websockets-11.0.3\n" + ] + } + ], + "source": [ + "!git clone https://github.com/mit-han-lab/torchquantum.git\n", + "!cd torchquantum && pip install --editable ." + ] + }, + { + "cell_type": "markdown", + "source": [ + "> **Note: To be able to install TorchQuantum on Colab, you must restart your runtime before continuing!**\n", + "\n", + "After installing from source (and restarting if using Colab!), you can import TorchQuantum." + ], + "metadata": { + "id": "Ckw9S9C0TzuH" + } + }, + { + "cell_type": "code", + "source": [ + "import torchquantum as tq" + ], + "metadata": { + "id": "vhmIuM9Wc70Z" + }, + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "## Creating a device" + ], + "metadata": { + "id": "PxW4zls2Y3QM" + } + }, + { + "cell_type": "markdown", + "source": [ + "Before we can construct our quantum node, we need to initialize a device.\n", + "\n", + "> **Definition**\n", + ">\n", + "> Any computational object that can apply quantum operations and return a measurement value is called a quantum **device**.\n", + "\n", + "> *Devices are loaded in PennyLane via the class [QuantumDevice()](https://github.com/mit-han-lab/torchquantum/blob/main/torchquantum/devices.py#L13)*\n" + ], + "metadata": { + "id": "Y08Q6dMKY6HC" + } + }, + { + "cell_type": "markdown", + "source": [ + "For this tutorial, we are using the qubit model, so let's initialize the 'default' device provided by TorchQuantum." + ], + "metadata": { + "id": "0bgRmzQLeOtt" + } + }, + { + "cell_type": "code", + "source": [ + "qdev = tq.QuantumDevice(n_wires=1, device_name=\"default\", bsz=1, device=\"cuda\", record_op=True)" + ], + "metadata": { + "id": "NUrCxUQvc_3i" + }, + "execution_count": 4, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "For all devices, [QuantumDevice()](https://github.com/mit-han-lab/torchquantum/blob/main/torchquantum/devices.py#L13) accepts the following arguments:\n", + "\n", + "* n_wires: number of qubits to initialize the device with\n", + "* device_name: name of the quantum device to be loaded\n", + "* bsz: batch size of the quantum state\n", + "* device: which classical computing device to use, 'cpu' or 'cuda' (similar to the device option in PyTorch)\n", + "* record_op: whether to record the operations on the quantum device and then they can be used to construct a static computation graph\n", + "\n", + "Here, as we only require a single qubit for this example, we set wires=1." + ], + "metadata": { + "id": "uJOZRR--dQ0n" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Constructing the Circuit" + ], + "metadata": { + "id": "n2bS-rw1em0a" + } + }, + { + "cell_type": "markdown", + "source": [ + "Now that we have initialized our device, we can begin to construct the circuit. In TorchQuantum, there are multiple ways to construct a circuit, and we can explore a few of them." + ], + "metadata": { + "id": "9W-rBf2CfCQd" + } + }, + { + "cell_type": "code", + "source": [ + "# specify parameters\n", + "params = [0.54, 0.12]\n", + "\n", + "# create circuit\n", + "qdev.rx(params=params[0], wires=0)\n", + "qdev.ry(params=params[1], wires=0)" + ], + "metadata": { + "id": "qcmWA-o4hBqa" + }, + "execution_count": 5, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "This method calls the gates directly from the QuantumDevice. For the rotations, we can specify which wire it belongs to (zero-indexed) and a parameter theta for the amount of rotation. However, the rotation gates also have other parameters.\n", + "\n", + "* wires: which qibits the gate is applied to\n", + "* theta: the amount of rotation\n", + "* n_wires: number of qubits the gate is applied to\n", + "* static: whether use static mode computation\n", + "* parent_graph: Parent QuantumGraph of current operation\n", + "* inverse: whether inverse the gate\n", + "* comp_method: option to use 'bmm' or 'einsum' method to perform matrix vector multiplication" + ], + "metadata": { + "id": "RQhCOnNAhm7q" + } + }, + { + "cell_type": "markdown", + "source": [ + "To get the following expected value, we can use two different functions from torchquantum's measurement module." + ], + "metadata": { + "id": "zY5lSe3Nl-78" + } + }, + { + "cell_type": "code", + "source": [ + "from torchquantum.measurement import expval_joint_analytical, expval_joint_sampling" + ], + "metadata": { + "id": "3IHmc_ILirVI" + }, + "execution_count": 6, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "* `expval_joint_analytical` will compute the expectation value of a joint observable in analytical way, assuming the statevector is available. This can only be run on a classical simulator, not real quantum hardware.\n", + "\n", + "* `expval_joint_analytical` will compute the expectation value of a joint observable from sampling the measurement bistring. This can be run on both a classical simualtion and real quantum hardware. Since this is sampling the measurements, it requires a parameters for the number of shots, `n_shots`.\n", + "\n" + ], + "metadata": { + "id": "h_05PJxAjIMk" + } + }, + { + "cell_type": "code", + "source": [ + "exp_a = expval_joint_analytical(qdev, 'Z')\n", + "exp_s = expval_joint_sampling(qdev, 'Z', n_shots=1024)\n", + "\n", + "print(exp_a, exp_s)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "3TIwrhn1kD-a", + "outputId": "0af08a9b-5c1c-475b-9845-3aa2331ed59e" + }, + "execution_count": 7, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "tensor([0.8515]) tensor([0.8184])\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "The two numbers are about the same, and if we increase the number of shots for the joint sampling, its expected value should approach the same value as the analytical." + ], + "metadata": { + "id": "9rUMiTshkuYk" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Calculating quantum gradients" + ], + "metadata": { + "id": "WyHxuz4_l0lB" + } + }, + { + "cell_type": "markdown", + "source": [ + "From the expected values output, notice that the analytical expected value has an automatically-calculated gradient which can be used when constructing quantum machine learning models. This is because TorchQuantum automatically calculates the gradients. Let's find the gradient of each individual gate.\n", + "\n", + "To do so, we can create the circuit slightly differently, saving each operation as a variable then adding it to the circuit. We can then once again get the expected value with `expval_joint_analytical`." + ], + "metadata": { + "id": "GNlFHcRDnqVl" + } + }, + { + "cell_type": "code", + "source": [ + "qdev = tq.QuantumDevice(n_wires=1)\n", + "\n", + "op1 = tq.RX(has_params=True, trainable=True, init_params=0.54)\n", + "op1(qdev, wires=0)\n", + "\n", + "op2 = tq.RY(has_params=True, trainable=True, init_params=0.12)\n", + "op2(qdev, wires=0)\n", + "\n", + "\n", + "expval = expval_joint_analytical(qdev, 'Z')" + ], + "metadata": { + "id": "m_n2ROPNoFzn" + }, + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "We can then call `.backward()` on the expected value, just like in PyTorch. Afterwards, we can see the gradient of each operation under the `params` option." + ], + "metadata": { + "id": "znstxaD3pFdK" + } + }, + { + "cell_type": "code", + "source": [ + "expval[0].backward()\n", + "\n", + "# calculate the gradients for each operation!\n", + "print(op1.params.grad, op2.params.grad)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "d6ehHkuSo5Oq", + "outputId": "d3610b9a-48b2-4797-c3c9-818db8ce0687" + }, + "execution_count": 9, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "tensor([[-0.5104]]) tensor([[-0.1027]])\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Optimization" + ], + "metadata": { + "id": "R8PqqWa5pbzU" + } + }, + { + "cell_type": "markdown", + "source": [ + "Next, let's make use of PyTorch's optimizers to optimize the two circuit parameters $\\phi_1$ and $\\phi_2$ such that the qubit, originally in state |0⟩, is rotated to be in state |1⟩. This is equivalent to measuring a Pauli-Z expectation value of -1, since the state |1⟩ is an eigenvector of the Pauli-Z matrix with eigenvalue λ=−1." + ], + "metadata": { + "id": "q4I7DC2Uphzs" + } + }, + { + "cell_type": "markdown", + "source": [ + "To construct this circuit, we can use a class similar to a PyTorch module! We can begin by importing torch." + ], + "metadata": { + "id": "G3h9LjzJqf0k" + } + }, + { + "cell_type": "code", + "source": [ + "import torch" + ], + "metadata": { + "id": "X3LeotDeqoIh" + }, + "execution_count": 38, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "We can next create the class extending the PyTorch module and add our gates in a similar fashion as the previous steps." + ], + "metadata": { + "id": "LbN7Fo67qpGI" + } + }, + { + "cell_type": "code", + "source": [ + "import torchquantum as tq\n", + "import torchquantum.functional as tqf\n", + "\n", + "class OptimizationModel(torch.nn.Module):\n", + " def __init__(self):\n", + " super().__init__()\n", + " self.rx0 = tq.RX(has_params=True, trainable=True, init_params=0.011)\n", + " self.ry0 = tq.RY(has_params=True, trainable=True, init_params=0.012)\n", + "\n", + " def forward(self):\n", + " # create a quantum device to run the gates\n", + " qdev = tq.QuantumDevice(n_wires=1)\n", + "\n", + " # add some trainable gates (need to instantiate ahead of time)\n", + " self.rx0(qdev, wires=0)\n", + " self.ry0(qdev, wires=0)\n", + "\n", + " return expval_joint_analytical(qdev, 'Z')" + ], + "metadata": { + "id": "gxve5-2SpdDA" + }, + "execution_count": 39, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "To optimize the rotation, we need to define a cost function. By minimizing the cost function, the optimizer will determine the values of the circuit parameters that produce the desired outcome.\n", + "\n", + "In this case, our desired outcome is a Pauli-Z expectation value of −1. Since we know that the Pauli-Z expectation is bound between [−1, 1], we can define our cost directly as the output of the circuit.\n", + "\n", + "Similar to PyTorch, we can create a train function to compute the gradients of the loss function and have the optimizer perform an optimization step." + ], + "metadata": { + "id": "Ifi5cH_eq_zW" + } + }, + { + "cell_type": "code", + "source": [ + "def train(model, device, optimizer):\n", + " targets = 0\n", + "\n", + " outputs = model()\n", + " loss = outputs\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + "\n", + " return loss.item()" + ], + "metadata": { + "id": "H5xxXrWUrAO3" + }, + "execution_count": 53, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "Finally, we can run the model. We can import PyTorch's gradient descent module and use it to optimize our model." + ], + "metadata": { + "id": "dn0131aKrjQ8" + } + }, + { + "cell_type": "code", + "source": [ + "def main():\n", + " seed = 0\n", + " torch.manual_seed(seed)\n", + "\n", + " use_cuda = torch.cuda.is_available()\n", + " device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n", + "\n", + " model = OptimizationModel()\n", + " n_epochs = 200\n", + " optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n", + "\n", + " for epoch in range(1, n_epochs + 1):\n", + " # train\n", + " loss = train(model, device, optimizer)\n", + " output = (model.rx0.params[0].item(), model.ry0.params[0].item())\n", + " print(f\"Epoch {epoch}: {output}\")\n", + "\n", + " if epoch % 10 == 0:\n", + " print(f\"Loss after step {epoch}: {loss}\")" + ], + "metadata": { + "id": "4WJ7yL5SrjkA" + }, + "execution_count": 54, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "Finally, we can call the main function and run the entire sequence!" + ], + "metadata": { + "id": "eY5PvCqhr1ZF" + } + }, + { + "cell_type": "code", + "source": [ + "main()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "_hCBPtMvr4wB", + "outputId": "2091f42b-7263-4e5d-d2f7-eab8b07bbe7f" + }, + "execution_count": 55, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Epoch 1: (0.012099898420274258, 0.013199898414313793)\n", + "Epoch 2: (0.013309753499925137, 0.014519752934575081)\n", + "Epoch 3: (0.014640549197793007, 0.015971548855304718)\n", + "Epoch 4: (0.01610436476767063, 0.017568465322256088)\n", + "Epoch 5: (0.01771448366343975, 0.01932499371469021)\n", + "Epoch 6: (0.019485509023070335, 0.02125706896185875)\n", + "Epoch 7: (0.021433496847748756, 0.023382212966680527)\n", + "Epoch 8: (0.023576095700263977, 0.02571968361735344)\n", + "Epoch 9: (0.025932706892490387, 0.028290653601288795)\n", + "Epoch 10: (0.028524650260806084, 0.03111839108169079)\n", + "Loss after step 10: 0.9992638230323792\n", + "Epoch 11: (0.031375348567962646, 0.03422846272587776)\n", + "Epoch 12: (0.0345105305314064, 0.03764895722270012)\n", + "Epoch 13: (0.037958454340696335, 0.041410721838474274)\n", + "Epoch 14: (0.04175013676285744, 0.04554762691259384)\n", + "Epoch 15: (0.04591960832476616, 0.050096847116947174)\n", + "Epoch 16: (0.05050419643521309, 0.055099159479141235)\n", + "Epoch 17: (0.05554480850696564, 0.06059926748275757)\n", + "Epoch 18: (0.06108624115586281, 0.06664614379405975)\n", + "Epoch 19: (0.06717751175165176, 0.07329340279102325)\n", + "Epoch 20: (0.07387219369411469, 0.08059966564178467)\n", + "Loss after step 20: 0.9950657486915588\n", + "Epoch 21: (0.08122873306274414, 0.08862894773483276)\n", + "Epoch 22: (0.08931083232164383, 0.09745106101036072)\n", + "Epoch 23: (0.09818772971630096, 0.10714197158813477)\n", + "Epoch 24: (0.10793451964855194, 0.11778417229652405)\n", + "Epoch 25: (0.11863239109516144, 0.12946699559688568)\n", + "Epoch 26: (0.13036876916885376, 0.14228680729866028)\n", + "Epoch 27: (0.14323736727237701, 0.15634718537330627)\n", + "Epoch 28: (0.15733805298805237, 0.17175881564617157)\n", + "Epoch 29: (0.172776460647583, 0.18863925337791443)\n", + "Epoch 30: (0.18966329097747803, 0.20711229741573334)\n", + "Loss after step 30: 0.9676356315612793\n", + "Epoch 31: (0.20811320841312408, 0.2273070216178894)\n", + "Epoch 32: (0.2282431572675705, 0.2493562251329422)\n", + "Epoch 33: (0.2501700222492218, 0.27339422702789307)\n", + "Epoch 34: (0.2740074098110199, 0.29955384135246277)\n", + "Epoch 35: (0.2998615801334381, 0.32796236872673035)\n", + "Epoch 36: (0.32782599329948425, 0.35873648524284363)\n", + "Epoch 37: (0.3579748272895813, 0.39197587966918945)\n", + "Epoch 38: (0.3903552293777466, 0.427755743265152)\n", + "Epoch 39: (0.42497843503952026, 0.46611812710762024)\n", + "Epoch 40: (0.4618101119995117, 0.5070626139640808)\n", + "Loss after step 40: 0.8138567805290222\n", + "Epoch 41: (0.5007606744766235, 0.5505368709564209)\n", + "Epoch 42: (0.5416762828826904, 0.5964280366897583)\n", + "Epoch 43: (0.5843320488929749, 0.6445562839508057)\n", + "Epoch 44: (0.6284285187721252, 0.6946715116500854)\n", + "Epoch 45: (0.6735928058624268, 0.7464552521705627)\n", + "Epoch 46: (0.7193858623504639, 0.7995281219482422)\n", + "Epoch 47: (0.7653157711029053, 0.8534636497497559)\n", + "Epoch 48: (0.8108565211296082, 0.9078077673912048)\n", + "Epoch 49: (0.8554709553718567, 0.9621021151542664)\n", + "Epoch 50: (0.8986347317695618, 1.0159088373184204)\n", + "Loss after step 50: 0.3750203549861908\n", + "Epoch 51: (0.9398593902587891, 1.0688340663909912)\n", + "Epoch 52: (0.9787107706069946, 1.1205471754074097)\n", + "Epoch 53: (1.0148218870162964, 1.1707944869995117)\n", + "Epoch 54: (1.0478986501693726, 1.2194054126739502)\n", + "Epoch 55: (1.0777196884155273, 1.2662931680679321)\n", + "Epoch 56: (1.1041301488876343, 1.311449408531189)\n", + "Epoch 57: (1.127032995223999, 1.354935884475708)\n", + "Epoch 58: (1.1463772058486938, 1.3968735933303833)\n", + "Epoch 59: (1.1621465682983398, 1.4374314546585083)\n", + "Epoch 60: (1.1743487119674683, 1.4768157005310059)\n", + "Loss after step 60: 0.052838265895843506\n", + "Epoch 61: (1.1830050945281982, 1.5152597427368164)\n", + "Epoch 62: (1.1881437301635742, 1.553015947341919)\n", + "Epoch 63: (1.1897931098937988, 1.590348243713379)\n", + "Epoch 64: (1.1879782676696777, 1.6275262832641602)\n", + "Epoch 65: (1.1827187538146973, 1.6648198366165161)\n", + "Epoch 66: (1.1740283966064453, 1.702493667602539)\n", + "Epoch 67: (1.1619168519973755, 1.7408030033111572)\n", + "Epoch 68: (1.146392583847046, 1.7799879312515259)\n", + "Epoch 69: (1.1274679899215698, 1.820267915725708)\n", + "Epoch 70: (1.1051654815673828, 1.8618348836898804)\n", + "Loss after step 70: -0.10590392351150513\n", + "Epoch 71: (1.0795255899429321, 1.9048453569412231)\n", + "Epoch 72: (1.0506160259246826, 1.9494123458862305)\n", + "Epoch 73: (1.018541693687439, 1.9955958127975464)\n", + "Epoch 74: (0.9834545850753784, 2.043394088745117)\n", + "Epoch 75: (0.9455628991127014, 2.0927350521087646)\n", + "Epoch 76: (0.9051381945610046, 2.1434707641601562)\n", + "Epoch 77: (0.8625186085700989, 2.1953752040863037)\n", + "Epoch 78: (0.8181073665618896, 2.2481465339660645)\n", + "Epoch 79: (0.7723652124404907, 2.30141544342041)\n", + "Epoch 80: (0.7257967591285706, 2.354759931564331)\n", + "Loss after step 80: -0.4779837727546692\n", + "Epoch 81: (0.6789312362670898, 2.4077253341674805)\n", + "Epoch 82: (0.6322994232177734, 2.459847927093506)\n", + "Epoch 83: (0.5864096879959106, 2.5106801986694336)\n", + "Epoch 84: (0.5417252779006958, 2.5598134994506836)\n", + "Epoch 85: (0.4986463487148285, 2.6068966388702393)\n", + "Epoch 86: (0.4574976861476898, 2.6516494750976562)\n", + "Epoch 87: (0.4185234606266022, 2.6938676834106445)\n", + "Epoch 88: (0.38188809156417847, 2.7334227561950684)\n", + "Epoch 89: (0.34768232703208923, 2.770256519317627)\n", + "Epoch 90: (0.31593260169029236, 2.8043713569641113)\n", + "Loss after step 90: -0.876086413860321\n", + "Epoch 91: (0.28661224246025085, 2.835820436477661)\n", + "Epoch 92: (0.25965315103530884, 2.8646953105926514)\n", + "Epoch 93: (0.23495660722255707, 2.891116142272949)\n", + "Epoch 94: (0.21240299940109253, 2.915221691131592)\n", + "Epoch 95: (0.1918598860502243, 2.937161445617676)\n", + "Epoch 96: (0.1731884628534317, 2.957089900970459)\n", + "Epoch 97: (0.156248539686203, 2.97516131401062)\n", + "Epoch 98: (0.14090220630168915, 2.991525888442993)\n", + "Epoch 99: (0.12701639533042908, 3.0063281059265137)\n", + "Epoch 100: (0.11446458846330643, 3.019704818725586)\n", + "Loss after step 100: -0.9828835129737854\n", + "Epoch 101: (0.1031278446316719, 3.0317838191986084)\n", + "Epoch 102: (0.09289533644914627, 3.042684316635132)\n", + "Epoch 103: (0.08366449177265167, 3.052516460418701)\n", + "Epoch 104: (0.07534093409776688, 3.0613811016082764)\n", + "Epoch 105: (0.0678381696343422, 3.069370985031128)\n", + "Epoch 106: (0.06107722595334053, 3.0765702724456787)\n", + "Epoch 107: (0.054986197501420975, 3.0830557346343994)\n", + "Epoch 108: (0.0494997613132, 3.088897228240967)\n", + "Epoch 109: (0.04455867409706116, 3.0941579341888428)\n", + "Epoch 110: (0.040109291672706604, 3.0988948345184326)\n", + "Loss after step 110: -0.997883677482605\n", + "Epoch 111: (0.03610309213399887, 3.1031599044799805)\n", + "Epoch 112: (0.03249623253941536, 3.106999635696411)\n", + "Epoch 113: (0.029249126091599464, 3.1104564666748047)\n", + "Epoch 114: (0.026326047256588936, 3.1135683059692383)\n", + "Epoch 115: (0.023694779723882675, 3.1163694858551025)\n", + "Epoch 116: (0.021326277405023575, 3.1188907623291016)\n", + "Epoch 117: (0.019194360822439194, 3.1211602687835693)\n", + "Epoch 118: (0.01727544330060482, 3.1232030391693115)\n", + "Epoch 119: (0.015548276714980602, 3.1250417232513428)\n", + "Epoch 120: (0.013993724249303341, 3.1266965866088867)\n", + "Loss after step 120: -0.9997422099113464\n", + "Epoch 121: (0.012594552710652351, 3.128185987472534)\n", + "Epoch 122: (0.011335243470966816, 3.1295266151428223)\n", + "Epoch 123: (0.010201825760304928, 3.130733013153076)\n", + "Epoch 124: (0.00918172113597393, 3.131819009780884)\n", + "Epoch 125: (0.008263605646789074, 3.132796287536621)\n", + "Epoch 126: (0.0074372864328324795, 3.1336758136749268)\n", + "Epoch 127: (0.006693588104099035, 3.134467363357544)\n", + "Epoch 128: (0.006024251226335764, 3.1351797580718994)\n", + "Epoch 129: (0.005421841982752085, 3.1358211040496826)\n", + "Epoch 130: (0.004879669286310673, 3.1363983154296875)\n", + "Loss after step 130: -0.9999685883522034\n", + "Epoch 131: (0.004391710739582777, 3.13691782951355)\n", + "Epoch 132: (0.0039525460451841354, 3.137385368347168)\n", + "Epoch 133: (0.0035572960041463375, 3.1378061771392822)\n", + "Epoch 134: (0.003201569663360715, 3.1381847858428955)\n", + "Epoch 135: (0.0028814151883125305, 3.1385254859924316)\n", + "Epoch 136: (0.0025932753924280405, 3.1388320922851562)\n", + "Epoch 137: (0.002333949087187648, 3.139108180999756)\n", + "Epoch 138: (0.002100554993376136, 3.1393566131591797)\n", + "Epoch 139: (0.0018905001925304532, 3.139580249786377)\n", + "Epoch 140: (0.0017014506738632917, 3.1397814750671387)\n", + "Loss after step 140: -0.9999963045120239\n", + "Epoch 141: (0.001531305955722928, 3.139962673187256)\n", + "Epoch 142: (0.0013781756861135364, 3.1401257514953613)\n", + "Epoch 143: (0.0012403583386912942, 3.140272378921509)\n", + "Epoch 144: (0.0011163227027282119, 3.140404462814331)\n", + "Epoch 145: (0.0010046905372291803, 3.1405231952667236)\n", + "Epoch 146: (0.0009042215533554554, 3.1406302452087402)\n", + "Epoch 147: (0.0008137994445860386, 3.1407265663146973)\n", + "Epoch 148: (0.0007324195466935635, 3.140813112258911)\n", + "Epoch 149: (0.0006591776036657393, 3.1408910751342773)\n", + "Epoch 150: (0.0005932598724029958, 3.140961170196533)\n", + "Loss after step 150: -0.9999995231628418\n", + "Epoch 151: (0.0005339339259080589, 3.141024351119995)\n", + "Epoch 152: (0.00048054056242108345, 3.1410810947418213)\n", + "Epoch 153: (0.000432486500358209, 3.141132354736328)\n", + "Epoch 154: (0.00038923785905353725, 3.1411783695220947)\n", + "Epoch 155: (0.00035031407605856657, 3.1412198543548584)\n", + "Epoch 156: (0.0003152826684527099, 3.1412570476531982)\n", + "Epoch 157: (0.0002837544016074389, 3.1412906646728516)\n", + "Epoch 158: (0.0002553789527155459, 3.1413209438323975)\n", + "Epoch 159: (0.00022984105453360826, 3.141348123550415)\n", + "Epoch 160: (0.00020685694471467286, 3.1413726806640625)\n", + "Loss after step 160: -1.0\n", + "Epoch 161: (0.0001861712516983971, 3.14139461517334)\n", + "Epoch 162: (0.0001675541279837489, 3.1414144039154053)\n", + "Epoch 163: (0.00015079871809575707, 3.141432285308838)\n", + "Epoch 164: (0.00013571884483098984, 3.1414482593536377)\n", + "Epoch 165: (0.0001221469574375078, 3.141462802886963)\n", + "Epoch 166: (0.00010993226169375703, 3.1414756774902344)\n", + "Epoch 167: (9.893903188640252e-05, 3.1414873600006104)\n", + "Epoch 168: (8.904512651497498e-05, 3.141497850418091)\n", + "Epoch 169: (8.014061313588172e-05, 3.141507387161255)\n", + "Epoch 170: (7.212655327748507e-05, 3.1415159702301025)\n", + "Loss after step 170: -1.0\n", + "Epoch 171: (6.491389649454504e-05, 3.141523599624634)\n", + "Epoch 172: (5.8422505389899015e-05, 3.1415305137634277)\n", + "Epoch 173: (5.258025339571759e-05, 3.1415367126464844)\n", + "Epoch 174: (4.732222805614583e-05, 3.1415421962738037)\n", + "Epoch 175: (4.2590003431541845e-05, 3.141547203063965)\n", + "Epoch 176: (3.833100345218554e-05, 3.1415517330169678)\n", + "Epoch 177: (3.4497901651775464e-05, 3.1415557861328125)\n", + "Epoch 178: (3.10481118503958e-05, 3.141559362411499)\n", + "Epoch 179: (2.794330066535622e-05, 3.1415627002716064)\n", + "Epoch 180: (2.5148970962618478e-05, 3.1415657997131348)\n", + "Loss after step 180: -1.0\n", + "Epoch 181: (2.263407441205345e-05, 3.141568422317505)\n", + "Epoch 182: (2.0370667698443867e-05, 3.141570806503296)\n", + "Epoch 183: (1.83336014742963e-05, 3.141572952270508)\n", + "Epoch 184: (1.6500242054462433e-05, 3.1415748596191406)\n", + "Epoch 185: (1.485021766711725e-05, 3.1415765285491943)\n", + "Epoch 186: (1.3365195627557114e-05, 3.141578197479248)\n", + "Epoch 187: (1.2028675882902462e-05, 3.1415796279907227)\n", + "Epoch 188: (1.0825808203662746e-05, 3.141580820083618)\n", + "Epoch 189: (9.743227565195411e-06, 3.1415820121765137)\n", + "Epoch 190: (8.76890499057481e-06, 3.14158296585083)\n", + "Loss after step 190: -1.0\n", + "Epoch 191: (7.89201476436574e-06, 3.1415839195251465)\n", + "Epoch 192: (7.1028134698281065e-06, 3.141584873199463)\n", + "Epoch 193: (6.392532213794766e-06, 3.1415855884552)\n", + "Epoch 194: (5.753278855991084e-06, 3.1415863037109375)\n", + "Epoch 195: (5.177951152290916e-06, 3.141587018966675)\n", + "Epoch 196: (4.660155809688149e-06, 3.141587495803833)\n", + "Epoch 197: (4.194140274194069e-06, 3.141587972640991)\n", + "Epoch 198: (3.7747263377241325e-06, 3.1415884494781494)\n", + "Epoch 199: (3.3972537494264543e-06, 3.1415889263153076)\n", + "Epoch 200: (3.057528374483809e-06, 3.141589403152466)\n", + "Loss after step 200: -1.0\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "We can see that the optimization converges after approximately 160 steps.\n", + "\n", + "Substituting this into the theoretical result $⟨ψ∣σ_z∣ψ⟩ = \\cos ϕ_1 \\cos ϕ_2$, we can verify that this is indeed one possible value of the circuit parameters that produces $⟨ψ∣σ_z∣ψ⟩ = −1$, resulting in the qubit being rotated to the state |1⟩.\n", + "\n" + ], + "metadata": { + "id": "GpzzV6kyr_Z1" + } + } + ] +} \ No newline at end of file diff --git a/examples/qubit_rotation/qubit_rotation.py b/examples/qubit_rotation/qubit_rotation.py new file mode 100644 index 00000000..3e0d17d6 --- /dev/null +++ b/examples/qubit_rotation/qubit_rotation.py @@ -0,0 +1,66 @@ +''' +Qubit Rotation Optimization, adapted from https://pennylane.ai/qml/demos/tutorial_qubit_rotation +''' + +# import dependencies +import torchquantum as tq +import torch +from torchquantum.measurement import expval_joint_analytical + +class OptimizationModel(torch.nn.Module): + ''' + Circuit with rx and ry gate + ''' + def __init__(self): + super().__init__() + self.rx0 = tq.RX(has_params=True, trainable=True, init_params=0.011) + self.ry0 = tq.RY(has_params=True, trainable=True, init_params=0.012) + + def forward(self): + # create a quantum device to run the gates + qdev = tq.QuantumDevice(n_wires=1) + + # add some trainable gates (need to instantiate ahead of time) + self.rx0(qdev, wires=0) + self.ry0(qdev, wires=0) + + # return the analytic expval from Z + return expval_joint_analytical(qdev, 'Z') + +# train function to get expval as low as possible (ideally -1) +def train(model, device, optimizer): + + outputs = model() + loss = outputs + optimizer.zero_grad() + loss.backward() + optimizer.step() + + return loss.item() + +# main function to run the optimization +def main(): + seed = 0 + torch.manual_seed(seed) + + use_cuda = torch.cuda.is_available() + device = torch.device("cuda" if use_cuda else "cpu") + + model = OptimizationModel() + n_epochs = 200 + optimizer = torch.optim.SGD(model.parameters(), lr=0.1) + + for epoch in range(1, n_epochs + 1): + # train + loss = train(model, device, optimizer) + output = (model.rx0.params[0].item(), model.ry0.params[0].item()) + + print(f"Epoch {epoch}: {output}") + + if epoch % 10 == 0: + print(f"Loss after step {epoch}: {loss}") + + +if __name__ == "__main__": + main() + From 550b999f09df07d2723972e2109a52168323b919 Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 14 Jul 2023 21:57:31 -0400 Subject: [PATCH 06/28] [minor] fixing the codespell check --- examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb b/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb index 64f8ef7a..07b0a809 100644 --- a/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb +++ b/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb @@ -458,7 +458,7 @@ "source": [ "* `expval_joint_analytical` will compute the expectation value of a joint observable in analytical way, assuming the statevector is available. This can only be run on a classical simulator, not real quantum hardware.\n", "\n", - "* `expval_joint_analytical` will compute the expectation value of a joint observable from sampling the measurement bistring. This can be run on both a classical simualtion and real quantum hardware. Since this is sampling the measurements, it requires a parameters for the number of shots, `n_shots`.\n", + "* `expval_joint_analytical` will compute the expectation value of a joint observable from sampling the measurement bistring. This can be run on both a classical simulation and real quantum hardware. Since this is sampling the measurements, it requires a parameters for the number of shots, `n_shots`.\n", "\n" ], "metadata": { @@ -985,4 +985,4 @@ } } ] -} \ No newline at end of file +} From bcf9d01a5834a5030e2bcd86226d93f82ad173cf Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 14 Jul 2023 22:01:55 -0400 Subject: [PATCH 07/28] [minor] updated format with black for lint tests --- .../TQ_Qubit_Rotation_Tutorial.ipynb | 1969 +++++++++-------- examples/qubit_rotation/qubit_rotation.py | 16 +- 2 files changed, 995 insertions(+), 990 deletions(-) diff --git a/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb b/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb index 07b0a809..af29d5ce 100644 --- a/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb +++ b/examples/qubit_rotation/TQ_Qubit_Rotation_Tutorial.ipynb @@ -1,988 +1,991 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "gpuType": "T4" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# TorchQuantum Qubit Rotation Tutorial\n", + "\n", + "> Note: This tutorial was adapted from Pennylane's [Basic tutorial: qubit rotation](https://pennylane.ai/qml/demos/tutorial_qubit_rotation) by Josh Izaac.\n", + "\n", + "To see how TorchQuantum allows the easy construction and optimization of quantum functions, let's consider the simple case of qubit rotation.\n", + "\n", + "The task at hand is to optimize two rotation gates in order to flip a single qubit from state |0⟩ to state |1⟩.\n", + "\n" + ], + "metadata": { + "id": "Y6HrDR9HLIgG" + } + }, + { + "cell_type": "markdown", + "source": [ + "## The quantum circuit" + ], + "metadata": { + "id": "Y7jxsrq-TcqC" + } + }, + { + "cell_type": "markdown", + "source": [ + "In the qubit rotation example, we wish to implement the following quantum circuit:\n", + "\n", + "![image.png](data:image/png;base64,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)\n", + "\n", + "Breaking this down step-by-step, we first start with a qubit in the ground state $|0⟩ = [1\\ 0]^T$, and rotate it around the x-axis by applying the gate\n", + "\n", + "$\\begin{split}R_x(\\phi_1) = e^{-i \\phi_1 \\sigma_x /2} =\n", + "\\begin{bmatrix}\n", + "\\cos \\frac{\\phi_1}{2} & -i \\sin \\frac{\\phi_1}{2}\n", + "\\\\\n", + "-i \\sin \\frac{\\phi_1}{2} & \\cos \\frac{\\phi_1}{2}\n", + "\\end{bmatrix},\n", + "\\end{split}$\n", + "\n", + "and then around the y-axis via the gate\n", + "\n", + "$\\begin{split}R_y(\\phi_2) = e^{-i \\phi_2 \\sigma_y/2} =\n", + "\\begin{bmatrix} \\cos \\frac{\\phi_2}{2} & - \\sin \\frac{\\phi_2}{2}\n", + "\\\\\n", + "\\sin \\frac{\\phi_2}{2} & \\cos \\frac{\\phi_2}{2}\n", + "\\end{bmatrix}.\\end{split}$\n", + "\n", + "After these operations the qubit is now in the state\n", + "\n", + "$| \\psi \\rangle = R_y(\\phi_2) R_x(\\phi_1) | 0 \\rangle.$\n", + "\n", + "Finally, we measure the expectation value $⟨ψ∣σ_z∣ψ⟩$ of the Pauli-Z operator\n", + "\n", + "Using the above to calculate the exact expectation value, we find that\n", + "\n", + "$\\begin{split}\\sigma_z =\n", + "\\begin{bmatrix} 1 & 0\n", + "\\\\\n", + "0 & -1\n", + "\\end{bmatrix}.\\end{split}$\n", + "\n", + "Depending on the circuit parameters $ϕ_1$ and $ϕ_2$, the output expectation lies between 1 (if $|ψ⟩ = |0⟩) and -1 (if |ψ⟩ = |1⟩).\n", + "\n", + "$\\langle \\psi \\mid \\sigma_z \\mid \\psi \\rangle\n", + " = \\langle 0 \\mid R_x(\\phi_1)^\\dagger R_y(\\phi_2)^\\dagger \\sigma_z R_y(\\phi_2) R_x(\\phi_1) \\mid 0 \\rangle\n", + " = \\cos(\\phi_1)\\cos(\\phi_2).$\n", + "\n", + "Let's see how we can easily implement and optimize this circuit using TorchQuantum.\n", + "\n" + ], + "metadata": { + "id": "oFuPFpXhTFAR" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Importing TorchQuantum" + ], + "metadata": { + "id": "5sge9dfJTer6" + } + }, + { + "cell_type": "markdown", + "source": [ + "The first thing we need to do is install and import TorchQuantum. To utilize all of TorchQuantum's features, install it from source." + ], + "metadata": { + "id": "4qF2oH1MTmHb" + } + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "omF7GkuHKaPp", "colab": { - "provenance": [], - "gpuType": "T4" - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "GPU" + "base_uri": "https://localhost:8080/" + }, + "outputId": "2c200ab7-f939-4193-d872-01c0f98b3ee6" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Cloning into 'torchquantum'...\n", + "remote: Enumerating objects: 13551, done.\u001b[K\n", + "remote: Counting objects: 100% (1822/1822), done.\u001b[K\n", + "remote: Compressing objects: 100% (758/758), done.\u001b[K\n", + "remote: Total 13551 (delta 1085), reused 1640 (delta 980), pack-reused 11729\u001b[K\n", + "Receiving objects: 100% (13551/13551), 104.07 MiB | 21.17 MiB/s, done.\n", + "Resolving 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symengine-0.10.0 tensorpack-0.11 torchdiffeq-0.2.3 torchpack-0.3.1 torchquantum-0.1.7 tweedledum-1.1.1 websockets-11.0.3\n" + ] + } + ], + "source": [ + "!git clone https://github.com/mit-han-lab/torchquantum.git\n", + "!cd torchquantum && pip install --editable ." + ] }, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# TorchQuantum Qubit Rotation Tutorial\n", - "\n", - "> Note: This tutorial was adapted from Pennylane's [Basic tutorial: qubit rotation](https://pennylane.ai/qml/demos/tutorial_qubit_rotation) by Josh Izaac.\n", - "\n", - "To see how TorchQuantum allows the easy construction and optimization of quantum functions, let's consider the simple case of qubit rotation.\n", - "\n", - "The task at hand is to optimize two rotation gates in order to flip a single qubit from state |0⟩ to state |1⟩.\n", - "\n" - ], - "metadata": { - "id": "Y6HrDR9HLIgG" - } - }, - { - "cell_type": "markdown", - "source": [ - "## The quantum circuit" - ], - "metadata": { - "id": "Y7jxsrq-TcqC" - } - }, - { - "cell_type": "markdown", - "source": [ - "In the qubit rotation example, we wish to implement the following quantum circuit:\n", - "\n", - "![image.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAA+CAYAAAD3VGWyAAAMbWlDQ1BJQ0MgUHJvZmlsZQAASImVVwdYE0kbni1JSEhCCURASuhNEOlFSggtgoBUwUZIAgklxoQgYlcOFTy7iGJFT0U89PQE5FAR9ayHYvcshwUV5TzUQ1FU/kkBy/3l+b/nmZ133/nmazuzuwOATh9PKs1DdQHIlxTIEiJDWePT0lmkJwABKKADD2DL48ul7Pj4GABlsP9a3lyH2lCuuCht/XP8v4q+QCjnA4BMhDhTIOfnQ9wCAL6RL5UVAEBU8tbTC6RKPA9iAxkMEOI1SpytxruVOFONm1U6SQkciC8BoEXl8WTZANDvQJ5VyM+GdugfIHaTCMQSAHRGQBzEF/EEECtjH5GfP1WJKyF2gPpSiGE8wDfzC5vZX9nPHLLP42UPYXVeKtEKE8ulebwZ/2dp/rfk5ykGfdjBRhXJohKU+cMa3sydGq3EVIi7JZmxccpaQ9wnFqjrDgBKESmiktX6qClfzoH1A0yI3QS8sGiITSGOkOTFxmj4zCxxBBdiuFrQInEBNwliI4gXC+XhiRqdrbKpCRpfaH2WjMPW8Gd4MpVfpa97itxktsb+K5GQq7GP0YtFSakQUyC2KRSnxEJMh9hVnpsYrdEZXSzixA7qyBQJyvhtIE4QSiJD1faxwixZRIJGvyxfPpgvtlUk5sZq8IECUVKUuj7YST5PFT/MBbsklLCTB+0I5eNjBnMRCMPC1bljT4WS5ESNnT5pQWiCei5OkebFa/RxK2FepJK3gthTXpiomYunFMDFqbaPZ0kL4pPUceLFObwx8ep48BUgBnBAGGABBWyZYCrIAeK27oZueKceiQA8IAPZQAhcNMzgjFTViAReE0Ex+BMiIZAPzQtVjQpBIeQ/DrHqqwvIUo0WqmbkgscQ54NokAfvFapZkiFvKeARZMT/8M6DjQ/jzYNNOf7v+UH2M8OGTIyGUQx6ZOkMahLDiWHEKGIE0RE3wYPwADwGXkNgc8d9cb/BPD7rEx4T2gkPCNcIHYRbU8QLZN9EORZ0QPsRmlpkflkL3A7a9MJD8UBoHVrGmbgJcME9oR82Hgw9e0GWo4lbWRXWN7a/yuCLp6HRI7uRUfIwcgjZ4duZdCe615AVZa2/rI861syhenOGRr71z/mi+gLYR3+riS3GDmKnsePYWawZawAs7BjWiF3Ajijx0Op6pFpdg94SVPHkQjvif/gbfLLKSsrdat263D6oxwqERQXKjceZKp0hE2eLClhs+HUQsrgSvusIlrubuwcAym+N+vX1mqn6hiDMc5+5hT4ABJYMDAw0f+aifwDgYBrc/lc/c/bv4DvaGoAzm/kKWaGaw5UXAnxL6MCdZgzMgTVwgPm4A28QAEJAOBgD4kASSAOTYfQiuM5lYDqYBeaDUlAOVoC1YAPYAraD3eBHcAA0gGZwHPwKzoNL4Bq4DVdPJ3gOesAb0I8gCAmhIQzEGLFAbBFnxB3xRYKQcCQGSUDSkAwkG5EgCmQWshApR1YhG5BtSA3yE3IYOY6cRdqRW8h9pAt5hbxHMZSKGqBmqB06EvVF2Wg0moROQrPRaWgxWoIuQyvRanQvWo8eR8+j19AO9DnaiwFMG2NilpgL5otxsDgsHcvCZNgcrAyrwKqxOqwJPucrWAfWjb3DiTgDZ+EucAVH4ck4H5+Gz8GX4hvw3Xg9fhK/gt/He/BPBBrBlOBM8CdwCeMJ2YTphFJCBWEn4RDhFNxLnYQ3RCKRSbQn+sC9mEbMIc4kLiVuIu4jthDbiQ+JvSQSyZjkTAokxZF4pAJSKWk9aS/pGOkyqZPUp6WtZaHlrhWhla4l0VqgVaG1R+uo1mWtJ1r9ZF2yLdmfHEcWkGeQl5N3kJvIF8md5H6KHsWeEkhJouRQ5lMqKXWUU5Q7lNfa2tpW2n7a47TF2vO0K7X3a5/Rvq/9jqpPdaJyqBOpCuoy6i5qC/UW9TWNRrOjhdDSaQW0ZbQa2gnaPVofnUF3pXPpAvpcehW9nn6Z/kKHrGOrw9aZrFOsU6FzUOeiTrcuWddOl6PL052jW6V7WPeGbq8eQ2+UXpxevt5SvT16Z/We6pP07fTD9QX6Jfrb9U/oP2RgDGsGh8FnLGTsYJxidBoQDewNuAY5BuUGPxq0GfQY6ht6GqYYFhlWGR4x7GBiTDsml5nHXM48wLzOfD/MbBh7mHDYkmF1wy4Pe2s03CjESGhUZrTP6JrRe2OWcbhxrvFK4wbjuya4iZPJOJPpJptNTpl0DzcYHjCcP7xs+IHhv5uipk6mCaYzTbebXjDtNTM3izSTmq03O2HWbc40DzHPMV9jftS8y4JhEWQhtlhjccziGcuQxWblsSpZJ1k9lqaWUZYKy22WbZb9VvZWyVYLrPZZ3bWmWPtaZ1mvsW617rGxsBlrM8um1uZ3W7Ktr63Idp3tadu3dvZ2qXaL7Brsntob2XPti+1r7e840ByCHaY5VDtcdSQ6+jrmOm5yvOSEOnk5iZyqnC46o87ezmLnTc7tIwgj/EZIRlSPuOFCdWG7FLrUutx3ZbrGuC5wbXB9MdJmZPrIlSNPj/zk5uWW57bD7fYo/VFjRi0Y1TTqlbuTO9+9yv2qB80jwmOuR6PHS09nT6HnZs+bXgyvsV6LvFq9Pnr7eMu867y7fGx8Mnw2+tzwNfCN913qe8aP4BfqN9ev2e+dv7d/gf8B/78CXAJyA/YEPB1tP1o4esfoh4FWgbzAbYEdQaygjKCtQR3BlsG84OrgByHWIYKQnSFP2I7sHPZe9otQt1BZ6KHQtxx/zmxOSxgWFhlWFtYWrh+eHL4h/F6EVUR2RG1ET6RX5MzIlihCVHTUyqgbXDMun1vD7RnjM2b2mJPR1OjE6A3RD2KcYmQxTWPRsWPGrh57J9Y2VhLbEAfiuHGr4+7G28dPi/9lHHFc/LiqcY8TRiXMSjidyEickrgn8U1SaNLypNvJDsmK5NYUnZSJKTUpb1PDUleldowfOX72+PNpJmnitMZ0UnpK+s703gnhE9ZO6JzoNbF04vVJ9pOKJp2dbDI5b/KRKTpTeFMOZhAyUjP2ZHzgxfGqeb2Z3MyNmT18Dn8d/7kgRLBG0CUMFK4SPskKzFqV9TQ7MHt1dpcoWFQh6hZzxBvEL3OicrbkvM2Ny92VO5CXmrcvXys/I/+wRF+SKzk51Xxq0dR2qbO0VNoxzX/a2mk9smjZTjkinyRvLDCAP/UXFA6K7xT3C4MKqwr7pqdMP1ikVyQpujDDacaSGU+KI4p/mInP5M9snWU5a/6s+7PZs7fNQeZkzmmdaz23ZG7nvMh5u+dT5ufO/22B24JVC/5emLqwqcSsZF7Jw+8iv6stpZfKSm8sCli0ZTG+WLy4bYnHkvVLPpUJys6Vu5VXlH9Yyl967vtR31d+P7Asa1nbcu/lm1cQV0hWXF8ZvHL3Kr1Vxaserh67un4Na03Zmr/XTll7tsKzYss6yjrFuo7KmMrG9TbrV6z/sEG04VpVaNW+jaYbl2x8u0mw6fLmkM11W8y2lG95v1W89ea2yG311XbVFduJ2wu3P96RsuP0D74/1Ow02Vm+8+Muya6O3Qm7T9b41NTsMd2zvBatVdR27Z2499KPYT821rnUbdvH3Fe+H+xX7H/2U8ZP1w9EH2g96Huw7mfbnzceYhwqq0fqZ9T3NIgaOhrTGtsPjznc2hTQdOgX1192NVs2Vx0xPLL8KOVoydGBY8XHelukLd3Hs48/bJ3SevvE+BNXT4472XYq+tSZXyN+PXGaffrYmcAzzWf9zx4+53uu4bz3+foLXhcO/eb126E277b6iz4XGy/5XWpqH91+9HLw5eNXwq78epV79fy12Gvt15Ov37wx8UbHTcHNp7fybr38vfD3/tvz7hDulN3VvVtxz/Re9R+Of+zr8O44cj/s/oUHiQ9uP+Q/fP5I/uhDZ8lj2uOKJxZPap66P23uiui69GzCs87n0uf93aV/6v258YXDi5//CvnrQs/4ns6XspcDr5a+Nn6962/Pv1t743vvvcl/0/+2rM+4b/c733en36e+f9I//QPpQ+VHx49Nn6I/3RnIHxiQ8mQ81a8ABhualQXAq10A0OC/AwOe2ygT1GdBlSDq86sKgf+E1edFlXgDUAc75W88pwWA/bDZzVMdVYDyFz4pBKAeHkNNI/IsD3e1LSo8CRH6BgZemwFAagLgo2xgoH/TwMDHHTDYWwC0TFOfQZVChGeGrZ5KdJlZNA98I+rz6Rc5ftsDZQSq6V/1/wJTu49WhcXIhQAAADhlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAAqACAAQAAAABAAACWKADAAQAAAABAAAAPgAAAADX7oNEAAAkRklEQVR4Ae2dB7xVxbXGY8MuUVFULICoYI2SiP2K0dh7j1E0ahJbjMaoWCKY6NNnjQZN1NiNvfeWYCVGo7Eg9ouCFcQgYsO8vO8Ps8xw3P3sfe6598z3+33s2TNrrZlZe/bMmtn3Xmb5VkDwQPBA8EBjPLClqrlNnLUx1YVamtADE9WmRZqwXaFJwQOleyBMdKW7NBgMHggeiPHAJsoPc06Mc1oku4f6OV+L9DV0s8U9MHuL978zdf9CNXaAOLozNTq0tW4PLC4L3cUdRXb/nRk2diepEz/rzB0Jbc/tgRWlMcxp/Se3dlAIHggeCB6oyAO9ZZdJKbB1fXBBRWOrkWb3d2N4fCMrDXU1hQfa3LNnDpu3KVoUGhE8ULEHwglWxQ4uyfw0z84TSk/x7kOya3tgXXVvbvG1rt3N0LvggeCB4IGu5YEQYHW+5/lTNfnZztfs0OKCHmiXXm/xk4L6QS14IHigfA90k8kNxI/KN93UFudS6/jEP6apW9kkjQsBVpM8iNCM4IHggeCB4IFO44Hn1NIVOk1ry2/oxjL5YPlmu5bF8Bs9Xet5ht4EDwQPBA8ED1TvAX7xpJWxZCt3PmvfwwlWVk8FueCB4IHggeCB4IEZHhiry2LiueLZYiuAA5lXXUffb4UO19vHEGDV68GgHzwQPBA8EDzQqh7gZ7DeaJHOhy9eOR90cFhOhwXx4IHggeCB4IHggeCB4IE0D4QAK81DoTx4IHggeKCYB2aRGn9gc3Ax9Q7V2k619+rQFoTKgwc6uQdCgNXJH2BofvBA8EDTeWAOtYg/qsqnI/56/RFivSBYO1lcv15DGfWvkNx48RGR/+IooGt5gP+u6PvibF2rW83Vm0YGWMup6/xq53eaywWhNcEDwQPBA6V5YFFZ+qvIX95fWBwulhFg9ZedoSL/l18jsLUquVhcR7xPPE8kcAzoGh64Tt14QDykibqzldrCX/r/UOTvjDU7iJ/eFmnzDlGN5YfcOQoGd4hfTU9V888qMnuj+J7Ir3j+WwwIHvA9wC6dl2yIyMS+uljvb6uwyM0jjhOrxpmqgL+8zt+HOUdkrAfU74GeMsH8kYZ/SYDJ+U3x/9KEKygnuOJ/WugtviBuKb4lloE1nRH7/xzLsJlkY6QK4RXibeIBIvM260VH+FbVBpTkgU1lZ3Nnq6zxWUbTdnVGrtf1yzIMVmyD94CY5hCRtt8kfgNEX3CBb5SUm8FfgGUCpK6NyjXd5a3xsxD2nFbror1dXv160vXzM10J+DnGrhe3ysAj9RrJqL+75Pg1Zp7Vp+JxIkFjPWiXMvYOrMdIk+ju7/rCp6c82E3CNv6zXD+RPJMdwW6jwKeWB0TaR/+WEMvECBnjvaCeRoP5+iuRvp1QsPI2p4+NrvB/EY5y/Rle0B8dpcb44Y+k8hz+JuaZn2Z1euhuJpYJ4oPJIrbbyjRcsa21XZun6hq5XtEhWHWApSq+dalIXX8UA7J7oKsHWLxQk0TGBp8jlhbLwjsydH5ZxjLYYcLaV/xYpD8cxdfzaaXd2WnlAIvPBX3F9cSHnT/w7Q3iTiKB7S9EnvMHImWQHeZBYiPA87F6d6mgQjYfT1dgN6vJ8yRI//jysHJWJU+uTWnzTwiwPMc0OLmf9xx4n/KgygBrRzWE8cF83RGbiDx+8GWZ79tF2s489A3YoM8aYOHkDUWOjIeK+4hZju8lNj3qpT6O8Zk0A7J5oGiAxUT2egY+IxkWrj+Je4lZx4JE68YysjBRZFzcK5Y5LrCN3YPFRmNDVciJA/WfLRZFuxSx0coBlu+7m50/8MkP/QKXZuzeI1IO+dSwrFgl5pTxcSL1PVVBRezuvxAvr8B2VpM9JPi5SB+vzarkybU5XfRDgOU5poFJ/E4AwzO4rkC9rP3owrJPsGgPds8UOxtOUYNp+y1RDTeHZVlUmdBsIjE9u/5dZQOjKvDy+Jmv90V0yn5AXjVdLlk0wCJYGS5eJPKzG/asOM6835HjYgJeK+NKwLO9WDV4YRk31MmLn2UMSiwzdpYktgdn1ihX8AhXP23YtqDpdmfjwIL6zaRW9BOh34exusGfsL8YhUWVacEAcr+MEioxj02mtemnJdo1U2s7+0dZRgddr3Ht4BSrb842tDld/BQCrJzOK0l8mOzgf4L15cS8qCrAmkcN4bM+bfte3kY1gTw/tkPbmXO617aHApi2uJ3l5JC9WtxAXF7cTmTXRj67xbTjcTtqvkSyAdk8UDTA8q3bESzPiZMiH7PoZn3xnyLlcJqYFjBLpC4wVqy+IXVZilY+zdlfJLq48lw+Db7k2jBaVyaovGiXAj4KAdaM38qz8TJFPkny5+POb8ifI1aJ22Wcegg8FqygokOd/a0qsJ3HJHO9+f/wPIqSbfN0Q4CV03kliPeUDfuxhaKnRFUFWLu7sfG6rqxFnRHM77wbQ2obby9MUoB1kFNG9uRaA7onAn1UpJwobi0xDgRmyPEDbXPFCYX8mTxQRoA1XBbtWf/PTNb/e7OQku95cpf/t6j0FC/SC66uD3TtVnoNMz57TqjAbh6Tv5Cw+T1t8xFlt93phwBrxt/tMV8y3yThPhWa7KlJgnWWESzYp2A2KFXgKhmlL72rMJ7DJvMDQSRteSiHHqJtoj2PEGDldF4J4nzFwP8fiQsXtFdVgHWLa9tvC7arGdR+7fpwV21jbNDHBViLSsF+up8ojV15FDiu59QDe5xoxe0uWVjHishtIwake6CMAMt22fh954Qq/ZNKAqCqMFCGbewV3VEltY0flOTY+S9JQg0o66E67L3gGeRFuxTwUwiwZvw9KRsz56Q4cozzG/L8aENVGCzD1qYRJVXCxvMH4jDxMpFFkTquEX8jfl+sYkMis6mwnTpfK/K0oU3y5qcQYKW6uVSBFWXN5qBf1mG5igCLuMM2KCvX0baOVl1WDWB8814sbI2JC4KsnOthogVfv1eaBxUFPoXc7wpYPLeOElIejbjBle0aIxOyy/fAdzyTz3jp2mS7l8FEXxW29QzbuPGy6k7ysjKRVxkkZmnkRAmZvzdRev4sSkEm0gOre7lPe+naZD9lsOED/xLvnJ6q5p+VPLPMgfWgj5SZYxkzfMZnV7yF+G2RRYg59TjxAfENkaCbDWsj8bKrjI32co2sONRV2ANsYGcXmdsZX82E7dUY1pnnxY6eq+vxC583/yHyXuxghnB6Enh5/SDopiRhld0sbu5k2DXe6tK1F3ZiRNIssiyCU8WA6jzAKeSSzvxkXRkMcbBgmvK34oRKyN/M2eCTw+Ml2DMTjKe+4h4ugzHODu4V8SuX1+jLw6rwe+Kc4obi7WJAfg9kCbBmldmzPNMEJIz5qjDAMzzWS+dJ0uYjxGHi3OIjIgvhPSJBORvS68V9xA3FYeL64giRky4+PbNzbgT8DRjv1ehGVBrqKOyBjaS5qdMequsXhS1Vo2jxBTFBESwopcFiX7FHTgOnSf7DnDpJ4vSBwyX6dKEJcqIE/YXVylZxZZS/ZpkJV1/+E8klBXDshLC7c4K9UDTDA710see0WgGnMAmb/sgU/Ts82V+lyBYtnk2Kn7p6CHzqRXcZOExkYZomWl/9K4vstWLSzwequBKw2bC2HJuzhnany2lFZ8f+6gB+GF+gIwTOBMjoc5rDTrEWTLZXi+Zrdu5V425VYPUVeTcJuhmX2Jgi7iH6OFU3lPnvIu/P5S6fsvPERuFQVWT9PSpHpW2eHs+ys2OUOoAfhjdxR2ZV25527XxCVw5M6gH27NnbBrkee7yvBHzY7JfTEF9k2HgwJ2DjVfEt8f9Ea2PSlQ1Jnk/cEk/FUpLgwAAugTQOS8LqXuGLXjouSdBEBwEv0fLTU9H/MKkAor2Aaj3gP0deuDiwIyUYAxPEC6anyv+nj0zO7cyOrcM8AfyRIi8Wi+mSIj+bQ0BD+8GPRBYpArpdRCbG88SyXy6ZjMVYr2SAlw7J7B5YVaIEFoBPcfOJC4vMMduJ54qvi7uJ74qMgcPFqjG/V8HHXjpr8kIJMi4/F7cUrxJ9DHI3L3iZTOA/Fd9xeaR5dxsBgkCD33fLC9fm8cA+aorN/b9UmoCjmcDhCvPwE+JrGRtGzHKc+KQ4WDxEZB5YTlxa7CX+TrS+Enix5nHg44M55Es/o4T0ONl4TKSNX38mtChvgYgK/ld5Vj4iojwqi5fedJKCp/5O7jNdo+qOst2qeQwa82mRXTJHl6ZPwBGFxZX5oogck/3GYlXYSoatPUWDuB6ywWDGzofiXqItwJQR6LPQGliQrxatXtKNAr61ep/KWWm70231Eyz6bz6MujJZ3ijuKc4pNgrPqiJrz2I5K2XMmu5hEbqMZxYGZJaMKD/FlVH+64jyKrJ28+pkIcuKNglaX+fNqtTEcqNcf4Y3aRvZwLLxxOc3lNRGAgd7hmWcYD3o7P0iY/tmkRzrBW2gbwRVcSAIQ26yaJsP1lGCsp+Ie4hVwOapR8y4OSwqyLlUQlZ+oimkXF/wdIguk2CTU1WdTaq7M5XVG2BxsmjPcaWaji+ie3Y3BCnIMHDbxCoxRMatPScVqGgh6YxxNji1WKbGxhau7P6afE68bGKk/p1qyqu6nUOGrb/tOStBHl1e3M6O/dUB+jK+QEcudLro3yMSXMCLxAki+a+I24iNxGuqjLohP4yeFQSBb4ro8c4xRmqxqjIo/6i2wN1z8mV1Xx0jU3Y2/rU6L85hvM3TCwFWDscVFD3B+ZuNx3IFbdSqzeps8vzrDbAWlY1pIqexrG9ZcIyEqJs+fTdFgfeJeQb5e1NkyyxmPaVfbPCXwWFJmN8r/MJLJyU5/TBEBW1WxvUad5N00uXLh3R+D/AM+3lqJyp9nXiXSOD1nni6yOeNoeKK4kNileA0ycAJZh6wi7lC7C9OFXnRWah8rOluCPZ9fKWb33gZB3vpKpO8cBD479SMnPBvFg+s7gmxeBztuJ+uK4j3iSwkN4tbio0CE6mBsZkVjNulnTDvo40PX3+Qu6kdxybzqSV0nd1LV5nkVM3A4hjQfB4geGHTDM4TX52eaq5/dlFzGLOsNW9naNoqkhnm5P6g61MuHXfhfbLAahOll4wTLDmfzR4nc8wFO6a9lHN5lUdNAF7x10k/EJvn69zoxJ+VfZLIZMOpxCSxTPSSMXaKnR096+gAnxT9QPr7umdR4AjZni8DkWCD3Xgj4AcZeQOs7dXALVwjT9Y1avJIWpj+Kh0CLcb+OiK+8RdJ3VYCFsPuot/3PBX1kHDfPApNKMvurgjmkNLKTpFn91yNEeaNPUQCbeacU8U7xUbgE68S3qm40yZPbHpycy/jcS/tJ5PGMXKLe8LtXjouyckR/vPn6DjZuHx/Tp8SJ5SS30flvA+dGR2xrrBoc0oKFxTfEvFjrS9/qzzmmX+JpJsRu7pGXZOxccdLjnmAufqsjDr4B+C3geJ4bhoA+rSpuCuLTBI4ITB0s0TKlUnGkPYCMiE+Ia4lbiteIpaF/WXogrKMNZEdFuk88Hf+50nxIKfMoNtAPFdkMLBo8QzuF6sGL4phmiUyXoc6OfTOj9ChX2u6/Kid/2cq+0hksacdTFZlB/Yy+Q1YP6mTNv7nGxLRGYu67OG6wq6AhXN2YkXJ24I2RmmeYS0mKuMucSdxJXFtcZRYNfwAyw8+0upd2hOIm/gHOZmocUwRu3rDXyxRc8UGp33riox5FqhnxdPEq8W88PuYNr/7tqnb8LwlusB1QAV9WFI2mZvZVCzv2E9Xf23V7Ux4W3eviBNE3gFwqsh70YygX+DVGZfEf5kDd3QSxAtZNhOI2wEC6bzrJjpFwXMAK7B7TwKfjQxJD9dkuPqd8vV9GT9tx8w2gfplIV2/B/wA6xnPHAv8Q+JG4rsiz5dPb1mfs0QL41NPM099TDwDne6TuhIo1WI5ZSwkspCMri3UPcGNnSKxk2eX1wjYwjRVlWUNrhrRrs5Qhz+Gn05o8EivzCZkL6uSpD9+FsxRgz9PWvDtqzNGB7iMqICEuXtLV/6eriNd2r/sqZvHxbHiZiIL9iFiX/HP4rFiXrAhMUy2RLjW5YFu0t5WvEgk4BgnXiWymWQcE0inzZO9JDNY3EW0dZ1Tn/tEAuw+YjPhNteYHTI06geSsT49nEHeRJawhK6NDDRt7rk17QSLqNhAFJkFPT2huJ2ZiSylxDoiQdZNllnS9ULZuUvsCoEbPmWiBHkntbTFiYF3gXiCSD0MjivFKjHFM542cXii31pDNwRIgIkoCmu6zLG6+qcLJru4Era4sVgTiMWBiY+d5FbiKPFasQhos/Uzqk1JNj9QYW+R51P1c1EVlWI3WT9J/DBnLTx3Q1KA9agJ6bqFeIR3X1XyFc9wb6UJ/LPAn1v7ScHf/KD/XdF+3ukFMmqwq+4JlMCp4ufTU//9hwDtjyIL0/mitZNNx1vi7eKvxUvEd8Ss6O0Jmk0vKzbJyYqBgOFTu+mk1xvUbubWMXW0f23pEgTzLBeqscPzfE7Exy+Lb4j4kA0aZXOIfO4l4GXzxuaTH/+wxV3J6fmb6ApPFllDrhKvFv2NgW4bDubS/UT6fphIX+KwolfwupdOSw50AszxT6UJl1TO+7aLszV9vWA3DRdwmf6Fh2Xl9/oFMel5PXn0esfIWfaRSiCXxbbptOKV3Yk9h9VyOIDg8guny5WAIQqDlGn2G/EsdvfqOy2qQTF5Qzy9M2JkznUyt8aU7+HZGBohw8TFpHedOFk0v5yodFH470WeRYn62kXacCA3nRz7q/30ZXzOfjzi9NBdN0GXyY3gDTnYX6wa+6oCq+9XOSrby9NjrNXiaGVg9+3aAt0vLX4gUj5SnF2sRU9lsGghs3xtoe7fcWW8D3lwp4Stv31zKLZ5erwPnR1suPDD8JwdYbO1jfi4aH7kShDwmHiC2CYyd+cBY/8fIraeEHuLQ8RLxQki+UbmNYLyxcQ8oA6zwYloPWDz8J6IvY1TDI1wcshumSJrxUspgU/RedQyG3DdwNU5SdduOCwJPDDDqpZIuPoyPNQ3E2Qp2s2VT4/0UmRDcX4PrCSVbk6NXfCXMSaeVr7tKNuUni9Grqxsf9Fg55UVH3uCPby0nyRYBM/PuHzj35+4nCm6XvCN0hkbjZ2V/5K4j3hOhEzeLF52wzhLhGsmDzBH2bzChPlsghbl/mTK7jgJBCY/EE8UB8YIMgZWjykje7RXtoqXTksy573hhHbUddMahTXdfe04Jmh8QFxEpIw+Ru3+31c+Nn8stou1sLk577tufZwqg2NrjYb7RA/wGZBndqu4tpMco+uxYh+RzcNw8SHxCzEPhkh4DadwhK5jxcvEvcUlxG1EAvnPxQVEDjcYF+eKC4uNxr9V4Y2uUosD4trg+yItZjEb+GMWd3O2ZTbgan2hb9PX2/8oAXF6FJ5WpsksGyXg5fFgTfZ8Lz8quYKTpRELRQmEvK890Esp82ueE6x9Pb0Lv7YWnXjQk90uWqS0XF5o68+oHFaXliyLKLrtYu3LNpfyeBkp312sBXlW72G1hTH3TH7osAgXBbs9q5cJLQ/aJYxuq55g2TyBD17J4Dj/GX8ieTYZcbhSBXw6IEAZLzJ+fCyvG8Yb5QTdUZhNmRNF2mcBU5RcVN5AZbJpQJeAhWDIxjSbEPJPFwEbChZf+kT+nWI98+ZYZ2c9XbOijwSpGxIk5EGbhE133jyKTSrLvEV/eCZpYN28Q7T+c2UjsLVoQYCShTG3NN8SsWtBS5yxRVQwTPxQtPZMUvpQkbGcBMam6TCn1YsNZAB7H4lzJhj7uZND9ogEOSvis6m9k39T2t4pK6/qOrsMs7GhnRtbJeawuACLhchkjjOlmOvfPdm1Y2Qs+wQne7tlhGusB4oGWCOcj3l+B8Ran1EwTBd7zpenyFpxTyUYVFEgiEqaPN5TOfXxIiTJqXgmPKA7a+ePZiqZ8duoVrZyTRkLiS1O7OSy1llGgHWw6rN25Q2U2p1uXj2pNR32V4vww/gMLTtFMozD10XzHcEOCzvj+ntiFBiPI0XT4WT2ZpFdLMFaFK5UJvKb1BSepXt2/Glzmeljo0+NjbRbAsBnRGvvWKUv8+4fUvqvIhtRZF4Wa8e9snKBwA5bL4p5Fp8fOz102bzlQZuE0YOtEmDh22PEz1y/6TvPM208SSQXjpc0thkjbAqygPWetk0R7bmwfvcX40B/THazOKEc+dhjLsAmwWYcbKOD3N/ihLz8y5VGdrLYz8vPkiTInK9GkLWsW01e1O2myqTeD8TZTYAMGBdg+dHxu5IjOozCxso0W7dFCdTkjXby9U4WNWa75G3RAOsx52Oey6AUz/DS2/NjUYpbjDCztzhKRP4JcQ7RsKwST4mU/d4yI64slFZfUl21qixIvDjoch0sGg5VgvwvRHshuLLrYaGk7ArRb69uE1FGgPVn1WB9ZXHLg3YJo9tqAdYj6jPjKI5Jp6zdpXeG+Kw4SZwgPifGBWVbqgwf/1Y0zKMEuodbRsJ1G5XZ8z0hQS6uaBYVYINx0i4SSJo9xu0/Rb4IbCrOJtYD6rpX5BPNRjkNjZQ87SJgWETMgzYJW59aIcBaVP29x+vzu0rvJeL/MkE9Nh/+roDhJaRDQGJjjrmfeTQKBET2DMsIsKjjTGfzKm4ScL3KrO6fxMjh21OdHIEjm+o8YJ3Al/hipLitOL94gUhgl/buXSIZ2jjTumeNXkAFcdhCBV+JyN4idhN99NbNWJFyorc+YhK+o0JkeVGZDAOSPZAnwOopUywkvMz4157vz5VeU6Q8Dg+pwORfVXoPkWfVQ/Sxvm5+JlqQvKMrZNJ9S2Rioe6bxTjsqwKra784oZh86n/P6bNQXCHywt/k8mg7i8dJIu2hnoniEDEvjpUC+ifmVfTkxzsb43TNO8G2O91WC7A891WeZO5jHN3t1cT4fEmczcuLS86qAgI4xsmb4pxiPThPythiov92PYYidFlEsH1URFlS1ooqtEX4nCTBmLI25VMv7OoBFnOPzU/092IxaX1VcWH8QZrU8bFIsFUUBO8EgfaMLlOawxUfjHMrZ74tA4NkBJufiEnjYiGV23rDu3qW2F+kTfOIW4iPiNh6QVxVzIMfS/h5Ebv3i9TBM2QOmCquJSaBd/4jkfrX9wXNYWkDgEWQI0jkXxR/JbIAnyJOEsl/X2QRTwM6yN+YJhjKp3ugl/6157Raik+u9WRNx7/elKC/uMr+EaF/boyOvRxXuvLbdT3MpQnMGPhx6KkCC9rvjhNKyCfoO02cIPr9q03Tn8PF+cQiqDfA4sW0Nv2+QAPanf6BBXSbTWV/1xcCzmYDk/cHXqM4OWN+y4rtJWjPeWhWpRg5ewfHxpQXzWYOZ+E4oYCB+6RD/1hsmI/yok0K5p+khTSv3Y6SH+X6M7ymATvo/jNXRtBT5RcaAoxprq4jda0Xi8jAXaI9J/q4sGe0igAL86+J1LkLNwkgRhkhfi5aGy3o5/4V8QCRYCcvnpDCVp5Sd6WXEdkw+fmeyEzJ7XRHG94W8dPXsIamBVgofFd8QOQlNT2uvHSXiiyaaZhFAu0iemkOTbPVKuVMaObvtACrr2QHJnDZFKfxfFYVtxaZHDYUCbzi8IwKiPQ3Fwmw8oBPIvSL8bR0HkVPlhOGQeKxovnoZqVpzxJivTC7JxY0dIH0rI8rFrDR7vRDgFXAeTlULnV+XkpXguLXxdnFPPiThHnWn4rr5FH0ZOdW+ksRO3d4+fUmD5YBFqMjCxhig0J74J4F9FFpE81GVw2wDlUf/+36+ZKuy4tVgvGBT8eJjJsyQHAwTLTA5TmlbR6lzJ7hZkqXBTtwSdr8+3URqzC/Myfi893Fen09WjY+EgkywUIieWxKsuAaCeGbM2uFzWE0Oitw+EbiTuK64vxiVqwtQeokKOsKL1rWftcjlyfAqqeeIrpHS4nnOV7sn9PAAMnbhHRRTt1acYJ1G8s71hbWcV9PgEUwa7vZqwu2oV169CsEWAUdmFHtIOfnbXS9TOS0LS9Y5B4ReV6TxCw7X4nNBOZTG8csPPWCDdPxIrv+ITXGCCA5aY4D5ceIttieFieYIb9NMtavrjDv155g7e317wmle4hVYkMZN3/+sIKK9pXNaa6OV3VlLFQVYK3u6mGMdhc7AiurUt59MJf4sHgCNxkwj2Q+EXkebPZngj2kPAHWTAZy3vxO8tTJ6UVANg/0kpg9p9WyqTRMqs21jYWlCE6XEn0j0NpQLIozpGg+WqGokQi9Y53dEyPKkrJmU+F9TvdDXXuLRdAuJfoVAqwi3suus6bz8zm64nMm2SLg88QlIs8McuK/g5gVh0vQdPfMqhQjRx8uFyeKbREyaymPQDAKRymTHTxt+VIkAK0H1G/96ooBFj8aQf/uFucTq8SsMv6USH1Pi9xXAQIODkLeFxnX1GPPcDOly8SLMobtIWUaLWCLPl4vXphDlxM02v6myIZmJpjDGhFg0Xi+UVLntjO1ItwkeaCZA6yr1PBx4hSRlzAv5pDCwyJjgiPaNcQieFRK2ODEiOCmLBQJsNjt/UmkPQSOW4hF0S5F7IQAq6gHs+kxdr8QCSaOyKaSKLWOSu8U2ZVzzYprJcjzhuzsi2IJKf5dZGe9n7hxBNnsxgVYvM+U/UHsLdaLNhmwfnXFAAv/9BdZ46rG3qrAfLlRxZUtJvsLuzrom9VbdoB1orNNgNqR4J24TWQOBzuLbHqScKsK8cspUULmsEYEWAwG6psszhXVmJAX6YFmDbDWU2vvF9nt8ly3EouAsccihA0WJF62ZcSsIEibKqL/dFaljHJ5Aizasalou0sWqe0z1hMn1q4C+hUCrDgPlZf/pExx2pjnRx7Saidw65cm5JWzC+Z5fyXyybEo2PhgJ40EUVEYoEwW1LLQJkPWlq4aYJXlqzQ7/3S+vCVNsORyxoM9w7IDrP7O9jRdFy253VnNsbEaJc7jFDiNekykz73FKHxbmaxZyKxeK2BRWm1+Vfe7OcM360qjAjqfB5ZRk1kEFhcvFncVWUTA3uIdJHLiY8lvIx4iEqwd78iLNkFMwyoSsJfihTThCstPl+2fi7xst4tDxdFiQPN7gLlwPvFokcC4LHAq9lpGY0zo+zpZTtI+y6gXJcZ7yMlyGuLqGJOmGMo7zAPXqWbGVdrJSoc1sEDFL0mHuXtlcUfxfLGRIDbh3dtBHCgSaLHJoS20jc+kUaCc9e8V8ZkoARYDuEBUYYl57O4nitS1eYl2W8FUs5xg8TMh/MDraeLL4pEiYGczXqRsd5HPE0uKRcCufTvxDLF7RgMHSM7G8VEZdZLEuqlwQbGveIGI7YtE8lgE47CHCg4VV4oTKJDfLh3qDydYBZyXQ4XA+GEx6fnmMBdEazzQpnvGMQwnWDXO6SS3VZ5g4YLjRMbHSLGRGKzKPhfZzNsvdLyjND8n/qQY+elP+eA+kTYP5yYKP1MmJACqElvKOA2ZJLKABWT3QLMEWJupyRzhfioOFf3FaFfds6si6if6Z9A2CvupInZ1cFAJlbIrYZzGcb0S6shqol2CvDchwMrqsXS5RSTiL/Jr6P5tcbl01SBR0ANt0mMcQ9/3Bc11uBpzHH2JXVg7vIXlN6DqAKu3mvxHkdMrToUaAfr0oMiGns39+iJfZpgPXhNZ52YTo8Cp9wiRNveLEmhkHkd/O4t0ICCfB5olwKLVC4lzxTSfAVp1oB5TdZfNblfPmMhDgFXOI+Yz4AfiQ+L84jYik+mGYkB1HmiTacYxDAFWdX6u0nLVAVaVbU+yTb8qCeiIwBoFvq925M/HNKqfXb0eTnXi8FlcQcgPHmgSD7DAc4K+gTjB8Ue6jhQDggeCB1rPA3wW5OtL6WhkgFV644PB4IHggeCBnB6YKnk+8XKa/p54jfiRGBA8EDwQPFCqB0KAVao7g7HggeCBTuCBcJreCR5SaGLwQGf3AN8eA4IHggeCB4IHggeCB4IHggdK9EA4wSrRmcFU8EDwQPBA8EBLecD+nEsrdDocyOR8yiHAyumwIB48EDwQPBA80PIe6O08cIiusNXQs9U6XKS/ISIt4rWgEzwQPBA8EDzQyh6Y3MqdV9/Ht3j/M3U/nGBlclMQCh4IHggeCB4IHvjaA6sqxZ/6aLXfQOVvIPKnesaIASkeCAFWioOasJi/GjulCdsVmlSNB+wonj+QGRA8EDzQHB74Us14oDmaElrRrB4IAVazPpmZ2+X/dfRBMxeFuxbxQL8W6WfoZvBA8EDwQJfwQAiwOsdjHKtmXiQOEEeLAa3jgcXVVf7T62O6UJf5L5X4Q58BreOBFVunq6GnwQMzPOD/Z73BJ8EDwQPBA1V64GwZP7TKCoLtTuEB/g/ITzpFS0Mjgwfq8ED4LcI6nBdUgweCB3J54H5J8/9+BbSuByaq6yG4at3n31I9/392nyCMizbVWgAAAABJRU5ErkJggg==)\n", - "\n", - "Breaking this down step-by-step, we first start with a qubit in the ground state $|0⟩ = [1\\ 0]^T$, and rotate it around the x-axis by applying the gate\n", - "\n", - "$\\begin{split}R_x(\\phi_1) = e^{-i \\phi_1 \\sigma_x /2} =\n", - "\\begin{bmatrix}\n", - "\\cos \\frac{\\phi_1}{2} & -i \\sin \\frac{\\phi_1}{2}\n", - "\\\\\n", - "-i \\sin \\frac{\\phi_1}{2} & \\cos \\frac{\\phi_1}{2}\n", - "\\end{bmatrix},\n", - "\\end{split}$\n", - "\n", - "and then around the y-axis via the gate\n", - "\n", - "$\\begin{split}R_y(\\phi_2) = e^{-i \\phi_2 \\sigma_y/2} =\n", - "\\begin{bmatrix} \\cos \\frac{\\phi_2}{2} & - \\sin \\frac{\\phi_2}{2}\n", - "\\\\\n", - "\\sin \\frac{\\phi_2}{2} & \\cos \\frac{\\phi_2}{2}\n", - "\\end{bmatrix}.\\end{split}$\n", - "\n", - "After these operations the qubit is now in the state\n", - "\n", - "$| \\psi \\rangle = R_y(\\phi_2) R_x(\\phi_1) | 0 \\rangle.$\n", - "\n", - "Finally, we measure the expectation value $⟨ψ∣σ_z∣ψ⟩$ of the Pauli-Z operator\n", - "\n", - "Using the above to calculate the exact expectation value, we find that\n", - "\n", - "$\\begin{split}\\sigma_z =\n", - "\\begin{bmatrix} 1 & 0\n", - "\\\\\n", - "0 & -1\n", - "\\end{bmatrix}.\\end{split}$\n", - "\n", - "Depending on the circuit parameters $ϕ_1$ and $ϕ_2$, the output expectation lies between 1 (if $|ψ⟩ = |0⟩) and -1 (if |ψ⟩ = |1⟩).\n", - "\n", - "$\\langle \\psi \\mid \\sigma_z \\mid \\psi \\rangle\n", - " = \\langle 0 \\mid R_x(\\phi_1)^\\dagger R_y(\\phi_2)^\\dagger \\sigma_z R_y(\\phi_2) R_x(\\phi_1) \\mid 0 \\rangle\n", - " = \\cos(\\phi_1)\\cos(\\phi_2).$\n", - "\n", - "Let's see how we can easily implement and optimize this circuit using TorchQuantum.\n", - "\n" - ], - "metadata": { - "id": "oFuPFpXhTFAR" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Importing TorchQuantum" - ], - "metadata": { - "id": "5sge9dfJTer6" - } - }, - { - "cell_type": "markdown", - "source": [ - "The first thing we need to do is install and import TorchQuantum. To utilize all of TorchQuantum's features, install it from source." - ], - "metadata": { - "id": "4qF2oH1MTmHb" - } - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "id": "omF7GkuHKaPp", - "colab": { - "base_uri": "https://localhost:8080/" - }, - "outputId": "2c200ab7-f939-4193-d872-01c0f98b3ee6" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Cloning into 'torchquantum'...\n", - "remote: Enumerating objects: 13551, done.\u001b[K\n", - "remote: Counting objects: 100% (1822/1822), done.\u001b[K\n", - "remote: Compressing objects: 100% (758/758), done.\u001b[K\n", - "remote: Total 13551 (delta 1085), reused 1640 (delta 980), pack-reused 11729\u001b[K\n", - "Receiving objects: 100% (13551/13551), 104.07 MiB | 21.17 MiB/s, done.\n", - "Resolving deltas: 100% (7442/7442), done.\n", - "Obtaining file:///content/torchquantum\n", - " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", - "Requirement already satisfied: numpy>=1.19.2 in /usr/local/lib/python3.10/dist-packages (from torchquantum==0.1.7) (1.22.4)\n", - 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] - } - ], - "source": [ - "!git clone https://github.com/mit-han-lab/torchquantum.git\n", - "!cd torchquantum && pip install --editable ." - ] - }, - { - "cell_type": "markdown", - "source": [ - "> **Note: To be able to install TorchQuantum on Colab, you must restart your runtime before continuing!**\n", - "\n", - "After installing from source (and restarting if using Colab!), you can import TorchQuantum." - ], - "metadata": { - "id": "Ckw9S9C0TzuH" - } - }, - { - "cell_type": "code", - "source": [ - "import torchquantum as tq" - ], - "metadata": { - "id": "vhmIuM9Wc70Z" - }, - "execution_count": 1, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "## Creating a device" - ], - "metadata": { - "id": "PxW4zls2Y3QM" - } - }, - { - "cell_type": "markdown", - "source": [ - "Before we can construct our quantum node, we need to initialize a device.\n", - "\n", - "> **Definition**\n", - ">\n", - "> Any computational object that can apply quantum operations and return a measurement value is called a quantum **device**.\n", - "\n", - "> *Devices are loaded in PennyLane via the class [QuantumDevice()](https://github.com/mit-han-lab/torchquantum/blob/main/torchquantum/devices.py#L13)*\n" - ], - "metadata": { - "id": "Y08Q6dMKY6HC" - } - }, - { - "cell_type": "markdown", - "source": [ - "For this tutorial, we are using the qubit model, so let's initialize the 'default' device provided by TorchQuantum." - ], - "metadata": { - "id": "0bgRmzQLeOtt" - } - }, - { - "cell_type": "code", - "source": [ - "qdev = tq.QuantumDevice(n_wires=1, device_name=\"default\", bsz=1, device=\"cuda\", record_op=True)" - ], - "metadata": { - "id": "NUrCxUQvc_3i" - }, - "execution_count": 4, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "For all devices, [QuantumDevice()](https://github.com/mit-han-lab/torchquantum/blob/main/torchquantum/devices.py#L13) accepts the following arguments:\n", - "\n", - "* n_wires: number of qubits to initialize the device with\n", - "* device_name: name of the quantum device to be loaded\n", - "* bsz: batch size of the quantum state\n", - "* device: which classical computing device to use, 'cpu' or 'cuda' (similar to the device option in PyTorch)\n", - "* record_op: whether to record the operations on the quantum device and then they can be used to construct a static computation graph\n", - "\n", - "Here, as we only require a single qubit for this example, we set wires=1." - ], - "metadata": { - "id": "uJOZRR--dQ0n" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Constructing the Circuit" - ], - "metadata": { - "id": "n2bS-rw1em0a" - } - }, - { - "cell_type": "markdown", - "source": [ - "Now that we have initialized our device, we can begin to construct the circuit. In TorchQuantum, there are multiple ways to construct a circuit, and we can explore a few of them." - ], - "metadata": { - "id": "9W-rBf2CfCQd" - } - }, - { - "cell_type": "code", - "source": [ - "# specify parameters\n", - "params = [0.54, 0.12]\n", - "\n", - "# create circuit\n", - "qdev.rx(params=params[0], wires=0)\n", - "qdev.ry(params=params[1], wires=0)" - ], - "metadata": { - "id": "qcmWA-o4hBqa" - }, - "execution_count": 5, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "This method calls the gates directly from the QuantumDevice. For the rotations, we can specify which wire it belongs to (zero-indexed) and a parameter theta for the amount of rotation. However, the rotation gates also have other parameters.\n", - "\n", - "* wires: which qibits the gate is applied to\n", - "* theta: the amount of rotation\n", - "* n_wires: number of qubits the gate is applied to\n", - "* static: whether use static mode computation\n", - "* parent_graph: Parent QuantumGraph of current operation\n", - "* inverse: whether inverse the gate\n", - "* comp_method: option to use 'bmm' or 'einsum' method to perform matrix vector multiplication" - ], - "metadata": { - "id": "RQhCOnNAhm7q" - } - }, - { - "cell_type": "markdown", - "source": [ - "To get the following expected value, we can use two different functions from torchquantum's measurement module." - ], - "metadata": { - "id": "zY5lSe3Nl-78" - } - }, - { - "cell_type": "code", - "source": [ - "from torchquantum.measurement import expval_joint_analytical, expval_joint_sampling" - ], - "metadata": { - "id": "3IHmc_ILirVI" - }, - "execution_count": 6, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "* `expval_joint_analytical` will compute the expectation value of a joint observable in analytical way, assuming the statevector is available. This can only be run on a classical simulator, not real quantum hardware.\n", - "\n", - "* `expval_joint_analytical` will compute the expectation value of a joint observable from sampling the measurement bistring. This can be run on both a classical simulation and real quantum hardware. Since this is sampling the measurements, it requires a parameters for the number of shots, `n_shots`.\n", - "\n" - ], - "metadata": { - "id": "h_05PJxAjIMk" - } - }, - { - "cell_type": "code", - "source": [ - "exp_a = expval_joint_analytical(qdev, 'Z')\n", - "exp_s = expval_joint_sampling(qdev, 'Z', n_shots=1024)\n", - "\n", - "print(exp_a, exp_s)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "3TIwrhn1kD-a", - "outputId": "0af08a9b-5c1c-475b-9845-3aa2331ed59e" - }, - "execution_count": 7, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "tensor([0.8515]) tensor([0.8184])\n" - ] - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "The two numbers are about the same, and if we increase the number of shots for the joint sampling, its expected value should approach the same value as the analytical." - ], - "metadata": { - "id": "9rUMiTshkuYk" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Calculating quantum gradients" - ], - "metadata": { - "id": "WyHxuz4_l0lB" - } - }, - { - "cell_type": "markdown", - "source": [ - "From the expected values output, notice that the analytical expected value has an automatically-calculated gradient which can be used when constructing quantum machine learning models. This is because TorchQuantum automatically calculates the gradients. Let's find the gradient of each individual gate.\n", - "\n", - "To do so, we can create the circuit slightly differently, saving each operation as a variable then adding it to the circuit. We can then once again get the expected value with `expval_joint_analytical`." - ], - "metadata": { - "id": "GNlFHcRDnqVl" - } - }, - { - "cell_type": "code", - "source": [ - "qdev = tq.QuantumDevice(n_wires=1)\n", - "\n", - "op1 = tq.RX(has_params=True, trainable=True, init_params=0.54)\n", - "op1(qdev, wires=0)\n", - "\n", - "op2 = tq.RY(has_params=True, trainable=True, init_params=0.12)\n", - "op2(qdev, wires=0)\n", - "\n", - "\n", - "expval = expval_joint_analytical(qdev, 'Z')" - ], - "metadata": { - "id": "m_n2ROPNoFzn" - }, - "execution_count": 8, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "We can then call `.backward()` on the expected value, just like in PyTorch. Afterwards, we can see the gradient of each operation under the `params` option." - ], - "metadata": { - "id": "znstxaD3pFdK" - } - }, - { - "cell_type": "code", - "source": [ - "expval[0].backward()\n", - "\n", - "# calculate the gradients for each operation!\n", - "print(op1.params.grad, op2.params.grad)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "d6ehHkuSo5Oq", - "outputId": "d3610b9a-48b2-4797-c3c9-818db8ce0687" - }, - "execution_count": 9, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "tensor([[-0.5104]]) tensor([[-0.1027]])\n" - ] - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "## Optimization" - ], - "metadata": { - "id": "R8PqqWa5pbzU" - } - }, - { - "cell_type": "markdown", - "source": [ - "Next, let's make use of PyTorch's optimizers to optimize the two circuit parameters $\\phi_1$ and $\\phi_2$ such that the qubit, originally in state |0⟩, is rotated to be in state |1⟩. This is equivalent to measuring a Pauli-Z expectation value of -1, since the state |1⟩ is an eigenvector of the Pauli-Z matrix with eigenvalue λ=−1." - ], - "metadata": { - "id": "q4I7DC2Uphzs" - } - }, - { - "cell_type": "markdown", - "source": [ - "To construct this circuit, we can use a class similar to a PyTorch module! We can begin by importing torch." - ], - "metadata": { - "id": "G3h9LjzJqf0k" - } - }, - { - "cell_type": "code", - "source": [ - "import torch" - ], - "metadata": { - "id": "X3LeotDeqoIh" - }, - "execution_count": 38, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "We can next create the class extending the PyTorch module and add our gates in a similar fashion as the previous steps." - ], - "metadata": { - "id": "LbN7Fo67qpGI" - } - }, - { - "cell_type": "code", - "source": [ - "import torchquantum as tq\n", - "import torchquantum.functional as tqf\n", - "\n", - "class OptimizationModel(torch.nn.Module):\n", - " def __init__(self):\n", - " super().__init__()\n", - " self.rx0 = tq.RX(has_params=True, trainable=True, init_params=0.011)\n", - " self.ry0 = tq.RY(has_params=True, trainable=True, init_params=0.012)\n", - "\n", - " def forward(self):\n", - " # create a quantum device to run the gates\n", - " qdev = tq.QuantumDevice(n_wires=1)\n", - "\n", - " # add some trainable gates (need to instantiate ahead of time)\n", - " self.rx0(qdev, wires=0)\n", - " self.ry0(qdev, wires=0)\n", - "\n", - " return expval_joint_analytical(qdev, 'Z')" - ], - "metadata": { - "id": "gxve5-2SpdDA" - }, - "execution_count": 39, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "To optimize the rotation, we need to define a cost function. By minimizing the cost function, the optimizer will determine the values of the circuit parameters that produce the desired outcome.\n", - "\n", - "In this case, our desired outcome is a Pauli-Z expectation value of −1. Since we know that the Pauli-Z expectation is bound between [−1, 1], we can define our cost directly as the output of the circuit.\n", - "\n", - "Similar to PyTorch, we can create a train function to compute the gradients of the loss function and have the optimizer perform an optimization step." - ], - "metadata": { - "id": "Ifi5cH_eq_zW" - } - }, - { - "cell_type": "code", - "source": [ - "def train(model, device, optimizer):\n", - " targets = 0\n", - "\n", - " outputs = model()\n", - " loss = outputs\n", - " optimizer.zero_grad()\n", - " loss.backward()\n", - " optimizer.step()\n", - "\n", - " return loss.item()" - ], - "metadata": { - "id": "H5xxXrWUrAO3" - }, - "execution_count": 53, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Finally, we can run the model. We can import PyTorch's gradient descent module and use it to optimize our model." - ], - "metadata": { - "id": "dn0131aKrjQ8" - } - }, - { - "cell_type": "code", - "source": [ - "def main():\n", - " seed = 0\n", - " torch.manual_seed(seed)\n", - "\n", - " use_cuda = torch.cuda.is_available()\n", - " device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n", - "\n", - " model = OptimizationModel()\n", - " n_epochs = 200\n", - " optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n", - "\n", - " for epoch in range(1, n_epochs + 1):\n", - " # train\n", - " loss = train(model, device, optimizer)\n", - " output = (model.rx0.params[0].item(), model.ry0.params[0].item())\n", - " print(f\"Epoch {epoch}: {output}\")\n", - "\n", - " if epoch % 10 == 0:\n", - " print(f\"Loss after step {epoch}: {loss}\")" - ], - "metadata": { - "id": "4WJ7yL5SrjkA" - }, - "execution_count": 54, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Finally, we can call the main function and run the entire sequence!" - ], - "metadata": { - "id": "eY5PvCqhr1ZF" - } - }, - { - "cell_type": "code", - "source": [ - "main()" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "_hCBPtMvr4wB", - "outputId": "2091f42b-7263-4e5d-d2f7-eab8b07bbe7f" - }, - "execution_count": 55, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Epoch 1: (0.012099898420274258, 0.013199898414313793)\n", - "Epoch 2: (0.013309753499925137, 0.014519752934575081)\n", - "Epoch 3: (0.014640549197793007, 0.015971548855304718)\n", - "Epoch 4: (0.01610436476767063, 0.017568465322256088)\n", - "Epoch 5: (0.01771448366343975, 0.01932499371469021)\n", - "Epoch 6: (0.019485509023070335, 0.02125706896185875)\n", - "Epoch 7: (0.021433496847748756, 0.023382212966680527)\n", - "Epoch 8: (0.023576095700263977, 0.02571968361735344)\n", - "Epoch 9: (0.025932706892490387, 0.028290653601288795)\n", - "Epoch 10: (0.028524650260806084, 0.03111839108169079)\n", - "Loss after step 10: 0.9992638230323792\n", - "Epoch 11: (0.031375348567962646, 0.03422846272587776)\n", - "Epoch 12: (0.0345105305314064, 0.03764895722270012)\n", - "Epoch 13: (0.037958454340696335, 0.041410721838474274)\n", - "Epoch 14: (0.04175013676285744, 0.04554762691259384)\n", - "Epoch 15: (0.04591960832476616, 0.050096847116947174)\n", - "Epoch 16: (0.05050419643521309, 0.055099159479141235)\n", - "Epoch 17: (0.05554480850696564, 0.06059926748275757)\n", - "Epoch 18: (0.06108624115586281, 0.06664614379405975)\n", - "Epoch 19: (0.06717751175165176, 0.07329340279102325)\n", - "Epoch 20: (0.07387219369411469, 0.08059966564178467)\n", - "Loss after step 20: 0.9950657486915588\n", - "Epoch 21: (0.08122873306274414, 0.08862894773483276)\n", - "Epoch 22: (0.08931083232164383, 0.09745106101036072)\n", - "Epoch 23: (0.09818772971630096, 0.10714197158813477)\n", - "Epoch 24: (0.10793451964855194, 0.11778417229652405)\n", - "Epoch 25: (0.11863239109516144, 0.12946699559688568)\n", - "Epoch 26: (0.13036876916885376, 0.14228680729866028)\n", - "Epoch 27: (0.14323736727237701, 0.15634718537330627)\n", - "Epoch 28: (0.15733805298805237, 0.17175881564617157)\n", - "Epoch 29: (0.172776460647583, 0.18863925337791443)\n", - "Epoch 30: (0.18966329097747803, 0.20711229741573334)\n", - "Loss after step 30: 0.9676356315612793\n", - "Epoch 31: (0.20811320841312408, 0.2273070216178894)\n", - "Epoch 32: (0.2282431572675705, 0.2493562251329422)\n", - "Epoch 33: (0.2501700222492218, 0.27339422702789307)\n", - "Epoch 34: (0.2740074098110199, 0.29955384135246277)\n", - "Epoch 35: (0.2998615801334381, 0.32796236872673035)\n", - "Epoch 36: (0.32782599329948425, 0.35873648524284363)\n", - "Epoch 37: (0.3579748272895813, 0.39197587966918945)\n", - "Epoch 38: (0.3903552293777466, 0.427755743265152)\n", - "Epoch 39: (0.42497843503952026, 0.46611812710762024)\n", - "Epoch 40: (0.4618101119995117, 0.5070626139640808)\n", - "Loss after step 40: 0.8138567805290222\n", - "Epoch 41: (0.5007606744766235, 0.5505368709564209)\n", - "Epoch 42: (0.5416762828826904, 0.5964280366897583)\n", - "Epoch 43: (0.5843320488929749, 0.6445562839508057)\n", - "Epoch 44: (0.6284285187721252, 0.6946715116500854)\n", - "Epoch 45: (0.6735928058624268, 0.7464552521705627)\n", - "Epoch 46: (0.7193858623504639, 0.7995281219482422)\n", - "Epoch 47: (0.7653157711029053, 0.8534636497497559)\n", - "Epoch 48: (0.8108565211296082, 0.9078077673912048)\n", - "Epoch 49: (0.8554709553718567, 0.9621021151542664)\n", - "Epoch 50: (0.8986347317695618, 1.0159088373184204)\n", - "Loss after step 50: 0.3750203549861908\n", - "Epoch 51: (0.9398593902587891, 1.0688340663909912)\n", - "Epoch 52: (0.9787107706069946, 1.1205471754074097)\n", - "Epoch 53: (1.0148218870162964, 1.1707944869995117)\n", - "Epoch 54: (1.0478986501693726, 1.2194054126739502)\n", - "Epoch 55: (1.0777196884155273, 1.2662931680679321)\n", - "Epoch 56: (1.1041301488876343, 1.311449408531189)\n", - "Epoch 57: (1.127032995223999, 1.354935884475708)\n", - "Epoch 58: (1.1463772058486938, 1.3968735933303833)\n", - "Epoch 59: (1.1621465682983398, 1.4374314546585083)\n", - "Epoch 60: (1.1743487119674683, 1.4768157005310059)\n", - "Loss after step 60: 0.052838265895843506\n", - "Epoch 61: (1.1830050945281982, 1.5152597427368164)\n", - "Epoch 62: (1.1881437301635742, 1.553015947341919)\n", - "Epoch 63: (1.1897931098937988, 1.590348243713379)\n", - "Epoch 64: (1.1879782676696777, 1.6275262832641602)\n", - "Epoch 65: (1.1827187538146973, 1.6648198366165161)\n", - "Epoch 66: (1.1740283966064453, 1.702493667602539)\n", - "Epoch 67: (1.1619168519973755, 1.7408030033111572)\n", - "Epoch 68: (1.146392583847046, 1.7799879312515259)\n", - "Epoch 69: (1.1274679899215698, 1.820267915725708)\n", - "Epoch 70: (1.1051654815673828, 1.8618348836898804)\n", - "Loss after step 70: -0.10590392351150513\n", - "Epoch 71: (1.0795255899429321, 1.9048453569412231)\n", - "Epoch 72: (1.0506160259246826, 1.9494123458862305)\n", - "Epoch 73: (1.018541693687439, 1.9955958127975464)\n", - "Epoch 74: (0.9834545850753784, 2.043394088745117)\n", - "Epoch 75: (0.9455628991127014, 2.0927350521087646)\n", - "Epoch 76: (0.9051381945610046, 2.1434707641601562)\n", - "Epoch 77: (0.8625186085700989, 2.1953752040863037)\n", - "Epoch 78: (0.8181073665618896, 2.2481465339660645)\n", - "Epoch 79: (0.7723652124404907, 2.30141544342041)\n", - "Epoch 80: (0.7257967591285706, 2.354759931564331)\n", - "Loss after step 80: -0.4779837727546692\n", - "Epoch 81: (0.6789312362670898, 2.4077253341674805)\n", - "Epoch 82: (0.6322994232177734, 2.459847927093506)\n", - "Epoch 83: (0.5864096879959106, 2.5106801986694336)\n", - "Epoch 84: (0.5417252779006958, 2.5598134994506836)\n", - "Epoch 85: (0.4986463487148285, 2.6068966388702393)\n", - "Epoch 86: (0.4574976861476898, 2.6516494750976562)\n", - "Epoch 87: (0.4185234606266022, 2.6938676834106445)\n", - "Epoch 88: (0.38188809156417847, 2.7334227561950684)\n", - "Epoch 89: (0.34768232703208923, 2.770256519317627)\n", - "Epoch 90: (0.31593260169029236, 2.8043713569641113)\n", - "Loss after step 90: -0.876086413860321\n", - "Epoch 91: (0.28661224246025085, 2.835820436477661)\n", - "Epoch 92: (0.25965315103530884, 2.8646953105926514)\n", - "Epoch 93: (0.23495660722255707, 2.891116142272949)\n", - "Epoch 94: (0.21240299940109253, 2.915221691131592)\n", - "Epoch 95: (0.1918598860502243, 2.937161445617676)\n", - "Epoch 96: (0.1731884628534317, 2.957089900970459)\n", - "Epoch 97: (0.156248539686203, 2.97516131401062)\n", - "Epoch 98: (0.14090220630168915, 2.991525888442993)\n", - "Epoch 99: (0.12701639533042908, 3.0063281059265137)\n", - "Epoch 100: (0.11446458846330643, 3.019704818725586)\n", - "Loss after step 100: -0.9828835129737854\n", - "Epoch 101: (0.1031278446316719, 3.0317838191986084)\n", - "Epoch 102: (0.09289533644914627, 3.042684316635132)\n", - "Epoch 103: (0.08366449177265167, 3.052516460418701)\n", - "Epoch 104: (0.07534093409776688, 3.0613811016082764)\n", - "Epoch 105: (0.0678381696343422, 3.069370985031128)\n", - "Epoch 106: (0.06107722595334053, 3.0765702724456787)\n", - "Epoch 107: (0.054986197501420975, 3.0830557346343994)\n", - "Epoch 108: (0.0494997613132, 3.088897228240967)\n", - "Epoch 109: (0.04455867409706116, 3.0941579341888428)\n", - "Epoch 110: (0.040109291672706604, 3.0988948345184326)\n", - "Loss after step 110: -0.997883677482605\n", - "Epoch 111: (0.03610309213399887, 3.1031599044799805)\n", - "Epoch 112: (0.03249623253941536, 3.106999635696411)\n", - "Epoch 113: (0.029249126091599464, 3.1104564666748047)\n", - "Epoch 114: (0.026326047256588936, 3.1135683059692383)\n", - "Epoch 115: (0.023694779723882675, 3.1163694858551025)\n", - "Epoch 116: (0.021326277405023575, 3.1188907623291016)\n", - "Epoch 117: (0.019194360822439194, 3.1211602687835693)\n", - "Epoch 118: (0.01727544330060482, 3.1232030391693115)\n", - "Epoch 119: (0.015548276714980602, 3.1250417232513428)\n", - "Epoch 120: (0.013993724249303341, 3.1266965866088867)\n", - "Loss after step 120: -0.9997422099113464\n", - "Epoch 121: (0.012594552710652351, 3.128185987472534)\n", - "Epoch 122: (0.011335243470966816, 3.1295266151428223)\n", - "Epoch 123: (0.010201825760304928, 3.130733013153076)\n", - "Epoch 124: (0.00918172113597393, 3.131819009780884)\n", - "Epoch 125: (0.008263605646789074, 3.132796287536621)\n", - "Epoch 126: (0.0074372864328324795, 3.1336758136749268)\n", - "Epoch 127: (0.006693588104099035, 3.134467363357544)\n", - "Epoch 128: (0.006024251226335764, 3.1351797580718994)\n", - "Epoch 129: (0.005421841982752085, 3.1358211040496826)\n", - "Epoch 130: (0.004879669286310673, 3.1363983154296875)\n", - "Loss after step 130: -0.9999685883522034\n", - "Epoch 131: (0.004391710739582777, 3.13691782951355)\n", - "Epoch 132: (0.0039525460451841354, 3.137385368347168)\n", - "Epoch 133: (0.0035572960041463375, 3.1378061771392822)\n", - "Epoch 134: (0.003201569663360715, 3.1381847858428955)\n", - "Epoch 135: (0.0028814151883125305, 3.1385254859924316)\n", - "Epoch 136: (0.0025932753924280405, 3.1388320922851562)\n", - "Epoch 137: (0.002333949087187648, 3.139108180999756)\n", - "Epoch 138: (0.002100554993376136, 3.1393566131591797)\n", - "Epoch 139: (0.0018905001925304532, 3.139580249786377)\n", - "Epoch 140: (0.0017014506738632917, 3.1397814750671387)\n", - "Loss after step 140: -0.9999963045120239\n", - "Epoch 141: (0.001531305955722928, 3.139962673187256)\n", - "Epoch 142: (0.0013781756861135364, 3.1401257514953613)\n", - "Epoch 143: (0.0012403583386912942, 3.140272378921509)\n", - "Epoch 144: (0.0011163227027282119, 3.140404462814331)\n", - "Epoch 145: (0.0010046905372291803, 3.1405231952667236)\n", - "Epoch 146: (0.0009042215533554554, 3.1406302452087402)\n", - "Epoch 147: (0.0008137994445860386, 3.1407265663146973)\n", - "Epoch 148: (0.0007324195466935635, 3.140813112258911)\n", - "Epoch 149: (0.0006591776036657393, 3.1408910751342773)\n", - "Epoch 150: (0.0005932598724029958, 3.140961170196533)\n", - "Loss after step 150: -0.9999995231628418\n", - "Epoch 151: (0.0005339339259080589, 3.141024351119995)\n", - "Epoch 152: (0.00048054056242108345, 3.1410810947418213)\n", - "Epoch 153: (0.000432486500358209, 3.141132354736328)\n", - "Epoch 154: (0.00038923785905353725, 3.1411783695220947)\n", - "Epoch 155: (0.00035031407605856657, 3.1412198543548584)\n", - "Epoch 156: (0.0003152826684527099, 3.1412570476531982)\n", - "Epoch 157: (0.0002837544016074389, 3.1412906646728516)\n", - "Epoch 158: (0.0002553789527155459, 3.1413209438323975)\n", - "Epoch 159: (0.00022984105453360826, 3.141348123550415)\n", - "Epoch 160: (0.00020685694471467286, 3.1413726806640625)\n", - "Loss after step 160: -1.0\n", - "Epoch 161: (0.0001861712516983971, 3.14139461517334)\n", - "Epoch 162: (0.0001675541279837489, 3.1414144039154053)\n", - "Epoch 163: (0.00015079871809575707, 3.141432285308838)\n", - "Epoch 164: (0.00013571884483098984, 3.1414482593536377)\n", - "Epoch 165: (0.0001221469574375078, 3.141462802886963)\n", - "Epoch 166: (0.00010993226169375703, 3.1414756774902344)\n", - "Epoch 167: (9.893903188640252e-05, 3.1414873600006104)\n", - "Epoch 168: (8.904512651497498e-05, 3.141497850418091)\n", - "Epoch 169: (8.014061313588172e-05, 3.141507387161255)\n", - "Epoch 170: (7.212655327748507e-05, 3.1415159702301025)\n", - "Loss after step 170: -1.0\n", - "Epoch 171: (6.491389649454504e-05, 3.141523599624634)\n", - "Epoch 172: (5.8422505389899015e-05, 3.1415305137634277)\n", - "Epoch 173: (5.258025339571759e-05, 3.1415367126464844)\n", - "Epoch 174: (4.732222805614583e-05, 3.1415421962738037)\n", - "Epoch 175: (4.2590003431541845e-05, 3.141547203063965)\n", - "Epoch 176: (3.833100345218554e-05, 3.1415517330169678)\n", - "Epoch 177: (3.4497901651775464e-05, 3.1415557861328125)\n", - "Epoch 178: (3.10481118503958e-05, 3.141559362411499)\n", - "Epoch 179: (2.794330066535622e-05, 3.1415627002716064)\n", - "Epoch 180: (2.5148970962618478e-05, 3.1415657997131348)\n", - "Loss after step 180: -1.0\n", - "Epoch 181: (2.263407441205345e-05, 3.141568422317505)\n", - "Epoch 182: (2.0370667698443867e-05, 3.141570806503296)\n", - "Epoch 183: (1.83336014742963e-05, 3.141572952270508)\n", - "Epoch 184: (1.6500242054462433e-05, 3.1415748596191406)\n", - "Epoch 185: (1.485021766711725e-05, 3.1415765285491943)\n", - "Epoch 186: (1.3365195627557114e-05, 3.141578197479248)\n", - "Epoch 187: (1.2028675882902462e-05, 3.1415796279907227)\n", - "Epoch 188: (1.0825808203662746e-05, 3.141580820083618)\n", - "Epoch 189: (9.743227565195411e-06, 3.1415820121765137)\n", - "Epoch 190: (8.76890499057481e-06, 3.14158296585083)\n", - "Loss after step 190: -1.0\n", - "Epoch 191: (7.89201476436574e-06, 3.1415839195251465)\n", - "Epoch 192: (7.1028134698281065e-06, 3.141584873199463)\n", - "Epoch 193: (6.392532213794766e-06, 3.1415855884552)\n", - "Epoch 194: (5.753278855991084e-06, 3.1415863037109375)\n", - "Epoch 195: (5.177951152290916e-06, 3.141587018966675)\n", - "Epoch 196: (4.660155809688149e-06, 3.141587495803833)\n", - "Epoch 197: (4.194140274194069e-06, 3.141587972640991)\n", - "Epoch 198: (3.7747263377241325e-06, 3.1415884494781494)\n", - "Epoch 199: (3.3972537494264543e-06, 3.1415889263153076)\n", - "Epoch 200: (3.057528374483809e-06, 3.141589403152466)\n", - "Loss after step 200: -1.0\n" - ] - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "We can see that the optimization converges after approximately 160 steps.\n", - "\n", - "Substituting this into the theoretical result $⟨ψ∣σ_z∣ψ⟩ = \\cos ϕ_1 \\cos ϕ_2$, we can verify that this is indeed one possible value of the circuit parameters that produces $⟨ψ∣σ_z∣ψ⟩ = −1$, resulting in the qubit being rotated to the state |1⟩.\n", - "\n" - ], - "metadata": { - "id": "GpzzV6kyr_Z1" - } + { + "cell_type": "markdown", + "source": [ + "> **Note: To be able to install TorchQuantum on Colab, you must restart your runtime before continuing!**\n", + "\n", + "After installing from source (and restarting if using Colab!), you can import TorchQuantum." + ], + "metadata": { + "id": "Ckw9S9C0TzuH" + } + }, + { + "cell_type": "code", + "source": [ + "import torchquantum as tq" + ], + "metadata": { + "id": "vhmIuM9Wc70Z" + }, + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "## Creating a device" + ], + "metadata": { + "id": "PxW4zls2Y3QM" + } + }, + { + "cell_type": "markdown", + "source": [ + "Before we can construct our quantum node, we need to initialize a device.\n", + "\n", + "> **Definition**\n", + ">\n", + "> Any computational object that can apply quantum operations and return a measurement value is called a quantum **device**.\n", + "\n", + "> *Devices are loaded in PennyLane via the class [QuantumDevice()](https://github.com/mit-han-lab/torchquantum/blob/main/torchquantum/devices.py#L13)*\n" + ], + "metadata": { + "id": "Y08Q6dMKY6HC" + } + }, + { + "cell_type": "markdown", + "source": [ + "For this tutorial, we are using the qubit model, so let's initialize the 'default' device provided by TorchQuantum." + ], + "metadata": { + "id": "0bgRmzQLeOtt" + } + }, + { + "cell_type": "code", + "source": [ + "qdev = tq.QuantumDevice(\n", + " n_wires=1, device_name=\"default\", bsz=1, device=\"cuda\", record_op=True\n", + ")" + ], + "metadata": { + "id": "NUrCxUQvc_3i" + }, + "execution_count": 4, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "For all devices, [QuantumDevice()](https://github.com/mit-han-lab/torchquantum/blob/main/torchquantum/devices.py#L13) accepts the following arguments:\n", + "\n", + "* n_wires: number of qubits to initialize the device with\n", + "* device_name: name of the quantum device to be loaded\n", + "* bsz: batch size of the quantum state\n", + "* device: which classical computing device to use, 'cpu' or 'cuda' (similar to the device option in PyTorch)\n", + "* record_op: whether to record the operations on the quantum device and then they can be used to construct a static computation graph\n", + "\n", + "Here, as we only require a single qubit for this example, we set wires=1." + ], + "metadata": { + "id": "uJOZRR--dQ0n" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Constructing the Circuit" + ], + "metadata": { + "id": "n2bS-rw1em0a" + } + }, + { + "cell_type": "markdown", + "source": [ + "Now that we have initialized our device, we can begin to construct the circuit. In TorchQuantum, there are multiple ways to construct a circuit, and we can explore a few of them." + ], + "metadata": { + "id": "9W-rBf2CfCQd" + } + }, + { + "cell_type": "code", + "source": [ + "# specify parameters\n", + "params = [0.54, 0.12]\n", + "\n", + "# create circuit\n", + "qdev.rx(params=params[0], wires=0)\n", + "qdev.ry(params=params[1], wires=0)" + ], + "metadata": { + "id": "qcmWA-o4hBqa" + }, + "execution_count": 5, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "This method calls the gates directly from the QuantumDevice. For the rotations, we can specify which wire it belongs to (zero-indexed) and a parameter theta for the amount of rotation. However, the rotation gates also have other parameters.\n", + "\n", + "* wires: which qibits the gate is applied to\n", + "* theta: the amount of rotation\n", + "* n_wires: number of qubits the gate is applied to\n", + "* static: whether use static mode computation\n", + "* parent_graph: Parent QuantumGraph of current operation\n", + "* inverse: whether inverse the gate\n", + "* comp_method: option to use 'bmm' or 'einsum' method to perform matrix vector multiplication" + ], + "metadata": { + "id": "RQhCOnNAhm7q" + } + }, + { + "cell_type": "markdown", + "source": [ + "To get the following expected value, we can use two different functions from torchquantum's measurement module." + ], + "metadata": { + "id": "zY5lSe3Nl-78" + } + }, + { + "cell_type": "code", + "source": [ + "from torchquantum.measurement import expval_joint_analytical, expval_joint_sampling" + ], + "metadata": { + "id": "3IHmc_ILirVI" + }, + "execution_count": 6, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "* `expval_joint_analytical` will compute the expectation value of a joint observable in analytical way, assuming the statevector is available. This can only be run on a classical simulator, not real quantum hardware.\n", + "\n", + "* `expval_joint_analytical` will compute the expectation value of a joint observable from sampling the measurement bistring. This can be run on both a classical simulation and real quantum hardware. Since this is sampling the measurements, it requires a parameters for the number of shots, `n_shots`.\n", + "\n" + ], + "metadata": { + "id": "h_05PJxAjIMk" + } + }, + { + "cell_type": "code", + "source": [ + "exp_a = expval_joint_analytical(qdev, \"Z\")\n", + "exp_s = expval_joint_sampling(qdev, \"Z\", n_shots=1024)\n", + "\n", + "print(exp_a, exp_s)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "3TIwrhn1kD-a", + "outputId": "0af08a9b-5c1c-475b-9845-3aa2331ed59e" + }, + "execution_count": 7, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "tensor([0.8515]) tensor([0.8184])\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "The two numbers are about the same, and if we increase the number of shots for the joint sampling, its expected value should approach the same value as the analytical." + ], + "metadata": { + "id": "9rUMiTshkuYk" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Calculating quantum gradients" + ], + "metadata": { + "id": "WyHxuz4_l0lB" + } + }, + { + "cell_type": "markdown", + "source": [ + "From the expected values output, notice that the analytical expected value has an automatically-calculated gradient which can be used when constructing quantum machine learning models. This is because TorchQuantum automatically calculates the gradients. Let's find the gradient of each individual gate.\n", + "\n", + "To do so, we can create the circuit slightly differently, saving each operation as a variable then adding it to the circuit. We can then once again get the expected value with `expval_joint_analytical`." + ], + "metadata": { + "id": "GNlFHcRDnqVl" + } + }, + { + "cell_type": "code", + "source": [ + "qdev = tq.QuantumDevice(n_wires=1)\n", + "\n", + "op1 = tq.RX(has_params=True, trainable=True, init_params=0.54)\n", + "op1(qdev, wires=0)\n", + "\n", + "op2 = tq.RY(has_params=True, trainable=True, init_params=0.12)\n", + "op2(qdev, wires=0)\n", + "\n", + "\n", + "expval = expval_joint_analytical(qdev, \"Z\")" + ], + "metadata": { + "id": "m_n2ROPNoFzn" + }, + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "We can then call `.backward()` on the expected value, just like in PyTorch. Afterwards, we can see the gradient of each operation under the `params` option." + ], + "metadata": { + "id": "znstxaD3pFdK" + } + }, + { + "cell_type": "code", + "source": [ + "expval[0].backward()\n", + "\n", + "# calculate the gradients for each operation!\n", + "print(op1.params.grad, op2.params.grad)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "d6ehHkuSo5Oq", + "outputId": "d3610b9a-48b2-4797-c3c9-818db8ce0687" + }, + "execution_count": 9, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "tensor([[-0.5104]]) tensor([[-0.1027]])\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Optimization" + ], + "metadata": { + "id": "R8PqqWa5pbzU" + } + }, + { + "cell_type": "markdown", + "source": [ + "Next, let's make use of PyTorch's optimizers to optimize the two circuit parameters $\\phi_1$ and $\\phi_2$ such that the qubit, originally in state |0⟩, is rotated to be in state |1⟩. This is equivalent to measuring a Pauli-Z expectation value of -1, since the state |1⟩ is an eigenvector of the Pauli-Z matrix with eigenvalue λ=−1." + ], + "metadata": { + "id": "q4I7DC2Uphzs" + } + }, + { + "cell_type": "markdown", + "source": [ + "To construct this circuit, we can use a class similar to a PyTorch module! We can begin by importing torch." + ], + "metadata": { + "id": "G3h9LjzJqf0k" + } + }, + { + "cell_type": "code", + "source": [ + "import torch" + ], + "metadata": { + "id": "X3LeotDeqoIh" + }, + "execution_count": 38, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "We can next create the class extending the PyTorch module and add our gates in a similar fashion as the previous steps." + ], + "metadata": { + "id": "LbN7Fo67qpGI" + } + }, + { + "cell_type": "code", + "source": [ + "import torchquantum as tq\n", + "import torchquantum.functional as tqf\n", + "\n", + "\n", + "class OptimizationModel(torch.nn.Module):\n", + " def __init__(self):\n", + " super().__init__()\n", + " self.rx0 = tq.RX(has_params=True, trainable=True, init_params=0.011)\n", + " self.ry0 = tq.RY(has_params=True, trainable=True, init_params=0.012)\n", + "\n", + " def forward(self):\n", + " # create a quantum device to run the gates\n", + " qdev = tq.QuantumDevice(n_wires=1)\n", + "\n", + " # add some trainable gates (need to instantiate ahead of time)\n", + " self.rx0(qdev, wires=0)\n", + " self.ry0(qdev, wires=0)\n", + "\n", + " return expval_joint_analytical(qdev, \"Z\")" + ], + "metadata": { + "id": "gxve5-2SpdDA" + }, + "execution_count": 39, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "To optimize the rotation, we need to define a cost function. By minimizing the cost function, the optimizer will determine the values of the circuit parameters that produce the desired outcome.\n", + "\n", + "In this case, our desired outcome is a Pauli-Z expectation value of −1. Since we know that the Pauli-Z expectation is bound between [−1, 1], we can define our cost directly as the output of the circuit.\n", + "\n", + "Similar to PyTorch, we can create a train function to compute the gradients of the loss function and have the optimizer perform an optimization step." + ], + "metadata": { + "id": "Ifi5cH_eq_zW" + } + }, + { + "cell_type": "code", + "source": [ + "def train(model, device, optimizer):\n", + " targets = 0\n", + "\n", + " outputs = model()\n", + " loss = outputs\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + "\n", + " return loss.item()" + ], + "metadata": { + "id": "H5xxXrWUrAO3" + }, + "execution_count": 53, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "Finally, we can run the model. We can import PyTorch's gradient descent module and use it to optimize our model." + ], + "metadata": { + "id": "dn0131aKrjQ8" + } + }, + { + "cell_type": "code", + "source": [ + "def main():\n", + " seed = 0\n", + " torch.manual_seed(seed)\n", + "\n", + " use_cuda = torch.cuda.is_available()\n", + " device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n", + "\n", + " model = OptimizationModel()\n", + " n_epochs = 200\n", + " optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n", + "\n", + " for epoch in range(1, n_epochs + 1):\n", + " # train\n", + " loss = train(model, device, optimizer)\n", + " output = (model.rx0.params[0].item(), model.ry0.params[0].item())\n", + " print(f\"Epoch {epoch}: {output}\")\n", + "\n", + " if epoch % 10 == 0:\n", + " print(f\"Loss after step {epoch}: {loss}\")" + ], + "metadata": { + "id": "4WJ7yL5SrjkA" + }, + "execution_count": 54, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "Finally, we can call the main function and run the entire sequence!" + ], + "metadata": { + "id": "eY5PvCqhr1ZF" + } + }, + { + "cell_type": "code", + "source": [ + "main()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "_hCBPtMvr4wB", + "outputId": "2091f42b-7263-4e5d-d2f7-eab8b07bbe7f" + }, + "execution_count": 55, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Epoch 1: (0.012099898420274258, 0.013199898414313793)\n", + "Epoch 2: (0.013309753499925137, 0.014519752934575081)\n", + "Epoch 3: (0.014640549197793007, 0.015971548855304718)\n", + "Epoch 4: (0.01610436476767063, 0.017568465322256088)\n", + "Epoch 5: (0.01771448366343975, 0.01932499371469021)\n", + "Epoch 6: (0.019485509023070335, 0.02125706896185875)\n", + "Epoch 7: (0.021433496847748756, 0.023382212966680527)\n", + "Epoch 8: (0.023576095700263977, 0.02571968361735344)\n", + "Epoch 9: (0.025932706892490387, 0.028290653601288795)\n", + "Epoch 10: (0.028524650260806084, 0.03111839108169079)\n", + "Loss after step 10: 0.9992638230323792\n", + "Epoch 11: (0.031375348567962646, 0.03422846272587776)\n", + "Epoch 12: (0.0345105305314064, 0.03764895722270012)\n", + "Epoch 13: (0.037958454340696335, 0.041410721838474274)\n", + "Epoch 14: (0.04175013676285744, 0.04554762691259384)\n", + "Epoch 15: (0.04591960832476616, 0.050096847116947174)\n", + "Epoch 16: (0.05050419643521309, 0.055099159479141235)\n", + "Epoch 17: (0.05554480850696564, 0.06059926748275757)\n", + "Epoch 18: (0.06108624115586281, 0.06664614379405975)\n", + "Epoch 19: (0.06717751175165176, 0.07329340279102325)\n", + "Epoch 20: (0.07387219369411469, 0.08059966564178467)\n", + "Loss after step 20: 0.9950657486915588\n", + "Epoch 21: (0.08122873306274414, 0.08862894773483276)\n", + "Epoch 22: (0.08931083232164383, 0.09745106101036072)\n", + "Epoch 23: (0.09818772971630096, 0.10714197158813477)\n", + "Epoch 24: (0.10793451964855194, 0.11778417229652405)\n", + "Epoch 25: (0.11863239109516144, 0.12946699559688568)\n", + "Epoch 26: (0.13036876916885376, 0.14228680729866028)\n", + "Epoch 27: (0.14323736727237701, 0.15634718537330627)\n", + "Epoch 28: (0.15733805298805237, 0.17175881564617157)\n", + "Epoch 29: (0.172776460647583, 0.18863925337791443)\n", + "Epoch 30: (0.18966329097747803, 0.20711229741573334)\n", + "Loss after step 30: 0.9676356315612793\n", + "Epoch 31: (0.20811320841312408, 0.2273070216178894)\n", + "Epoch 32: (0.2282431572675705, 0.2493562251329422)\n", + "Epoch 33: (0.2501700222492218, 0.27339422702789307)\n", + "Epoch 34: (0.2740074098110199, 0.29955384135246277)\n", + "Epoch 35: (0.2998615801334381, 0.32796236872673035)\n", + "Epoch 36: (0.32782599329948425, 0.35873648524284363)\n", + "Epoch 37: (0.3579748272895813, 0.39197587966918945)\n", + "Epoch 38: (0.3903552293777466, 0.427755743265152)\n", + "Epoch 39: (0.42497843503952026, 0.46611812710762024)\n", + "Epoch 40: (0.4618101119995117, 0.5070626139640808)\n", + "Loss after step 40: 0.8138567805290222\n", + "Epoch 41: (0.5007606744766235, 0.5505368709564209)\n", + "Epoch 42: (0.5416762828826904, 0.5964280366897583)\n", + "Epoch 43: (0.5843320488929749, 0.6445562839508057)\n", + "Epoch 44: (0.6284285187721252, 0.6946715116500854)\n", + "Epoch 45: (0.6735928058624268, 0.7464552521705627)\n", + "Epoch 46: (0.7193858623504639, 0.7995281219482422)\n", + "Epoch 47: (0.7653157711029053, 0.8534636497497559)\n", + "Epoch 48: (0.8108565211296082, 0.9078077673912048)\n", + "Epoch 49: (0.8554709553718567, 0.9621021151542664)\n", + "Epoch 50: (0.8986347317695618, 1.0159088373184204)\n", + "Loss after step 50: 0.3750203549861908\n", + "Epoch 51: (0.9398593902587891, 1.0688340663909912)\n", + "Epoch 52: (0.9787107706069946, 1.1205471754074097)\n", + "Epoch 53: (1.0148218870162964, 1.1707944869995117)\n", + "Epoch 54: (1.0478986501693726, 1.2194054126739502)\n", + "Epoch 55: (1.0777196884155273, 1.2662931680679321)\n", + "Epoch 56: (1.1041301488876343, 1.311449408531189)\n", + "Epoch 57: (1.127032995223999, 1.354935884475708)\n", + "Epoch 58: (1.1463772058486938, 1.3968735933303833)\n", + "Epoch 59: (1.1621465682983398, 1.4374314546585083)\n", + "Epoch 60: (1.1743487119674683, 1.4768157005310059)\n", + "Loss after step 60: 0.052838265895843506\n", + "Epoch 61: (1.1830050945281982, 1.5152597427368164)\n", + "Epoch 62: (1.1881437301635742, 1.553015947341919)\n", + "Epoch 63: (1.1897931098937988, 1.590348243713379)\n", + "Epoch 64: (1.1879782676696777, 1.6275262832641602)\n", + "Epoch 65: (1.1827187538146973, 1.6648198366165161)\n", + "Epoch 66: (1.1740283966064453, 1.702493667602539)\n", + "Epoch 67: (1.1619168519973755, 1.7408030033111572)\n", + "Epoch 68: (1.146392583847046, 1.7799879312515259)\n", + "Epoch 69: (1.1274679899215698, 1.820267915725708)\n", + "Epoch 70: (1.1051654815673828, 1.8618348836898804)\n", + "Loss after step 70: -0.10590392351150513\n", + "Epoch 71: (1.0795255899429321, 1.9048453569412231)\n", + "Epoch 72: (1.0506160259246826, 1.9494123458862305)\n", + "Epoch 73: (1.018541693687439, 1.9955958127975464)\n", + "Epoch 74: (0.9834545850753784, 2.043394088745117)\n", + "Epoch 75: (0.9455628991127014, 2.0927350521087646)\n", + "Epoch 76: (0.9051381945610046, 2.1434707641601562)\n", + "Epoch 77: (0.8625186085700989, 2.1953752040863037)\n", + "Epoch 78: (0.8181073665618896, 2.2481465339660645)\n", + "Epoch 79: (0.7723652124404907, 2.30141544342041)\n", + "Epoch 80: (0.7257967591285706, 2.354759931564331)\n", + "Loss after step 80: -0.4779837727546692\n", + "Epoch 81: (0.6789312362670898, 2.4077253341674805)\n", + "Epoch 82: (0.6322994232177734, 2.459847927093506)\n", + "Epoch 83: (0.5864096879959106, 2.5106801986694336)\n", + "Epoch 84: (0.5417252779006958, 2.5598134994506836)\n", + "Epoch 85: (0.4986463487148285, 2.6068966388702393)\n", + "Epoch 86: (0.4574976861476898, 2.6516494750976562)\n", + "Epoch 87: (0.4185234606266022, 2.6938676834106445)\n", + "Epoch 88: (0.38188809156417847, 2.7334227561950684)\n", + "Epoch 89: (0.34768232703208923, 2.770256519317627)\n", + "Epoch 90: (0.31593260169029236, 2.8043713569641113)\n", + "Loss after step 90: -0.876086413860321\n", + "Epoch 91: (0.28661224246025085, 2.835820436477661)\n", + "Epoch 92: (0.25965315103530884, 2.8646953105926514)\n", + "Epoch 93: (0.23495660722255707, 2.891116142272949)\n", + "Epoch 94: (0.21240299940109253, 2.915221691131592)\n", + "Epoch 95: (0.1918598860502243, 2.937161445617676)\n", + "Epoch 96: (0.1731884628534317, 2.957089900970459)\n", + "Epoch 97: (0.156248539686203, 2.97516131401062)\n", + "Epoch 98: (0.14090220630168915, 2.991525888442993)\n", + "Epoch 99: (0.12701639533042908, 3.0063281059265137)\n", + "Epoch 100: (0.11446458846330643, 3.019704818725586)\n", + "Loss after step 100: -0.9828835129737854\n", + "Epoch 101: (0.1031278446316719, 3.0317838191986084)\n", + "Epoch 102: (0.09289533644914627, 3.042684316635132)\n", + "Epoch 103: (0.08366449177265167, 3.052516460418701)\n", + "Epoch 104: (0.07534093409776688, 3.0613811016082764)\n", + "Epoch 105: (0.0678381696343422, 3.069370985031128)\n", + "Epoch 106: (0.06107722595334053, 3.0765702724456787)\n", + "Epoch 107: (0.054986197501420975, 3.0830557346343994)\n", + "Epoch 108: (0.0494997613132, 3.088897228240967)\n", + "Epoch 109: (0.04455867409706116, 3.0941579341888428)\n", + "Epoch 110: (0.040109291672706604, 3.0988948345184326)\n", + "Loss after step 110: -0.997883677482605\n", + "Epoch 111: (0.03610309213399887, 3.1031599044799805)\n", + "Epoch 112: (0.03249623253941536, 3.106999635696411)\n", + "Epoch 113: (0.029249126091599464, 3.1104564666748047)\n", + "Epoch 114: (0.026326047256588936, 3.1135683059692383)\n", + "Epoch 115: (0.023694779723882675, 3.1163694858551025)\n", + "Epoch 116: (0.021326277405023575, 3.1188907623291016)\n", + "Epoch 117: (0.019194360822439194, 3.1211602687835693)\n", + "Epoch 118: (0.01727544330060482, 3.1232030391693115)\n", + "Epoch 119: (0.015548276714980602, 3.1250417232513428)\n", + "Epoch 120: (0.013993724249303341, 3.1266965866088867)\n", + "Loss after step 120: -0.9997422099113464\n", + "Epoch 121: (0.012594552710652351, 3.128185987472534)\n", + "Epoch 122: (0.011335243470966816, 3.1295266151428223)\n", + "Epoch 123: (0.010201825760304928, 3.130733013153076)\n", + "Epoch 124: (0.00918172113597393, 3.131819009780884)\n", + "Epoch 125: (0.008263605646789074, 3.132796287536621)\n", + "Epoch 126: (0.0074372864328324795, 3.1336758136749268)\n", + "Epoch 127: (0.006693588104099035, 3.134467363357544)\n", + "Epoch 128: (0.006024251226335764, 3.1351797580718994)\n", + "Epoch 129: (0.005421841982752085, 3.1358211040496826)\n", + "Epoch 130: (0.004879669286310673, 3.1363983154296875)\n", + "Loss after step 130: -0.9999685883522034\n", + "Epoch 131: (0.004391710739582777, 3.13691782951355)\n", + "Epoch 132: (0.0039525460451841354, 3.137385368347168)\n", + "Epoch 133: (0.0035572960041463375, 3.1378061771392822)\n", + "Epoch 134: (0.003201569663360715, 3.1381847858428955)\n", + "Epoch 135: (0.0028814151883125305, 3.1385254859924316)\n", + "Epoch 136: (0.0025932753924280405, 3.1388320922851562)\n", + "Epoch 137: (0.002333949087187648, 3.139108180999756)\n", + "Epoch 138: (0.002100554993376136, 3.1393566131591797)\n", + "Epoch 139: (0.0018905001925304532, 3.139580249786377)\n", + "Epoch 140: (0.0017014506738632917, 3.1397814750671387)\n", + "Loss after step 140: -0.9999963045120239\n", + "Epoch 141: (0.001531305955722928, 3.139962673187256)\n", + "Epoch 142: (0.0013781756861135364, 3.1401257514953613)\n", + "Epoch 143: (0.0012403583386912942, 3.140272378921509)\n", + "Epoch 144: (0.0011163227027282119, 3.140404462814331)\n", + "Epoch 145: (0.0010046905372291803, 3.1405231952667236)\n", + "Epoch 146: (0.0009042215533554554, 3.1406302452087402)\n", + "Epoch 147: (0.0008137994445860386, 3.1407265663146973)\n", + "Epoch 148: (0.0007324195466935635, 3.140813112258911)\n", + "Epoch 149: (0.0006591776036657393, 3.1408910751342773)\n", + "Epoch 150: (0.0005932598724029958, 3.140961170196533)\n", + "Loss after step 150: -0.9999995231628418\n", + "Epoch 151: (0.0005339339259080589, 3.141024351119995)\n", + "Epoch 152: (0.00048054056242108345, 3.1410810947418213)\n", + "Epoch 153: (0.000432486500358209, 3.141132354736328)\n", + "Epoch 154: (0.00038923785905353725, 3.1411783695220947)\n", + "Epoch 155: (0.00035031407605856657, 3.1412198543548584)\n", + "Epoch 156: (0.0003152826684527099, 3.1412570476531982)\n", + "Epoch 157: (0.0002837544016074389, 3.1412906646728516)\n", + "Epoch 158: (0.0002553789527155459, 3.1413209438323975)\n", + "Epoch 159: (0.00022984105453360826, 3.141348123550415)\n", + "Epoch 160: (0.00020685694471467286, 3.1413726806640625)\n", + "Loss after step 160: -1.0\n", + "Epoch 161: (0.0001861712516983971, 3.14139461517334)\n", + "Epoch 162: (0.0001675541279837489, 3.1414144039154053)\n", + "Epoch 163: (0.00015079871809575707, 3.141432285308838)\n", + "Epoch 164: (0.00013571884483098984, 3.1414482593536377)\n", + "Epoch 165: (0.0001221469574375078, 3.141462802886963)\n", + "Epoch 166: (0.00010993226169375703, 3.1414756774902344)\n", + "Epoch 167: (9.893903188640252e-05, 3.1414873600006104)\n", + "Epoch 168: (8.904512651497498e-05, 3.141497850418091)\n", + "Epoch 169: (8.014061313588172e-05, 3.141507387161255)\n", + "Epoch 170: (7.212655327748507e-05, 3.1415159702301025)\n", + "Loss after step 170: -1.0\n", + "Epoch 171: (6.491389649454504e-05, 3.141523599624634)\n", + "Epoch 172: (5.8422505389899015e-05, 3.1415305137634277)\n", + "Epoch 173: (5.258025339571759e-05, 3.1415367126464844)\n", + "Epoch 174: (4.732222805614583e-05, 3.1415421962738037)\n", + "Epoch 175: (4.2590003431541845e-05, 3.141547203063965)\n", + "Epoch 176: (3.833100345218554e-05, 3.1415517330169678)\n", + "Epoch 177: (3.4497901651775464e-05, 3.1415557861328125)\n", + "Epoch 178: (3.10481118503958e-05, 3.141559362411499)\n", + "Epoch 179: (2.794330066535622e-05, 3.1415627002716064)\n", + "Epoch 180: (2.5148970962618478e-05, 3.1415657997131348)\n", + "Loss after step 180: -1.0\n", + "Epoch 181: (2.263407441205345e-05, 3.141568422317505)\n", + "Epoch 182: (2.0370667698443867e-05, 3.141570806503296)\n", + "Epoch 183: (1.83336014742963e-05, 3.141572952270508)\n", + "Epoch 184: (1.6500242054462433e-05, 3.1415748596191406)\n", + "Epoch 185: (1.485021766711725e-05, 3.1415765285491943)\n", + "Epoch 186: (1.3365195627557114e-05, 3.141578197479248)\n", + "Epoch 187: (1.2028675882902462e-05, 3.1415796279907227)\n", + "Epoch 188: (1.0825808203662746e-05, 3.141580820083618)\n", + "Epoch 189: (9.743227565195411e-06, 3.1415820121765137)\n", + "Epoch 190: (8.76890499057481e-06, 3.14158296585083)\n", + "Loss after step 190: -1.0\n", + "Epoch 191: (7.89201476436574e-06, 3.1415839195251465)\n", + "Epoch 192: (7.1028134698281065e-06, 3.141584873199463)\n", + "Epoch 193: (6.392532213794766e-06, 3.1415855884552)\n", + "Epoch 194: (5.753278855991084e-06, 3.1415863037109375)\n", + "Epoch 195: (5.177951152290916e-06, 3.141587018966675)\n", + "Epoch 196: (4.660155809688149e-06, 3.141587495803833)\n", + "Epoch 197: (4.194140274194069e-06, 3.141587972640991)\n", + "Epoch 198: (3.7747263377241325e-06, 3.1415884494781494)\n", + "Epoch 199: (3.3972537494264543e-06, 3.1415889263153076)\n", + "Epoch 200: (3.057528374483809e-06, 3.141589403152466)\n", + "Loss after step 200: -1.0\n" + ] } - ] + ] + }, + { + "cell_type": "markdown", + "source": [ + "We can see that the optimization converges after approximately 160 steps.\n", + "\n", + "Substituting this into the theoretical result $⟨ψ∣σ_z∣ψ⟩ = \\cos ϕ_1 \\cos ϕ_2$, we can verify that this is indeed one possible value of the circuit parameters that produces $⟨ψ∣σ_z∣ψ⟩ = −1$, resulting in the qubit being rotated to the state |1⟩.\n", + "\n" + ], + "metadata": { + "id": "GpzzV6kyr_Z1" + } + } + ] } diff --git a/examples/qubit_rotation/qubit_rotation.py b/examples/qubit_rotation/qubit_rotation.py index 3e0d17d6..be2dfc82 100644 --- a/examples/qubit_rotation/qubit_rotation.py +++ b/examples/qubit_rotation/qubit_rotation.py @@ -1,16 +1,18 @@ -''' +""" Qubit Rotation Optimization, adapted from https://pennylane.ai/qml/demos/tutorial_qubit_rotation -''' +""" # import dependencies import torchquantum as tq import torch from torchquantum.measurement import expval_joint_analytical + class OptimizationModel(torch.nn.Module): - ''' + """ Circuit with rx and ry gate - ''' + """ + def __init__(self): super().__init__() self.rx0 = tq.RX(has_params=True, trainable=True, init_params=0.011) @@ -25,11 +27,11 @@ def forward(self): self.ry0(qdev, wires=0) # return the analytic expval from Z - return expval_joint_analytical(qdev, 'Z') + return expval_joint_analytical(qdev, "Z") + # train function to get expval as low as possible (ideally -1) def train(model, device, optimizer): - outputs = model() loss = outputs optimizer.zero_grad() @@ -38,6 +40,7 @@ def train(model, device, optimizer): return loss.item() + # main function to run the optimization def main(): seed = 0 @@ -63,4 +66,3 @@ def main(): if __name__ == "__main__": main() - From 84d32ec433c3a7224184de71cd1359d720f3bebd Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 14 Jul 2023 22:05:40 -0400 Subject: [PATCH 08/28] [minor] fixing end-of-files --- examples/qubit_rotation/README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/examples/qubit_rotation/README.md b/examples/qubit_rotation/README.md index 1b553fd0..470cb271 100644 --- a/examples/qubit_rotation/README.md +++ b/examples/qubit_rotation/README.md @@ -7,4 +7,3 @@ python3 qubit_rotation.py ``` Expected to reach a loss of -1 by epoch 160 - From 00674cef83f6b390ef6782ced2fa057480428b75 Mon Sep 17 00:00:00 2001 From: Teague Tomesh Date: Tue, 18 Jul 2023 13:53:19 -0500 Subject: [PATCH 09/28] Added opt_einsum to pip requirements --- requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements.txt b/requirements.txt index 69ffd92b..ca616411 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,6 +3,7 @@ matplotlib>=3.3.2 nbsphinx numpy>=1.19.2 +opt_einsum pathos>=0.2.7 pyscf>=2.0.1 From bc9ed97ad76f4a89c431d3194ba56cb74db5f169 Mon Sep 17 00:00:00 2001 From: Teague Tomesh Date: Thu, 17 Aug 2023 15:21:03 -0500 Subject: [PATCH 10/28] Read from requirements.txt from within setup.py --- requirements.txt | 6 ++++-- setup.py | 18 ++++-------------- 2 files changed, 8 insertions(+), 16 deletions(-) diff --git a/requirements.txt b/requirements.txt index ca616411..f41cb0ef 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,19 +1,21 @@ furo @ git+https://github.com/frogcjn/torchquantum-doc-furo-theme.git +dill==0.3.4 matplotlib>=3.3.2 nbsphinx numpy>=1.19.2 opt_einsum pathos>=0.2.7 - +pylatexenc>=2.10 pyscf>=2.0.1 -qiskit>=0.24.0 +qiskit==0.38.0 recommonmark scipy>=1.5.2 setuptools>=52.0.0 tensorflow>=2.4.1 torch>=1.8.0 +torchdiffeq>=0.2.3 torchpack>=0.3.0 torchquantum>=0.1 torchvision>=0.9.0.dev20210130 diff --git a/setup.py b/setup.py index 823d557c..71454356 100644 --- a/setup.py +++ b/setup.py @@ -6,6 +6,9 @@ exec(version_file.read(), VERSION) if __name__ == "__main__": + requirements = open("requirements.txt").readlines() + requirements = [r.strip() for r in requirements] + setup( name="torchquantum", version=VERSION["version"], @@ -14,20 +17,7 @@ author="Hanrui Wang, Jiannan Cao, Jessica Ding, Jiai Gu, Song Han, Zirui Li, Zhiding Liang, Pengyu Liu, Mohammadreza Tavasoli", author_email="hanruiwang.hw@gmail.com", license="MIT", - install_requires=[ - "numpy>=1.19.2", - "torchvision>=0.9.0.dev20210130", - "tqdm>=4.56.0", - "setuptools>=52.0.0", - "torch>=1.8.0", - "torchdiffeq>=0.2.3", - "torchpack>=0.3.0", - "qiskit==0.38.0", - "matplotlib>=3.3.2", - "pathos>=0.2.7", - "pylatexenc>=2.10", - "dill==0.3.4", - ], + install_requires=requirements, extras_require={"doc": ["nbsphinx", "recommonmark"]}, python_requires=">=3.5", include_package_data=True, From a259ef0e4312e01144e48403252bfbeda843e044 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Fri, 18 Aug 2023 14:06:35 -0400 Subject: [PATCH 11/28] Update requirements.txt --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index f41cb0ef..037b54fc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,7 +8,7 @@ opt_einsum pathos>=0.2.7 pylatexenc>=2.10 pyscf>=2.0.1 -qiskit==0.38.0 +qiskit>=0.24.0 recommonmark scipy>=1.5.2 From 9b9e7f2a86ea8466c33cae18ce9e647fb0516d16 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Fri, 18 Aug 2023 14:16:08 -0400 Subject: [PATCH 12/28] Update requirements.txt --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 037b54fc..f41cb0ef 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,7 +8,7 @@ opt_einsum pathos>=0.2.7 pylatexenc>=2.10 pyscf>=2.0.1 -qiskit>=0.24.0 +qiskit==0.38.0 recommonmark scipy>=1.5.2 From 5dc4ab8f22afffc95dec89793fabeba17486612a Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 25 Aug 2023 15:00:27 -0500 Subject: [PATCH 13/28] fixed xxplusyy matrix --- test/operator/test_op.py | 4 ++-- torchquantum/functional/functionals.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/test/operator/test_op.py b/test/operator/test_op.py index 5ccb622d..012eda1e 100644 --- a/test/operator/test_op.py +++ b/test/operator/test_op.py @@ -75,7 +75,7 @@ {"qiskit": qiskit_gate.CU1Gate, "tq": tq.CU1}, # {'qiskit': qiskit_gate.?, 'tq': tq.CU2}, {"qiskit": qiskit_gate.CU3Gate, "tq": tq.CU3}, - # {"qiskit": qiskit_gate.ECRGate, "tq": tq.ECR}, + {"qiskit": qiskit_gate.ECRGate, "tq": tq.ECR}, # {"qiskit": qiskit_library.QFT, "tq": tq.QFT}, {"qiskit": qiskit_gate.SdgGate, "tq": tq.SDG}, {"qiskit": qiskit_gate.TdgGate, "tq": tq.TDG}, @@ -88,7 +88,7 @@ {"qiskit": qiskit_gate.CSXGate, "tq": tq.CSX}, {"qiskit": qiskit_gate.DCXGate, "tq": tq.DCX}, {"qiskit": qiskit_gate.XXMinusYYGate, "tq": tq.XXMINYY}, - # {"qiskit": qiskit_gate.XXPlusYYGate, "tq": tq.XXPLUSYY}, + {"qiskit": qiskit_gate.XXPlusYYGate, "tq": tq.XXPLUSYY}, # {"qiskit": qiskit_gate.C3XGate, "tq": tq.C3X}, # {"qiskit": qiskit_gate.RGate, "tq": tq.R}, ] diff --git a/torchquantum/functional/functionals.py b/torchquantum/functional/functionals.py index 80cd9068..b010f7df 100644 --- a/torchquantum/functional/functionals.py +++ b/torchquantum/functional/functionals.py @@ -623,7 +623,7 @@ def xxplusyy_matrix(params): [ torch.tensor([[0]]), co, - (-1j * si * torch.exp(-1j * beta)), + (-1j * si * torch.exp(1j * beta)), torch.tensor([[0]]), ], dim=-1, @@ -631,7 +631,7 @@ def xxplusyy_matrix(params): torch.cat( [ torch.tensor([[0]]), - (-1j * si * torch.exp(1j * beta)), + (-1j * si * torch.exp(-1j * beta)), co, torch.tensor([[0]]), ], From 86e2255b51b4bc8cb0da9c26f6373285eff71742 Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 25 Aug 2023 15:36:36 -0500 Subject: [PATCH 14/28] fixed matrices for ecr, ch, iswap, dcx, csx --- test/operator/test_op.py | 2 +- torchquantum/functional/functionals.py | 21 ++++++++++----------- 2 files changed, 11 insertions(+), 12 deletions(-) diff --git a/test/operator/test_op.py b/test/operator/test_op.py index 012eda1e..9ed0195a 100644 --- a/test/operator/test_op.py +++ b/test/operator/test_op.py @@ -125,7 +125,7 @@ def test_op(): qiskit_matrix = pair["qiskit"]().to_matrix() tq_matrix = pair["tq"].matrix.numpy() tq_matrix = switch_little_big_endian_matrix(tq_matrix) - # assert np.allclose(qiskit_matrix, tq_matrix) + assert np.allclose(qiskit_matrix, tq_matrix) else: for k in tqdm(range(RND_TIMES)): rnd_params = np.random.rand(pair["tq"].num_params).tolist() diff --git a/torchquantum/functional/functionals.py b/torchquantum/functional/functionals.py index b010f7df..cdea4d5c 100644 --- a/torchquantum/functional/functionals.py +++ b/torchquantum/functional/functionals.py @@ -1421,7 +1421,7 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: ], dtype=C_DTYPE, ), - "ecr": torch.tensor( + "ecr": INV_SQRT2 * torch.tensor( [[0, 0, 1, 1j], [0, 0, 1j, 1], [1, -1j, 0, 0], [-1j, 1, 0, 0]], dtype=C_DTYPE ), "sdg": torch.tensor([[1, 0], [0, -1j]], dtype=C_DTYPE), @@ -1432,14 +1432,14 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: "chadamard": torch.tensor( [ [1, 0, 0, 0], - [0, INV_SQRT2, 0, INV_SQRT2], - [0, 0, 1, 0], - [0, INV_SQRT2, 0, -INV_SQRT2], + [0, 1, 0, 0], + [0, 0, INV_SQRT2, INV_SQRT2], + [0, 0, INV_SQRT2, -INV_SQRT2], ], dtype=C_DTYPE, ), "iswap": torch.tensor( - [[1, 0, 0, 0], [0, 1j, 0, 0], [0, 0, 1j, 0], [0, 0, 0, 1]], dtype=C_DTYPE + [[1, 0, 0, 0], [0, 0, 1j, 0], [0, 1j, 0, 0], [0, 0, 0, 1]], dtype=C_DTYPE ), "ccz": torch.tensor( [ @@ -1463,13 +1463,12 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: "csx": torch.tensor( [ [1, 0, 0, 0], - [0, 0.5 + 0.5j, 0, 0.5 - 0.5j], - [0, 0, 1, 0], - [0, 0.5 - 0.5j, 0, 0.5 + 0.5j], + [0, 1, 0, 0], + [0, 0, 0.5 + 0.5j, 0.5 - 0.5j], + [0, 0, 0.5 - 0.5j, 0.5 + 0.5j], ], dtype=C_DTYPE, - ) - / np.sqrt(2), + ), "rx": rx_matrix, "ry": ry_matrix, "rz": rz_matrix, @@ -1499,7 +1498,7 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: "singleexcitation": singleexcitation_matrix, "qft": qft_matrix, "dcx": torch.tensor( - [[1, 0, 0, 0], [0, 0, 0, 1], [0, 1, 0, 0], [0, 0, 1, 0]], dtype=C_DTYPE + [[1, 0, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]], dtype=C_DTYPE ), "xxminyy": xxminyy_matrix, "xxplusyy": xxplusyy_matrix, From 39957ab9bf94990bf87fd3ddd53fca25de59ff53 Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 25 Aug 2023 17:36:23 -0500 Subject: [PATCH 15/28] added phi param for r gate and matrix for c3x --- test/operator/test_op.py | 4 ++-- torchquantum/functional/functionals.py | 24 +++++++++++++++++++----- torchquantum/operator/operators.py | 5 +++-- 3 files changed, 24 insertions(+), 9 deletions(-) diff --git a/test/operator/test_op.py b/test/operator/test_op.py index 9ed0195a..ced27e73 100644 --- a/test/operator/test_op.py +++ b/test/operator/test_op.py @@ -89,8 +89,8 @@ {"qiskit": qiskit_gate.DCXGate, "tq": tq.DCX}, {"qiskit": qiskit_gate.XXMinusYYGate, "tq": tq.XXMINYY}, {"qiskit": qiskit_gate.XXPlusYYGate, "tq": tq.XXPLUSYY}, - # {"qiskit": qiskit_gate.C3XGate, "tq": tq.C3X}, - # {"qiskit": qiskit_gate.RGate, "tq": tq.R}, + {"qiskit": qiskit_gate.C3XGate, "tq": tq.C3X}, + {"qiskit": qiskit_gate.RGate, "tq": tq.R}, ] import os diff --git a/torchquantum/functional/functionals.py b/torchquantum/functional/functionals.py index cdea4d5c..1fe6972f 100644 --- a/torchquantum/functional/functionals.py +++ b/torchquantum/functional/functionals.py @@ -1330,8 +1330,8 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: """ - theta = params.type(C_DTYPE) - phi = params.type(C_DTYPE) + theta = params[:, 0].unsqueeze(dim=-1).type(C_DTYPE) + phi = params[:, 1].unsqueeze(dim=-1).type(C_DTYPE) exp = torch.exp(-1j * phi) """ Seems to be a pytorch bug. Have to explicitly cast the theta to a @@ -1356,6 +1356,18 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: ).squeeze(0) +def c3x_matrix(): + """Compute unitary matrix for C3X.""" + + mat = torch.eye(16, dtype=C_DTYPE) + mat[15][15] = 0 + mat[14][14] = 0 + mat[15][14] = 1 + mat[14][15] = 1 + + return mat + + mat_dict = { "hadamard": torch.tensor( [[INV_SQRT2, INV_SQRT2], [INV_SQRT2, -INV_SQRT2]], dtype=C_DTYPE @@ -1421,7 +1433,8 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: ], dtype=C_DTYPE, ), - "ecr": INV_SQRT2 * torch.tensor( + "ecr": INV_SQRT2 + * torch.tensor( [[0, 0, 1, 1j], [0, 0, 1j, 1], [1, -1j, 0, 0], [-1j, 1, 0, 0]], dtype=C_DTYPE ), "sdg": torch.tensor([[1, 0], [0, -1j]], dtype=C_DTYPE), @@ -1503,6 +1516,7 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: "xxminyy": xxminyy_matrix, "xxplusyy": xxplusyy_matrix, "r": r_matrix, + "c3x": c3x_matrix(), } @@ -3508,7 +3522,7 @@ def c3x( None. """ - name = "qubitunitary" + name = "c3x" mat = mat_dict[name] gate_wrapper( name=name, @@ -3516,7 +3530,7 @@ def c3x( method=comp_method, q_device=q_device, wires=wires, - params=mat_dict["toffoli"], + params=params, n_wires=n_wires, static=static, parent_graph=parent_graph, diff --git a/torchquantum/operator/operators.py b/torchquantum/operator/operators.py index 502a63f4..02941d7d 100644 --- a/torchquantum/operator/operators.py +++ b/torchquantum/operator/operators.py @@ -1589,17 +1589,18 @@ class C3X(Operation, metaclass=ABCMeta): num_params = 0 num_wires = 4 + matrix = mat_dict["c3x"] func = staticmethod(tqf.c3x) @classmethod def _matrix(cls, params): - return tqf.qubitunitary_matrix(mat_dict["toffoli"]) + return cls.matrix class R(DiagonalOperation, metaclass=ABCMeta): """Class for R Gate.""" - num_params = 1 + num_params = 2 num_wires = 1 func = staticmethod(tqf.r) From 7afae7e03c3dc99c9430f9e6d4021dbaa839af5a Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Fri, 25 Aug 2023 23:31:25 -0500 Subject: [PATCH 16/28] added c4x, rccx, rc3x, c3sx, and globalphase gates --- test/operator/test_op.py | 8 + torchquantum/functional/functionals.py | 321 ++++++++++++++++++++++++- torchquantum/operator/operators.py | 79 ++++++ 3 files changed, 407 insertions(+), 1 deletion(-) diff --git a/test/operator/test_op.py b/test/operator/test_op.py index ced27e73..519bb2ef 100644 --- a/test/operator/test_op.py +++ b/test/operator/test_op.py @@ -34,6 +34,7 @@ import qiskit.circuit.library.standard_gates as qiskit_gate import qiskit.circuit.library as qiskit_library +from qiskit.quantum_info import Operator RND_TIMES = 100 @@ -91,6 +92,11 @@ {"qiskit": qiskit_gate.XXPlusYYGate, "tq": tq.XXPLUSYY}, {"qiskit": qiskit_gate.C3XGate, "tq": tq.C3X}, {"qiskit": qiskit_gate.RGate, "tq": tq.R}, + {"qiskit": qiskit_gate.C4XGate, "tq": tq.C4X}, + {"qiskit": qiskit_gate.RCCXGate, "tq": tq.RCCX}, + {"qiskit": qiskit_gate.RC3XGate, "tq": tq.RC3X}, + {"qiskit": qiskit_gate.GlobalPhaseGate, "tq": tq.GlobalPhase}, + {"qiskit": qiskit_gate.C3SXGate, "tq": tq.C3SX}, ] import os @@ -121,6 +127,8 @@ def test_op(): if pair["tq"]().name == "SHadamard": """Square root of Hadamard is RY(pi/4)""" qiskit_matrix = qiskit_gate.RYGate(theta=np.pi / 4).to_matrix() + elif pair["tq"]().name == "C3SX": + qiskit_matrix = Operator(pair["qiskit"]()) else: qiskit_matrix = pair["qiskit"]().to_matrix() tq_matrix = pair["tq"].matrix.numpy() diff --git a/torchquantum/functional/functionals.py b/torchquantum/functional/functionals.py index 1fe6972f..d459cdb8 100644 --- a/torchquantum/functional/functionals.py +++ b/torchquantum/functional/functionals.py @@ -122,6 +122,11 @@ "sxdg", "ch", "r", + "c4x", + "rccx", + "rc3x", + "globalphase", + "c3sx", ] @@ -1356,8 +1361,27 @@ def r_matrix(params: torch.Tensor) -> torch.Tensor: ).squeeze(0) +def globalphase_matrix(params): + """Compute unitary matrix for Multi qubit XCNOT gate. + Args: + params (torch.Tensor): The phase. + Returns: + torch.Tensor: The computed unitary matrix. + """ + phase = params.type(C_DTYPE) + exp = torch.exp(1j * phase) + matrix = torch.tensor([[exp]], dtype=C_DTYPE, device=params.device) + + return matrix + + def c3x_matrix(): - """Compute unitary matrix for C3X.""" + """Compute unitary matrix for C3X. + Args: + None + Returns: + torch.Tensor: The computed unitary matrix. + """ mat = torch.eye(16, dtype=C_DTYPE) mat[15][15] = 0 @@ -1368,6 +1392,38 @@ def c3x_matrix(): return mat +def c4x_matrix(): + """Compute unitary matrix for C4X gate. + Args: + None + Returns: + torch.Tensor: The computed unitary matrix. + """ + mat = torch.eye(32, dtype=C_DTYPE) + mat[30][30] = 0 + mat[30][31] = 1 + mat[31][31] = 0 + mat[31][30] = 1 + + return mat + + +def c3sx_matrix(): + """Compute unitary matrix for c3sx gate. + Args: + None. + Returns: + torch.Tensor: The computed unitary matrix. + """ + mat = torch.eye(16, dtype=C_DTYPE) + mat[14][14] = (1 + 1j) / 2 + mat[14][15] = (1 - 1j) / 2 + mat[15][14] = (1 - 1j) / 2 + mat[15][15] = (1 + 1j) / 2 + + return mat + + mat_dict = { "hadamard": torch.tensor( [[INV_SQRT2, INV_SQRT2], [INV_SQRT2, -INV_SQRT2]], dtype=C_DTYPE @@ -1516,7 +1572,44 @@ def c3x_matrix(): "xxminyy": xxminyy_matrix, "xxplusyy": xxplusyy_matrix, "r": r_matrix, + "globalphase": globalphase_matrix, "c3x": c3x_matrix(), + "c4x": c4x_matrix(), + "c3sx": c3sx_matrix(), + "rccx": torch.tensor( + [ + [1, 0, 0, 0, 0, 0, 0, 0], + [0, 1, 0, 0, 0, 0, 0, 0], + [0, 0, 1, 0, 0, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0], + [0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 0, 0, -1, 0, 0], + [0, 0, 0, 0, 0, 0, 0, -1j], + [0, 0, 0, 0, 0, 0, 1j, 0], + ], + dtype=C_DTYPE, + ), + "rc3x": torch.tensor( + [ + [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1j, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1j, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0], + ], + dtype=C_DTYPE, + ), } @@ -4279,6 +4372,227 @@ def r( ) +def c4x( + q_device, + wires, + params=None, + n_wires=None, + static=False, + parent_graph=None, + inverse=False, + comp_method="bmm", +): + """Perform the c4x gate. + Args: + q_device (tq.QuantumDevice): The QuantumDevice. + wires (Union[List[int], int]): Which qubit(s) to apply the gate. + params (torch.Tensor, optional): Parameters (if any) of the gate. + Default to None. + n_wires (int, optional): Number of qubits the gate is applied to. + Default to None. + static (bool, optional): Whether use static mode computation. + Default to False. + parent_graph (tq.QuantumGraph, optional): Parent QuantumGraph of + current operation. Default to None. + inverse (bool, optional): Whether inverse the gate. Default to False. + comp_method (bool, optional): Use 'bmm' or 'einsum' method to perform + matrix vector multiplication. Default to 'bmm'. + Returns: + None. + """ + name = "c4x" + mat = mat_dict[name] + gate_wrapper( + name=name, + mat=mat, + method=comp_method, + q_device=q_device, + wires=wires, + params=params, + n_wires=n_wires, + static=static, + parent_graph=parent_graph, + inverse=inverse, + ) + + +def rc3x( + q_device, + wires, + params=None, + n_wires=None, + static=False, + parent_graph=None, + inverse=False, + comp_method="bmm", +): + """Perform the rc3x (simplified 3-controlled Toffoli) gate. + Args: + q_device (tq.QuantumDevice): The QuantumDevice. + wires (Union[List[int], int]): Which qubit(s) to apply the gate. + params (torch.Tensor, optional): Parameters (if any) of the gate. + Default to None. + n_wires (int, optional): Number of qubits the gate is applied to. + Default to None. + static (bool, optional): Whether use static mode computation. + Default to False. + parent_graph (tq.QuantumGraph, optional): Parent QuantumGraph of + current operation. Default to None. + inverse (bool, optional): Whether inverse the gate. Default to False. + comp_method (bool, optional): Use 'bmm' or 'einsum' method to perform + matrix vector multiplication. Default to 'bmm'. + Returns: + None. + """ + name = "rc3x" + mat = mat_dict[name] + gate_wrapper( + name=name, + mat=mat, + method=comp_method, + q_device=q_device, + wires=wires, + params=params, + n_wires=n_wires, + static=static, + parent_graph=parent_graph, + inverse=inverse, + ) + + +def rccx( + q_device, + wires, + params=None, + n_wires=None, + static=False, + parent_graph=None, + inverse=False, + comp_method="bmm", +): + """Perform the rccx (simplified Toffoli) gate. + Args: + q_device (tq.QuantumDevice): The QuantumDevice. + wires (Union[List[int], int]): Which qubit(s) to apply the gate. + params (torch.Tensor, optional): Parameters (if any) of the gate. + Default to None. + n_wires (int, optional): Number of qubits the gate is applied to. + Default to None. + static (bool, optional): Whether use static mode computation. + Default to False. + parent_graph (tq.QuantumGraph, optional): Parent QuantumGraph of + current operation. Default to None. + inverse (bool, optional): Whether inverse the gate. Default to False. + comp_method (bool, optional): Use 'bmm' or 'einsum' method to perform + matrix vector multiplication. Default to 'bmm'. + Returns: + None. + """ + name = "rccx" + mat = mat_dict[name] + gate_wrapper( + name=name, + mat=mat, + method=comp_method, + q_device=q_device, + wires=wires, + params=params, + n_wires=n_wires, + static=static, + parent_graph=parent_graph, + inverse=inverse, + ) + + +def globalphase( + q_device, + wires, + params=None, + n_wires=None, + static=False, + parent_graph=None, + inverse=False, + comp_method="bmm", +): + """Perform the echoed cross-resonance gate. + https://qiskit.org/documentation/stubs/qiskit.circuit.library.ECRGate.html + Args: + q_device (tq.QuantumDevice): The QuantumDevice. + wires (Union[List[int], int]): Which qubit(s) to apply the gate. + params (torch.Tensor, optional): Parameters (if any) of the gate. + Default to None. + n_wires (int, optional): Number of qubits the gate is applied to. + Default to None. + static (bool, optional): Whether use static mode computation. + Default to False. + parent_graph (tq.QuantumGraph, optional): Parent QuantumGraph of + current operation. Default to None. + inverse (bool, optional): Whether inverse the gate. Default to False. + comp_method (bool, optional): Use 'bmm' or 'einsum' method to perform + matrix vector multiplication. Default to 'bmm'. + Returns: + None. + """ + name = "globalphase" + mat = mat_dict[name] + gate_wrapper( + name=name, + mat=mat, + method=comp_method, + q_device=q_device, + wires=wires, + params=params, + n_wires=n_wires, + static=static, + parent_graph=parent_graph, + inverse=inverse, + ) + + +def c3sx( + q_device, + wires, + params=None, + n_wires=None, + static=False, + parent_graph=None, + inverse=False, + comp_method="bmm", +): + """Perform the c3sx gate. + Args: + q_device (tq.QuantumDevice): The QuantumDevice. + wires (Union[List[int], int]): Which qubit(s) to apply the gate. + params (torch.Tensor, optional): Parameters (if any) of the gate. + Default to None. + n_wires (int, optional): Number of qubits the gate is applied to. + Default to None. + static (bool, optional): Whether use static mode computation. + Default to False. + parent_graph (tq.QuantumGraph, optional): Parent QuantumGraph of + current operation. Default to None. + inverse (bool, optional): Whether inverse the gate. Default to False. + comp_method (bool, optional): Use 'bmm' or 'einsum' method to perform + matrix vector multiplication. Default to 'bmm'. + Returns: + None. + """ + name = "c3sx" + mat = mat_dict[name] + gate_wrapper( + name=name, + mat=mat, + method=comp_method, + q_device=q_device, + wires=wires, + params=params, + n_wires=n_wires, + static=static, + parent_graph=parent_graph, + inverse=inverse, + ) + + h = hadamard sh = shadamard x = paulix @@ -4380,4 +4694,9 @@ def r( "xxplusyy": xxplusyy, "c3x": c3x, "r": r, + "globalphase": globalphase, + "c3sx": c3sx, + "rccx": rccx, + "rc3x": rc3x, + "c4x": c4x, } diff --git a/torchquantum/operator/operators.py b/torchquantum/operator/operators.py index 02941d7d..1d1d4b8b 100644 --- a/torchquantum/operator/operators.py +++ b/torchquantum/operator/operators.py @@ -108,6 +108,11 @@ "XXPLUSYY", "C3X", "R", + "C4X", + "RC3X", + "RCCX", + "GlobalPhase", + "C3SX", ] @@ -177,6 +182,10 @@ class Operator(tq.QuantumModule): "CHadamard", "DCX", "C3X", + "C3SX", + "RCCX", + "RC3X", + "C4X", ] parameterized_ops = [ @@ -209,6 +218,7 @@ class Operator(tq.QuantumModule): "XXMINYY", "XXPLUSYY", "R", + "GlobalPhase", ] @property @@ -1609,6 +1619,70 @@ def _matrix(cls, params): return tqf.r_matrix(params) +class C4X(Operation, metaclass=ABCMeta): + """Class for C4X Gate.""" + + num_params = 0 + num_wires = 5 + matrix = mat_dict["c4x"] + func = staticmethod(tqf.c4x) + + @classmethod + def _matrix(cls, params): + return cls.matrix + + +class RC3X(Operation, metaclass=ABCMeta): + """Class for RC3X Gate.""" + + num_params = 0 + num_wires = 4 + matrix = mat_dict["rc3x"] + func = staticmethod(tqf.rc3x) + + @classmethod + def _matrix(cls, params): + return cls.matrix + + +class RCCX(Operation, metaclass=ABCMeta): + """Class for RCCX Gate.""" + + num_params = 0 + num_wires = 3 + matrix = mat_dict["rccx"] + func = staticmethod(tqf.rccx) + + @classmethod + def _matrix(cls, params): + return cls.matrix + + +class GlobalPhase(Operation, metaclass=ABCMeta): + """Class for Global Phase gate.""" + + num_params = 1 + num_wires = 0 + func = staticmethod(tqf.globalphase) + + @classmethod + def _matrix(cls, params): + return tqf.globalphase_matrix(params) + + +class C3SX(Operation, metaclass=ABCMeta): + """Class for C3SX Gate.""" + + num_params = 0 + num_wires = 4 + matrix = mat_dict["c3sx"] + func = staticmethod(tqf.c3sx) + + @classmethod + def _matrix(cls, params): + return cls.matrix + + H = Hadamard SH = SHadamard EchoedCrossResonance = ECR @@ -1696,4 +1770,9 @@ def _matrix(cls, params): "csdg": CSDG, "csx": CSX, "r": R, + "c3sx": C3SX, + "globalphase": GlobalPhase, + "rccx": RCCX, + "rc3x": RC3X, + "c4x": C4X, } From 8df03ee88ae7995bfceca5135ef6462941f2393e Mon Sep 17 00:00:00 2001 From: GenericP3rson Date: Sun, 27 Aug 2023 00:01:54 -0500 Subject: [PATCH 17/28] [minor] indentation update --- torchquantum/density/density_mat.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchquantum/density/density_mat.py b/torchquantum/density/density_mat.py index b8147615..b7e42244 100644 --- a/torchquantum/density/density_mat.py +++ b/torchquantum/density/density_mat.py @@ -751,7 +751,7 @@ def sswap( inverse: bool = False, comp_method: str = "bmm", ): - """Apply a symmetric swap gate on the specified wires. + """Apply a symmetric swap gate on the specified wires. This method applies a symmetric swap gate on the specified wires of the quantum device. The gate is applied to all the wires if the inverse flag is set to False. From 9ef0fb90200b3627df84a06ecbe51f92af913cea Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Tue, 29 Aug 2023 21:21:18 -0400 Subject: [PATCH 18/28] [minor] remove simple_mnist duplication --- examples/simple_mnist/mnist_2qubit_4class.py | 213 ------------- examples/simple_mnist/mnist_example.py | 281 ----------------- .../mnist_example_no_binding.py | 291 ------------------ .../mnist_example_with_binding.py | 270 ---------------- 4 files changed, 1055 deletions(-) delete mode 100644 examples/simple_mnist/mnist_2qubit_4class.py delete mode 100644 examples/simple_mnist/mnist_example.py delete mode 100644 examples/simple_mnist/other_implementations/mnist_example_no_binding.py delete mode 100644 examples/simple_mnist/other_implementations/mnist_example_with_binding.py diff --git a/examples/simple_mnist/mnist_2qubit_4class.py b/examples/simple_mnist/mnist_2qubit_4class.py deleted file mode 100644 index 21a7519b..00000000 --- a/examples/simple_mnist/mnist_2qubit_4class.py +++ /dev/null @@ -1,213 +0,0 @@ -""" -MIT License - -Copyright (c) 2020-present TorchQuantum Authors - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. -""" - -""" -use 2 qubit to perform 4 class classification, -We can choose four different observables to measure the qubit state: - 1. XX - 2. YY - 3. ZZ - 4. XY -""" - -import torch -import torch.nn.functional as F -import torch.optim as optim -import argparse - -import torchquantum as tq -import torchquantum.functional as tqf - -from torchquantum.measurement import expval_joint_analytical - -from torchquantum.dataset import MNIST -from torch.optim.lr_scheduler import CosineAnnealingLR - -import random -import numpy as np - - -class QFCModel(tq.QuantumModule): - class QLayer(tq.QuantumModule): - def __init__(self): - super().__init__() - self.n_wires = 2 - self.random_layer = tq.RandomLayer( - n_ops=50, wires=list(range(self.n_wires)) - ) - - # gates with trainable parameters - self.rx0 = tq.RX(has_params=True, trainable=True) - self.ry0 = tq.RY(has_params=True, trainable=True) - self.rz0 = tq.RZ(has_params=True, trainable=True) - self.crx0 = tq.CRX(has_params=True, trainable=True) - - def forward(self, qdev: tq.QuantumDevice): - self.random_layer(qdev) - - # some trainable gates (instantiated ahead of time) - self.rx0(qdev, wires=0) - self.ry0(qdev, wires=1) - self.rz0(qdev, wires=0) - self.crx0(qdev, wires=[0, 1]) - - def __init__(self): - super().__init__() - self.n_wires = 2 - # the encoder here is just for illustration purpose, may not be the best choice - self.encoder = tq.GeneralEncoder( - tq.encoder_op_list_name_dict["2x8_rxryrzrxryrzrxry"] - ) - - self.q_layer = self.QLayer() - - def forward(self, x, use_qiskit=False): - qdev = tq.QuantumDevice( - n_wires=self.n_wires, bsz=x.shape[0], device=x.device, record_op=True - ) - - bsz = x.shape[0] - x = F.avg_pool2d(x, 6).view(bsz, 16) - - self.encoder(qdev, x) - self.q_layer(qdev) - obs_xx = expval_joint_analytical(qdev, "XX") - obs_yy = expval_joint_analytical(qdev, "YY") - obs_zz = expval_joint_analytical(qdev, "ZZ") - obs_xy = expval_joint_analytical(qdev, "XY") - - x = torch.stack([obs_xx, obs_yy, obs_zz, obs_xy], dim=1) - x = F.log_softmax(x, dim=1) - - return x - - -def train(dataflow, model, device, optimizer): - for feed_dict in dataflow["train"]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs) - loss = F.nll_loss(outputs, targets) - optimizer.zero_grad() - loss.backward() - optimizer.step() - print(f"loss: {loss.item()}", end="\r") - - -def valid_test(dataflow, split, model, device, qiskit=False): - target_all = [] - output_all = [] - with torch.no_grad(): - for feed_dict in dataflow[split]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs, use_qiskit=qiskit) - - target_all.append(targets) - output_all.append(outputs) - target_all = torch.cat(target_all, dim=0) - output_all = torch.cat(output_all, dim=0) - - _, indices = output_all.topk(1, dim=1) - masks = indices.eq(target_all.view(-1, 1).expand_as(indices)) - size = target_all.shape[0] - corrects = masks.sum().item() - accuracy = corrects / size - loss = F.nll_loss(output_all, target_all).item() - - print(f"{split} set accuracy: {accuracy}") - print(f"{split} set loss: {loss}") - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument( - "--static", action="store_true", help="compute with " "static mode" - ) - parser.add_argument("--pdb", action="store_true", help="debug with pdb") - parser.add_argument( - "--wires-per-block", type=int, default=2, help="wires per block int static mode" - ) - parser.add_argument( - "--epochs", type=int, default=5, help="number of training epochs" - ) - - args = parser.parse_args() - - if args.pdb: - import pdb - - pdb.set_trace() - - seed = 0 - random.seed(seed) - np.random.seed(seed) - torch.manual_seed(seed) - - dataset = MNIST( - root="./mnist_data", - train_valid_split_ratio=[0.9, 0.1], - digits_of_interest=[0, 1, 2, 3], - n_test_samples=100, - ) - - dataflow = dict() - - for split in dataset: - sampler = torch.utils.data.RandomSampler(dataset[split]) - dataflow[split] = torch.utils.data.DataLoader( - dataset[split], - batch_size=256, - sampler=sampler, - num_workers=8, - pin_memory=True, - ) - - use_cuda = torch.cuda.is_available() - device = torch.device("cuda" if use_cuda else "cpu") - - model = QFCModel().to(device) - - n_epochs = args.epochs - optimizer = optim.Adam(model.parameters(), lr=5e-3, weight_decay=1e-4) - scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) - - for epoch in range(1, n_epochs + 1): - # train - print(f"Epoch {epoch}:") - train(dataflow, model, device, optimizer) - print(optimizer.param_groups[0]["lr"]) - - # valid - valid_test(dataflow, "valid", model, device) - scheduler.step() - - # test - valid_test(dataflow, "test", model, device, qiskit=False) - - -if __name__ == "__main__": - main() diff --git a/examples/simple_mnist/mnist_example.py b/examples/simple_mnist/mnist_example.py deleted file mode 100644 index 65276e91..00000000 --- a/examples/simple_mnist/mnist_example.py +++ /dev/null @@ -1,281 +0,0 @@ -""" -MIT License - -Copyright (c) 2020-present TorchQuantum Authors - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. -""" - -import torch -import torch.nn.functional as F -import torch.optim as optim -import argparse -import random -import numpy as np - -import torchquantum as tq -from torchquantum.plugin import ( - tq2qiskit_measurement, - qiskit_assemble_circs, - op_history2qiskit, - op_history2qiskit_expand_params, -) - -from torchquantum.dataset import MNIST -from torch.optim.lr_scheduler import CosineAnnealingLR - - -class QFCModel(tq.QuantumModule): - class QLayer(tq.QuantumModule): - def __init__(self): - super().__init__() - self.n_wires = 4 - self.random_layer = tq.RandomLayer( - n_ops=50, wires=list(range(self.n_wires)) - ) - - # gates with trainable parameters - self.rx0 = tq.RX(has_params=True, trainable=True) - self.ry0 = tq.RY(has_params=True, trainable=True) - self.rz0 = tq.RZ(has_params=True, trainable=True) - self.crx0 = tq.CRX(has_params=True, trainable=True) - - def forward(self, qdev: tq.QuantumDevice): - self.random_layer(qdev) - - # some trainable gates (instantiated ahead of time) - self.rx0(qdev, wires=0) - self.ry0(qdev, wires=1) - self.rz0(qdev, wires=3) - self.crx0(qdev, wires=[0, 2]) - - # add some more non-parameterized gates (add on-the-fly) - qdev.h(wires=3) # type: ignore - qdev.sx(wires=2) # type: ignore - qdev.cnot(wires=[3, 0]) # type: ignore - qdev.rx( - wires=1, - params=torch.tensor([0.1]), - static=self.static_mode, - parent_graph=self.graph, - ) # type: ignore - - def __init__(self): - super().__init__() - self.n_wires = 4 - self.encoder = tq.GeneralEncoder(tq.encoder_op_list_name_dict["4x4_u3rx"]) - - self.q_layer = self.QLayer() - self.measure = tq.MeasureAll(tq.PauliZ) - - def forward(self, x, use_qiskit=False): - qdev = tq.QuantumDevice( - n_wires=self.n_wires, bsz=x.shape[0], device=x.device, record_op=True - ) - - bsz = x.shape[0] - x = F.avg_pool2d(x, 6).view(bsz, 16) - devi = x.device - - if use_qiskit: - # use qiskit to process the circuit - # create the qiskit circuit for encoder - self.encoder(qdev, x) - op_history_parameterized = qdev.op_history - qdev.reset_op_history() - encoder_circs = op_history2qiskit_expand_params(self.n_wires, op_history_parameterized, bsz=bsz) - - # create the qiskit circuit for trainable quantum layers - self.q_layer(qdev) - op_history_fixed = qdev.op_history - qdev.reset_op_history() - q_layer_circ = op_history2qiskit(self.n_wires, op_history_fixed) - - # create the qiskit circuit for measurement - measurement_circ = tq2qiskit_measurement(qdev, self.measure) - - # assemble the encoder, trainable quantum layers, and measurement circuits - assembled_circs = qiskit_assemble_circs( - encoder_circs, q_layer_circ, measurement_circ - ) - - # call the qiskit processor to process the circuit - x0 = self.qiskit_processor.process_ready_circs(qdev, assembled_circs).to( # type: ignore - devi - ) - x = x0 - - else: - # use torchquantum to process the circuit - self.encoder(qdev, x) - qdev.reset_op_history() - self.q_layer(qdev) - x = self.measure(qdev) - - x = x.reshape(bsz, 2, 2).sum(-1).squeeze() - x = F.log_softmax(x, dim=1) - - return x - - -def train(dataflow, model, device, optimizer): - for feed_dict in dataflow["train"]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs) - loss = F.nll_loss(outputs, targets) - optimizer.zero_grad() - loss.backward() - optimizer.step() - print(f"loss: {loss.item()}", end="\r") - - -def valid_test(dataflow, split, model, device, qiskit=False): - target_all = [] - output_all = [] - with torch.no_grad(): - for feed_dict in dataflow[split]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs, use_qiskit=qiskit) - - target_all.append(targets) - output_all.append(outputs) - target_all = torch.cat(target_all, dim=0) - output_all = torch.cat(output_all, dim=0) - - _, indices = output_all.topk(1, dim=1) - masks = indices.eq(target_all.view(-1, 1).expand_as(indices)) - size = target_all.shape[0] - corrects = masks.sum().item() - accuracy = corrects / size - loss = F.nll_loss(output_all, target_all).item() - - print(f"{split} set accuracy: {accuracy}") - print(f"{split} set loss: {loss}") - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument( - "--static", action="store_true", help="compute with " "static mode" - ) - parser.add_argument("--pdb", action="store_true", help="debug with pdb") - parser.add_argument( - "--wires-per-block", type=int, default=2, help="wires per block int static mode" - ) - parser.add_argument( - "--epochs", type=int, default=2, help="number of training epochs" - ) - - args = parser.parse_args() - - if args.pdb: - import pdb - - pdb.set_trace() - - seed = 0 - random.seed(seed) - np.random.seed(seed) - torch.manual_seed(seed) - - dataset = MNIST( - root="./mnist_data", - train_valid_split_ratio=[0.9, 0.1], - digits_of_interest=[3, 6], - n_test_samples=75, - ) - dataflow = dict() - - for split in dataset: - sampler = torch.utils.data.RandomSampler(dataset[split]) - dataflow[split] = torch.utils.data.DataLoader( - dataset[split], - batch_size=256, - sampler=sampler, - num_workers=8, - pin_memory=True, - ) - - use_cuda = torch.cuda.is_available() - device = torch.device("cuda" if use_cuda else "cpu") - - model = QFCModel().to(device) - - n_epochs = args.epochs - optimizer = optim.Adam(model.parameters(), lr=5e-3, weight_decay=1e-4) - scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) - - if args.static: - # optionally to switch to the static mode, which can bring speedup - # on training - model.q_layer.static_on(wires_per_block=args.wires_per_block) - - for epoch in range(1, n_epochs + 1): - # train - print(f"Epoch {epoch}:") - train(dataflow, model, device, optimizer) - print(optimizer.param_groups[0]["lr"]) - - # valid - valid_test(dataflow, "valid", model, device) - scheduler.step() - - # test - valid_test(dataflow, "test", model, device, qiskit=False) - - # run on Qiskit simulator and real Quantum Computers - try: - from qiskit import IBMQ - from torchquantum.plugin import QiskitProcessor - - # firstly perform simulate - print(f"\nTest with Qiskit Simulator") - processor_simulation = QiskitProcessor(use_real_qc=False) - model.set_qiskit_processor(processor_simulation) - valid_test(dataflow, "test", model, device, qiskit=True) - - # then try to run on REAL QC - backend_name = "ibmq_lima" - print(f"\nTest on Real Quantum Computer {backend_name}") - # Please specify your own hub group and project if you have the - # IBMQ premium plan to access more machines. - processor_real_qc = QiskitProcessor( - use_real_qc=True, - backend_name=backend_name, - hub="ibm-q", - group="open", - project="main", - ) - model.set_qiskit_processor(processor_real_qc) - valid_test(dataflow, "test", model, device, qiskit=True) - except ImportError: - print( - "Please install qiskit, create an IBM Q Experience Account and " - "save the account token according to the instruction at " - "'https://github.com/Qiskit/qiskit-ibmq-provider', " - "then try again." - ) - - -if __name__ == "__main__": - main() diff --git a/examples/simple_mnist/other_implementations/mnist_example_no_binding.py b/examples/simple_mnist/other_implementations/mnist_example_no_binding.py deleted file mode 100644 index 1ac849ff..00000000 --- a/examples/simple_mnist/other_implementations/mnist_example_no_binding.py +++ /dev/null @@ -1,291 +0,0 @@ -""" -MIT License - -Copyright (c) 2020-present TorchQuantum Authors - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. -""" - -import torch -import torch.nn.functional as F -import torch.optim as optim -import argparse - -import torchquantum as tq -import torchquantum.functional as tqf - -from torchquantum.plugin import ( - tq2qiskit_expand_params, - tq2qiskit, - tq2qiskit_measurement, - qiskit_assemble_circs, -) - -from torchquantum.dataset import MNIST -from torch.optim.lr_scheduler import CosineAnnealingLR - -import random -import numpy as np - - -class QFCModel(tq.QuantumModule): - class QLayer(tq.QuantumModule): - def __init__(self): - super().__init__() - self.n_wires = 4 - self.random_layer = tq.RandomLayer( - n_ops=50, wires=list(range(self.n_wires)) - ) - - # gates with trainable parameters - self.rx0 = tq.RX(has_params=True, trainable=True) - self.ry0 = tq.RY(has_params=True, trainable=True) - self.rz0 = tq.RZ(has_params=True, trainable=True) - self.crx0 = tq.CRX(has_params=True, trainable=True) - - @tq.static_support - def forward(self, q_device: tq.QuantumDevice): - """ - 1. To convert tq QuantumModule to qiskit or run in the static - model, need to: - (1) add @tq.static_support before the forward - (2) make sure to add - static=self.static_mode and - parent_graph=self.graph - to all the tqf functions, such as tqf.hadamard below - """ - self.q_device = q_device - - self.random_layer(self.q_device) - - # some trainable gates (instantiated ahead of time) - self.rx0(self.q_device, wires=0) - self.ry0(self.q_device, wires=1) - self.rz0(self.q_device, wires=3) - self.crx0(self.q_device, wires=[0, 2]) - - # add some more non-parameterized gates (add on-the-fly) - tqf.hadamard( - self.q_device, wires=3, static=self.static_mode, parent_graph=self.graph - ) - tqf.sx( - self.q_device, wires=2, static=self.static_mode, parent_graph=self.graph - ) - tqf.cnot( - self.q_device, - wires=[3, 0], - static=self.static_mode, - parent_graph=self.graph, - ) - tqf.rx( - self.q_device, - wires=1, - params=torch.tensor([0.1]), - static=self.static_mode, - parent_graph=self.graph, - ) - - def __init__(self): - super().__init__() - self.n_wires = 4 - self.q_device = tq.QuantumDevice(n_wires=self.n_wires) - self.encoder = tq.GeneralEncoder(tq.encoder_op_list_name_dict["4x4_ryzxy"]) - - self.q_layer = self.QLayer() - self.measure = tq.MeasureAll(tq.PauliZ) - - def forward(self, x, use_qiskit=False): - self.q_device.reset_states(x.shape[0]) - bsz = x.shape[0] - x = F.avg_pool2d(x, 6).view(bsz, 16) - devi = x.device - - if use_qiskit: - encoder_circs = tq2qiskit_expand_params( - self.q_device, x, self.encoder.func_list - ) - q_layer_circ = tq2qiskit(self.q_device, self.q_layer) - measurement_circ = tq2qiskit_measurement(self.q_device, self.measure) - assembled_circs = qiskit_assemble_circs( - encoder_circs, q_layer_circ, measurement_circ - ) - x0 = self.qiskit_processor.process_ready_circs( - self.q_device, assembled_circs - ).to(devi) - # x1 = self.qiskit_processor.process_parameterized( - # self.q_device, self.encoder, self.q_layer, self.measure, x) - # print((x0-x1).max()) - x = x0 - - else: - self.encoder(self.q_device, x) - self.q_layer(self.q_device) - x = self.measure(self.q_device) - - x = x.reshape(bsz, 2, 2).sum(-1).squeeze() - x = F.log_softmax(x, dim=1) - - return x - - -def train(dataflow, model, device, optimizer): - for feed_dict in dataflow["train"]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs) - loss = F.nll_loss(outputs, targets) - optimizer.zero_grad() - loss.backward() - optimizer.step() - print(f"loss: {loss.item()}", end="\r") - - -def valid_test(dataflow, split, model, device, qiskit=False): - target_all = [] - output_all = [] - with torch.no_grad(): - for feed_dict in dataflow[split]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs, use_qiskit=qiskit) - - target_all.append(targets) - output_all.append(outputs) - target_all = torch.cat(target_all, dim=0) - output_all = torch.cat(output_all, dim=0) - - _, indices = output_all.topk(1, dim=1) - masks = indices.eq(target_all.view(-1, 1).expand_as(indices)) - size = target_all.shape[0] - corrects = masks.sum().item() - accuracy = corrects / size - loss = F.nll_loss(output_all, target_all).item() - - print(f"{split} set accuracy: {accuracy}") - print(f"{split} set loss: {loss}") - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument( - "--static", action="store_true", help="compute with " "static mode" - ) - parser.add_argument("--pdb", action="store_true", help="debug with pdb") - parser.add_argument( - "--wires-per-block", type=int, default=2, help="wires per block int static mode" - ) - parser.add_argument( - "--epochs", type=int, default=5, help="number of training epochs" - ) - - args = parser.parse_args() - - if args.pdb: - import pdb - - pdb.set_trace() - - seed = 0 - random.seed(seed) - np.random.seed(seed) - torch.manual_seed(seed) - - dataset = MNIST( - root="./mnist_data", - train_valid_split_ratio=[0.9, 0.1], - digits_of_interest=[3, 6], - n_test_samples=75, - ) - dataflow = dict() - - for split in dataset: - sampler = torch.utils.data.RandomSampler(dataset[split]) - dataflow[split] = torch.utils.data.DataLoader( - dataset[split], - batch_size=256, - sampler=sampler, - num_workers=8, - pin_memory=True, - ) - - use_cuda = torch.cuda.is_available() - device = torch.device("cuda" if use_cuda else "cpu") - - model = QFCModel().to(device) - - n_epochs = args.epochs - optimizer = optim.Adam(model.parameters(), lr=5e-3, weight_decay=1e-4) - scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) - - if args.static: - # optionally to switch to the static mode, which can bring speedup - # on training - model.q_layer.static_on(wires_per_block=args.wires_per_block) - - for epoch in range(1, n_epochs + 1): - # train - print(f"Epoch {epoch}:") - train(dataflow, model, device, optimizer) - print(optimizer.param_groups[0]["lr"]) - - # valid - valid_test(dataflow, "valid", model, device) - scheduler.step() - - # test - valid_test(dataflow, "test", model, device, qiskit=False) - - # run on Qiskit simulator and real Quantum Computers - try: - from qiskit import IBMQ - from torchquantum.plugin import QiskitProcessor - - # firstly perform simulate - print(f"\nTest with Qiskit Simulator") - processor_simulation = QiskitProcessor(use_real_qc=False) - model.set_qiskit_processor(processor_simulation) - valid_test(dataflow, "test", model, device, qiskit=True) - - # then try to run on REAL QC - backend_name = "ibmq_lima" - print(f"\nTest on Real Quantum Computer {backend_name}") - # Please specify your own hub group and project if you have the - # IBMQ premium plan to access more machines. - processor_real_qc = QiskitProcessor( - use_real_qc=True, - backend_name=backend_name, - hub="ibm-q", - group="open", - project="main", - ) - model.set_qiskit_processor(processor_real_qc) - valid_test(dataflow, "test", model, device, qiskit=True) - except ImportError: - print( - "Please install qiskit, create an IBM Q Experience Account and " - "save the account token according to the instruction at " - "'https://github.com/Qiskit/qiskit-ibmq-provider', " - "then try again." - ) - - -if __name__ == "__main__": - main() diff --git a/examples/simple_mnist/other_implementations/mnist_example_with_binding.py b/examples/simple_mnist/other_implementations/mnist_example_with_binding.py deleted file mode 100644 index 6b779c43..00000000 --- a/examples/simple_mnist/other_implementations/mnist_example_with_binding.py +++ /dev/null @@ -1,270 +0,0 @@ -""" -MIT License - -Copyright (c) 2020-present TorchQuantum Authors - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. -""" - -import torch -import torch.nn.functional as F -import torch.optim as optim -import argparse - -import torchquantum as tq -import torchquantum.functional as tqf - -from torchquantum.dataset import MNIST -from torch.optim.lr_scheduler import CosineAnnealingLR - -import random -import numpy as np - - -class QFCModel(tq.QuantumModule): - class QLayer(tq.QuantumModule): - def __init__(self): - super().__init__() - self.n_wires = 4 - self.random_layer = tq.RandomLayer( - n_ops=50, wires=list(range(self.n_wires)) - ) - - # gates with trainable parameters - self.rx0 = tq.RX(has_params=True, trainable=True) - self.ry0 = tq.RY(has_params=True, trainable=True) - self.rz0 = tq.RZ(has_params=True, trainable=True) - self.crx0 = tq.CRX(has_params=True, trainable=True) - - @tq.static_support - def forward(self, q_device: tq.QuantumDevice): - """ - 1. To convert tq QuantumModule to qiskit or run in the static - model, need to: - (1) add @tq.static_support before the forward - (2) make sure to add - static=self.static_mode and - parent_graph=self.graph - to all the tqf functions, such as tqf.hadamard below - """ - self.q_device = q_device - - self.random_layer(self.q_device) - - # some trainable gates (instantiated ahead of time) - self.rx0(self.q_device, wires=0) - self.ry0(self.q_device, wires=1) - self.rz0(self.q_device, wires=3) - self.crx0(self.q_device, wires=[0, 2]) - - # add some more non-parameterized gates (add on-the-fly) - tqf.hadamard( - self.q_device, wires=3, static=self.static_mode, parent_graph=self.graph - ) - tqf.sx( - self.q_device, wires=2, static=self.static_mode, parent_graph=self.graph - ) - tqf.cnot( - self.q_device, - wires=[3, 0], - static=self.static_mode, - parent_graph=self.graph, - ) - tqf.rx( - self.q_device, - wires=1, - params=torch.tensor([0.1]), - static=self.static_mode, - parent_graph=self.graph, - ) - - def __init__(self): - super().__init__() - self.n_wires = 4 - self.q_device = tq.QuantumDevice(n_wires=self.n_wires) - self.encoder = tq.GeneralEncoder(tq.encoder_op_list_name_dict["4x4_ryzxy"]) - - self.q_layer = self.QLayer() - self.measure = tq.MeasureAll(tq.PauliZ) - - def forward(self, x, use_qiskit=False): - self.q_device.reset_states(x.shape[0]) - bsz = x.shape[0] - x = F.avg_pool2d(x, 6).view(bsz, 16) - - if use_qiskit: - x = self.qiskit_processor.process_parameterized( - self.q_device, self.encoder, self.q_layer, self.measure, x - ) - else: - self.encoder(self.q_device, x) - self.q_layer(self.q_device) - x = self.measure(self.q_device) - - x = x.reshape(bsz, 2, 2).sum(-1).squeeze() - x = F.log_softmax(x, dim=1) - - return x - - -def train(dataflow, model, device, optimizer): - for feed_dict in dataflow["train"]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs) - loss = F.nll_loss(outputs, targets) - optimizer.zero_grad() - loss.backward() - optimizer.step() - print(f"loss: {loss.item()}", end="\r") - - -def valid_test(dataflow, split, model, device, qiskit=False): - target_all = [] - output_all = [] - with torch.no_grad(): - for feed_dict in dataflow[split]: - inputs = feed_dict["image"].to(device) - targets = feed_dict["digit"].to(device) - - outputs = model(inputs, use_qiskit=qiskit) - - target_all.append(targets) - output_all.append(outputs) - target_all = torch.cat(target_all, dim=0) - output_all = torch.cat(output_all, dim=0) - - _, indices = output_all.topk(1, dim=1) - masks = indices.eq(target_all.view(-1, 1).expand_as(indices)) - size = target_all.shape[0] - corrects = masks.sum().item() - accuracy = corrects / size - loss = F.nll_loss(output_all, target_all).item() - - print(f"{split} set accuracy: {accuracy}") - print(f"{split} set loss: {loss}") - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument( - "--static", action="store_true", help="compute with " "static mode" - ) - parser.add_argument("--pdb", action="store_true", help="debug with pdb") - parser.add_argument( - "--wires-per-block", type=int, default=2, help="wires per block int static mode" - ) - parser.add_argument( - "--epochs", type=int, default=5, help="number of training epochs" - ) - - args = parser.parse_args() - - if args.pdb: - import pdb - - pdb.set_trace() - - seed = 0 - random.seed(seed) - np.random.seed(seed) - torch.manual_seed(seed) - - dataset = MNIST( - root="./mnist_data", - train_valid_split_ratio=[0.9, 0.1], - digits_of_interest=[3, 6], - n_test_samples=75, - ) - dataflow = dict() - - for split in dataset: - sampler = torch.utils.data.RandomSampler(dataset[split]) - dataflow[split] = torch.utils.data.DataLoader( - dataset[split], - batch_size=256, - sampler=sampler, - num_workers=8, - pin_memory=True, - ) - - use_cuda = torch.cuda.is_available() - device = torch.device("cuda" if use_cuda else "cpu") - - model = QFCModel().to(device) - - n_epochs = args.epochs - optimizer = optim.Adam(model.parameters(), lr=5e-3, weight_decay=1e-4) - scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) - - if args.static: - # optionally to switch to the static mode, which can bring speedup - # on training - model.q_layer.static_on(wires_per_block=args.wires_per_block) - - for epoch in range(1, n_epochs + 1): - # train - print(f"Epoch {epoch}:") - train(dataflow, model, device, optimizer) - print(optimizer.param_groups[0]["lr"]) - - # valid - valid_test(dataflow, "valid", model, device) - scheduler.step() - - # test - valid_test(dataflow, "test", model, device, qiskit=False) - - # run on Qiskit simulator and real Quantum Computers - try: - from qiskit import IBMQ - from torchquantum.plugin import QiskitProcessor - - # firstly perform simulate - print(f"\nTest with Qiskit Simulator") - processor_simulation = QiskitProcessor(use_real_qc=False) - model.set_qiskit_processor(processor_simulation) - valid_test(dataflow, "test", model, device, qiskit=True) - - # then try to run on REAL QC - backend_name = "ibmq_lima" - print(f"\nTest on Real Quantum Computer {backend_name}") - # Please specify your own hub group and project if you have the - # IBMQ premium plan to access more machines. - processor_real_qc = QiskitProcessor( - use_real_qc=True, - backend_name=backend_name, - hub="ibm-q", - group="open", - project="main", - ) - model.set_qiskit_processor(processor_real_qc) - valid_test(dataflow, "test", model, device, qiskit=True) - except ImportError: - print( - "Please install qiskit, create an IBM Q Experience Account and " - "save the account token according to the instruction at " - "'https://github.com/Qiskit/qiskit-ibmq-provider', " - "then try again." - ) - - -if __name__ == "__main__": - main() From c29f7ff48d8f046ed545fc6c16550c2f9c4d3af2 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Tue, 29 Aug 2023 21:22:01 -0400 Subject: [PATCH 19/28] [major] fix get_unitary from a module add example --- .../train_unitary_prep/train_unitary_prep.py | 118 ++++++++++++++++++ torchquantum/module/modules.py | 34 ++--- 2 files changed, 128 insertions(+), 24 deletions(-) create mode 100644 examples/train_unitary_prep/train_unitary_prep.py diff --git a/examples/train_unitary_prep/train_unitary_prep.py b/examples/train_unitary_prep/train_unitary_prep.py new file mode 100644 index 00000000..dea7a3cf --- /dev/null +++ b/examples/train_unitary_prep/train_unitary_prep.py @@ -0,0 +1,118 @@ +""" +MIT License + +Copyright (c) 2020-present TorchQuantum Authors + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" + +import torch +import torch.optim as optim +import argparse + +import torchquantum as tq +from torch.optim.lr_scheduler import CosineAnnealingLR + +import random +import numpy as np + + +class QModel(tq.QuantumModule): + def __init__(self): + super().__init__() + self.n_wires = 2 + self.u3_0 = tq.U3(has_params=True, trainable=True) + self.u3_1 = tq.U3(has_params=True, trainable=True) + self.cu3_0 = tq.CU3(has_params=True, trainable=True) + self.cu3_1 = tq.CU3(has_params=True, trainable=True) + self.u3_2 = tq.U3(has_params=True, trainable=True) + self.u3_3 = tq.U3(has_params=True, trainable=True) + + def forward(self, q_device: tq.QuantumDevice): + self.u3_0(q_device, wires=0) + self.u3_1(q_device, wires=1) + self.cu3_0(q_device, wires=[0, 1]) + self.u3_2(q_device, wires=0) + self.u3_3(q_device, wires=1) + self.cu3_1(q_device, wires=[1, 0]) + + +def train(target_unitary, model, optimizer): + result_unitary = model.get_unitary() + + # https://link.aps.org/accepted/10.1103/PhysRevA.95.042318 unitary fidelity according to table 1 + + # compute the unitary infidelity + loss = 1 - (torch.trace(target_unitary.T.conj() @ result_unitary) / target_unitary.shape[0]).abs() ** 2 + + optimizer.zero_grad() + loss.backward() + optimizer.step() + print( + f"infidelity (loss): {loss.item()}, \n target unitary : " + f"{target_unitary.detach().cpu().numpy()}, \n " + f"result unitary : {result_unitary.detach().cpu().numpy()}\n" + ) + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument( + "--epochs", type=int, default=1000, help="number of training epochs" + ) + + parser.add_argument("--pdb", action="store_true", help="debug with pdb") + + args = parser.parse_args() + + if args.pdb: + import pdb + pdb.set_trace() + + seed = 42 + random.seed(seed) + np.random.seed(seed) + torch.manual_seed(seed) + + use_cuda = torch.cuda.is_available() + device = torch.device("cuda" if use_cuda else "cpu") + + model = QModel().to(device) + + n_epochs = args.epochs + optimizer = optim.Adam(model.parameters(), lr=1e-2, weight_decay=0) + scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) + + target_state = torch.tensor( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, 1, 0], + [0, 0, 0, 1j] + ] + , dtype=torch.complex64) + + for epoch in range(1, n_epochs + 1): + print(f"Epoch {epoch}, LR: {optimizer.param_groups[0]['lr']}") + train(target_state, model, optimizer) + scheduler.step() + + +if __name__ == "__main__": + main() diff --git a/torchquantum/module/modules.py b/torchquantum/module/modules.py index 34f2ec11..e766185c 100644 --- a/torchquantum/module/modules.py +++ b/torchquantum/module/modules.py @@ -323,7 +323,7 @@ def static_forward(self, q_device: tq.QuantumDevice): # else: # return "QuantumModule" - def get_unitary(self, q_device: tq.QuantumDevice, x=None): + def get_unitary(self, x=None): """Compute the unitary matrix for the QuantumModule with the given quantum device and input. Args: @@ -338,32 +338,18 @@ def get_unitary(self, q_device: tq.QuantumDevice, x=None): >>> q_device = tq.QuantumDevice(n_wires=2) >>> unitary = qmodule.get_unitary(q_device) """ + assert self.n_wires is not None, "n_wires should not be None, specify it in the Quantum Module \ + before calling get_unitary()" - original_wires_per_block = self.wires_per_block - original_static_mode = self.static_mode - self.static_off() - self.static_on(wires_per_block=q_device.n_wires) - self.q_device = q_device - self.device = q_device.state.device - self.graph.q_device = q_device - self.graph.device = q_device.state.device - - self.is_graph_top = False - # forward to register all modules to the module list, but do not - # apply the unitary to the state vector + qdev = tq.QuantumDevice(n_wires=self.n_wires) + qdev.reset_identity_states() + if x is None: - self.forward(q_device) + self.forward(qdev) else: - self.forward(q_device, x) - self.is_graph_top = True - - self.graph.build(wires_per_block=q_device.n_wires) - self.graph.build_static_matrix() - unitary = self.graph.get_unitary() - - self.static_off() - if original_static_mode: - self.static_on(original_wires_per_block) + self.forward(qdev, x) + + unitary = qdev.get_states_1d().T return unitary From 179dbfd885ea348f0f6afd0dc02506e39749754b Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Tue, 29 Aug 2023 21:23:15 -0400 Subject: [PATCH 20/28] [minor] fixed typo --- examples/train_unitary_prep/train_unitary_prep.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/train_unitary_prep/train_unitary_prep.py b/examples/train_unitary_prep/train_unitary_prep.py index dea7a3cf..6bf2dcf9 100644 --- a/examples/train_unitary_prep/train_unitary_prep.py +++ b/examples/train_unitary_prep/train_unitary_prep.py @@ -99,7 +99,7 @@ def main(): optimizer = optim.Adam(model.parameters(), lr=1e-2, weight_decay=0) scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) - target_state = torch.tensor( + target_unitary = torch.tensor( [ [1, 0, 0, 0], [0, 1, 0, 0], @@ -110,7 +110,7 @@ def main(): for epoch in range(1, n_epochs + 1): print(f"Epoch {epoch}, LR: {optimizer.param_groups[0]['lr']}") - train(target_state, model, optimizer) + train(target_unitary, model, optimizer) scheduler.step() From 5c179070e054ffb1afa2513b4810e920705f07a7 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Tue, 29 Aug 2023 21:58:36 -0400 Subject: [PATCH 21/28] [major] fix critical bug in qiskit2tq_Operator --- torchquantum/plugin/qiskit/qiskit_plugin.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/torchquantum/plugin/qiskit/qiskit_plugin.py b/torchquantum/plugin/qiskit/qiskit_plugin.py index e407ada3..6b533b3f 100644 --- a/torchquantum/plugin/qiskit/qiskit_plugin.py +++ b/torchquantum/plugin/qiskit/qiskit_plugin.py @@ -754,7 +754,8 @@ def qiskit2tq_Operator(circ: QuantumCircuit): raise NotImplementedError( f"{op_name} conversion to tq is currently not supported." ) - return ops + + return ops def qiskit2tq(circ: QuantumCircuit): From 66666309d96956b75720ca7aca88bccc12cebd96 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Wed, 30 Aug 2023 00:22:45 -0400 Subject: [PATCH 22/28] [minor] update QuantumNAT code --- examples/quantumnat/quantize.py | 298 ++++++++++++++++++++++++++++++ examples/quantumnat/quantumnat.py | 80 ++++---- 2 files changed, 331 insertions(+), 47 deletions(-) create mode 100644 examples/quantumnat/quantize.py diff --git a/examples/quantumnat/quantize.py b/examples/quantumnat/quantize.py new file mode 100644 index 00000000..ff305952 --- /dev/null +++ b/examples/quantumnat/quantize.py @@ -0,0 +1,298 @@ +''' +Description: +Author: Jiaqi Gu (jqgu@utexas.edu) +Date: 2021-05-09 21:28:08 +LastEditors: Jiaqi Gu (jqgu@utexas.edu) +LastEditTime: 2021-05-11 01:19:11 +''' +from typing import Optional + +import torch +from torch import Tensor +from torch.types import Device +from torchpack.utils.logging import logger + + +__all__ = ["PACTActivationQuantizer"] + + +# PACT activation: https://arxiv.org/pdf/1805.06085.pdf + + +class PACTQuantFunc(torch.autograd.Function): + r"""PACT (PArametrized Clipping acTivation) quantization function for activations. + Implements a :py:class:`torch.autograd.Function` for quantizing activations in :math:`Q` bits using the PACT strategy. + In forward propagation, the function is defined as + + .. math:: + \mathbf{y} = f(\mathbf{x}) = 1/\varepsilon \cdot \left\lfloor\mathrm{clip}_{ [0,\alpha) } (\mathbf{x})\right\rfloor \cdot \varepsilon + + where :math:`\varepsilon` is the quantization precision: + + .. math:: + \varepsilon = \alpha / (2^Q - 1) + + In backward propagation, using the Straight-Through Estimator, the gradient of the function is defined as + + .. math:: + \mathbf{\nabla}_\mathbf{x} \mathcal{L} &\doteq \mathbf{\nabla}_\mathbf{y} \mathcal{L} + + It can be applied by using its static `.apply` method: + + :param input: the tensor containing :math:`x`, the activations to be quantized. + :type input: `torch.Tensor` + :param eps: the precomputed value of :math:`\varepsilon`. + :type eps: `torch.Tensor` or float + :param alpha: the value of :math:`\alpha`. + :type alpha: `torch.Tensor` or float + :param delta: constant to sum to `eps` for numerical stability (default unused, 0 ). + :type delta: `torch.Tensor` or float + + :return: The quantized input activations tensor. + :rtype: `torch.Tensor` + """ + + @staticmethod + def forward(ctx, input, level, alpha, quant_noise_mask, lower_bound, + upper_bound): + # where_input_clipped = (input < -1) | (input > alpha) + # where_input_ltalpha = (input < alpha) + # ctx.save_for_backward(where_input_clipped, where_input_ltalpha) + # upper_thres = alpha.data[0]-eps.data[0] + input = input.clamp(lower_bound, upper_bound) + input = input - lower_bound + eps = (upper_bound - lower_bound) / (level - 1) + input_q = (input / eps).round() * eps + lower_bound + + # input_q = input.div(eps).floor_().mul_(eps) + + if quant_noise_mask is not None: + return input_q.data.sub_(input.data).masked_fill_(quant_noise_mask, 0).add_(input) + else: + return input_q + + @staticmethod + def backward(ctx, grad_output): + # see Hubara et al., Section 2.3 + # where_input_clipped, where_input_ltalpha = ctx.saved_tensors + # grad_input = grad_output.masked_fill(where_input_clipped, 0) + # if ctx.needs_input_grad[2]: + # grad_alpha = grad_output.masked_fill( + # where_input_ltalpha, 0).sum().expand(1) + # else: + # grad_alpha = None + grad_input = grad_output + return grad_input, None, None, None, None, None + + +pact_quantize = PACTQuantFunc.apply + + +class PACTActivationQuantizer(torch.nn.Module): + r"""PACT (PArametrized Clipping acTivation) activation. + Implements a :py:class:`torch.nn.Module` to implement PACT-style activations. It is meant to replace :py:class:`torch.nn.ReLU`, :py:class:`torch.nn.ReLU6` and + similar activations in a PACT-quantized network. + This layer can also operate in a special mode, defined by the `statistics_only` member, in which the layer runs in + forward-prop without quantization, collecting statistics on the activations that can then be + used to reset the value of :math:`\alpha`. + In this mode, the layer collects: + - tensor-wise maximum value ever seen + - running average with momentum 0.9 + - running variance with momentum 0.9 + """ + + def __init__(self, module: torch.nn.Module, precision: Optional[float]=None, level=None, alpha: float = 1.0, backprop_alpha: bool = True, + statistics_only: bool = False, leaky: Optional[float] = + None, quant_ratio: float = 1.0, device: Device = + torch.device("cuda"), lower_bound=-2, upper_bound=2) -> None: + r"""Constructor. Initializes a :py:class:`torch.nn.Parameter` for :math:`\alpha` and sets + up the initial value of the `statistics_only` member. + :param precision: instance defining the current quantization level (default `None`). + :type precision: : bitwidth + :param alpha: the value of :math:`\alpha`. + :type alpha: `torch.Tensor` or float + :param backprop_alpha: default `True`; if `False`, do not update the value of `\alpha` with backpropagation. + :type backprop_alpha: bool + :param statistics_only: initialization value of `statistics_only` member. + :type statistics_only: bool + :param leaky: leaky relu alpha + :type leaky: float + :param quant_ratio: quantization ratio used in QuantNoise [ICLR'21] + :type quant_ratio: float + """ + + super().__init__() + self.module = module + self.precision = precision + self.level = level + self.device = device + self.alpha = torch.nn.Parameter(torch.tensor( + (alpha,), device=device), requires_grad=backprop_alpha) + self.alpha_p = alpha + self.statistics_only = statistics_only + self.deployment = False + self.eps_in = None + self.leaky = leaky + self.lower_bound = lower_bound + self.upper_bound = upper_bound + + # these are only used to gather statistics + self.max = torch.nn.Parameter(torch.zeros_like( + self.alpha.data), requires_grad=False) + self.min = torch.nn.Parameter(torch.zeros_like( + self.alpha.data), requires_grad=False) + self.running_mean = torch.nn.Parameter( + torch.zeros_like(self.alpha.data), requires_grad=False) + self.running_var = torch.nn.Parameter( + torch.ones_like(self.alpha.data), requires_grad=False) + + self.precise = False + + # set quant noise ratio + self.set_quant_ratio(quant_ratio) + + ## quantization hook + self.handle = None + # self.register_hook() + + def set_static_precision(self, limit_at_32_bits: bool = True, **kwargs) -> None: + r"""Sets static parameters used only for deployment. + """ + # item() --> conversion to float + # apparently causes a slight, but not invisibile, numerical divergence + # between FQ and QD stages + self.eps_static = self.alpha.clone().detach()/(2.0**(self.precision)-1) + self.alpha_static = self.alpha.clone().detach() + # D is selected as a power-of-two + D = 2.0**torch.ceil(torch.log2(self.requantization_factor * + self.eps_static / self.eps_in)) + if not limit_at_32_bits: + self.D = D + else: + self.D = min(D, 2.0**(32-1-(self.precision))) + + def get_output_eps(self, eps_in: Tensor) -> Tensor: + r"""Get the output quantum (:math:`\varepsilon`) given the input one. + :param eps_in: input quantum :math:`\varepsilon_{in}`. + :type eps_in: :py:class:`torch.Tensor` + :return: output quantum :math:`\varepsilon_{out}`. + :rtype: :py:class:`torch.Tensor` + """ + + return self.alpha/(2.0**(self.precision)-1) + + def reset_alpha(self, use_max: bool = True, nb_std: float = 5.0) -> None: + r"""Reset the value of :math:`\alpha`. If `use_max` is `True`, then the highest tensor-wise value collected + in the statistics collection phase is used. If `False`, the collected standard deviation multiplied by + `nb_std` is used as a parameter + :param use_max: if True, use the tensor-wise maximum value collected in the statistics run as new :math:`\alpha` (default True). + :type use_max: bool + :param nb_std: number of standard deviations to be used to initialize :math:`\alpha` if `use_max` is False. + :type nb_std: float + """ + + if use_max: + self.alpha.data.copy_(self.max) + else: + self.alpha.data.copy_(self.running_var.data.sqrt().mul(nb_std)) + + def get_statistics(self): + r"""Returns the statistics collected up to now. + + :return: The collected statistics (maximum, running average, running variance). + :rtype: tuple of floats + """ + return self.max.item(), self.running_mean.item(), self.running_var.item() + + def set_quant_ratio(self, quant_ratio=None): + if(quant_ratio is None): + # get recommended value + quant_ratio = [None, 0.2, 0.3, 0.4, 0.5, 0.55, 0.6, 0.7, 0.8, 0.83, + 0.86, 0.89, 0.92, 0.95, 0.98, 0.99, 1][min(self.precision, 16)] + assert 0 <= quant_ratio <= 1, logger.error( + f"Wrong quant ratio. Must in [0,1], but got {quant_ratio}") + self.quant_ratio = quant_ratio + + def register_hook(self): + + def quantize_hook(module, x, y): + r"""Forward-prop function for PACT-quantized activations. + + See :py:class:`nemo.quant.pact_quant.PACT_QuantFunc` for details on the normal operation performed by this layer. + In statistics mode, it uses a normal ReLU and collects statistics in the background. + :param x: input activations tensor. + :type x: :py:class:`torch.Tensor` + + :return: output activations tensor. + :rtype: :py:class:`torch.Tensor` + """ + + if self.statistics_only: + if self.leaky is None: + y = torch.nn.functional.relu(y, inplace=True) + else: + y = torch.nn.functional.leaky_relu(y, self.leaky, inplace=True) + with torch.no_grad(): + self.max[:] = max(self.max.item(), y.max()) + self.min[:] = min(self.min.item(), y.min()) + self.running_mean[:] = 0.9 * \ + self.running_mean.item() + 0.1 * y.mean() + self.running_var[:] = 0.9 * \ + self.running_var.item() + 0.1 * y.std()*y.std() + return y + else: + # QuantNoise ICLR 2021 + if(self.quant_ratio < 1 and module.training): + # implementation from fairseq + # must fully quantize during inference + quant_noise_mask = torch.empty_like( + y, dtype=torch.bool).bernoulli_(1-self.quant_ratio) + else: + quant_noise_mask = None + if self.level is not None: + level = self.level + else: + level = 2 ** self.precision + # eps = self.alpha/(2.0**(self.precision)-1) + return pact_quantize(y, level, self.alpha, quant_noise_mask, + self.lower_bound, self.upper_bound) + + # register hook + self.handle = self.module.register_forward_hook(quantize_hook) + return self.handle + + def remove_hook(self) -> None: + ## remove the forward hook + if(self.handle is not None): + self.handle.remove() + + +if __name__ == "__main__": + import pdb + pdb.set_trace() + device = torch.device("cuda") + class Model(torch.nn.Module): + def __init__(self) -> None: + super().__init__() + + def forward(self, x): + y = x + 0.3 + return y + model = Model().to(device) + model.train() + quantizer = PACTActivationQuantizer(module=model, precision=4, + quant_ratio=0.1, device=device, + backprop_alpha=False) + quantizer.set_quant_ratio(0.8) + torch.manual_seed(10) + torch.cuda.manual_seed_all(10) + x = torch.randn(4,4, device=device, requires_grad=True) + y = model(x) + loss = y.sum() + loss.backward() + print(x) + print(y) + print(quantizer.alpha.data) + print(quantizer.alpha.grad) + + \ No newline at end of file diff --git a/examples/quantumnat/quantumnat.py b/examples/quantumnat/quantumnat.py index 14ca8182..35a7042e 100644 --- a/examples/quantumnat/quantumnat.py +++ b/examples/quantumnat/quantumnat.py @@ -54,6 +54,8 @@ import random import numpy as np +from quantize import PACTActivationQuantizer + class QFCModel(tq.QuantumModule): class QLayer(tq.QuantumModule): @@ -101,6 +103,7 @@ def __init__(self): self.q_layer = self.QLayer() self.measure = tq.MeasureAll(tq.PauliZ) + self.norm = torch.nn.BatchNorm1d(self.n_wires) def forward(self, x, use_qiskit=False): qdev = tq.QuantumDevice(n_wires=self.n_wires, bsz=x.shape[0], device=x.device, record_op=True) @@ -125,9 +128,9 @@ def forward(self, x, use_qiskit=False): self.encoder(qdev, x) self.q_layer(qdev) x = self.measure(qdev) - - x = x.reshape(bsz, 2, 2).sum(-1).squeeze() - x = F.log_softmax(x, dim=1) + + # simplified version of post-measurement normalization, implemented with batch norm + x = self.norm(x) return x @@ -138,6 +141,11 @@ def train(dataflow, model, device, optimizer): targets = feed_dict["digit"].to(device) outputs = model(inputs) + + bsz = outputs.shape[0] + outputs = outputs.reshape(bsz, 2, 2).sum(-1).squeeze() + outputs = F.log_softmax(outputs, dim=1) + loss = F.nll_loss(outputs, targets) optimizer.zero_grad() loss.backward() @@ -154,6 +162,9 @@ def valid_test(dataflow, split, model, device, qiskit=False): targets = feed_dict["digit"].to(device) outputs = model(inputs, use_qiskit=qiskit) + bsz = outputs.shape[0] + outputs = outputs.reshape(bsz, 2, 2).sum(-1).squeeze() + outputs = F.log_softmax(outputs, dim=1) target_all.append(targets) output_all.append(outputs) @@ -177,9 +188,7 @@ def main(): "--static", action="store_true", help="compute with " "static mode" ) parser.add_argument("--pdb", action="store_true", help="debug with pdb") - parser.add_argument( - "--wires-per-block", type=int, default=2, help="wires per block int static mode" - ) + parser.add_argument( "--epochs", type=int, default=30, help="number of training epochs" ) @@ -244,77 +253,54 @@ def main(): model.measure.set_v_c_reg_mapping(get_v_c_reg_mapping(circ_transpiled)) model.q_layer = q_layer + # noise inject, initilized this noise model which will inject noise to gates noise_model_tq = tq.NoiseModelTQ( noise_model_name="ibmq_quito", n_epochs=n_epochs, # noise_total_prob=0.5, # ignored_ops=configs.trainer.ignored_noise_ops, - factor=1, + factor=10, add_thermal=True, ) noise_model_tq.is_add_noise = True - # noise_model_tq.v_c_reg_mapping = {'v2c': {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6}, - # 'c2v': {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6}, - # } - # noise_model_tq.p_c_reg_mapping = {'p2c': {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6}, - # 'c2p': {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6}, - # } - # noise_model_tq.p_v_reg_mapping ={'p2v': {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6}, - # 'v2p': {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6}, - # } noise_model_tq.v_c_reg_mapping = get_v_c_reg_mapping(circ_transpiled) noise_model_tq.p_c_reg_mapping = get_p_c_reg_mapping(circ_transpiled) noise_model_tq.p_v_reg_mapping = get_p_v_reg_mapping(circ_transpiled) - model.set_noise_model_tq(noise_model_tq) + # model.set_noise_model_tq(noise_model_tq) optimizer = optim.Adam(model.parameters(), lr=5e-3, weight_decay=1e-4) scheduler = CosineAnnealingLR(optimizer, T_max=n_epochs) - if args.static: - # optionally to switch to the static mode, which can bring speedup - # on training - model.q_layer.static_on(wires_per_block=args.wires_per_block) + # post-training quantization quantizer, in this model, there is only one node, meaning the output of the quantum layer is not encoded + # again in the later quantum layer. post-training quantization is more effective for multi-node models. + quantizer = PACTActivationQuantizer( + module=model, + precision=4, + alpha=1.0, + backprop_alpha=False, + device=device, + lower_bound=-5, + upper_bound=5, + ) for epoch in range(1, n_epochs + 1): # train print(f"Epoch {epoch}:") + quantizer.register_hook() train(dataflow, model, device, optimizer) print(optimizer.param_groups[0]["lr"]) # valid valid_test(dataflow, "valid", model, device) scheduler.step() + quantizer.remove_hook() + print(noise_model_tq.noise_counter) # test valid_test(dataflow, "test", model, device, qiskit=False) - # run on Qiskit simulator and real Quantum Computers - try: - from qiskit import IBMQ - - # firstly perform simulate - print(f"\nTest with Qiskit Simulator") - backend_name = "ibmq_quito" - processor_simulation = QiskitProcessor(use_real_qc=False, noise_model_name=backend_name) - model.set_qiskit_processor(processor_simulation) - valid_test(dataflow, "test", model, device, qiskit=True) - # valid_test(dataflow, "valid", model, device, qiskit=True) - - # then try to run on REAL QC - print(f"\nTest on Real Quantum Computer {backend_name}") - processor_real_qc = QiskitProcessor(use_real_qc=True, backend_name=backend_name) - model.set_qiskit_processor(processor_real_qc) - valid_test(dataflow, "test", model, device, qiskit=True) - except ImportError: - print( - "Please install qiskit, create an IBM Q Experience Account and " - "save the account token according to the instruction at " - "'https://github.com/Qiskit/qiskit-ibmq-provider', " - "then try again." - ) - if __name__ == "__main__": - main() \ No newline at end of file + main() From af0bc60220317d48159c2582c97676e00441e8b3 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Wed, 30 Aug 2023 20:46:04 -0400 Subject: [PATCH 23/28] [minor] expand_param supports fixed gate --- examples/mnist/mnist.py | 2 +- torchquantum/encoding/encodings.py | 14 ++++++++++++++ torchquantum/plugin/qiskit/qiskit_plugin.py | 9 +++++++-- 3 files changed, 22 insertions(+), 3 deletions(-) diff --git a/examples/mnist/mnist.py b/examples/mnist/mnist.py index 65276e91..23e5eafe 100644 --- a/examples/mnist/mnist.py +++ b/examples/mnist/mnist.py @@ -79,7 +79,7 @@ def forward(self, qdev: tq.QuantumDevice): def __init__(self): super().__init__() self.n_wires = 4 - self.encoder = tq.GeneralEncoder(tq.encoder_op_list_name_dict["4x4_u3rx"]) + self.encoder = tq.GeneralEncoder(tq.encoder_op_list_name_dict["4x4_u3_h_rx"]) self.q_layer = self.QLayer() self.measure = tq.MeasureAll(tq.PauliZ) diff --git a/torchquantum/encoding/encodings.py b/torchquantum/encoding/encodings.py index e519181b..f8d2056d 100644 --- a/torchquantum/encoding/encodings.py +++ b/torchquantum/encoding/encodings.py @@ -301,6 +301,20 @@ def __init__(self): {"input_idx": [12, 13, 14], "func": "u3", "wires": [3]}, {"input_idx": [15], "func": "rx", "wires": [3]}, ], + "4x4_u3_h_rx": [ + {"input_idx": [0, 1, 2], "func": "u3", "wires": [0]}, + {"input_idx": [3], "func": "rx", "wires": [0]}, + {"func": "h", "wires": [0]}, + {"func": "h", "wires": [1]}, + {"func": "h", "wires": [2]}, + {"func": "h", "wires": [3]}, + {"input_idx": [4, 5, 6], "func": "u3", "wires": [1]}, + {"input_idx": [7], "func": "rx", "wires": [1]}, + {"input_idx": [8, 9, 10], "func": "u3", "wires": [2]}, + {"input_idx": [11], "func": "rx", "wires": [2]}, + {"input_idx": [12, 13, 14], "func": "u3", "wires": [3]}, + {"input_idx": [15], "func": "rx", "wires": [3]}, + ], "4x4_ryzxy": [ {"input_idx": [0], "func": "ry", "wires": [0]}, {"input_idx": [1], "func": "ry", "wires": [1]}, diff --git a/torchquantum/plugin/qiskit/qiskit_plugin.py b/torchquantum/plugin/qiskit/qiskit_plugin.py index 6b533b3f..954c3b8a 100644 --- a/torchquantum/plugin/qiskit/qiskit_plugin.py +++ b/torchquantum/plugin/qiskit/qiskit_plugin.py @@ -661,10 +661,15 @@ def op_history2qiskit_expand_params(n_wires, op_history, bsz): for i in range(bsz): circ = QuantumCircuit(n_wires) for op in op_history: + if "params" in op.keys() and op["params"] is not None: + param = op["params"][i] + else: + param = None + append_fixed_gate( - circ, op["name"], op["params"][i], op["wires"], op["inverse"] + circ, op["name"], param, op["wires"], op["inverse"] ) - + circs_all.append(circ) return circs_all From 2422ce9a9216bf4346f06dfb45b391167e9cf433 Mon Sep 17 00:00:00 2001 From: Teague Tomesh Date: Thu, 31 Aug 2023 12:53:16 -0500 Subject: [PATCH 24/28] Update module path to qiskit_unitary_gate --- torchquantum/plugin/qiskit/qiskit_plugin.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/torchquantum/plugin/qiskit/qiskit_plugin.py b/torchquantum/plugin/qiskit/qiskit_plugin.py index 954c3b8a..9dca0649 100644 --- a/torchquantum/plugin/qiskit/qiskit_plugin.py +++ b/torchquantum/plugin/qiskit/qiskit_plugin.py @@ -274,7 +274,7 @@ def append_fixed_gate(circ, func, params, wires, inverse): circ.swap(*wires) elif func == "sswap": # square root of swap - from torchquantum.plugin.qiskit_unitary_gate import UnitaryGate + from torchquantum.plugin.qiskit.qiskit_unitary_gate import UnitaryGate mat = mat_dict["sswap"].detach().cpu().numpy() mat = switch_little_big_endian_matrix(mat) @@ -308,7 +308,7 @@ def append_fixed_gate(circ, func, params, wires, inverse): or func == "qubitunitaryfast" or func == "qubitunitarystrict" ): - from torchquantum.plugin.qiskit_unitary_gate import UnitaryGate + from torchquantum.plugin.qiskit.qiskit_unitary_gate import UnitaryGate mat = np.array(params) mat = switch_little_big_endian_matrix(mat) @@ -512,7 +512,7 @@ def tq2qiskit( circ.swap(*module.wires) elif module.name == "SSWAP": # square root of swap - from torchquantum.plugin.qiskit_unitary_gate import UnitaryGate + from torchquantum.plugin.qiskit.qiskit_unitary_gate import UnitaryGate mat = module.matrix.data.cpu().numpy() mat = switch_little_big_endian_matrix(mat) @@ -547,7 +547,7 @@ def tq2qiskit( or module.name == "TrainableUnitary" or module.name == "TrainableUnitaryStrict" ): - from torchquantum.plugin.qiskit_unitary_gate import UnitaryGate + from torchquantum.plugin.qiskit.qiskit_unitary_gate import UnitaryGate mat = module.params[0].data.cpu().numpy() mat = switch_little_big_endian_matrix(mat) From 810c4febf35cf43c74ea35a2116b6ccc66fcf31e Mon Sep 17 00:00:00 2001 From: GenericP3rson <41024739+GenericP3rson@users.noreply.github.com> Date: Fri, 1 Sep 2023 20:04:53 -0400 Subject: [PATCH 25/28] [minor] update example paths in readme --- README.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 57501fb3..9105e0f8 100644 --- a/README.md +++ b/README.md @@ -165,11 +165,11 @@ print(tq.measure(x, n_shots=2048)) We also prepare many example and tutorials using TorchQuantum. -For **beginning level**, you may check [QNN for MNIST](examples/simple_mnist), [Quantum Convolution (Quanvolution)](examples/quanvolution) and [Quantum Kernel Method](examples/quantum_kernel_method), and [Quantum Regression](examples/regression). +For **beginning level**, you may check [QNN for MNIST](examples/mnist), [Quantum Convolution (Quanvolution)](examples/quanvolution) and [Quantum Kernel Method](examples/quantum_kernel_method), and [Quantum Regression](examples/regression). For **intermediate level**, you may check [Amplitude Encoding for MNIST](examples/amplitude_encoding_mnist), [Clifford gate QNN](examples/clifford_qnn), [Save and Load QNN models](examples/save_load_example), [PauliSum Operation](examples/PauliSumOp), [How to convert tq to Qiskit](examples/converter_tq_qiskit). -For **expert**, you may check [Parameter Shift on-chip Training](examples/param_shift_onchip_training), [VQA Gradient Pruning](examples/gradient_pruning), [VQE](examples/simple_vqe), [VQA for State Prepration](examples/train_state_prep), [QAOA (Quantum Approximate Optimization Algorithm)](examples/qaoa). +For **expert**, you may check [Parameter Shift on-chip Training](examples/param_shift_onchip_training), [VQA Gradient Pruning](examples/gradient_pruning), [VQE](examples/vqe), [VQA for State Prepration](examples/train_state_prep), [QAOA (Quantum Approximate Optimization Algorithm)](examples/qaoa). ## Usage @@ -238,8 +238,8 @@ Train a quantum circuit to perform VQE task. Quito quantum computer as in [simple_vqe.py](./examples/simple_vqe/simple_vqe.py) script: ```python -cd examples/simple_vqe -python simple_vqe.py +cd examples/vqe +python vqe.py ``` ## MNIST Example @@ -248,8 +248,8 @@ Train a quantum circuit to perform MNIST classification task and deploy on the r Quito quantum computer as in [mnist_example.py](./examples/simple_mnist/mnist_example_no_binding.py) script: ```python -cd examples/simple_mnist -python mnist_example.py +cd examples/mnist +python mnist.py ``` ## Files From 70f877cf91bd358c775afc9085cc0e2b6d2a8d50 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Sat, 2 Sep 2023 14:06:54 -0400 Subject: [PATCH 26/28] Update hardware.py --- torchquantum/pulse/hardware/hardware.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/torchquantum/pulse/hardware/hardware.py b/torchquantum/pulse/hardware/hardware.py index cd63fd6c..db3e6b0b 100644 --- a/torchquantum/pulse/hardware/hardware.py +++ b/torchquantum/pulse/hardware/hardware.py @@ -7,5 +7,5 @@ class Hardware(torch.nn.Modele): - def __init__(self,): - + def __init__(self): + pass From 4b0bc11a2a57eb37cea34511a4b5147d318127c6 Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Sat, 2 Sep 2023 14:10:50 -0400 Subject: [PATCH 27/28] Update hardware.py --- torchquantum/pulse/hardware/hardware.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchquantum/pulse/hardware/hardware.py b/torchquantum/pulse/hardware/hardware.py index db3e6b0b..76e78bf5 100644 --- a/torchquantum/pulse/hardware/hardware.py +++ b/torchquantum/pulse/hardware/hardware.py @@ -6,6 +6,6 @@ -class Hardware(torch.nn.Modele): +class Hardware(torch.nn.Module): def __init__(self): pass From 8f40ff3abcbbf66f10eef63571284b59d0b7908c Mon Sep 17 00:00:00 2001 From: Hanrui Wang Date: Sat, 2 Sep 2023 14:27:33 -0400 Subject: [PATCH 28/28] [minor] remove pulse/hardware folder --- torchquantum/pulse/hardware/__init__.py | 1 - torchquantum/pulse/hardware/hardware.py | 11 ----------- 2 files changed, 12 deletions(-) delete mode 100644 torchquantum/pulse/hardware/__init__.py delete mode 100644 torchquantum/pulse/hardware/hardware.py diff --git a/torchquantum/pulse/hardware/__init__.py b/torchquantum/pulse/hardware/__init__.py deleted file mode 100644 index d7e1c466..00000000 --- a/torchquantum/pulse/hardware/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .hardware import hardware diff --git a/torchquantum/pulse/hardware/hardware.py b/torchquantum/pulse/hardware/hardware.py deleted file mode 100644 index 76e78bf5..00000000 --- a/torchquantum/pulse/hardware/hardware.py +++ /dev/null @@ -1,11 +0,0 @@ -import torch -import numpy as np -import torchquantum as tq -import torchdiffeq - - - - -class Hardware(torch.nn.Module): - def __init__(self): - pass