NB2-QC-2_Bit.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from qiskit import(\n",
    "  QuantumCircuit,\n",
    "  execute,\n",
    "  Aer)\n",
    "from qiskit.visualization import plot_histogram\n",
    "from qiskit.visualization import plot_bloch_multivector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use Aer's qasm_simulator\n",
    "simulator1 = Aer.get_backend('qasm_simulator')\n",
    "simulator2 = Aer.get_backend('statevector_simulator')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Aer Simulators:\n",
    "QasmSimulator: Allows ideal and noisy multi-shot execution of qiskit\n",
    "circuits and returns counts or memory.\n",
    "\n",
    "UnitarySimulator: Allows ideal single-shot execution of qiskit\n",
    "circuits and returns the final unitary matrix of the circuit itself.\n",
    "\n",
    "StatevectorSimulator: Allows ideal single-shot execution of qiskit\n",
    "circuits and returns the final statevector of the simulator after \n",
    "application."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a Quantum Circuit acting on the q register\n",
    "circuit = QuantumCircuit(2, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x153ffef7488>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add a H gate on qubit 0\n",
    "circuit.h(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "$H = \\tfrac{1}{\\sqrt{2}}\\begin{bmatrix} 1 & 1 \\\\ 1 & -1 \\end{bmatrix}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#This puts the qubit 0 into a superposition state.\n",
    "#|ψ⟩=(|00⟩+|11⟩)/√2\n",
    "# Its qbit 1 then H puts it to |ψ⟩=(|00⟩ - |11⟩)/√2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x153fff00e08>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add a CX (CNOT) gate on control qubit 0 and target qubit 1\n",
    "circuit.cx(0, 1)\n",
    "#A controlled-Not operation (CX) on control qubit 0 and target qubit 1,\n",
    "#putting the qubits in an entangled state."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "The CNOT gate operates on a quantum register consisting of 2 qubits. The CNOT gate flips the second qubit (the target qubit) if and only if the first qubit (the control qubit) is |1>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x153fff047c8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Map the quantum measurement to the classical bits\n",
    "# Syntax: circuit.measure(qubit, cbit)\n",
    "circuit.measure([0,1], [0,1])\n",
    "# if you pass the entire quantum and classical registers to measure,\n",
    "#the ith qubit’s measurement result will be stored in the ith classical bit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Execute the circuit on the qasm simulator for 1000 times\n",
    "job1 = execute(circuit, simulator1, shots=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Grab results from the job\n",
    "result1 = job1.result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total count for 00 and 11 are: {'00': 496, '11': 504}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">        ┌───┐     ┌─┐   \n",
       "q_0: |0>┤ H ├──■──┤M├───\n",
       "        └───┘┌─┴─┐└╥┘┌─┐\n",
       "q_1: |0>─────┤ X ├─╫─┤M├\n",
       "             └───┘ ║ └╥┘\n",
       " c_0: 0 ═══════════╩══╬═\n",
       "                      ║ \n",
       " c_1: 0 ══════════════╩═\n",
       "                        </pre>"
      ],
      "text/plain": [
       "<qiskit.visualization.text.TextDrawing at 0x153ffef7208>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Returns counts\n",
    "counts = result1.get_counts(circuit)\n",
    "print(\"\\nTotal count for 00 and 11 are:\",counts)\n",
    "\n",
    "# Draw the circuit\n",
    "circuit.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot a histogram\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Read about Qiskit Elements Here: \n",
    " https://qiskit.org/documentation/the_elements.html   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.+0.j 0.+0.j 0.+0.j 1.+0.j]\n"
     ]
    }
   ],
   "source": [
    "# Find the output state of above transformation\n",
    "job2 = execute(circuit, simulator2)\n",
    "result2=job2.result()\n",
    "outputstate = result2.get_statevector(circuit, decimals=3)\n",
    "print(outputstate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ok! Let's grab a pen and paper and see if this answer is correct!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total count for 00 and 11 are: {'00': 1000}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">             ┌─┐   \n",
       "q_0: |0>──■──┤M├───\n",
       "        ┌─┴─┐└╥┘┌─┐\n",
       "q_1: |0>┤ X ├─╫─┤M├\n",
       "        └───┘ ║ └╥┘\n",
       " c_0: 0 ══════╩══╬═\n",
       "                 ║ \n",
       " c_1: 0 ═════════╩═\n",
       "                   </pre>"
      ],
      "text/plain": [
       "<qiskit.visualization.text.TextDrawing at 0x153ffef4488>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking how C-NOT works by itself!\n",
    "circuit = QuantumCircuit(2, 2)\n",
    "circuit.cx(0, 1)\n",
    "circuit.measure([0,1], [0,1])\n",
    "job1 = execute(circuit, simulator1, shots=1000)\n",
    "result3 = job1.result()\n",
    "counts = result3.get_counts(circuit)\n",
    "print(\"\\nTotal count for 00 and 11 are:\",counts)\n",
    "# Draw the circuit\n",
    "circuit.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot a histogram\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Looks like NOT gate does not do anything. \n",
    "# What if |01> ?\n",
    "#Turns out C-NOT gate is not the classical NOT Gate.\n",
    "# The controlled NOT gate (or CNOT or cX) acts on 2 qubits,\n",
    "#and performs the NOT operation on the second qubit only when the first\n",
    "#qubit is |1> otherwise leaves it unchanged.\n",
    "# Upon gooling Pauli-X gate is NOT gate.\n",
    "# Lets apply Pauli_X gate 2nd bit and the do C-NOT!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "$X|0>=\\begin{bmatrix} 0 & 1\\\\ 1 & 0 \\end{bmatrix} \\begin{bmatrix} 1 \\\\ 0 \\end{bmatrix} = \\begin{bmatrix} 0 \\\\ 1 \\end{bmatrix} = |1>$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total count for 00 and 11 are: {'10': 1000}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">                  ┌─┐   \n",
       "q_0: |0>───────■──┤M├───\n",
       "        ┌───┐┌─┴─┐└╥┘┌─┐\n",
       "q_1: |0>┤ X ├┤ X ├─╫─┤M├\n",
       "        └───┘└───┘ ║ └╥┘\n",
       " c_0: 0 ═══════════╩══╬═\n",
       "                      ║ \n",
       " c_1: 0 ══════════════╩═\n",
       "                        </pre>"
      ],
      "text/plain": [
       "<qiskit.visualization.text.TextDrawing at 0x1538f5dff88>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking how C-NOT works by itself!\n",
    "circuit = QuantumCircuit(2, 2)\n",
    "circuit.x(1) # Using Pauli-X gate to flip 2nd Bit!\n",
    "circuit.cx(0, 1)\n",
    "circuit.measure([0,1], [0,1])\n",
    "job1 = execute(circuit, simulator1, shots=1000)\n",
    "result4 = job1.result()\n",
    "counts = result4.get_counts(circuit)\n",
    "print(\"\\nTotal count for 00 and 11 are:\",counts)\n",
    "# Draw the circuit\n",
    "circuit.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# It worked ! |01> flipped to |10>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#OK! Now let's see Pauli Y and Z- gate!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "scrolled": true
   },
   "source": [
    "\n",
    "$Y = \\begin{bmatrix} 0 & -i \\\\ i & 0 \\end{bmatrix} \\quad\\quad\\quad\\quad Z = \\begin{bmatrix} 1 & 0 \\\\ 0 & -1 \\end{bmatrix}$ \\\n",
    "\\\n",
    "$Y = i|0\\rangle\\langle1| - i|1\\rangle\\langle0| \\quad\\quad Z = |0\\rangle\\langle0| - |1\\rangle\\langle1|$\n",
    "\n",
    "And, unsurprisingly, they also respectively perform rotations by\n",
    "π  around the y and z-axis of the Bloch sphere."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">        ┌───┐┌─┐\n",
       "q_0: |0>┤ Y ├┤M├\n",
       "        └───┘└╥┘\n",
       " c_0: 0 ══════╩═\n",
       "                </pre>"
      ],
      "text/plain": [
       "<qiskit.visualization.text.TextDrawing at 0x1538e5cdd48>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuitn = QuantumCircuit(1, 1)\n",
    "circuitn.y(0)\n",
    "circuitn.measure([0], [0])\n",
    "job5 = execute(circuitn, simulator2).result().get_statevector()\n",
    "# Draw the circuit\n",
    "circuitn.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_bloch_multivector(job5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}