Add apply_clifford_basis_change_tensor

pytket/binders/tailoring.cpp

@@ -26,12 +26,16 @@ namespace py = pybind11;
 
 namespace tket {
 
-QubitPauliString apply_clifford_basis_change(
+QubitPauliTensor apply_clifford_basis_change(
     const QubitPauliString &in_pauli, const Circuit &circ) {
   UnitaryRevTableau tab = circuit_to_unitary_rev_tableau(circ);
   QubitPauliTensor new_operator =
       tab.get_row_product(QubitPauliTensor(in_pauli));
-  return new_operator.string;
+  return new_operator;
+}
+
+QubitPauliString apply_clifford_basis_change_string(const QubitPauliString &in_pauli, const Circuit &circ) {
+    return apply_clifford_basis_change(in_pauli, circ).string;
 }
 
 PYBIND11_MODULE(tailoring, m) {
@@ -163,13 +167,22 @@ PYBIND11_MODULE(tailoring, m) {
           py::arg("circuit"), py::arg("samples"))
       .def("__repr__", &UniversalFrameRandomisation::to_string);
   m.def(
-      "apply_clifford_basis_change", &apply_clifford_basis_change,
+      "apply_clifford_basis_change", &apply_clifford_basis_change_string,
       "Given Pauli operator P and Clifford circuit C, "
       "returns C_dagger.P.C in multiplication order. This ignores any -1 "
       "phase that could be introduced.\n\n:param pauli: Pauli "
       "operator being transformed. \n:param circuit: "
       "Clifford circuit acting on Pauli operator.\n"
       ":return: :py:class:`QubitPauliString` for new operator",
       py::arg("pauli"), py::arg("circuit"));
+  m.def(
+      "apply_clifford_basis_change_tensor", &apply_clifford_basis_change,
+      "Given Pauli operator P and Clifford circuit C, "
+      "returns C_dagger.P.C in multiplication order"
+      "\n\n:param pauli: Pauli "
+      "operator being transformed. \n:param circuit: "
+      "Clifford circuit acting on Pauli operator.\n"
+      ":return: :py:class:`QubitPauliTensor` for new operator",
+      py::arg("pauli"), py::arg("circuit"));
 }
 }  // namespace tket

pytket/pytket/_tket/tailoring.pyi

@@ -19,3 +19,4 @@ class UniversalFrameRandomisation:
     def sample_circuits(self, circuit: pytket._tket.circuit.Circuit, samples: int) -> List[pytket._tket.circuit.Circuit]: ...
 
 def apply_clifford_basis_change(pauli: pytket._tket.pauli.QubitPauliString, circuit: pytket._tket.circuit.Circuit) -> pytket._tket.pauli.QubitPauliString: ...
+def apply_clifford_basis_change_tensor(pauli: pytket._tket.pauli.QubitPauliString, circuit: pytket._tket.circuit.Circuit) -> pytket._tket.pauli.QubitPauliTensor: ...

pytket/tests/characterisation_test.py

@@ -18,6 +18,7 @@
     PauliFrameRandomisation,
     UniversalFrameRandomisation,
     apply_clifford_basis_change,
+    apply_clifford_basis_change_tensor,
 )
 from pytket.pauli import Pauli, QubitPauliString
 
@@ -116,15 +117,24 @@ def test_apply_clifford_basis_change() -> None:
     z_op = QubitPauliString(Qubit(0), Pauli.Z)
     x_op = QubitPauliString(Qubit(0), Pauli.X)
     assert apply_clifford_basis_change(z_op, circ_0) == x_op
+    t = apply_clifford_basis_change_tensor(z_op, circ_0)
+    assert t.string == x_op
+    assert t.coeff == 1
 
     circ_1 = Circuit(2).CX(0, 1)
     zz_op = QubitPauliString([Qubit(0), Qubit(1)], [Pauli.Z, Pauli.Z])
     iz_op = QubitPauliString([Qubit(0), Qubit(1)], [Pauli.I, Pauli.Z])
     assert apply_clifford_basis_change(zz_op, circ_1) == iz_op
+    t = apply_clifford_basis_change_tensor(zz_op, circ_1)
+    assert t.string == iz_op
+    assert t.coeff == 1
 
     circ_2 = Circuit(2).H(0).CX(0, 1).S(1).X(0)
     zz_op = QubitPauliString([Qubit(0), Qubit(1)], [Pauli.Z, Pauli.Z])
     assert apply_clifford_basis_change(zz_op, circ_2) == iz_op
+    t = apply_clifford_basis_change_tensor(zz_op, circ_2)
+    assert t.string == iz_op
+    assert t.coeff == -1
 
     circ_3 = (
         Circuit(4).H(0).H(1).H(2).H(3).CX(0, 1).CX(1, 2).CX(2, 3).S(0).Y(1).Z(2).X(3)
@@ -136,6 +146,10 @@ def test_apply_clifford_basis_change() -> None:
         [Qubit(0), Qubit(1), Qubit(2), Qubit(3)], [Pauli.Y, Pauli.X, Pauli.Y, Pauli.I]
     )
     assert apply_clifford_basis_change(yxzi_op, circ_3) == yxyi_op
+    t = apply_clifford_basis_change_tensor(yxzi_op, circ_3)
+
+    assert t.string == yxyi_op
+    assert t.coeff == 1
 
 
 if __name__ == "__main__":