diff --git a/pytket/binders/pauli.cpp b/pytket/binders/pauli.cpp index 7a46363001..1acf5562f0 100644 --- a/pytket/binders/pauli.cpp +++ b/pytket/binders/pauli.cpp @@ -50,7 +50,9 @@ PYBIND11_MODULE(pauli, m) { py::arg("qubits"), py::arg("paulis")) .def( py::init(), - "Construct a QubitPauliString from a QubitPauliMap.", py::arg("map")) + "Construct a QubitPauliString from a dictionary mapping " + ":py:class:`Qubit` to :py:class:`Pauli`.", + py::arg("map")) .def( "__hash__", [](const QubitPauliString &qps) { return hash_value(qps); }) @@ -211,7 +213,7 @@ PYBIND11_MODULE(pauli, m) { m, "PauliStabiliser", "A string of Pauli letters from the alphabet {I, X, Y, Z} " "with a +/- 1 coefficient.") - .def(py::init<>(), "Constructs an empty QubitPauliString.") + .def(py::init<>(), "Constructs an empty PauliStabiliser.") .def( py::init([](const std::vector &string, const int &coeff) { if (coeff == 1) { @@ -237,6 +239,185 @@ PYBIND11_MODULE(pauli, m) { "The list of Pauli terms") .def("__eq__", &PauliStabiliser::operator==) .def("__ne__", &PauliStabiliser::operator!=); + + py::class_( + m, "QubitPauliTensor", + "A tensor formed by Pauli terms, consisting of a sparse map from " + ":py:class:`Qubit` to :py:class:`Pauli` (implemented as a " + ":py:class:`QubitPauliString`) and a complex coefficient.") + .def( + py::init(), + "Constructs an empty QubitPauliTensor, representing the identity.", + py::arg("coeff") = 1.) + .def( + py::init(), + "Constructs a QubitPauliTensor with a single Pauli term.", + py::arg("qubit"), py::arg("pauli"), py::arg("coeff") = 1.) + .def( + py::init([](const std::list &qubits, + const std::list &paulis, const Complex &coeff) { + return QubitPauliTensor(QubitPauliString(qubits, paulis), coeff); + }), + "Constructs a QubitPauliTensor from two matching lists of " + "Qubits and Paulis.", + py::arg("qubits"), py::arg("paulis"), py::arg("coeff") = 1.) + .def( + py::init(), + "Construct a QubitPauliTensor from a dictionary mapping " + ":py:class:`Qubit` to :py:class:`Pauli`.", + py::arg("map"), py::arg("coeff") = 1.) + .def( + py::init(), + "Construct a QubitPauliTensor from a QubitPauliString.", + py::arg("string"), py::arg("coeff") = 1.) + .def( + "__hash__", + [](const QubitPauliTensor &qps) { return hash_value(qps); }) + .def("__repr__", &QubitPauliTensor::to_str) + .def("__eq__", &QubitPauliTensor::operator==) + .def("__ne__", &QubitPauliTensor::operator!=) + .def("__lt__", &QubitPauliTensor::operator<) + .def( + "__getitem__", [](const QubitPauliTensor &qpt, + const Qubit &q) { return qpt.string.get(q); }) + .def( + "__setitem__", [](QubitPauliTensor &qpt, const Qubit &q, + Pauli p) { return qpt.string.set(q, p); }) + .def(py::self * py::self) + .def(Complex() * py::self) + .def_readwrite( + "string", &QubitPauliTensor::string, + "The QubitPauliTensor's underlying :py:class:`QubitPauliString`") + .def_readwrite( + "coeff", &QubitPauliTensor::coeff, + "The global coefficient of the tensor") + .def( + "compress", &QubitPauliTensor::compress, + "Removes I terms to compress the sparse representation.") + .def( + "commutes_with", &QubitPauliTensor::commutes_with, + ":return: True if the two tensors commute, else False", + py::arg("other")) + .def( + "to_sparse_matrix", + [](const QubitPauliTensor &qpt) { + return (CmplxSpMat)(qpt.coeff * qpt.string.to_sparse_matrix()); + }, + "Represents the sparse string as a dense string (without " + "padding for extra qubits) and generates the matrix for the " + "tensor. Uses the ILO-BE convention, so ``Qubit(\"a\", 0)`` " + "is more significant that ``Qubit(\"a\", 1)`` and " + "``Qubit(\"b\")`` for indexing into the matrix." + "\n\n:return: a sparse matrix corresponding to the tensor") + .def( + "to_sparse_matrix", + [](const QubitPauliTensor &qpt, unsigned n_qubits) { + return (CmplxSpMat)(qpt.coeff * + qpt.string.to_sparse_matrix(n_qubits)); + }, + "Represents the sparse string as a dense string over " + "`n_qubits` qubits (sequentially indexed from 0 in the " + "default register) and generates the matrix for the tensor. " + "Uses the ILO-BE convention, so ``Qubit(0)`` is the most " + "significant bit for indexing into the matrix." + "\n\n:param n_qubits: the number of qubits in the full " + "operator" + "\n:return: a sparse matrix corresponding to the operator", + py::arg("n_qubits")) + .def( + "to_sparse_matrix", + [](const QubitPauliTensor &qpt, const qubit_vector_t &qubits) { + return (CmplxSpMat)(qpt.coeff * + qpt.string.to_sparse_matrix(qubits)); + }, + "Represents the sparse string as a dense string and generates " + "the matrix for the tensor. Orders qubits according to " + "`qubits` (padding with identities if they are not in the " + "sparse string), so ``qubits[0]`` is the most significant bit " + "for indexing into the matrix." + "\n\n:param qubits: the ordered list of qubits in the full " + "operator" + "\n:return: a sparse matrix corresponding to the operator", + py::arg("qubits")) + .def( + "dot_state", + [](const QubitPauliTensor &qpt, const Eigen::VectorXcd &state) { + return qpt.coeff * qpt.string.dot_state(state); + }, + "Performs the dot product of the state with the pauli tensor. " + "Maps the qubits of the statevector with sequentially-indexed " + "qubits in the default register, with ``Qubit(0)`` being the " + "most significant qubit." + "\n\n:param state: statevector for qubits ``Qubit(0)`` to " + "``Qubit(n-1)``" + "\n:return: dot product of operator with state", + py::arg("state")) + .def( + "dot_state", + [](const QubitPauliTensor &qpt, const Eigen::VectorXcd &state, + const qubit_vector_t &qubits) { + return qpt.coeff * qpt.string.dot_state(state, qubits); + }, + "Performs the dot product of the state with the pauli tensor. " + "Maps the qubits of the statevector according to the ordered " + "list `qubits`, with ``qubits[0]`` being the most significant " + "qubit." + "\n\n:param state: statevector" + "\n:param qubits: order of qubits in `state` from most to " + "least significant" + "\n:return: dot product of operator with state", + py::arg("state"), py::arg("qubits")) + .def( + "state_expectation", + [](const QubitPauliTensor &qpt, const Eigen::VectorXcd &state) { + return qpt.coeff * qpt.string.state_expectation(state); + }, + "Calculates the expectation value of the state with the pauli " + "operator. Maps the qubits of the statevector with " + "sequentially-indexed qubits in the default register, with " + "``Qubit(0)`` being the most significant qubit." + "\n\n:param state: statevector for qubits ``Qubit(0)`` to " + "``Qubit(n-1)``" + "\n:return: expectation value with respect to state", + py::arg("state")) + .def( + "state_expectation", + [](const QubitPauliTensor &qpt, const Eigen::VectorXcd &state, + const qubit_vector_t &qubits) { + return qpt.coeff * qpt.string.state_expectation(state, qubits); + }, + "Calculates the expectation value of the state with the pauli " + "operator. Maps the qubits of the statevector according to the " + "ordered list `qubits`, with ``qubits[0]`` being the most " + "significant qubit." + "\n\n:param state: statevector" + "\n:param qubits: order of qubits in `state` from most to " + "least significant" + "\n:return: expectation value with respect to state", + py::arg("state"), py::arg("qubits")) + + .def(py::pickle( + [](const QubitPauliTensor &qpt) { + std::list qubits; + std::list paulis; + for (const std::pair &qp_pair : + qpt.string.map) { + qubits.push_back(qp_pair.first); + paulis.push_back(qp_pair.second); + } + return py::make_tuple(qubits, paulis, qpt.coeff); + }, + [](const py::tuple &t) { + if (t.size() != 3) + throw std::runtime_error( + "Invalid state: tuple size: " + std::to_string(t.size())); + return QubitPauliTensor( + QubitPauliString( + t[0].cast>(), + t[1].cast>()), + t[2].cast()); + })); + ; } } // namespace tket diff --git a/pytket/binders/tableau.cpp b/pytket/binders/tableau.cpp index 9eb7cf9ab6..eb2f54d945 100644 --- a/pytket/binders/tableau.cpp +++ b/pytket/binders/tableau.cpp @@ -51,6 +51,14 @@ PYBIND11_MODULE(tableau, m) { "\n:param zph: The phases of the Z rows.", py::arg("xx"), py::arg("xz"), py::arg("xph"), py::arg("zx"), py::arg("zz"), py::arg("zph")) + .def( + py::init<>([](const Circuit& circ) { + return circuit_to_unitary_tableau(circ); + }), + "Constructs a :py:class:`UnitaryTableau` from a unitary " + ":py:class:`Circuit`. Throws an exception if the input contains " + "non-unitary operations." + "\n\n:param circ: The unitary circuit to convert to a tableau.") .def( "__repr__", [](const UnitaryTableau& tab) { @@ -94,7 +102,14 @@ PYBIND11_MODULE(tableau, m) { "\n\n:param type: The :py:class:`OpType` of the gate to add. Must be " "an unparameterised Clifford gate type." "\n:param qbs: The qubits to apply the gate to. Length must match " - "the arity of the given gate type."); + "the arity of the given gate type.") + .def( + "to_circuit", &unitary_tableau_to_circuit, + "Synthesises a unitary :py:class:`Circuit` realising the same " + "unitary as the tableau. Uses the method from Aaronson & Gottesman: " + "\"Improved Simulation of Stabilizer Circuits\", Theorem 8. This is " + "not optimised for gate count, so is not recommended for " + "performance-sensitive usage."); py::class_, Op>( m, "UnitaryTableauBox", "A Clifford unitary specified by its actions on Paulis.") diff --git a/pytket/docs/changelog.rst b/pytket/docs/changelog.rst index 0104345d58..ec46d0127f 100644 --- a/pytket/docs/changelog.rst +++ b/pytket/docs/changelog.rst @@ -18,6 +18,9 @@ Minor new features: be overridden using the ``always_squash_symbols`` parameter to ``SquashCustom``. * Add ``control_state`` argument to ``QControlBox``. +* Add ``QubitPauliTensor`` (combining ``QubitPauliString`` with a complex + coefficient) to python binding. This is incorporated into ``UnitaryTableau`` + row inspection for phase tracking. Fixes: diff --git a/pytket/tests/tableau_test.py b/pytket/tests/tableau_test.py index 42866b0b7d..877ddcaf17 100644 --- a/pytket/tests/tableau_test.py +++ b/pytket/tests/tableau_test.py @@ -14,6 +14,7 @@ import pytest # type: ignore from pytket.circuit import Circuit, OpType, Qubit # type: ignore +from pytket.pauli import Pauli, QubitPauliTensor # type: ignore from pytket.tableau import UnitaryTableau, UnitaryTableauBox # type: ignore from pytket.utils.results import compare_unitaries import numpy as np @@ -81,3 +82,22 @@ def test_tableau_box_from_matrix() -> None: circ.X(2) circ.Sdg(2) assert compare_unitaries(circ.get_unitary(), np.eye(8, dtype=complex)) + + +def test_tableau_rows() -> None: + circ = Circuit(3) + circ.H(0) + circ.CX(0, 1) + circ.V(1) + circ.CZ(2, 1) + circ.Vdg(2) + tab = UnitaryTableau(circ) + assert tab.get_zrow(Qubit(0)) == QubitPauliTensor( + [Qubit(0), Qubit(1), Qubit(2)], [Pauli.X, Pauli.X, Pauli.Y], 1.0 + ) + assert tab.get_xrow(Qubit(1)) == QubitPauliTensor( + {Qubit(1): Pauli.X, Qubit(2): Pauli.Y}, 1.0 + ) + assert tab.get_row_product( + QubitPauliTensor(Qubit(0), Pauli.Z) * QubitPauliTensor(Qubit(1), Pauli.X, -1.0) + ) == QubitPauliTensor(Qubit(0), Pauli.X, -1.0)