Source code for pennylane_cirq.simulator_device

# Copyright 2018 Xanadu Quantum Technologies Inc.

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at

#     http://www.apache.org/licenses/LICENSE-2.0

# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Cirq Simulator Devices
======================

**Module name:** :mod:`pennylane_cirq.simulator_device`

.. currentmodule:: pennylane_cirq.simulator_device

This Device implements all the :class:`~pennylane.device.Device` methods,
for using Cirq simulators as PennyLane device.

Classes
-------

.. autosummary::
   SimulatorDevice
   MixedStateSimulatorDevice

----
"""
import numpy as np
import cirq
import pennylane as qml

from .cirq_device import CirqDevice
from .cirq_operation import CirqOperation


[docs]class SimulatorDevice(CirqDevice): r"""Cirq simulator device for PennyLane. Args: wires (int or Iterable[Number, str]]): Number of subsystems represented by the device, or iterable that contains unique labels for the subsystems as numbers (i.e., ``[-1, 0, 2]``) or strings (``['ancilla', 'q1', 'q2']``). shots (int): Number of circuit evaluations/random samples used to estimate expectation values of observables. Shots need to >= 1. If ``None``, expectation values are calculated analytically. qubits (List[cirq.Qubit]): A list of Cirq qubits that are used as wires. The wire number corresponds to the index in the list. By default, an array of ``cirq.LineQubit`` instances is created. simulator (Optional[cirq.Simulator]): Optional custom simulator object to use. If None, the default ``cirq.Simulator()`` will be used instead. """ name = "Cirq Simulator device for PennyLane" short_name = "cirq.simulator" # pylint: disable=too-many-arguments def __init__(self, wires, shots=None, qubits=None, simulator=None): super().__init__(wires, shots, qubits) self._simulator = simulator or cirq.Simulator() self._initial_state = None self._result = None self._state = None
[docs] def reset(self): # pylint: disable=missing-function-docstring super().reset() self._initial_state = None self._result = None self._state = None
[docs] def capabilities(self): # pylint: disable=missing-function-docstring capabilities = super().capabilities().copy() capabilities.update( returns_state=self.shots is None # State information is only set if obtaining shots ) return capabilities
def _apply_basis_state(self, basis_state_operation): # pylint: disable=missing-function-docstring if self.shots is not None: raise qml.DeviceError("The operation BasisState is only supported in analytic mode.") self._initial_state = basis_state_operation.state_vector(wire_order=self.wires).flatten() def _apply_state_prep(self, state_prep_operation): # pylint: disable=missing-function-docstring if self.shots is not None: raise qml.DeviceError("The operator StatePrep is only supported in analytic mode.") self._initial_state = state_prep_operation.state_vector(wire_order=self.wires).flatten()
[docs] def apply(self, operations, **kwargs): # pylint: disable=missing-function-docstring super().apply(operations, **kwargs) if self.shots is None: self._result = self._simulator.simulate( self.circuit, qubit_order=self.qubits, initial_state=self._initial_state ) self._state = self._get_state_from_cirq(self._result)
[docs] def analytic_probability(self, wires=None): # pylint: disable=missing-function-docstring if self._state is None: return None probs = self._get_computational_basis_probs() return self.marginal_prob(probs, wires)
@staticmethod def _get_state_from_cirq(result): """Extract the state array from a Cirq TrialResult ``result``""" return np.array(result.state_vector()) def _get_computational_basis_probs(self): """Extract the probabilities of all computational basis measurements.""" return np.abs(self._state) ** 2 @property def state(self): """Returns the state vector of the circuit prior to measurement. .. note:: The state includes possible basis rotations for non-diagonal observables. Note that this behaviour differs from PennyLane's default.qubit plugin. """ return self._state
[docs] def generate_samples(self): # pylint: disable=missing-function-docstring if self.shots is None: return super().generate_samples() for wire in range(self.num_wires): self.circuit.append(cirq.measure(self.qubits[wire], key=str(wire))) self._result = self._simulator.run(self.circuit, repetitions=self.shots) return np.array( [self._result.measurements[str(wire)].flatten() for wire in range(self.num_wires)] ).T.astype(int)
[docs] def expval(self, observable, shot_range=None, bin_size=None): # pylint: disable=missing-function-docstring # Analytic mode if self.shots is None: all_observables = ( list(observable.operands) if isinstance(observable, qml.ops.Prod) else [observable] ) for obs in all_observables: if self._observable_map[obs.name] is None or obs.name == "Projector": return super().expval(observable, shot_range, bin_size) if "Hadamard" in [op.name for op in all_observables]: list_obs = [] for obs in all_observables: list_obs.append(qml.PauliZ(wires=obs.wires)) T = qml.prod(*list_obs) circuit = self.circuit obs = cirq.PauliSum() + self.to_paulistring(T) else: circuit = self.pre_rotated_circuit obs = cirq.PauliSum() + self.to_paulistring(observable) return self._simulator.simulate_expectation_values( program=circuit, qubit_order=self.qubits, observables=obs, initial_state=self._initial_state, )[0].real # Shots mode samples = self.sample(observable, shot_range=shot_range, bin_size=bin_size) return np.squeeze(np.mean(samples, axis=0))
[docs]class MixedStateSimulatorDevice(SimulatorDevice): r"""Cirq mixed-state simulator device for PennyLane. Args: wires (int or Iterable[Number, str]]): Number of subsystems represented by the device, or iterable that contains unique labels for the subsystems as numbers (i.e., ``[-1, 0, 2]``) or strings (``['ancilla', 'q1', 'q2']``). shots (int): Number of circuit evaluations/random samples used to estimate expectation values of observables. Shots need to >= 1. If ``None``, expectation values are calculated analytically. qubits (List[cirq.Qubit]): A list of Cirq qubits that are used as wires. The wire number corresponds to the index in the list. By default, an array of ``cirq.LineQubit`` instances is created. """ name = "Cirq Mixed-State Simulator device for PennyLane" short_name = "cirq.mixedsimulator" _mixed_sim_operation_map = { "BitFlip": CirqOperation(cirq.bit_flip), "PhaseFlip": CirqOperation(cirq.phase_flip), "PhaseDamp": CirqOperation(cirq.phase_damp), "AmplitudeDamp": CirqOperation(cirq.amplitude_damp), "Depolarize": CirqOperation(cirq.depolarize), } def __init__(self, wires, shots=None, qubits=None): self._operation_map = dict(self._operation_map, **self._mixed_sim_operation_map) super().__init__(wires, shots, qubits) self._simulator = cirq.DensityMatrixSimulator() self._initial_state = None self._result = None self._state = None
[docs] def capabilities(self): # pylint: disable=missing-function-docstring capabilities = super().capabilities().copy() capabilities.update( returns_state=self.shots is None # State information is only set if obtaining shots ) return capabilities
[docs] def expval(self, observable, shot_range=None, bin_size=None): # The simulate_expectation_values from Cirq for mixed states involves # a density matrix check, which does not always pass because the tolerance # is too low. If the error is raised we use the PennyLane function for # expectation value. try: return super().expval(observable, shot_range, bin_size) except ValueError: return qml.devices.QubitDevice.expval(self, observable, shot_range, bin_size)
def _apply_basis_state(self, basis_state_operation): super()._apply_basis_state(basis_state_operation) self._initial_state = self._convert_to_density_matrix(self._initial_state) def _apply_state_prep(self, state_prep_operation): super()._apply_state_prep(state_prep_operation) self._initial_state = self._convert_to_density_matrix(self._initial_state) def _convert_to_density_matrix(self, state_vec): """Convert ``state_vec`` into a density matrix.""" dim = 2**self.num_wires return np.kron(state_vec, state_vec.conj()).reshape((dim, dim)) @staticmethod def _get_state_from_cirq(result): """Extract the state array from a Cirq TrialResult""" return np.array(result.final_density_matrix) def _get_computational_basis_probs(self): """Extract the probabilities of all computational basis measurements.""" return np.diag(self._state).real @property def state(self): """Returns the density matrix of the circuit prior to measurement. .. note:: The state includes possible basis rotations for non-diagonal observables. Note that this behaviour differs from PennyLane's default.qubit plugin. """ return self._state