# This code is part of Qiskit. # # (C) Copyright IBM 2017, 2023. # # This code is licensed under the Apache License, Version 2.0. You may # obtain a copy of this license in the LICENSE.txt file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain this # copyright notice, and modified files need to carry a notice indicating # that they have been altered from the originals. """Contains a (slow) Python simulator. It simulates a quantum circuit (an experiment) that has been compiled to run on the simulator. It is exponential in the number of qubits. The simulator is run using .. code-block:: python BasicSimulator().run(run_input) Where the input is a :class:`.QuantumCircuit` object and the output is a :class:`.BasicProviderJob` object, which can later be queried for the Result object. The result will contain a 'memory' data field, which is a result of measurements for each shot. """ from __future__ import annotations import math import uuid import time import logging import warnings from collections import Counter import numpy as np from qiskit.circuit import QuantumCircuit from qiskit.circuit.library import UnitaryGate from qiskit.circuit.library.standard_gates import get_standard_gate_name_mapping, GlobalPhaseGate from qiskit.providers import Provider from qiskit.providers.backend import BackendV2 from qiskit.providers.models.backendconfiguration import BackendConfiguration from qiskit.providers.options import Options from qiskit.qobj import QasmQobj, QasmQobjConfig, QasmQobjExperiment from qiskit.result import Result from qiskit.transpiler import Target from qiskit.utils.deprecation import deprecate_func from .basic_provider_job import BasicProviderJob from .basic_provider_tools import single_gate_matrix from .basic_provider_tools import ( SINGLE_QUBIT_GATES, TWO_QUBIT_GATES, TWO_QUBIT_GATES_WITH_PARAMETERS, THREE_QUBIT_GATES, ) from .basic_provider_tools import einsum_vecmul_index from .exceptions import BasicProviderError logger = logging.getLogger(__name__) class BasicSimulator(BackendV2): """Python implementation of a basic (non-efficient) quantum simulator.""" # Formerly calculated as `int(log2(local_hardware_info()["memory"]*(1024**3)/16))`. # After the removal of `local_hardware_info()`, it's hardcoded to 24 qubits, # which matches the ~268 MB of required memory. MAX_QUBITS_MEMORY = 24 def __init__( self, provider: Provider | None = None, target: Target | None = None, **fields, ) -> None: """ Args: provider: An optional backwards reference to the :class:`~qiskit.providers.Provider` object that the backend is from. target: An optional target to configure the simulator. fields: kwargs for the values to use to override the default options. Raises: AttributeError: If a field is specified that's outside the backend's options. """ super().__init__( provider=provider, name="basic_simulator", description="A python simulator for quantum experiments", backend_version="0.1", **fields, ) self._target = target self._configuration = None # Internal simulator variables self._local_random = None self._classical_memory = 0 self._classical_register = 0 self._statevector = 0 self._number_of_cmembits = 0 self._number_of_qubits = 0 self._shots = 0 self._memory = False self._initial_statevector = self.options.get("initial_statevector") self._chop_threshold = self.options.get("chop_threashold") self._qobj_config = None self._sample_measure = False @property def max_circuits(self) -> None: return None @property def target(self) -> Target: if not self._target: self._target = self._build_basic_target() return self._target def _build_basic_target(self) -> Target: """Helper method that returns a minimal target with a basis gate set but no coupling map, instruction properties or calibrations. Returns: The configured target. """ # Set num_qubits to None to signal the transpiler not to # resize the circuit to fit a specific (potentially too large) # number of qubits. The number of qubits in the circuits given to the # `run` method will determine the size of the simulated statevector. target = Target( description="Basic Target", num_qubits=None, ) basis_gates = [ "ccx", "ccz", "ch", "cp", "crx", "cry", "crz", "cs", "csdg", "cswap", "csx", "cu", "cu1", "cu3", "cx", "cy", "cz", "dcx", "delay", "ecr", "global_phase", "h", "id", "iswap", "measure", "p", "r", "rccx", "reset", "rx", "rxx", "ry", "ryy", "rz", "rzx", "rzz", "s", "sdg", "swap", "sx", "sxdg", "t", "tdg", "u", "u1", "u2", "u3", "unitary", "x", "xx_minus_yy", "xx_plus_yy", "y", "z", ] inst_mapping = get_standard_gate_name_mapping() for name in basis_gates: if name in inst_mapping: instruction = inst_mapping[name] target.add_instruction(instruction, properties=None, name=name) elif name == "unitary": # This is a placeholder for a UnitaryGate instance, # to signal the transpiler not to decompose unitaries # in the circuit. target.add_instruction(UnitaryGate, name="unitary") else: raise BasicProviderError( f"Gate is not a valid basis gate for this simulator: {name}" ) return target @deprecate_func( since="1.3.0", removal_timeline="in Qiskit 2.0.0", additional_msg="The `BackendConfiguration` class is part of the deprecated `BackendV1` " "workflow, and no longer necessary for `BackendV2`. The individual configuration elements " "can be retrieved directly from the backend or from the contained `Target` instance " "(`backend.target)`).", ) def configuration(self) -> BackendConfiguration: """Return the simulator backend configuration. Returns: The configuration for the backend. """ # Note: this is a custom attribute of the BasicSimulator class and # not part of the BackendV2 interface. It has only been added for # compatibility with the `assemble` function (currently used in `run`), # which still relies on legacy BackendV1 attributes. Once the internal # use of `assemble` is resolved, this attribute will no longer be # necessary. if self._configuration: return self._configuration gates = [ { "name": name, "parameters": self.target.operation_from_name(name).params, } for name in self.target.operation_names ] with warnings.catch_warnings(): # TODO Provider models are deprecated # https://github.com/Qiskit/qiskit/issues/12843 warnings.filterwarnings( "ignore", category=DeprecationWarning, message=r".+qiskit\.providers\.models\.backendconfiguration\..+", ) self._configuration = BackendConfiguration( backend_name=self.name, backend_version=self.backend_version, n_qubits=self.num_qubits, basis_gates=list(self.target.operation_names), gates=gates, local=True, simulator=True, conditional=True, open_pulse=False, memory=True, # This max_shots is used by the assembler, setting it to 0 # to maintain the behavior from the previous implementation. # Not related to the actual shots set in the backend options max_shots=0, coupling_map=None, description="A python simulator for quantum experiments", ) return self._configuration @classmethod def _default_options(cls) -> Options: return Options( shots=1024, memory=False, initial_statevector=None, chop_threshold=1e-15, allow_sample_measuring=True, seed_simulator=None, parameter_binds=None, ) def _add_unitary(self, gate: np.ndarray, qubits: list[int]) -> None: """Apply an N-qubit unitary matrix. Args: gate (matrix_like): an N-qubit unitary matrix qubits (list): the list of N-qubits. """ # Get the number of qubits num_qubits = len(qubits) # Compute einsum index string for 1-qubit matrix multiplication indexes = einsum_vecmul_index(qubits, self._number_of_qubits) # Convert to complex rank-2N tensor gate_tensor = np.reshape(np.array(gate, dtype=complex), num_qubits * [2, 2]) # Apply matrix multiplication self._statevector = np.einsum( indexes, gate_tensor, self._statevector, dtype=complex, casting="no" ) def _get_measure_outcome(self, qubit: int) -> tuple[str, int]: """Simulate the outcome of measurement of a qubit. Args: qubit: the qubit to measure Return: pair (outcome, probability) where outcome is '0' or '1' and probability is the probability of the returned outcome. """ # Axis for numpy.sum to compute probabilities axis = list(range(self._number_of_qubits)) axis.remove(self._number_of_qubits - 1 - qubit) probabilities = np.sum(np.abs(self._statevector) ** 2, axis=tuple(axis)) # Compute einsum index string for 1-qubit matrix multiplication random_number = self._local_random.random() if random_number < probabilities[0]: return "0", probabilities[0] # Else outcome was '1' return "1", probabilities[1] def _add_sample_measure( self, measure_params: list[list[int, int]], num_samples: int ) -> list[hex]: """Generate memory samples from current statevector. Args: measure_params: List of (qubit, cmembit) values for measure instructions to sample. num_samples: The number of memory samples to generate. Returns: A list of memory values in hex format. """ # Get unique qubits that are actually measured and sort in # ascending order measured_qubits = sorted({qubit for qubit, cmembit in measure_params}) num_measured = len(measured_qubits) # We use the axis kwarg for numpy.sum to compute probabilities # this sums over all non-measured qubits to return a vector # of measure probabilities for the measured qubits axis = list(range(self._number_of_qubits)) for qubit in reversed(measured_qubits): # Remove from largest qubit to smallest so list position is correct # with respect to position from end of the list axis.remove(self._number_of_qubits - 1 - qubit) probabilities = np.reshape( np.sum(np.abs(self._statevector) ** 2, axis=tuple(axis)), 2**num_measured ) # Generate samples on measured qubits as ints with qubit # position in the bit-string for each int given by the qubit # position in the sorted measured_qubits list samples = self._local_random.choice(range(2**num_measured), num_samples, p=probabilities) # Convert the ints to bitstrings memory = [] for sample in samples: classical_memory = self._classical_memory for qubit, cmembit in measure_params: pos = measured_qubits.index(qubit) qubit_outcome = int((sample & (1 << pos)) >> pos) membit = 1 << cmembit classical_memory = (classical_memory & (~membit)) | (qubit_outcome << cmembit) value = bin(classical_memory)[2:] memory.append(hex(int(value, 2))) return memory def _add_measure(self, qubit: int, cmembit: int, cregbit: int | None = None) -> None: """Apply a measure instruction to a qubit. Args: qubit: qubit is the qubit measured. cmembit: is the classical memory bit to store outcome in. cregbit: is the classical register bit to store outcome in. """ # get measure outcome outcome, probability = self._get_measure_outcome(qubit) # update classical state membit = 1 << cmembit self._classical_memory = (self._classical_memory & (~membit)) | (int(outcome) << cmembit) if cregbit is not None: regbit = 1 << cregbit self._classical_register = (self._classical_register & (~regbit)) | ( int(outcome) << cregbit ) # update quantum state if outcome == "0": update_diag = [[1 / math.sqrt(probability), 0], [0, 0]] else: update_diag = [[0, 0], [0, 1 / math.sqrt(probability)]] # update classical state self._add_unitary(update_diag, [qubit]) def _add_reset(self, qubit: int) -> None: """Apply a reset instruction to a qubit. Args: qubit: the qubit being rest This is done by doing a simulating a measurement outcome and projecting onto the outcome state while renormalizing. """ # get measure outcome outcome, probability = self._get_measure_outcome(qubit) # update quantum state if outcome == "0": update = [[1 / math.sqrt(probability), 0], [0, 0]] self._add_unitary(update, [qubit]) else: update = [[0, 1 / math.sqrt(probability)], [0, 0]] self._add_unitary(update, [qubit]) def _validate_initial_statevector(self) -> None: """Validate an initial statevector""" # If the initial statevector isn't set we don't need to validate if self._initial_statevector is None: return # Check statevector is correct length for number of qubits length = len(self._initial_statevector) required_dim = 2**self._number_of_qubits if length != required_dim: raise BasicProviderError( f"initial statevector is incorrect length: {length} != {required_dim}" ) def _set_options( self, qobj_config: QasmQobjConfig | None = None, backend_options: dict | None = None ) -> None: """Set the backend options for all experiments in a qobj""" # Reset default options self._initial_statevector = self.options.get("initial_statevector") self._chop_threshold = self.options.get("chop_threshold") if "backend_options" in backend_options and backend_options["backend_options"]: backend_options = backend_options["backend_options"] # Check for custom initial statevector in backend_options first, # then config second if ( "initial_statevector" in backend_options and backend_options["initial_statevector"] is not None ): self._initial_statevector = np.array( backend_options["initial_statevector"], dtype=complex ) elif hasattr(qobj_config, "initial_statevector"): self._initial_statevector = np.array(qobj_config.initial_statevector, dtype=complex) if self._initial_statevector is not None: # Check the initial statevector is normalized norm = np.linalg.norm(self._initial_statevector) if round(norm, 12) != 1: raise BasicProviderError(f"initial statevector is not normalized: norm {norm} != 1") # Check for custom chop threshold # Replace with custom options if "chop_threshold" in backend_options: self._chop_threshold = backend_options["chop_threshold"] elif hasattr(qobj_config, "chop_threshold"): self._chop_threshold = qobj_config.chop_threshold def _initialize_statevector(self) -> None: """Set the initial statevector for simulation""" if self._initial_statevector is None: # Set to default state of all qubits in |0> self._statevector = np.zeros(2**self._number_of_qubits, dtype=complex) self._statevector[0] = 1 else: self._statevector = self._initial_statevector.copy() # Reshape to rank-N tensor self._statevector = np.reshape(self._statevector, self._number_of_qubits * [2]) def _validate_measure_sampling(self, experiment: QasmQobjExperiment) -> None: """Determine if measure sampling is allowed for an experiment Args: experiment: a qobj experiment. """ # If shots=1 we should disable measure sampling. # This is also required for statevector simulator to return the # correct final statevector without silently dropping final measurements. if self._shots <= 1: self._sample_measure = False return # Check for config flag if hasattr(experiment.config, "allows_measure_sampling"): self._sample_measure = experiment.config.allows_measure_sampling # If flag isn't found do a simple test to see if a circuit contains # no reset instructions, and no gates instructions after # the first measure. else: measure_flag = False for instruction in experiment.instructions: # If circuit contains reset operations we cannot sample if instruction.name == "reset": self._sample_measure = False return # If circuit contains a measure option then we can # sample only if all following operations are measures if measure_flag: # If we find a non-measure instruction # we cannot do measure sampling if instruction.name not in ["measure", "barrier", "id", "u0"]: self._sample_measure = False return elif instruction.name == "measure": measure_flag = True # If we made it to the end of the circuit without returning # measure sampling is allowed self._sample_measure = True def run( self, run_input: QuantumCircuit | list[QuantumCircuit], **backend_options ) -> BasicProviderJob: """Run on the backend. Args: run_input: payload of the experiment backend_options: backend options Returns: BasicProviderJob: derived from BaseJob Additional Information: backend_options: Is a dict of options for the backend. It may contain * "initial_statevector": vector_like The "initial_statevector" option specifies a custom initial initial statevector for the simulator to be used instead of the all zero state. This size of this vector must be correct for the number of qubits in ``run_input`` parameter. Example:: backend_options = { "initial_statevector": np.array([1, 0, 0, 1j]) / math.sqrt(2), } """ # TODO: replace assemble with new run flow. If this is not achieved before 2.0, # see removal note on `def _assemble`, L192 of qiskit/compiler/assembler.py from qiskit.compiler.assembler import _assemble out_options = {} for key, value in backend_options.items(): if not hasattr(self.options, key): warnings.warn( f"Option {key} is not used by this backend", UserWarning, stacklevel=2 ) else: out_options[key] = value qobj = _assemble(run_input, self, **out_options) qobj_options = qobj.config self._set_options(qobj_config=qobj_options, backend_options=backend_options) job_id = str(uuid.uuid4()) job = BasicProviderJob(self, job_id, self._run_job(job_id, qobj)) return job def _run_job(self, job_id: str, qobj: QasmQobj) -> Result: """Run experiments in qobj Args: job_id: unique id for the job. qobj: job description Returns: Result object """ self._validate(qobj) result_list = [] self._shots = qobj.config.shots self._memory = getattr(qobj.config, "memory", False) self._qobj_config = qobj.config start = time.time() with warnings.catch_warnings(): warnings.filterwarnings( "ignore", category=DeprecationWarning, message=r".+qiskit\.providers\.basic_provider\.basic_simulator\..+", ) for experiment in qobj.experiments: result_list.append(self.run_experiment(experiment)) end = time.time() result = { "backend_name": self.name, "backend_version": self.backend_version, "qobj_id": qobj.qobj_id, "job_id": job_id, "results": result_list, "status": "COMPLETED", "success": True, "time_taken": (end - start), "header": qobj.header.to_dict(), } return Result.from_dict(result) @deprecate_func( since="1.4.0", removal_timeline="in Qiskit 2.0.0", additional_msg="This method takes a `QasmQobjExperiment` as input argument. " "The `Qobj` class and related functionality are part of the deprecated " "`BackendV1` workflow, and no longer necessary for `BackendV2`. Use `run` instead.", ) def run_experiment(self, experiment: QasmQobjExperiment) -> dict[str, ...]: """Run an experiment (circuit) and return a single experiment result. Args: experiment: experiment from qobj experiments list Returns: A result dictionary which looks something like:: { "name": name of this experiment (obtained from qobj.experiment header) "seed": random seed used for simulation "shots": number of shots used in the simulation "data": { "counts": {'0x9: 5, ...}, "memory": ['0x9', '0xF', '0x1D', ..., '0x9'] }, "status": status string for the simulation "success": boolean "time_taken": simulation time of this single experiment } Raises: BasicProviderError: if an error occurred. """ start = time.time() self._number_of_qubits = experiment.config.n_qubits self._number_of_cmembits = experiment.config.memory_slots self._statevector = 0 self._classical_memory = 0 self._classical_register = 0 self._sample_measure = False global_phase = experiment.header.global_phase # Validate the dimension of initial statevector if set self._validate_initial_statevector() # Get the seed looking in circuit, qobj, and then random. if hasattr(experiment.config, "seed_simulator"): seed_simulator = experiment.config.seed_simulator elif hasattr(self._qobj_config, "seed_simulator"): seed_simulator = self._qobj_config.seed_simulator else: # For compatibility on Windows force dyte to be int32 # and set the maximum value to be (2 ** 31) - 1 seed_simulator = np.random.randint(2147483647, dtype="int32") self._local_random = np.random.default_rng(seed=seed_simulator) # Check if measure sampling is supported for current circuit self._validate_measure_sampling(experiment) # List of final counts for all shots memory = [] # Check if we can sample measurements, if so we only perform 1 shot # and sample all outcomes from the final state vector if self._sample_measure: shots = 1 # Store (qubit, cmembit) pairs for all measure ops in circuit to # be sampled measure_sample_ops = [] else: shots = self._shots for _ in range(shots): self._initialize_statevector() # apply global_phase self._statevector *= np.exp(1j * global_phase) # Initialize classical memory to all 0 self._classical_memory = 0 self._classical_register = 0 for operation in experiment.instructions: conditional = getattr(operation, "conditional", None) if isinstance(conditional, int): conditional_bit_set = (self._classical_register >> conditional) & 1 if not conditional_bit_set: continue elif conditional is not None: mask = int(operation.conditional.mask, 16) if mask > 0: value = self._classical_memory & mask while (mask & 0x1) == 0: mask >>= 1 value >>= 1 if value != int(operation.conditional.val, 16): continue if operation.name == "unitary": qubits = operation.qubits gate = operation.params[0] self._add_unitary(gate, qubits) elif operation.name in ("id", "u0", "delay"): pass elif operation.name == "global_phase": params = getattr(operation, "params", None) gate = GlobalPhaseGate(*params).to_matrix() self._add_unitary(gate, []) # Check if single qubit gate elif operation.name in SINGLE_QUBIT_GATES: params = getattr(operation, "params", None) qubit = operation.qubits[0] gate = single_gate_matrix(operation.name, params) self._add_unitary(gate, [qubit]) elif operation.name in TWO_QUBIT_GATES_WITH_PARAMETERS: params = getattr(operation, "params", None) qubit0 = operation.qubits[0] qubit1 = operation.qubits[1] gate = TWO_QUBIT_GATES_WITH_PARAMETERS[operation.name](*params).to_matrix() self._add_unitary(gate, [qubit0, qubit1]) elif operation.name in ("id", "u0"): pass elif operation.name in TWO_QUBIT_GATES: qubit0 = operation.qubits[0] qubit1 = operation.qubits[1] gate = TWO_QUBIT_GATES[operation.name] self._add_unitary(gate, [qubit0, qubit1]) elif operation.name in THREE_QUBIT_GATES: qubit0 = operation.qubits[0] qubit1 = operation.qubits[1] qubit2 = operation.qubits[2] gate = THREE_QUBIT_GATES[operation.name] self._add_unitary(gate, [qubit0, qubit1, qubit2]) # Check if reset elif operation.name == "reset": qubit = operation.qubits[0] self._add_reset(qubit) # Check if barrier elif operation.name == "barrier": pass # Check if measure elif operation.name == "measure": qubit = operation.qubits[0] cmembit = operation.memory[0] cregbit = operation.register[0] if hasattr(operation, "register") else None if self._sample_measure: # If sampling measurements record the qubit and cmembit # for this measurement for later sampling measure_sample_ops.append((qubit, cmembit)) else: # If not sampling perform measurement as normal self._add_measure(qubit, cmembit, cregbit) elif operation.name == "bfunc": mask = int(operation.mask, 16) relation = operation.relation val = int(operation.val, 16) cregbit = operation.register cmembit = operation.memory if hasattr(operation, "memory") else None compared = (self._classical_register & mask) - val if relation == "==": outcome = compared == 0 elif relation == "!=": outcome = compared != 0 elif relation == "<": outcome = compared < 0 elif relation == "<=": outcome = compared <= 0 elif relation == ">": outcome = compared > 0 elif relation == ">=": outcome = compared >= 0 else: raise BasicProviderError("Invalid boolean function relation.") # Store outcome in register and optionally memory slot regbit = 1 << cregbit self._classical_register = (self._classical_register & (~regbit)) | ( int(outcome) << cregbit ) if cmembit is not None: membit = 1 << cmembit self._classical_memory = (self._classical_memory & (~membit)) | ( int(outcome) << cmembit ) else: backend = self.name err_msg = '{0} encountered unrecognized operation "{1}"' raise BasicProviderError(err_msg.format(backend, operation.name)) # Add final creg data to memory list if self._number_of_cmembits > 0: if self._sample_measure: # If sampling we generate all shot samples from the final statevector memory = self._add_sample_measure(measure_sample_ops, self._shots) else: # Turn classical_memory (int) into bit string and pad zero for unused cmembits outcome = bin(self._classical_memory)[2:] memory.append(hex(int(outcome, 2))) # Add data data = {"counts": dict(Counter(memory))} # Optionally add memory list if self._memory: data["memory"] = memory end = time.time() return { "name": experiment.header.name, "seed_simulator": seed_simulator, "shots": self._shots, "data": data, "status": "DONE", "success": True, "time_taken": (end - start), "header": experiment.header.to_dict(), } def _validate(self, qobj: QasmQobj) -> None: """Semantic validations of the qobj which cannot be done via schemas.""" n_qubits = qobj.config.n_qubits max_qubits = self.MAX_QUBITS_MEMORY if n_qubits > max_qubits: raise BasicProviderError( f"Number of qubits {n_qubits} is greater than maximum ({max_qubits}) " f'for "{self.name}".' ) for experiment in qobj.experiments: name = experiment.header.name if experiment.config.memory_slots == 0: logger.warning( 'No classical registers in circuit "%s", counts will be empty.', name ) elif "measure" not in [op.name for op in experiment.instructions]: logger.warning( 'No measurements in circuit "%s", classical register will remain all zeros.', name, )