Source code for qiskit_aer.backends.qasm_simulator

# This code is part of Qiskit.
#
# (C) Copyright IBM 2018, 2019.
#
# 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.
"""
Aer qasm simulator backend.
"""

import copy
import logging
from warnings import warn
from qiskit.providers.options import Options
from qiskit.providers.models import QasmBackendConfiguration
from qiskit.providers.backend import BackendV2

from ..version import __version__
from ..aererror import AerError
from .aerbackend import AerBackend
from .backend_utils import (
    cpp_execute_qobj,
    cpp_execute_circuits,
    available_methods,
    MAX_QUBITS_STATEVECTOR,
    LEGACY_METHOD_MAP,
    map_legacy_method_options,
    map_legacy_method_config,
)

# pylint: disable=import-error, no-name-in-module, abstract-method
from .controller_wrappers import aer_controller_execute

logger = logging.getLogger(__name__)


[docs]class QasmSimulator(AerBackend): """ Noisy quantum circuit simulator backend. **Configurable Options** The `QasmSimulator` supports multiple simulation methods and configurable options for each simulation method. These may be set using the appropriate kwargs during initialization. They can also be set of updated using the :meth:`set_options` method. Run-time options may also be specified as kwargs using the :meth:`run` method. These will not be stored in the backend and will only apply to that execution. They will also override any previously set options. For example, to configure a density matrix simulator with a custom noise model to use for every execution .. code-block:: python noise_model = NoiseModel.from_backend(backend) backend = QasmSimulator(method='density_matrix', noise_model=noise_model) **Simulating an IBM Quantum Backend** The simulator can be automatically configured to mimic an IBM Quantum backend using the :meth:`from_backend` method. This will configure the simulator to use the basic device :class:`NoiseModel` for that backend, and the same basis gates and coupling map. .. code-block:: python backend = QasmSimulator.from_backend(backend) **Simulation Method Option** The simulation method is set using the ``method`` kwarg. Supported simulation methods are * ``"statevector"``: A dense statevector simulation that can sample measurement outcomes from *ideal* circuits with all measurements at end of the circuit. For noisy simulations each shot samples a randomly sampled noisy circuit from the noise model. ``"statevector_cpu"`` is an alias of ``"statevector"``. * ``"statevector_gpu"``: A dense statevector simulation that provides the same functionalities with ``"statevector"``. GPU performs the computation to calculate probability amplitudes as CPU does. If no GPU is available, a runtime error is raised. * ``"density_matrix"``: A dense density matrix simulation that may sample measurement outcomes from *noisy* circuits with all measurements at end of the circuit. It can only simulate half the number of qubits as the statevector method. * ``"density_matrix_gpu"``: A dense density matrix simulation that provides the same functionalities with ``"density_matrix"``. GPU performs the computation to calculate probability amplitudes as CPU does. If no GPU is available, a runtime error is raised. * ``"stabilizer"``: An efficient Clifford stabilizer state simulator that can simulate noisy Clifford circuits if all errors in the noise model are also Clifford errors. * ``"extended_stabilizer"``: An approximate simulated based on a ranked-stabilizer decomposition that decomposes circuits into stabilizer state terms. The number of terms grows with the number of non-Clifford gates. * ``"matrix_product_state"``: A tensor-network statevector simulator that uses a Matrix Product State (MPS) representation for the state. * ``"automatic"``: The default behavior where the method is chosen automatically for each circuit based on the circuit instructions, number of qubits, and noise model. **Additional Backend Options** The following simulator specific backend options are supported * ``method`` (str): Set the simulation method (Default: ``"automatic"``). Use :meth:`available_methods` to return a list of all availabe methods. * ``device`` (str): Set the simulation device (Default: ``"CPU"``). Use :meth:`available_devices` to return a list of devices supported on the current system. * ``precision`` (str): Set the floating point precision for certain simulation methods to either ``"single"`` or ``"double"`` precision (default: ``"double"``). * ``executor`` (futures.Executor): Set a custom executor for asynchronous running of simulation jobs (Default: None). * ``max_job_size`` (int or None): If the number of run circuits exceeds this value simulation will be run as a set of of sub-jobs on the executor. If ``None`` simulation of all circuits are submitted to the executor as a single job (Default: None). * ``max_shot_size`` (int or None): If the number of shots of a noisy circuit exceeds this value simulation will be split into multi circuits for execution and the results accumulated. If ``None`` circuits will not be split based on shots. When splitting circuits use the ``max_job_size`` option to control how these split circuits should be submitted to the executor (Default: None). * ``enable_truncation`` (bool): If set to True this removes unnecessary qubits which do not affect the simulation outcome from the simulated circuits (Default: True). * ``zero_threshold`` (double): Sets the threshold for truncating small values to zero in the result data (Default: 1e-10). * ``validation_threshold`` (double): Sets the threshold for checking if initial states are valid (Default: 1e-8). * ``max_parallel_threads`` (int): Sets the maximum number of CPU cores used by OpenMP for parallelization. If set to 0 the maximum will be set to the number of CPU cores (Default: 0). * ``max_parallel_experiments`` (int): Sets the maximum number of qobj experiments that may be executed in parallel up to the max_parallel_threads value. If set to 1 parallel circuit execution will be disabled. If set to 0 the maximum will be automatically set to max_parallel_threads (Default: 1). * ``max_parallel_shots`` (int): Sets the maximum number of shots that may be executed in parallel during each experiment execution, up to the max_parallel_threads value. If set to 1 parallel shot execution will be disabled. If set to 0 the maximum will be automatically set to max_parallel_threads. Note that this cannot be enabled at the same time as parallel experiment execution (Default: 0). * ``max_memory_mb`` (int): Sets the maximum size of memory to store a state vector. If a state vector needs more, an error is thrown. In general, a state vector of n-qubits uses 2^n complex values (16 Bytes). If set to 0, the maximum will be automatically set to the system memory size (Default: 0). These backend options only apply when using the ``"statevector"`` simulation method: * ``statevector_parallel_threshold`` (int): Sets the threshold that the number of qubits must be greater than to enable OpenMP parallelization for matrix multiplication during execution of an experiment. If parallel circuit or shot execution is enabled this will only use unallocated CPU cores up to max_parallel_threads. Note that setting this too low can reduce performance (Default: 14). * ``statevector_sample_measure_opt`` (int): Sets the threshold that the number of qubits must be greater than to enable a large qubit optimized implementation of measurement sampling. Note that setting this two low can reduce performance (Default: 10) These backend options only apply when using the ``"stabilizer"`` simulation method: * ``stabilizer_max_snapshot_probabilities`` (int): set the maximum qubit number for the :class:`~qiskit_aer.library.SaveProbabilities` instruction (Default: 32). These backend options only apply when using the ``"extended_stabilizer"`` simulation method: * ``extended_stabilizer_sampling_method`` (string): Choose how to simulate measurements on qubits. The performance of the simulator depends significantly on this choice. In the following, let n be the number of qubits in the circuit, m the number of qubits measured, and S be the number of shots (Default: resampled_metropolis). - ``"metropolis"``: Use a Monte-Carlo method to sample many output strings from the simulator at once. To be accurate, this method requires that all the possible output strings have a non-zero probability. It will give inaccurate results on cases where the circuit has many zero-probability outcomes. This method has an overall runtime that scales as n^{2} + (S-1)n. - ``"resampled_metropolis"``: A variant of the metropolis method, where the Monte-Carlo method is reinitialised for every shot. This gives better results for circuits where some outcomes have zero probability, but will still fail if the output distribution is sparse. The overall runtime scales as Sn^{2}. - ``"norm_estimation"``: An alternative sampling method using random state inner products to estimate outcome probabilites. This method requires twice as much memory, and significantly longer runtimes, but gives accurate results on circuits with sparse output distributions. The overall runtime scales as Sn^{3}m^{3}. * ``extended_stabilizer_metropolis_mixing_time`` (int): Set how long the monte-carlo method runs before performing measurements. If the output distribution is strongly peaked, this can be decreased alongside setting extended_stabilizer_disable_measurement_opt to True (Default: 5000). * ``"extended_stabilizer_approximation_error"`` (double): Set the error in the approximation for the extended_stabilizer method. A smaller error needs more memory and computational time (Default: 0.05). * ``extended_stabilizer_norm_estimation_samples`` (int): The default number of samples for the norm estimation sampler. The method will use the default, or 4m^{2} samples where m is the number of qubits to be measured, whichever is larger (Default: 100). * ``extended_stabilizer_norm_estimation_repetitions`` (int): The number of times to repeat the norm estimation. The median of these reptitions is used to estimate and sample output strings (Default: 3). * ``extended_stabilizer_parallel_threshold`` (int): Set the minimum size of the extended stabilizer decomposition before we enable OpenMP parallelization. If parallel circuit or shot execution is enabled this will only use unallocated CPU cores up to max_parallel_threads (Default: 100). * ``extended_stabilizer_probabilities_snapshot_samples`` (int): If using the metropolis or resampled_metropolis sampling method, set the number of samples used to estimate probabilities in a probabilities snapshot (Default: 3000). These backend options only apply when using the ``"matrix_product_state"`` simulation method: * ``matrix_product_state_max_bond_dimension`` (int): Sets a limit on the number of Schmidt coefficients retained at the end of the svd algorithm. Coefficients beyond this limit will be discarded. (Default: None, i.e., no limit on the bond dimension). * ``matrix_product_state_truncation_threshold`` (double): Discard the smallest coefficients for which the sum of their squares is smaller than this threshold. (Default: 1e-16). * ``mps_sample_measure_algorithm`` (str): Choose which algorithm to use for ``"sample_measure"`` (Default: "mps_apply_measure"). - ``"mps_probabilities"``: This method first constructs the probability vector and then generates a sample per shot. It is more efficient for a large number of shots and a small number of qubits, with complexity O(2^n * n * D^2) to create the vector and O(1) per shot, where n is the number of qubits and D is the bond dimension. - ``"mps_apply_measure"``: This method creates a copy of the mps structure and measures directly on it. It is more efficient for a small number of shots, and a large number of qubits, with complexity around O(n * D^2) per shot. * ``mps_log_data`` (str): if True, output logging data of the MPS structure: bond dimensions and values discarded during approximation. (Default: False) These backend options apply in circuit optimization passes: * ``fusion_enable`` (bool): Enable fusion optimization in circuit optimization passes [Default: True] * ``fusion_verbose`` (bool): Output gates generated in fusion optimization into metadata [Default: False] * ``fusion_max_qubit`` (int): Maximum number of qubits for a operation generated in a fusion optimization [Default: 5] * ``fusion_threshold`` (int): Threshold that number of qubits must be greater than or equal to enable fusion optimization [Default: 14] """ _DEFAULT_BASIS_GATES = sorted( [ "u1", "u2", "u3", "u", "p", "r", "rx", "ry", "rz", "id", "x", "y", "z", "h", "s", "sdg", "sx", "sxdg", "t", "tdg", "swap", "cx", "cy", "cz", "csx", "cp", "cu", "cu1", "cu2", "cu3", "rxx", "ryy", "rzz", "rzx", "ccx", "cswap", "mcx", "mcy", "mcz", "mcsx", "mcp", "mcphase", "mcu", "mcu1", "mcu2", "mcu3", "mcrx", "mcry", "mcrz", "mcr", "mcswap", "unitary", "diagonal", "multiplexer", "initialize", "delay", "pauli", "mcx_gray", "ecr", ] ) _DEFAULT_CUSTOM_INSTR = sorted( [ "quantum_channel", "qerror_loc", "roerror", "kraus", "save_expval", "save_expval_var", "save_probabilities", "save_probabilities_dict", "save_amplitudes", "save_amplitudes_sq", "save_state", "save_density_matrix", "save_statevector", "save_statevector_dict", "save_stabilizer", "set_statevector", "set_density_matrix", "set_stabilizer", "reset", ] ) _DEFAULT_CONFIGURATION = { "backend_name": "qasm_simulator", "backend_version": __version__, "n_qubits": MAX_QUBITS_STATEVECTOR, "url": "https://github.com/Qiskit/qiskit-aer", "simulator": True, "local": True, "conditional": True, "open_pulse": False, "memory": True, "max_shots": int(1e6), "description": "A C++ QasmQobj simulator with noise", "coupling_map": None, "basis_gates": _DEFAULT_BASIS_GATES, "custom_instructions": _DEFAULT_CUSTOM_INSTR, "gates": [], } _SIMULATION_METHODS = [ "automatic", "statevector", "statevector_gpu", "statevector_custatevec", "statevector_thrust", "density_matrix", "density_matrix_gpu", "density_matrix_custatevec", "density_matrix_thrust", "stabilizer", "matrix_product_state", "extended_stabilizer", ] _AVAILABLE_METHODS = None _SIMULATION_DEVICES = ("CPU", "GPU", "Thrust") _AVAILABLE_DEVICES = None def __init__(self, configuration=None, properties=None, provider=None, **backend_options): warn( "The `QasmSimulator` backend will be deprecated in the" " future. It has been superseded by the `AerSimulator`" " backend.", PendingDeprecationWarning, ) self._controller = aer_controller_execute() # Update available methods for class if QasmSimulator._AVAILABLE_METHODS is None: QasmSimulator._AVAILABLE_METHODS = available_methods( QasmSimulator._SIMULATION_METHODS, QasmSimulator._SIMULATION_DEVICES, ) # Default configuration if configuration is None: configuration = QasmBackendConfiguration.from_dict(QasmSimulator._DEFAULT_CONFIGURATION) else: configuration.open_pulse = False # Cache basis gates since computing the intersection # of noise model, method, and config gates is expensive. self._cached_basis_gates = self._DEFAULT_BASIS_GATES super().__init__( configuration, properties=properties, provider=provider, backend_options=backend_options ) def __repr__(self): """String representation of an AerBackend.""" display = super().__repr__()[:-1] pad = " " * (len(self.__class__.__name__) + 1) method = getattr(self.options, "method", None) if method not in [None, "automatic"]: display += f",\n{pad}method='{method}'" noise_model = getattr(self.options, "noise_model", None) if noise_model is not None and not noise_model.is_ideal(): display += f",\n{pad}noise_model={repr(noise_model)})" display += ")" return display @classmethod def _default_options(cls): return Options( # Global options shots=1024, method=None, device="CPU", precision="double", executor=None, max_job_size=None, max_shot_size=None, enable_truncation=True, zero_threshold=1e-10, validation_threshold=None, max_parallel_threads=None, max_parallel_experiments=None, max_parallel_shots=None, max_memory_mb=None, fusion_enable=True, fusion_verbose=False, fusion_max_qubit=5, fusion_threshold=14, accept_distributed_results=None, blocking_qubits=None, blocking_enable=False, memory=None, noise_model=None, seed_simulator=None, # statevector options statevector_parallel_threshold=14, statevector_sample_measure_opt=10, # stabilizer options stabilizer_max_snapshot_probabilities=32, # extended stabilizer options extended_stabilizer_sampling_method="resampled_metropolis", extended_stabilizer_metropolis_mixing_time=5000, extended_stabilizer_approximation_error=0.05, extended_stabilizer_norm_estimation_samples=100, extended_stabilizer_norm_estimation_repetitions=3, extended_stabilizer_parallel_threshold=100, extended_stabilizer_probabilities_snapshot_samples=3000, # MPS options matrix_product_state_truncation_threshold=1e-16, matrix_product_state_max_bond_dimension=None, mps_sample_measure_algorithm="mps_heuristic", mps_log_data=False, chop_threshold=1e-8, mps_parallel_threshold=14, mps_omp_threads=1, )
[docs] @classmethod def from_backend(cls, backend, **options): """Initialize simulator from backend.""" if isinstance(backend, BackendV2): raise AerError("QasmSimulator.from_backend does not currently support V2 Backends.") # pylint: disable=import-outside-toplevel # Avoid cyclic import from ..noise.noise_model import NoiseModel # Get configuration and properties from backend configuration = copy.copy(backend.configuration()) properties = copy.copy(backend.properties()) # Customize configuration name name = configuration.backend_name configuration.backend_name = f"qasm_simulator({name})" # Use automatic noise model if none is provided if "noise_model" not in options: noise_model = NoiseModel.from_backend(backend) if not noise_model.is_ideal(): options["noise_model"] = noise_model # Initialize simulator sim = cls(configuration=configuration, properties=properties, **options) return sim
[docs] def configuration(self): """Return the simulator backend configuration. Returns: BackendConfiguration: the configuration for the backend. """ config = copy.copy(self._configuration) for key, val in self._options_configuration.items(): setattr(config, key, val) # Update basis gates based on custom options, config, method, # and noise model config.custom_instructions = self._custom_instructions() config.basis_gates = self._cached_basis_gates + config.custom_instructions return config
[docs] def available_methods(self): """Return the available simulation methods.""" return copy.copy(self._AVAILABLE_METHODS)
[docs] def available_devices(self): """Return the available simulation methods.""" return copy.copy(self._AVAILABLE_DEVICES)
def _execute_qobj(self, qobj): """Execute a qobj on the backend. Args: qobj (QasmQobj): simulator input. Returns: dict: return a dictionary of results. """ qobj = map_legacy_method_options(qobj) return cpp_execute_qobj(self._controller, qobj) def _execute_circuits(self, aer_circuits, noise_model, config): """Execute circuits on the backend.""" config = map_legacy_method_config(config) return cpp_execute_circuits(self._controller, aer_circuits, noise_model, config)
[docs] def set_option(self, key, value): if key == "custom_instructions": self._set_configuration_option(key, value) return if key == "method": if value in LEGACY_METHOD_MAP: value, device = LEGACY_METHOD_MAP[value] self.set_option("device", device) if value is not None and value not in self.available_methods(): raise AerError( f"Invalid simulation method {value}. Available methods" f" are: {self.available_methods()}" ) self._set_method_config(value) super().set_option(key, value) if key in ["method", "noise_model", "basis_gates"]: self._cached_basis_gates = self._basis_gates()
def _validate(self, qobj): """Semantic validations of the qobj which cannot be done via schemas. Warn if no measurements in circuit with classical registers. """ for experiment in qobj.experiments: # If circuit contains classical registers but not # measurements raise a warning if experiment.config.memory_slots > 0: # Check if measure opts missing no_measure = True for op in experiment.instructions: if not no_measure: break # we don't need to check any more ops if no_measure and op.name == "measure": no_measure = False # Print warning if clbits but no measure if no_measure: logger.warning( 'No measurements in circuit "%s": ' "count data will return all zeros.", experiment.header.name, ) def _basis_gates(self): """Return simualtor basis gates. This will be the option value of basis gates if it was set, otherwise it will be the intersection of the configuration, noise model and method supported basis gates. """ # Use option value for basis gates if set if "basis_gates" in self._options_configuration: return self._options_configuration["basis_gates"] # Compute intersection with method basis gates method_gates = self._method_basis_gates() config_gates = self._configuration.basis_gates if config_gates: basis_gates = set(config_gates).intersection(method_gates) else: basis_gates = method_gates # Compute intersection with noise model basis gates noise_model = getattr(self.options, "noise_model", None) if noise_model: noise_gates = noise_model.basis_gates basis_gates = basis_gates.intersection(noise_gates) else: noise_gates = None if not basis_gates: logger.warning( "The intersection of configuration basis gates (%s), " "simulation method basis gates (%s), and " "noise model basis gates (%s) is empty", config_gates, method_gates, noise_gates, ) return sorted(basis_gates) def _method_basis_gates(self): """Return method basis gates and custom instructions""" method = self._options.get("method", None) if method in [ "density_matrix", "density_matrix_gpu", "density_matrix_custatevec", "density_matrix_thrust", ]: return sorted( [ "u1", "u2", "u3", "u", "p", "r", "rx", "ry", "rz", "id", "x", "y", "z", "h", "s", "sdg", "sx", "sxdg", "t", "tdg", "swap", "cx", "cy", "cz", "cp", "cu1", "rxx", "ryy", "rzz", "rzx", "ccx", "unitary", "diagonal", "delay", "pauli", "ecr", ] ) if method == "matrix_product_state": return sorted( [ "u1", "u2", "u3", "u", "p", "cp", "cx", "cy", "cz", "id", "x", "y", "z", "h", "s", "sdg", "sx", "sxdg", "t", "tdg", "swap", "ccx", "unitary", "roerror", "delay", "pauli", "r", "rx", "ry", "rz", "rxx", "ryy", "rzz", "rzx", "csx", "cswap", "diagonal", "initialize", ] ) if method == "stabilizer": return sorted( [ "id", "x", "y", "z", "h", "s", "sdg", "sx", "sxdg", "cx", "cy", "cz", "swap", "delay", "pauli", "ecr", ] ) if method == "extended_stabilizer": return sorted( [ "cx", "cz", "id", "x", "y", "z", "h", "s", "sdg", "sx", "sxdg", "swap", "u0", "t", "tdg", "u1", "p", "ccx", "ccz", "delay", "pauli", ] ) return QasmSimulator._DEFAULT_BASIS_GATES def _custom_instructions(self): """Return method basis gates and custom instructions""" # pylint: disable = too-many-return-statements if "custom_instructions" in self._options_configuration: return self._options_configuration["custom_instructions"] method = self._options.get("method", None) if method in [ "statevector", "statevector_gpu", "statevector_custatevec", "statevector_thrust", ]: return sorted( [ "quantum_channel", "qerror_loc", "roerror", "kraus", "save_expval", "save_expval_var", "save_probabilities", "save_probabilities_dict", "save_amplitudes", "save_amplitudes_sq", "save_state", "save_density_matrix", "save_statevector", "save_statevector_dict", "set_statevector", ] ) if method in [ "density_matrix", "density_matrix_gpu", "density_matrix_custatevec", "density_matrix_thrust", ]: return sorted( [ "quantum_channel", "qerror_loc", "roerror", "kraus", "superop", "save_expval", "save_expval_var", "save_probabilities", "save_probabilities_dict", "save_state", "save_density_matrix", "save_amplitudes_sq", "set_statevector", "set_density_matrix", ] ) if method == "matrix_product_state": return sorted( [ "quantum_channel", "qerror_loc", "roerror", "kraus", "save_expval", "save_expval_var", "save_probabilities", "save_probabilities_dict", "save_density_matrix", "save_state", "save_statevector", "save_amplitudes", "save_amplitudes_sq", "save_matrix_product_state", "set_matrix_product_state", ] ) if method == "stabilizer": return sorted( [ "quantum_channel", "qerror_loc", "roerror", "save_expval", "save_expval_var", "save_probabilities", "save_probabilities_dict", "save_amplitudes_sq", "save_state", "save_stabilizer", "set_stabilizer", ] ) if method == "extended_stabilizer": return sorted(["quantum_channel", "qerror_loc", "roerror", "save_statevector"]) return QasmSimulator._DEFAULT_CUSTOM_INSTR def _set_method_config(self, method=None): """Set non-basis gate options when setting method""" # Update configuration description and number of qubits if method in [ "statevector", "statevector_gpu", "statevector_custatevec", "statevector_thrust", ]: description = "A C++ statevector simulator with noise" n_qubits = MAX_QUBITS_STATEVECTOR elif method in [ "density_matrix", "density_matrix_gpu", "density_matrix_custatevec", "density_matrix_thrust", ]: description = "A C++ density matrix simulator with noise" n_qubits = MAX_QUBITS_STATEVECTOR // 2 elif method == "matrix_product_state": description = "A C++ matrix product state simulator with noise" n_qubits = 63 # TODO: not sure what to put here? elif method == "stabilizer": description = "A C++ Clifford stabilizer simulator with noise" n_qubits = 10000 # TODO: estimate from memory elif method == "extended_stabilizer": description = "A C++ Clifford+T extended stabilizer simulator with noise" n_qubits = 63 # TODO: estimate from memory else: # Clear options to default description = None n_qubits = None self._set_configuration_option("description", description) self._set_configuration_option("n_qubits", n_qubits)