QasmSimulator¶

class
QasmSimulator
(configuration=None, properties=None, provider=None, **backend_options)[Quellcode]¶ 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
set_options()
method.Runtime options may also be specified as kwargs using the
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
noise_model = NoiseModel.from_backend(backend) backend = QasmSimulator(method='density_matrix', noise_model=noise_model)
Simulating an IBMQ Backend
The simulator can be automatically configured to mimic an IBMQ backend using the
from_backend()
method. This will configure the simulator to use the basic deviceNoiseModel
for that backend, and the same basis gates and coupling map.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 rankedstabilizer decomposition that decomposes circuits into stabilizer state terms. The number of terms grows with the number of nonClifford gates."matrix_product_state"
: A tensornetwork 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"
).precision
(str): Set the floating point precision for certain simulation methods to either"single"
or"double"
precision (default:"double"
).zero_threshold
(double): Sets the threshold for truncating small values to zero in the result data (Default: 1e10).validation_threshold
(double): Sets the threshold for checking if initial states are valid (Default: 1e8).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 nqubits uses 2^n complex values (16 Bytes). If set to 0, the maximum will be automatically set to half the system memory size (Default: 0).optimize_ideal_threshold
(int): Sets the qubit threshold for applying circuit optimization passes on ideal circuits. Passes include gate fusion and truncation of unused qubits (Default: 5).optimize_noise_threshold
(int): Sets the qubit threshold for applying circuit optimization passes on ideal circuits. Passes include gate fusion and truncation of unused qubits (Default: 12).
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 ~qiskit.providers.aer.extensions.SnapshotProbabilities instruction (Default: 32).
These backend options only apply when using the
"extended_stabilizer"
simulation method:extended_stabilizer_measure_sampling
(bool): Enable measure sampling optimization on supported circuits. This prevents the simulator from rerunning the measure montecarlo step for each shot. Enabling measure sampling may reduce accuracy of the measurement counts if the output distribution is strongly peaked (Default: False).extended_stabilizer_mixing_time
(int): Set how long the montecarlo 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): Number of samples used to compute the correct normalization for a statevector snapshot (Default: 100).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).
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: 1e16).mps_sample_measure_algorithm
(str): Choose which algorithm to use for"sample_measure"
."mps_probabilities"
means all state probabilities are computed and measurements are based on them. It is more efficient for a large number of shots, small number of qubits and low entanglement."mps_apply_measure"
creates a copy of the mps structure and makes a measurement on it. It is more effients for a small number of shots, high number of qubits, and low entanglement. If the user does not specify the algorithm, a heuristic algorithm is used to select between the two algorithms. (Default: „mps_heuristic“).
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]
Aer class for backends.
This method should initialize the module and its configuration, and raise an exception if a component of the module is not available.
 Parameter
configuration (BackendConfiguration) – backend configuration.
properties (BackendProperties or None) – Optional, backend properties.
defaults (PulseDefaults or None) – Optional, backend pulse defaults.
available_methods (list or None) – Optional, the available simulation methods if backend supports multiple methods.
provider (BaseProvider) – Optional, provider responsible for this backend.
backend_options (dict or None) – Optional set custom backend options.
 Verursacht
AerError – if there is no name in the configuration
Attributes
Return the current simulator options
Methods
Return the available simulation methods.
Reset the simulator options to default values.
Return the simulator backend configuration.
Return the simulator backend pulse defaults.
QasmSimulator.from_backend
(backend, **options)Initialize simulator from backend.
Return the backend name.
Return the simulator backend properties if set.
Return the backend Provider.
QasmSimulator.run
(qobj[, backend_options, …])Run a qobj on the backend.
QasmSimulator.set_options
(**backend_options)Set the simulator options
Return backend status.
Return the backend version.