qrunch.quantum.estimators.tensor_network_estimator

Tensor network estimator.

Classes

TensorNetworkEstimator	Estimator using a tensor network simulator.
TensorNetworkEstimatorOptions	Configuration options for the TensorNetworkEstimator.

class TensorNetworkEstimator

Bases: Estimator

Estimator using a tensor network simulator.

__init__(simulator: TensorNetworkSimulator, error_mitigator: EstimatorErrorMitigator | None = None, options: TensorNetworkEstimatorOptions | None = None) → None

Initialize the tensor network estimator.

Parameters:

• simulator (TensorNetworkSimulator) – The tensor network simulator to use.

• error_mitigator (EstimatorErrorMitigator | None) – Error mitigator to be used for encoding the observable or circuit more error resistantly.

• options (TensorNetworkEstimatorOptions | None) – Configuration options for preprocessing. If None, defaults to no preprocessing.

Return type:

None

clear_cache() → None

Clear the measurement cache.

Return type:

None

has_spin_particle_conservation() → bool

Return True, if the estimator is set to use spin particle conservation.

Return type:

bool

has_total_particle_conservation() → bool

Return True, if the estimator is set to use total particle conservation.

Return type:

bool

run(observables: Sequence[int | float | complex | Expression[PauliOperators]] | int | float | complex | Expression[PauliOperators] | Sequence[HermitianPauliSum] | HermitianPauliSum, circuits: Circuit | Sequence[Circuit], shots: int | None) → ExpectationValue | list[ExpectationValue] | EstimatorResults

Estimate the value of the observables using the circuit state.

For each observable the following will be calculated: <circuit|observable|circuit>.

Parameters:

• observables (Sequence[int | float | complex | Expression[PauliOperators]] | int | float | complex | Expression[PauliOperators] | Sequence[HermitianPauliSum] | HermitianPauliSum) – Observable(s) to be estimated.

• circuits (Circuit | Sequence[Circuit]) – States to make estimation from.

• shots (int | None) – number of shots or None if using a full state vector calculation.

Return type:

ExpectationValue | list[ExpectationValue] | EstimatorResults

supports_shots_equals_none() → bool

Return whether the estimator supports shots = None.

Shots = None means that a full state vector simulation is done.

Return type:

bool

class TensorNetworkEstimatorOptions

Bases: object

Configuration options for the TensorNetworkEstimator.

Parameters:

• use_lightcone_preprocessing – If True, apply light cone cancellation preprocessing to remove gate/conjugate pairs that cancel (G·G† = I). Default is False.

• use_rank_simplification_preprocessing – If True, apply rank-2 simplification preprocessing to contract all low-rank (≤2) tensors. Default is False.

__init__(use_lightcone_preprocessing: bool = False, use_rank_simplification_preprocessing: bool = False) → None

Parameters:

• use_lightcone_preprocessing (bool)

• use_rank_simplification_preprocessing (bool)

Return type:

None

use_lightcone_preprocessing: bool = False

use_rank_simplification_preprocessing: bool = False