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IBM Quantum Platform

BackendEstimatorV2

class qiskit.primitives.BackendEstimatorV2(*, backend, options=None)

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Bases: BaseEstimatorV2

Evaluates expectation values for provided quantum circuit and observable combinations.

The BackendEstimatorV2 class is a generic implementation of the BaseEstimatorV2 interface that is used to wrap a BackendV2 (or BackendV1) object in the BaseEstimatorV2 API. It facilitates using backends that do not provide a native BaseEstimatorV2 implementation in places that work with BaseEstimatorV2. However, if you’re using a provider that has a native implementation of BaseEstimatorV2, it is a better choice to leverage that native implementation as it will likely include additional optimizations and be a more efficient implementation. The generic nature of this class precludes doing any provider- or backend-specific optimizations.

This class does not perform any measurement or gate mitigation, and, presently, is only compatible with Pauli-based observables. More formally, given an observable of the type O=i=1NaiPiO=\sum_{i=1}^Na_iP_i, where aia_i is a complex number and PiP_i is a Pauli operator, the estimator calculates the expectation E(Pi)\mathbb{E}(P_i) of each PiP_i and finally calculates the expectation value of OO as E(O)=i=1NaiE(Pi)\mathbb{E}(O)=\sum_{i=1}^Na_i\mathbb{E}(P_i). The reported std is calculated as

i=1naiVar(Pi)N,\frac{\sum_{i=1}^{n}|a_i|\sqrt{\textrm{Var}\big(P_i\big)}}{\sqrt{N}}\:,

where Var(Pi)\textrm{Var}(P_i) is the variance of PiP_i, N=O(ϵ2)N=O(\epsilon^{-2}) is the number of shots, and ϵ\epsilon is the target precision [1].

Each tuple of (circuit, observables, <optional> parameter values, <optional> precision), called an estimator primitive unified bloc (PUB), produces its own array-based result. The run() method can be given a sequence of pubs to run in one call.

The options for BackendEstimatorV2 consist of the following items.

  • default_precision: The default precision to use if none are specified in run(). Default: 0.015625 (1 / sqrt(4096)).
  • abelian_grouping: Whether the observables should be grouped into sets of qubit-wise commuting observables. Default: True.
  • seed_simulator: The seed to use in the simulator. If None, a random seed will be used. Default: None.

Reference:

[1] O. Crawford, B. van Straaten, D. Wang, T. Parks, E. Campbell, St. Brierley, Efficient quantum measurement of Pauli operators in the presence of finite sampling error. Quantum 5, 385

Deprecated since version 1.4

The method BackendEstimatorV2.__init__ will stop supporting inputs of type BackendV1 in the backend parameter in a future release no earlier than 2.0. BackendV1 is deprecated and implementations should move to BackendV2.

Parameters

  • backend (BackendV1 |BackendV2) – The backend to run the primitive on.
  • options (dict | None) – The options to control the default precision (default_precision), the operator grouping (abelian_grouping), and the random seed for the simulator (seed_simulator).

Attributes

backend

Returns the backend which this sampler object based on.

options

Return the options


Methods

run

run(pubs, *, precision=None)

GitHub

Estimate expectation values for each provided pub (Primitive Unified Bloc).

Parameters

  • pubs (Iterable[EstimatorPubLike]) – An iterable of pub-like objects, such as tuples (circuit, observables) or (circuit, observables, parameter_values).
  • precision (float | None) – The target precision for expectation value estimates of each run Estimator Pub that does not specify its own precision. If None the estimator’s default precision value will be used.

Returns

A job object that contains results.

Return type

PrimitiveJob[PrimitiveResult[PubResult]]

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