Neat

class Neat(backend, noise_model=None)[source]

Bases: object

A class to help understand the expected performance of estimator jobs.

The “Noisy Estimator Analyzer Tool” (or “NEAT”) is a convenience tool that users of the Estimator primitive can employ to analyze and predict the performance of their queries. Its simulate method uses qiskit-aer to simulate the estimation task classically efficiently, either in ideal conditions or in the presence of noise. The simulations’ results can be compared with other simulation results or with primitive results results to draw custom figures of merit.

Parameters:

  • backend (Backend) – A backend.

  • noise_model (Optional[NoiseModel]) – A noise model for the operations of the given backend. If None, it defaults to the noise model generated by NoiseModel.from_backend().

Attributes

noise_model

The noise model used by this analyzer tool for the noisy simulations.

Methods

backend()[source]

The backend used by this analyzer tool.

Return type:

BackendV2

ideal_sim(pubs, cliffordize=False, seed_simulator=None, precision=0)[source]

Perform an ideal, noiseless simulation of the estimator task specified by pubs.

This function uses qiskit-aer’s Estimator class to simulate the estimation task classically.

Note

To ensure scalability, every circuit in pubs is required to be a Clifford circuit, so that it can be simulated efficiently regardless of its size. For estimation tasks that involve non-Clifford circuits, the recommended workflow consists of mapping the non-Clifford circuits to the nearest Clifford circuits using the ConvertISAToClifford transpiler pass, or equivalently, to use the Neat’s to_clifford() convenience method. Alternatively, setting cliffordize to True ensures that the to_clifford() method is applied automatically to the given pubs prior to the simulation.

Parameters:

  • pubs (Sequence[EstimatorPubLike]) – The PUBs specifying the estimation task of interest.

  • cliffordize (bool) – Whether or not to automatically apply the ConvertISAToClifford transpiler pass to the given pubs before performing the simulations.

  • seed_simulator (int | None) – A seed for the simulator.

  • precision (float) – The target precision for the estimates of each expectation value in the returned results.

Returns:

The results of the simulation.

Return type:

NeatResult

noisy_sim(pubs, cliffordize=False, seed_simulator=None, precision=0)[source]

Perform a noisy simulation of the estimator task specified by pubs.

This function uses qiskit-aer’s Estimator class to simulate the estimation task classically.

Note

To ensure scalability, every circuit in pubs is required to be a Clifford circuit, so that it can be simulated efficiently regardless of its size. For estimation tasks that involve non-Clifford circuits, the recommended workflow consists of mapping the non-Clifford circuits to the nearest Clifford circuits using the ConvertISAToClifford transpiler pass, or equivalently, to use the Neat’s to_clifford() convenience method. Alternatively, setting cliffordize to True ensures that the to_clifford() method is applied automatically to the given pubs prior to the simulation.

Parameters:

  • pubs (Sequence[EstimatorPubLike]) – The PUBs specifying the estimation task of interest.

  • cliffordize (bool) – Whether or not to automatically apply the ConvertISAToClifford transpiler pass to the given pubs before performing the simulations.

  • seed_simulator (int | None) – A seed for the simulator.

  • precision (float) – The target precision for the estimates of each expectation value in the returned results.

Returns:

The results of the simulation.

Return type:

NeatResult

to_clifford(pubs)[source]

Return the cliffordized version of the given pubs.

This convenience method runs the ConvertISAToClifford transpiler pass on the PUBs’ circuits.

Parameters:

pubs (Sequence[EstimatorPubLike]) – The PUBs to turn into Clifford PUBs.

Returns:

The Clifford PUBs.

Return type:

list[EstimatorPub]