qrunch.quantum.algorithms.pauli.vqes.adapt_gate_selector

Implementation of ADAPT-VQE (https://arxiv.org/pdf/1812.11173).

The core logic that defines the ADAPT-specific behavior is defined in the ADAPTGateSelector, and the class for running the ADAPT-VQE algorithm is just a class that calls the AdaptiveVqe class with the ADAPTGateSelector and some standard options.

Classes

AdaptGateSelector	Implementation of the GateSelector for ADAPT-VQE.
AdaptGateSelectorCreator	Builder of an ADAPT gate selector.

class AdaptGateSelector

Bases: GateSelector

Implementation of the GateSelector for ADAPT-VQE.

This gate selector uses the gate parameter gradient as the importance metric and does not perform any modifications on the gate pool.

Using this in the AdaptiveVQE results in an implementation of the ADAPT-VQE algorithm.

__init__(estimator: Estimator, shots: int | None) → None

Initialize the ADAPT GateSelector.

Parameters:

• estimator (Estimator)

• shots (int | None)

Return type:

None

register_gate_pool(gate_pool: GatePool) → None

Register the gate pool.

Parameters:

gate_pool (GatePool) – the gate pool to register in the GateSelector. The GateSelector can only choose gates from this.

Return type:

None

select_gates(observable: HermitianPauliSum, circuit: Circuit, *, number_of_gates: int = 1) → list[GatePoolOperator]

Select the best gates from the gate pool for minimizing the expectation value of the observable.

Parameters:

• observable (HermitianPauliSum) – The observable whose expectation value should be minimized.

• circuit (Circuit) – The circuit to extend with a gate from the gate pool.

• number_of_gates (int) – Number of gates to select.

Returns:

The gate to append to the circuit.

Return type:

list[GatePoolOperator]

class AdaptGateSelectorCreator

Bases: object

Builder of an ADAPT gate selector.

__init__() → None

Initialize builder for the ADAPT gate selector.

Return type:

None

create() → AdaptGateSelector

Create an instance of AdaptGateSelector.

Return type:

AdaptGateSelector

with_estimator(estimator: Estimator) → Self

Set the estimator to use for the ADAPT gate selector.

Parameters:

estimator (Estimator) – The estimator to use. Can be created using the estimator_creator().

Return type:

Self

with_shots(shots: int | None) → Self

Set the number of shots to use in the ADAPT gate selector.

Parameters:

shots (int | None) – Number of shots to use. If None, use exact sampling (requires an exact estimator like the excitation gate estimator).

Return type:

Self