Create a ADAPT Gate Selector

Goal

Construct an ADAPT gate selector for adaptive/iterative VQE, optionally configuring its estimator and shot number. See Gate Selection to learn more about gate selection.

Prerequisites

• (Optional) An estimator (see Create an Estimator)

Steps

1. Quick start: default ADAPT gate selector

   If nothing else is specified, the default metric is the heuristic gradient.

   import qrunch as qc
   
   gate_selector = (
       qc.gate_selector_creator()
       .adapt()
       .create()
   )
   

2. Provide an estimator

You can provide an estimator and the number of shots that will be used to evaluate the commutator expectation values in the ADAPT scheme.

import qrunch as qc

gate_selector = (
    qc.gate_selector_creator()
    .adapt()
    .with_estimator(user_estimator)
    .with_shots(shots=1000)   # finite-shots sampling
    .create()
)

See Create an Estimator for how to create an estimator.

Note

with_shots(shots=None) is only valid with a state-vector simulator (no sampling noise). For hardware-like runs, use a positive integer.

Verify the Result

• The variable gate_selector is a configured ADAPT gate selector instance suitable for iterative VQE.

• Integrate it into a VQE calculator explained in Build a VQE Calculator with calculator_creator

See Also

• Understanding and Using Kvantify Qrunch’s Fluent Builder Pattern

• Create an Estimator

Next Step

You can use the gate selector to build a VQE calculator:

• Calculate the Ground State Energy Using the FAST-VQE