Evolutionary computation for adaptive quantum device design

TL;DR

This paper introduces an evolutionary algorithm that automatically tunes parameters of NISQ quantum devices, enabling high-fidelity task performance and rapid convergence, thus aiding device design and calibration.

Contribution

The paper presents a novel evolutionary algorithm for automatic parameter tuning of quantum devices, demonstrating rapid convergence and high fidelity in quantum state distribution and multi-qubit gate design.

Findings

Algorithm converges rapidly.

Achieves high fidelity in quantum tasks.

Generates innovative quantum device designs.

Abstract

As Noisy Intermediate-Scale Quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm is presented here which allows for the automatic tuning of the parameters of any arrangement of coupled qubits, to perform a given task with high fidelity. The algorithm's use is exemplified with the generation of schemes for the distribution of quantum states and the design of multi-qubit gates. The algorithm is demonstrated to converge very rapidly, yielding unforeseeable designs of quantum devices that perform their required tasks with excellent fidelities. Given these promising results, practical scalability and application versatility, the approach has the potential to become a powerful technique to aid the design and calibration of NISQ devices.