Evolutionary computation for adaptive quantum device design

Luke Mortimer, Marta P. Estarellas, Timothy P. Spiller, Irene D'Amico*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number2100013
Number of pages9
JournalAdvanced Quantum Technologies
Early online date15 Jun 2021
Publication statusPublished - 10 Aug 2021

Bibliographical note

Funding Information:
M.P.E. would like to acknowledge support from the Japanese MEXT Quantum Leap Flagship Program (MEXT Q‐LEAP) Grant Number JPMXS0118069605. This project was in part undertaken on the Viking Cluster, a high‐performance computing facility provided by the University of York. The authors are grateful for the computational support from the University of York High Performance Computing service, Viking and the Research Computing team.

Publisher Copyright:
© 2021 The Authors. Advanced Quantum Technologies published by Wiley-VCH GmbH


  • evolutionary computation
  • genetic algorithms
  • quantum computing
  • quantum devices
  • quantum information processing
  • spin chains
  • spin networks

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