Evolutionary Computation for Adaptive Quantum Device Design. Issue 8 (15th June 2021)

• Record Type: Journal Article
• Authors: Mortimer, Luke; Estarellas, Marta P.; Spiller, Timothy P.; D'Amico, Irene
• Is Part Of: Advanced quantum technologies. Volume 4:Issue 8(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-15
• Subjects: evolutionary computation -- genetic algorithms -- spin chains -- spin networks -- quantum computing -- quantum information processing -- quantum devices; Quantum theory -- Periodicals; Quantum computing -- Periodicals; Quantum chemistry -- Periodicals; Quantum electronics -- Periodicals; 537.5
• DOI: 10.1002/qute.202100013
• Languages: English
• ISSNs: 2511-9044

Abstract

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. Abstract : When designing quantum devices, it is important to have the appropriate means of communicating between components, one such proposal is using spin networks. Complex designs achieving more advanced tasks are possible, but require precise tuning. It is shown here how to use genetics to efficiently design such networks, which are able to perform custom quantum information tasks with high fidelity.