Evolving quantum logic gate circuits in Qiskit
dc.contributor.author | Newbold, T | |
dc.contributor.author | Moraglio, A | |
dc.date.accessioned | 2024-05-16T14:35:13Z | |
dc.date.issued | 2024-08-01 | |
dc.date.updated | 2024-05-16T13:51:05Z | |
dc.description.abstract | The emergence of quantum computers represents a crucial leap forward in practical computability, when compared to classical architectures. Harnessing that power effectively is an exercise of increasing importance. Despite research in this field expanding rapidly, little headway has been made towards new quantum algorithms. The complexity of quantum systems makes them conceptually inaccessible to non-experts; therefore, programs are hard to design, hindering advancement. This paper presents a method for genetically encoding and designing arbitrary circuits in Qiskit, a software library developed by IBM for simulating quantum logic gates. The effectiveness of the system is verified by evolving solutions to the Toffoli gate and Quantum Fourier Transform problems. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | GECCO '24, Melbourne, Australia, 14 - 18 July 2024, pp. 2111 - 2114 | en_GB |
dc.identifier.doi | https://doi.org/10.1145/3638530.3664108 | |
dc.identifier.uri | http://hdl.handle.net/10871/135963 | |
dc.identifier | ORCID: 0000-0003-4782-6590 (Moraglio, Alberto) | |
dc.language.iso | en | en_GB |
dc.publisher | Association for Computing Machinery (ACM) | en_GB |
dc.rights | © 2024 Copyright held by the owner/author(s). Open access. This work is licensed under a Creative Commons Attribution International 4.0 License | en_GB |
dc.subject | Genetic Programming | en_GB |
dc.subject | Evolutionary Algorithms | en_GB |
dc.subject | Quantum Logic Gates | en_GB |
dc.subject | Quantum Fourier Transform | en_GB |
dc.subject | Qiskit | en_GB |
dc.title | Evolving quantum logic gate circuits in Qiskit | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2024-05-16T14:35:13Z | |
dc.identifier.isbn | 9798400704956 | |
exeter.location | Melbourne, Australia | |
dc.description | This is the final version. Available on open access from ACM via the DOI in this record | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2024-05-03 | |
dcterms.dateSubmitted | 2024-03-28 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2024-05-03 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2024-05-16T13:51:07Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2024-08-23T12:22:42Z | |
refterms.panel | B | en_GB |
pubs.name-of-conference | GECCO 2024 | |
exeter.rights-retention-statement | Yes |
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Except where otherwise noted, this item's licence is described as © 2024 Copyright held by the owner/author(s). Open access. This work is licensed under a Creative Commons Attribution International 4.0 License