Non-Markovian cost function for quantum error mitigation with Dirac Gamma matrices representation.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
16 Nov 2023
Historique:
received: 17 06 2023
accepted: 15 10 2023
medline: 17 11 2023
pubmed: 17 11 2023
entrez: 17 11 2023
Statut: epublish

Résumé

This paper investigates the non-Markovian cost function in quantum error mitigation (QEM) and employs Dirac Gamma matrices to illustrate two-qubit operators, significant in relativistic quantum mechanics. Amid the focus on error reduction in noisy intermediate-scale quantum (NISQ) devices, understanding non-Markovian noise, commonly found in solid-state quantum computers, is crucial. We propose a non-Markovian model for quantum state evolution and a corresponding QEM cost function, using simple harmonic oscillators as a proxy for environmental noise. Owing to their shared algebraic structure with two-qubit gate operators, Gamma matrices allow for enhanced analysis and manipulation of these operators. We evaluate the fluctuations of the output quantum state across various input states for identity and SWAP gate operations, and by comparing our findings with ion-trap and superconducting quantum computing systems' experimental data, we derive essential QEM cost function parameters. Our findings indicate a direct relationship between the quantum system's coupling strength with its environment and the QEM cost function. The research highlights non-Markovian models' importance in understanding quantum state evolution and assessing experimental outcomes from NISQ devices.

Identifiants

pubmed: 37973833
doi: 10.1038/s41598-023-45053-y
pii: 10.1038/s41598-023-45053-y
pmc: PMC10654775
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

20069

Subventions

Organisme : NRF
ID : NRF-2023R1A2C1003570
Organisme : Ministry of Science and ICT, South Korea
ID : RS-2023-00225385
Organisme : Air Force Office of Scientific Research
ID : FA2386-21-1-0089

Informations de copyright

© 2023. The Author(s).

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Auteurs

Doyeol Ahn (D)

Department of Electrical and Computer Engineering, University of Seoul, 163 Seoulsiripdae-Ro, Tongdaimoon-Gu, Seoul, 02504, Republic of Korea. dahn@uos.ac.kr.

Classifications MeSH