Robust and fast post-processing of single-shot spin qubit detection events with a neural network.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
10 Aug 2021
10 Aug 2021
Historique:
received:
22
03
2021
accepted:
23
07
2021
entrez:
11
8
2021
pubmed:
12
8
2021
medline:
12
8
2021
Statut:
epublish
Résumé
Establishing low-error and fast detection methods for qubit readout is crucial for efficient quantum error correction. Here, we test neural networks to classify a collection of single-shot spin detection events, which are the readout signal of our qubit measurements. This readout signal contains a stochastic peak, for which a Bayesian inference filter including Gaussian noise is theoretically optimal. Hence, we benchmark our neural networks trained by various strategies versus this latter algorithm. Training of the network with 10
Identifiants
pubmed: 34376730
doi: 10.1038/s41598-021-95562-x
pii: 10.1038/s41598-021-95562-x
pmc: PMC8355192
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16203Subventions
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : BO 3140/4-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 289786932
Organisme : Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
ID : 13N14778
Informations de copyright
© 2021. The Author(s).
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