Hybrid actor-critic algorithm for quantum reinforcement learning at cern beam lines

dc.contributor.author	Schenk, M.
dc.contributor.author	Fernández-Combarro Álvarez, Elías
dc.contributor.author	Grossi, M.
dc.contributor.author	Kain, V.
dc.contributor.author	Li, K. S. B.
dc.contributor.author	Popa, M. M.
dc.contributor.author	Vallecorsa, S.
dc.date.accessioned	2024-07-11T07:31:54Z
dc.date.available	2024-07-11T07:31:54Z
dc.date.issued	2024
dc.identifier.citation	Quantum Science and Technology, 9(2), (2024); doi:10.1088/2058-9565/ad261b
dc.identifier.issn	2058-9565
dc.identifier.uri	https://hdl.handle.net/10651/73470
dc.description.sponsorship	Gobierno del Principado de Asturias [MCIN/AEI/10.13039/501100011033, PID2020-119082RB-C22]; Quantum Spain project - Ministry of Economic Affairs and Digital Transformation of the Spanish Government [AYUD/2021/50994]; European Union through the Recovery, Transformation and Resilience Plan-NextGenerationEU
dc.language.iso	eng
dc.relation.ispartof	Quantum Science and Technology
dc.rights	©,
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185839251&doi=10.1088%2f2058-9565%2fad261b&partnerID=40&md5=64324e070b4fbaf70f6007c705e0df8f
dc.title	Hybrid actor-critic algorithm for quantum reinforcement learning at cern beam lines
dc.type	journal article
dc.identifier.doi	10.1088/2058-9565/ad261b
dc.relation.publisherversion	http://dx.doi.org/10.1088/2058-9565/ad261b

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