Machine learning protocol to identify pairing symmetries via quasiparticle interference imaging in Ising superconductors

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Title:	Machine learning protocol to identify pairing symmetries via quasiparticle interference imaging in Ising superconductors
Authors:	Hlozny, Adam; Hanis, Jozef; Gmitra, Martin; Milivojevic, Marko
Issue Date:	2026
Publication:	PHYSICAL REVIEW B
ISSN:	2469-9950 Physical Review B Search Idenfier
Type:	Article
Collation:	vol. 114 br. 2
DOI:	10.1103/7zvs-rnmt
WoS-ID:	001830601400001
URI:	https://enauka.gov.rs/handle/123456789/1049320
Project:	European Regional Development Fund [311070AKF2] EU Structural Funds Informatization of society Operational Program Integrated Infrastructure [APVV-21-0272] Ministry of Education, Research, Development and Youth of the Slovak Republic [APVV-21-0272, VEGA 2/0133/25, VEGA 1/0104/25] Slovak Academy of Sciences Project [IMPULZ IM-2021-42] Programme Johannes Amos Commenius, called Excellent Research [CZ.02.01.01/00/22_-008/0004572] EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia [09I02-03-V01-00012] APVV [APVV-23-0430] VEGA [APVV-21-0272, APVV-23-0430]
Metadata source:	(Preuzeto iz Nasi u WoS)
M-category:	21M21

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