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pro vyhledávání: '"Birgit Hillebrecht"'
Autor:
Birgit Hillebrecht, Benjamin Unger
Physics-informed neural networks (PINNs) are one popular approach to incorporate a priori knowledge about physical systems into the learning framework. PINNs are known to be robust for smaller training sets, derive better generalization problems, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37ad36e1f9661a6560c5fe545ba757d7
Publikováno v:
Journal of Statistical Mechanics: Theory and Experiment
Patra, A, Hillebrecht, B & Nielsen, A E B 2021, ' Continuum limit of lattice quasielectron wavefunctions ', Journal of Statistical Mechanics: Theory and Experiment, vol. 2021, no. 8, 083101 . https://doi.org/10.1088/1742-5468/ac0f63
Patra, A, Hillebrecht, B & Nielsen, A E B 2021, ' Continuum limit of lattice quasielectron wavefunctions ', Journal of Statistical Mechanics: Theory and Experiment, vol. 2021, no. 8, 083101 . https://doi.org/10.1088/1742-5468/ac0f63
Trial states describing anyonic quasiholes in the Laughlin state were found early on, and it is therefore natural to expect that one should also be able to create anyonic quasielectrons. Nevertheless, the existing trial wavefunctions for quasielectro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3ad8eaa91248f46e624f3baeabb63bf
http://arxiv.org/abs/2004.12205
http://arxiv.org/abs/2004.12205