Detecting ergodic bubbles at the crossover to many-body localization using neural networks

2021
journal article
article
9
cris.lastimport.wos2024-04-10T02:54:29Z
dc.abstract.enThe transition between ergodic and many-body localized (MBL) phases is expected to occur via an avalanche mechanism, in which ergodic bubbles that arise due to local fluctuations in system properties thermalize their surroundings leading to delocalization of the system, unless the disorder is sufficiently strong to stop this process. We propose an algorithm based on neural networks that allows us to detect the ergodic bubbles using experimentally measurable two-site correlation functions. Investigating the time evolution of the system, we observe a logarithmic in time growth of the ergodic bubbles in the MBL regime. The distribution of the size of ergodic bubbles converges during time evolution to an exponentially decaying distribution in the MBL regime, and a power-law distribution with a thermal peak in the critical regime, supporting thus the scenario of delocalization through the avalanche mechanism. Our algorithm permits us to pinpoint the quantitative differences in the time evolution of systems with random and quasiperiodic potentials, as well as to identify rare (Griffiths) events. Our results open different pathways in studies of the mechanisms of thermalization of disordered many-body systems and beyond.pl
dc.affiliationWydział Fizyki, Astronomii i Informatyki Stosowanej : Zespół Zakładów Fizyki Teoretycznejpl
dc.affiliationWydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki im. Mariana Smoluchowskiegopl
dc.affiliationSzkoła Doktorska Nauk Ścisłych i Przyrodniczychpl
dc.contributor.authorSzołdra, Tomasz - 257493 pl
dc.contributor.authorSierant, Piotr - 187960 pl
dc.contributor.authorKottmann, Korbinianpl
dc.contributor.authorLewenstein, Maciejpl
dc.contributor.authorZakrzewski, Jakub - 100023 pl
dc.date.accessioned2021-11-25T21:09:20Z
dc.date.available2021-11-25T21:09:20Z
dc.date.issued2021pl
dc.description.number14pl
dc.description.volume104pl
dc.identifier.articleidL140202pl
dc.identifier.doi10.1103/PhysRevB.104.L140202pl
dc.identifier.eissn2469-9969pl
dc.identifier.issn2469-9950pl
dc.identifier.urihttps://ruj.uj.edu.pl/xmlui/handle/item/284347
dc.languageengpl
dc.language.containerengpl
dc.rightsDodaję tylko opis bibliograficzny*
dc.rights.licencebez licencji
dc.rights.uri*
dc.subtypeArticlepl
dc.titleDetecting ergodic bubbles at the crossover to many-body localization using neural networkspl
dc.title.journalPhysical Review. Bpl
dc.typeJournalArticlepl
dspace.entity.typePublication
cris.lastimport.wos
2024-04-10T02:54:29Z
dc.abstract.enpl
The transition between ergodic and many-body localized (MBL) phases is expected to occur via an avalanche mechanism, in which ergodic bubbles that arise due to local fluctuations in system properties thermalize their surroundings leading to delocalization of the system, unless the disorder is sufficiently strong to stop this process. We propose an algorithm based on neural networks that allows us to detect the ergodic bubbles using experimentally measurable two-site correlation functions. Investigating the time evolution of the system, we observe a logarithmic in time growth of the ergodic bubbles in the MBL regime. The distribution of the size of ergodic bubbles converges during time evolution to an exponentially decaying distribution in the MBL regime, and a power-law distribution with a thermal peak in the critical regime, supporting thus the scenario of delocalization through the avalanche mechanism. Our algorithm permits us to pinpoint the quantitative differences in the time evolution of systems with random and quasiperiodic potentials, as well as to identify rare (Griffiths) events. Our results open different pathways in studies of the mechanisms of thermalization of disordered many-body systems and beyond.
dc.affiliationpl
Wydział Fizyki, Astronomii i Informatyki Stosowanej : Zespół Zakładów Fizyki Teoretycznej
dc.affiliationpl
Wydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki im. Mariana Smoluchowskiego
dc.affiliationpl
Szkoła Doktorska Nauk Ścisłych i Przyrodniczych
dc.contributor.authorpl
Szołdra, Tomasz - 257493
dc.contributor.authorpl
Sierant, Piotr - 187960
dc.contributor.authorpl
Kottmann, Korbinian
dc.contributor.authorpl
Lewenstein, Maciej
dc.contributor.authorpl
Zakrzewski, Jakub - 100023
dc.date.accessioned
2021-11-25T21:09:20Z
dc.date.available
2021-11-25T21:09:20Z
dc.date.issuedpl
2021
dc.description.numberpl
14
dc.description.volumepl
104
dc.identifier.articleidpl
L140202
dc.identifier.doipl
10.1103/PhysRevB.104.L140202
dc.identifier.eissnpl
2469-9969
dc.identifier.issnpl
2469-9950
dc.identifier.uri
https://ruj.uj.edu.pl/xmlui/handle/item/284347
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Dodaję tylko opis bibliograficzny
dc.rights.licence
bez licencji
dc.rights.uri*
dc.subtypepl
Article
dc.titlepl
Detecting ergodic bubbles at the crossover to many-body localization using neural networks
dc.title.journalpl
Physical Review. B
dc.typepl
JournalArticle
dspace.entity.type
Publication
Affiliations

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