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Titel:

Analyzing Nonequilibrium Quantum States through Snapshots with Artificial Neural Networks

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Bohrdt, A.; Kim, S.; Lukin, A.; Rispoli, M.; Schittko, R.; Knap, M.; Greiner, M.; Léonard, J.
Abstract:
Current quantum simulation experiments are starting to explore nonequilibrium many-body dynamics in previously inaccessible regimes in terms of system sizes and timescales. Therefore, the question emerges as to which observables are best suited to study the dynamics in such quantum many-body systems. Using machine learning techniques, we investigate the dynamics and, in particular, the thermalization behavior of an interacting quantum system that undergoes a nonequilibrium phase transition from...     »
Zeitschriftentitel:
Physical Review Letters 2021-10
Jahr:
2021
Band / Volume:
127
Heft / Issue:
15
Volltext / DOI:
doi:10.1103/physrevlett.127.150504
Verlag / Institution:
American Physical Society (APS)
E-ISSN:
0031-90071079-7114
Publikationsdatum:
07.10.2021
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