User: Guest  Login
Title:

Analyzing Nonequilibrium Quantum States through Snapshots with Artificial Neural Networks

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Journal title:
Physical Review Letters 2021-10
Year:
2021
Journal volume:
127
Journal issue:
15
Fulltext / DOI:
doi:10.1103/physrevlett.127.150504
Publisher:
American Physical Society (APS)
E-ISSN:
0031-90071079-7114
Date of publication:
07.10.2021
 BibTeX