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Dynamical Phase Transitions in a 2D Classical Nonequilibrium Model via 2D Tensor Networks

Helms, Phillip and Chan, Garnet Kin-Lic (2020) Dynamical Phase Transitions in a 2D Classical Nonequilibrium Model via 2D Tensor Networks. Physical Review Letters, 125 (14). Art. No. 140601. ISSN 0031-9007. https://resolver.caltech.edu/CaltechAUTHORS:20200504-123744760

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Abstract

We demonstrate the power of 2D tensor networks for obtaining large deviation functions of dynamical observables in a classical nonequilibrium setting. Using these methods, we analyze the previously unstudied dynamical phase behavior of the fully 2D asymmetric simple exclusion process with biases in both the x and y directions. We identify a dynamical phase transition, from a jammed to a flowing phase, and characterize the phases and the transition, with an estimate of the critical point and exponents.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1103/PhysRevLett.125.140601DOIArticle
https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.125.140601PublisherArticle
https://arxiv.org/abs/2003.03050arXivDiscussion Paper
ORCID:
AuthorORCID
Helms, Phillip0000-0002-6064-3193
Chan, Garnet Kin-Lic0000-0001-8009-6038
Additional Information:© 2020 American Physical Society. Received 18 March 2020; accepted 9 September 2020; published 29 September 2020. This work was supported primarily by the U.S. National Science Foundation via Grant No. 1665333. P. H. was also supported by a NSF Graduate Research Fellowship under Grant No. DGE-1745301 and an ARCS Foundation Award.
Funders:
Funding AgencyGrant Number
NSFCHE-1665333
NSF Graduate Research FellowshipDGE-1745301
ARCS FoundationUNSPECIFIED
Issue or Number:14
Record Number:CaltechAUTHORS:20200504-123744760
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200504-123744760
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:102976
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:04 May 2020 20:10
Last Modified:29 Sep 2020 17:26

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