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arXiv · 2003.03050

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

Phillip Helms·Garnet Kin-Lic Chan
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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.

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Phillip Helms, Garnet Kin-Lic Chan. 2020-03-06. Dynamical Phase Transitions in a 2D Classical Nonequilibrium Model via 2D Tensor Networks. https://doi.org/10.1103/physrevlett.125.140601

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