Unitary long-time evolution with quantum renormalization groups and artificial neural networks

Heiko Burau; Markus Heyl

doi:10.1103/physrevlett.127.050601

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arXiv · 2009.04473

Unitary long-time evolution with quantum renormalization groups and artificial neural networks

Heiko Burau·Markus Heyl

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Abstract

In this work we combine quantum renormalization group approaches with deep artificial neural networks for the description of the real-time evolution in strongly disordered quantum matter. We find that this allows us to accurately compute the long-time coherent dynamics of large, many-body localized systems in non-perturbative regimes including the effects of many-body resonances. Concretely, we use this approach to describe the spatiotemporal buildup of many-body localized spin glass order in random Ising chains. We observe a fundamental difference to a non-interacting Anderson insulating Ising chain, where the order only develops over a finite spatial range. We further apply the approach to strongly disordered two-dimensional Ising models highlighting that our method can be used also for the description of the real-time dynamics of nonergodic quantum matter in a general context.

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Heiko Burau, Markus Heyl. 2020-09-09. Unitary long-time evolution with quantum renormalization groups and artificial neural networks. https://doi.org/10.1103/physrevlett.127.050601

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