Simulating non-equilibrium quantum matter with neural quantum states
ORAL · Invited
Abstract
The numerical simulation of many-body quantum dynamics constitutes a pivotal challenge of computational physics due to the typical growth of entanglement in the course of the evolution. I will discuss how combining the time-dependent variational principle with artificial neural networks as ansatz for the variational wave function allows us to overcome some of the current limitations. As an application I will address quantum phase transition dynamics in two spatial dimensions of a model that is experimentally realized in Rydberg quantum simulators.
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Publication: M. Schmitt and M. Heyl, "Quantum many-body dynamics in two dimensions with artificial neural networks", Phys. Rev. Lett. 125, 100503 (2020)<br>M. Reh, M. Schmitt, M. Gärttner, "Time-dependent variational principle for open quantum systems with artificial neural networks", Phys. Rev. Lett. 127, 230501 (2021)<br>M. Schmitt, M. M. Rams, J. Dziarmaga, M. Heyl, W. H. Zurek, "Quantum phase transition dynamics in the two-dimensional transverse-field Ising model", Sci. Adv. 8, abl6850 (2022)
Presenters
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Markus Schmitt
FZ Jülich
Authors
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Markus Schmitt
FZ Jülich