Additive Manufacturing of Active and Passive Optical Components
Prof. Dr. Andreas Heinrich (Aalen University)
High Impedance Quantum Circuits
Dr. Ioan Pop
Audible Axions
Prof. Pedro Schwaller
Mon, 25 Nov 2019, 16:30
Low-scale inflation and QCD axion
Wen Yin
Tue, 26 Nov 2019, 14:00
Active galactic nuclei as cosmological probes
Elisabeta Lusso
Tue, 26 Nov 2019, 15:15

Non-equilibrium dynamics in two-dimensional quantum matter from (deep) neural networks

Dr. Markus Schmitt , University of California, Berkeley, USA

Despite a growing number of realizations in experiment the efficient numerical simulation of real time evolution of isolated quantum many-body systems far from equilibrium remains challenging. Especially, systems of intermediate spatial dimensions are still largely elusive to the established approaches. In this work we demonstrate that combining a time-dependent variational principle with deep neural networks as ansatz for the wave function yields a versatile and reliable method in the sense that it is not tailored to the specific problem and the error can be quantified and systematically reduced. A deep network architecture is particularly well suited to exploit the locality of physical dynamics for the representation of the time-evolved wave function. As a concrete example, we simulate the dynamics of the paradigmatic and experimentally relevant two-dimensional transverse field Ising model. The maximal times reached are comparable to or exceed the capabilities of state-of-the-art tensor network methods.

CQD Colloquia
7 Nov 2019, 14:30
Kirchhoff-Institut für Physik, INF 227, Seminar box 2.107

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