Berlin 2018 – scientific programme

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TT: Fachverband Tiefe Temperaturen

TT 40: Dual-Method Approaches to Quantum Many-Body Systems II

TT 40.1: Talk

Tuesday, March 13, 2018, 10:00–10:15, H 3010

A practical guide to training neural networks of quantum many body systems — •Thomas C. Lang, Jonas B. Rigo, and Andreas M. Läuchli — Institute for Theoretical Physics, University of Innsbruck, Austria

Encoding the representation of the electronic wave function of a minuscule fragment of a crystal is a nearly impossible task. learning promises to cut through the complexity and to allow for efficient encoding of a vastly complex system in a limited number of degrees of freedom by identifying the subtle, yet relevant signatures of phases of matter. We assess the efficiency and practical limits of the representational power of basic neural networks for the many body wave functions of quantum spin systems. We identify the types of wave functions, bases and network topologies, which are favorable and investigate what features the neural networks learn and how to exploit them in scaling up the network. Finally, we comment on the predictive power and entanglement properties of neural networks trained on small portions of the full phase space.