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Q: Fachverband Quantenoptik und Photonik

Q 3: Quantum Information (Concepts and Methods) I

Q 3.3: Talk

Monday, March 9, 2020, 11:45–12:00, e001

Sampling scheme for neuromorphic simulation of entangled quantum systems — •Stefanie Czischek, Martin Gärttner, and Thomas Gasenzer — Kirchhoff-Institut für Physik, INF 227, 69120 Heidelberg, Germany

It has been shown recently that a large class of quantum many-body states can be represented efficiently by artificial neural networks. Furthermore, neural network architectures can be implemented in a controlled manner by means of analog hardware setups. This opens the prospect that neuromorphic computers can be used to efficiently emulate quantum many-body systems. We propose a phase-reweighted sampling scheme to draw spin states from the network-encoded distribution on neuromorphic hardware, such as the BrainScaleS system. Combining this scheme with a deep-neural-network ansatz representing quantum spin-1/2 states allows for measurements in various orthogonal spin bases. We apply the scheme to small systems with non-classical features to show that quantum entanglement can be simulated using the classical stochastic networks.