Hannover 2020 – scientific programme
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Q: Fachverband Quantenoptik und Photonik
Q 8: Quantum Information (Concepts and Methods) II
Q 8.8: Talk
Monday, March 9, 2020, 15:45–16:00, e001
Representing quantum states on neuromorphic hardware — •Julius Vernie1, Marcel Neugebauer1, Laurin Fischer1, Andreas Baumbach2, Martin Gärttner2, Selim Jochim1, and Matthias Weidemüller1 — 1Physikalisches Institut, Universität Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg — 2Kirchhoff-Institut für Physik, Universität Heidelberg, Im Neuenheimer Feld 227, 69120 Heidelberg
Artificial Neural Networks have already successfully been used to reproduce the results of quantum mechanical experiments. Spiking Neural Networks are now offering a promising new approach in this field. Especially, they can be implemented physically in the form of neuromorphic hardware, which leads to a great increase of computation speed compared to emulations on classical hardware. In our current work, we are training a neuromorphic computer to reproduce the results of quantum mechanical experiments and looking for new ways to encode quantum information, leading to more efficient predictions for complex quantum systems.