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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 111: Data analytics for dynamical systems II (joint session SOE/CPP/DY)

CPP 111.2: Talk

Friday, March 20, 2020, 09:45–10:00, GÖR 226

A differentiable programming method for quantum control — •Frank Schäfer, Michal Kloc, Christoph Bruder, and Niels Lörch — Department of Physics, University of Basel, Klingelbergstrasse 82, CH-4056 Basel, Switzerland

Precise control of quantum systems is highly desirable in many current experimental setups and quantum information technologies. In quantum control, by optimization of control pulse sequences, protocols that maximize a case-specific figure of merit are obtained. To solve quantum state control problems, we treat (closed) quantum systems as differentiable programs. Within a framework that combines machine learning and the knowledge of the differential equations governing the dynamics of the physical system, we employ predictive models for optimal parameter estimation. We analyse the sensitivity of this approach against noise in the initial states and verify the robustness of the method.

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