Heidelberg 2022 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 105: Search for Dark Matter 6

T 105.10: Vortrag

Donnerstag, 24. März 2022, 18:30–18:45, T-H37

A novel approach to simulate axion-induced electrodynamics utilizing deep learning techniques in the MADMAX experiment — Dominik Bergermann, Tim Graulich, •Alexander Jung, Andrzej Novak, Ali Riahinia, and Alexander Schmidt — III. Physikalisches Institut A RWTH Aachen, Aachen, Deutschland

Promising concepts for the search for axion dark matter are dielectric haloscopes, such as the MAgnetized Disk and Mirror Axion eXperiment (MADMAX). The realisation of the experiment strongly depends on an accurate and reliable simulation leading to ever-increasing demands on computing resources, due to the complexity of simulations. A proof of principle is presented that modern deep learning techniques can be used in the simulation of the axion haloscope, and thereby assist in its optimisation.