Heidelberg 2022 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 86: Neutrino Physics (Theory) 1 and Theoretical Astroparticle Physics and Cosmology 1

T 86.6: Vortrag

Donnerstag, 24. März 2022, 17:30–17:45, T-H17

Constraining dark matter annihilation with cosmic ray antiprotons using neural networksFelix Kahlhoefer1, Michael Korsmeier2, Michael Krämer1, Silvia Manconi1, and •Kathrin Nippel11Institute for Theoretical Particle Physics and Cosmology (TTK), RWTH Aachen University, D-52056 Aachen, Germany — 2The Oskar Klein Centre for Cosmoparticle Physics, Department of Physics, Stockholm University, Alba Nova, 10691 Stockholm, Sweden

The interpretation of data from indirect detection experiments searching for dark matter annihilations requires computationally expensive simulations of cosmic-ray propagation. We present new methods based on Recurrent and Bayesian Neural Networks that significantly accelerate simulations of secondary and dark matter Galactic cosmic ray antiprotons by at least two orders of magnitude compared to conventional approaches while achieving excellent accuracy. This approach allows for an efficient profiling or marginalisation over the nuisance parameters of a cosmic ray propagation model in order to perform parameter scans for a wide range of dark matter models. We present resulting constraints using the most recent AMS-02 antiproton data on several models of Weakly Interacting Massive Particles.

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