5 papers · 1 filter
Machine Learning is Good for Physics - and Vice Versa
Michael Krämer, Tilman Plehn
Scientific AI is rapidly transforming fundamental physics research and challenging defining aspects of the fundamental physics methodology. We discuss opportunities and dangers of…
Toward a Comprehensive Exploration of Flavored Dark Matter Models
Benedetta Belfatto, Monika Blanke, Jan Heisig +3
We present a comprehensive framework for the study of flavored dark matter models, combining relic density calculations with direct and indirect detection limits, collider constrai…
Semi-visible jets, energy-based models, and self-supervision
Luigi Favaro, Michael Krämer, Tanmoy Modak +2
We present DarkCLR, a novel framework for detecting semi-visible jets at the LHC. DarkCLR uses a self-supervised contrastive-learning approach to create observables that are approx…
arkRayNet: Emulation of cosmic-ray antideuteron fluxes from dark matter
Jan Heisig, Michael Korsmeier, Michael Krämer +2
Cosmic-ray antimatter, particularly low-energy antideuterons, serves as a sensitive probe of dark matter annihilating in our Galaxy. We study this smoking-gun signature and explore…
Flavoured Majorana Dark Matter then and now: From freeze-out scenarios to LHC signatures
Harun AcaroÄlu, Monika Blanke, Jan Heisig +2
We study a simplified Dark Matter model in the Dark Minimal Flavour Violation framework. Our model complements the Standard Model with a flavoured Dark Matter Majorana triplet and…