SMuK 2023 – wissenschaftliches Programm

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

T: Fachverband Teilchenphysik

T 12: Gamma Astronomy I

T 12.1: Vortrag

Montag, 20. März 2023, 16:30–16:45, POT/0151

Generation of IACT images using generative models — •Christian Elflein, Jonas Glombitza, and Stefan Funk for the H.E.S.S. collaboration — Erlangen Centre for Astroparticle Physics, Erlangen, Germany

The development of precise, fast, and computationally efficient simulations is a central challenge of modern physics. With the advent of deep learning, new methods are emerging from the field of generative models. Recent applications to the generation of calorimeter images showed promising results, which motivates the application in astroparticle physics. In this contribution, we introduce a deep-learning-based model for the generation of camera images of Imaging Air Cherenkov Telescopes (IACTs).

In our case study, we use simulations of the High Energy Stereoscopic System (H.E.S.S.) to train a Wasserstein generative adversarial network (WGAN) for the generation of IACT images. We examine basic image properties of the generated samples, discuss their physical properties, and outline possibilities for stereoscopic image generation.