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T: Fachverband Teilchenphysik

T 61: Gamma Astronomy I

T 61.5: Vortrag

Mittwoch, 18. März 2026, 17:15–17:30, KS 00.005

Get More for Less - Adaptive Sampling in Event Simulations For the Cherenkov Telescope Array Observatory — •Tristan Gradetzke and Luca Di Bella — TU Dortmund University, Dortmund, Germany

Monte Carlo (MC) simulations of particle induced extensive air showers are crucial to the analysis of observational data taken by Imaging Air Cherenkov Telescopes (IACTs). They serve the purpose of training and test data for the algorithmic reconstruction of particle type, energy, and direction of the originating particle. The performance of this reconstruction on the Monte Carlo data is mathematically described by the Instrument Response Functions (IRFs). Their usage however, comes at the extensive cost of computational resources. Consequently, considerable effort has been invested in improving the efficiency of these MC simulations. The objective of this work is to investigate the potential of adaptive sampling-based methods, that focus on specific phase-space regions to enhance event statistics and, to a certain extent, possibly reduce uncertainties in the IRFs. Thus reducing the extent of Monte Carlo productions. Phase space in this context refers to, among others, detector field of view and primary particle energy . The main challenges arise from the definition of a metric, that is optimized by any given algorithm. Here, a simple event-per-bin based metric is adopted. Possible improvements in efficiencies and an overview of potential avenues for future research are presented.

Keywords: Monte Carlo Shower Simulations; Adaptive Sampling; Cherenkov Telescope Array Observatory; Software and Analysis