Erlangen 2026 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 106: Gamma Astronomy III
T 106.2: Vortrag
Freitag, 20. März 2026, 09:15–09:30, KS 00.005
Exploring goodness of fit methods to improve gamma-hadron separation for the CTA Observatory — •Jayendra Pundarikaksha Kavipurapu1,2, Georg Schwefer1,2, and James Anthony Hinton1 — 1Max-Planck-Institut für Kernphysik, Saupfercheckweg 1, 69117, Heidelberg, Germany — 2Fakultät für Physik und Astronomie, Universität Heidelberg, Im Neuenheimer Feld 226, 69120, Heidelberg, Germany
Background rejection of hadrons is one of the limiting factors for the performance of IACTs. Unfortunately, hadron showers look similar in telescope cameras, even if they produce broader images. A promising approach to differentiate between them is to implement goodness-of-fit measures based on the per-pixel charge probability distribution. In this talk, we explore these goodness-of-fit metrics exploiting the differences between the reconstructed and predicted charges. We do this using methods from likelihood-free inference and simulations of the Cherenkov Telescope Array Observatory, allowing us to create classification criteria to differentiate shower observations
Keywords: Cherenkov Telescope Array Observatory; gamma-hadron seperation; likelihood-free inference; analytic methods; machine learning