SMuK 2023 – scientific programme

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EP: Fachverband Extraterrestrische Physik

EP 9: Poster

EP 9.3: Poster

Wednesday, March 22, 2023, 17:30–19:00, HSZ OG1

BlaST: A machine-learning estimator for the synchrotron peak of blazars — Theo Glauch and •Tobias Kerscher — Technische Universität München, Physik-Department, James-Frank-Str. 1, Garching bei München, D-85748, Germany

Blazars, jetted Active Galaxy Nuclei (AGN) pointing towards us, occupy an important place in the field of high-energy astrophysics. Their classification depends heavily on the peak frequency of the synchrotron emission in the spectral energy disitribution (SED), yet this value is usually determined manually. In this contribution, we present a tool using machine learning to not only streamline this process, but also give a reliable uncertainty evaluation. By the very nature of this method, additional components of the SED stemming from the host galaxy or disk emission, possible sources of confusion, are accounted for.