Reconstructing air showers using probabilistic forward modelling for LOFAR

Terveer K, Bouma S, Buitink S, Corstanje A, De Henau V, Desmet M, van Dongen L, Enßlin TA, Hare B, Hörandel JR, Huege T, Laub P, Mulrey K, Nelles A, Scholten O, Sharma S, Sterpka C, Strähnz S, ter Veen S, Trinh TN, Turekova P, Watanabe K (2025)


Publication Type: Conference contribution

Publication year: 2025

Journal

Publisher: Sissa Medialab Srl

Book Volume: 501

Conference Proceedings Title: Proceedings of Science

Event location: Geneva, CHE

DOI: 10.22323/1.501.0413

Abstract

The Low Frequency Array’s (LOFAR) dense core of antenna fields makes it an ideal tool for studying the radio emission of extensive air showers, sensitive to energies between 1016.5 eV and 1018 eV. Each air shower is recorded using a small particle detector array and hundreds of antennas. We present the current state of development of a new reconstruction approach using Information Field Theory (IFT) that incorporates all available information within the data, and combines both particle detector and antenna data. This method uses probabilistic forward modeling of the radio signal and offers a physics-informed, simulation-independent reconstruction. Additionally, by treating the signal as a random field, IFT simultaneously provides uncertainty quantification.

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How to cite

APA:

Terveer, K., Bouma, S., Buitink, S., Corstanje, A., De Henau, V., Desmet, M.,... Watanabe, K. (2025). Reconstructing air showers using probabilistic forward modelling for LOFAR. In Proceedings of Science. Geneva, CHE: Sissa Medialab Srl.

MLA:

Terveer, Karen, et al. "Reconstructing air showers using probabilistic forward modelling for LOFAR." Proceedings of the 39th International Cosmic Ray Conference, ICRC 2025, Geneva, CHE Sissa Medialab Srl, 2025.

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