Hannes Warnhofer | Searcharxiv

arXiv2026

What is new in NuRadioMC: Multilayer Analytic Raytracer

NuRadioMC is a framework for the simulation of ultra-high-energy neutrino detectors that measure the radio signal emitted in neutrino-induced particle cascades used in different radio neutrino experiments. We present an extension to the analytic raytracing method for multilayered exponential refractive index models, where the full refractive index profile is described by a set of different single-exponential layers, supporting realistic medium descriptions at various experiment sites while maintaining computational efficiency. This approach also enables a realistic exponential refractive index description of the atmosphere and allows us to model signal propagation over non-smooth changes in the refractive index. This report outlines the fundamentals of the multilayered analytic raytracing method and shows some applied examples.

astro-ph.IM↗

arXiv2024

Multi-View Deep Learning for Imaging Atmospheric Cherenkov Telescopes

This research note concerns the application of deep-learning-based multi-view-imaging techniques to data from the H.E.S.S. Imaging Atmospheric Cherenkov Telescope array. We find that the earlier the fusion of layer information from different views takes place in the neural network, the better our model performs with this data. Our analysis shows that the point in the network where the information from the different views is combined is far more important for the model performance than the method used to combine the information.

astro-ph.IM↗