Astrophysical neutrino production and impact of associated uncertainties in photo-hadronic interactions of UHECRs
Daniel Biehl, Denise Boncioli, Anatoli Fedynitch, Leonel Morejon,, Walter Winter

TL;DR
This paper investigates how uncertainties in photo-hadronic interaction models affect the prediction of astrophysical neutrino fluxes from UHECRs, emphasizing the need for improved nuclear cross-section measurements.
Contribution
It highlights the impact of current model uncertainties on neutrino production predictions and discusses extensions to existing photo-meson interaction models.
Findings
Uncertainties in cross-section data significantly affect neutrino flux estimates.
Nuclear cascade development depends on the level of interactions in UHECR sources.
Understanding UHECR interactions with the Glashow resonance is crucial for accurate modeling.
Abstract
High energy neutrinos can be produced by interactions of ultra-high energy cosmic rays (UHECRs) in the dense radiation fields of their sources as well as off the cosmic backgrounds when they propagate through the universe. Multi-messenger interpretations of current measurements deeply rely on the understanding of these interactions. In order to efficiently produce neutrinos in the sources of UHECRs, at least a moderate level of interactions is needed, which means that a nuclear cascade develops if nuclei are involved. On the other hand, the available cross-section data and interaction models turn out to make poor predictions for most nuclei heavier than protons. We show the impact of these uncertainties in state-of-the-art photo-disintegration models and motivate nuclear cross-section measurements. Further, we discuss extensions for photo-meson models currently used in astrophysics and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
