Papers › DAEMONFLUX: DAta-drivEn MuOn-calibrated atmospheric Neutrino Flux
DAEMONFLUX: DAta-drivEn MuOn-calibrated atmospheric Neutrino Flux
Juan Pablo Yañez, Anatoli Fedynitch
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
In this paper, we present a refined calculation of the atmospheric neutrino flux spanning from GeV to PeV energies. Our method, Daemonflux, utilizes data-driven inputs and incorporates adjustable parameters to take their uncertainties into account. By optimizing these parameters using a combination of muon data and constraints from fixed-target experiments, we achieve uncertainties in the calculated neutrino fluxes of less than 10% up to 1 TeV, with neutrino ratios constrained to below 10%. Our model performs particularly well at energies below 100 GeV, where the smallest errors are obtained. We make our model available as a software package that provides access to predictions of fluxes, ratios, and errors, including the covariance matrix obtained from the fit.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections