Speaker
Oliver Janik
(FAU Erlangen-Nürnberg (DE))
Description
Measurements of the astrophysical neutrino flux with the IceCube Neutrino Observatory traditionally rely on binned forward-folding likelihood analyses. These methods require Monte Carlo simulations to predict event distributions. Limited Monte Carlo statistics restrict the dimensionality of the binning and therefore the amount of exploitable information.
This talk presents a fully differentiable analysis framework that enables end-to-end optimization of summary statistics, combining arbitrarily many input variables to improve the sensitivity of the analysis. As a demonstration, the method is applied to the measurement of the neutrino flux from the Galactic Plane.