Bayesian Inference Constraints on Astrophysical Production of Ultra-high Energy Cosmic Rays and Cosmogenic Neutrino Flux Predictions

Abstract

A flux of extra-terrestrial neutrinos at energies $\gg10^{15}$ eV has the potential to serve as a cosmological probe of the high-energy universe as well as tests of fundamental particle interactions. Cosmogenic neutrinos, produced from the interactions of ultra-high energy cosmic rays (UHECRs) with cosmic photon backgrounds, have been regarded as a guaranteed flux. However, the expected neutrino flux depends on the composition of UHECRs at the highest energies; heavier nuclei result in lower neutrino fluxes compared to lighter nuclei and protons. The objective of this study is to estimate the range of cosmogenic neutrino spectra consistent with recent cosmic-ray spectral and compositional data using a fully inferential Bayesian approach. The study assumes a range of source distributions consistent with astrophysical sources, the flux and composition of cosmic rays, and detector systematic uncertainties. The technique applied to this study is the use of an affine-invariant Markov Chain Monte Carlo, which is an effective Bayesian inference tool for characterizing multi-dimensional parameter spaces and their correlations.