Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multi-dimensional supernova simulations

Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz

Published 2023-10-23Version 1

The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the core-collapse supernova (CCSN) rate, neutrino emission spectra, and the fraction of failed supernovae are not precisely known. We quantify the uncertainty on each of these ingredients by (i) compiling a large database of recent star formation rate density measurements, (ii) combining neutrino emission from long-term axisymmetric CCSNe simulations and strategies for estimating the emission from the protoneutron star cooling phase, and (iii) assuming different models of failed supernovae. Finally, we calculate the fluxes and event rates at multiple experiments and perform a simplified statistical estimate of the time required to significantly detect the DSNB at SK with the gadolinium upgrade and JUNO. Our fiducial model predicts a flux of $5.1\pm0.4^{+0.0+0.5}_{-2.0-2.7}\,{\rm cm^2~s^{-1}}$ at SK employing Gd-tagging, or $3.6\pm0.3^{+0.0+0.8}_{-1.6-1.9}$ events per year, where the errors represent our uncertainty from star formation rate density measurements, uncertainty in neutrino emission, and uncertainty in the failed-supernova scenario. In this fiducial calculation, we could see a $3\sigma$ detection by $\sim2030$ with SK-Gd and a $5\sigma$ detection by $\sim2035$ with a joint SK-Gd/JUNO analysis, but background reduction remains crucial.