Speaker
Description
A Python-based public code "CARNE" is being developed for spectral analysis on dataset from water Cherenkov and liquid scintillation detectors, targeting the diffuse supernova neutrino background (DSNB) search. The analysis relies on an extended unbinned maximum likelihood method and takes into account multiple background sources at each type detector. Inverse beta decay of electron antineutrinos on free protons is considered as a signal channel at both detectors, while the code is generally written for other interactions to be flexibly considered in the future. This presentation introduces CARNE with focusing on its scientific importance and usability, as well as shows detection sensitivities at future detectors estimated on the previously proposed DSNB models as a demonstration.