Improving the sensitivity of KM3NeT to MeV-GeV neutrinos from solar flares
(2023)
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- Abstract
- The detection of MeV-GeV neutrinos from astronomical sources is a long-lasting challenge forneutrino experiments. The low flux predicted for transient sources, such as solar flares, and theirlow-energy signature, requires a detector with both a large instrumented volume as well as a highdensity of photomultiplier tubes (PMTs). We discuss how KM3NeT can play a key role in thesearch for these neutrinos. KM3NeT is a Cherenkov neutrino telescope currently under deployment, located at the bottom of the Mediterranean Sea. It consists of two arrays of Digital OpticalModules (DOMs): KM3NeT/ORCA and KM3NeT/ARCA, which are optimised for the detectionof GeV neutrinos for oscillation studies, and higher-energy astronomical neutrinos respectively.We exploit the multi-PMT configuration of KM3NeT’s DOMs to develop the techniques that allowthe disentangling of the MeV-GeV neutrino signature from the atmospheric and environmentalbackground. Comparing data with neutrino simulations we identify the variables with discriminating power, and by applying hard cuts we are able to reject a large fraction of background. Wepresent a graph neural network approach to classify signal from background. To further improvethe sensitivities compared to previous studies, we will make use of the Hierarchical Graph Poolingwith Structure Learning algorithm and will use graph-structured data to reproduce the hit geometry on the DOM. This will allow for stronger constraints on the hits and reduce the fraction ofbackground that survives the selection.
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Mauro, J., de Wasseige, G., & KM3NeT. (2023). Improving the sensitivity of KM3NeT to MeV-GeV neutrinos from solar flares. Proceedings of Science, ICRC2023. https://doi.org/10.22323/1.444.1294 (Original work published 2023)