Speaker
Nicola Fulvio Calabria
(Dipartimento Interateneo di Fisica "M. Merlin", Politecnico di Bari)
Description
In this preliminary study we consider and explore the application of Machine Learning algorithms for reconstruction in Super-Kamiokande. To do so simulated event samples have been used. The aim is the development of a tool to be employed in proton decay analysis along with the official reconstruction software (fiTQun). The final goal will be to improve Cherenkov ring detection and reconstruction in multi-ring events.
| Type of contribution | Talk: 15 minutes. |
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Primary author
Nicola Fulvio Calabria
(Dipartimento Interateneo di Fisica "M. Merlin", Politecnico di Bari)
