Speaker
Description
The Super-Kamiokande experiment (SK) is the water Cherenkov detector which discovered the oscillation of atmospheric neutrinos. The dominant effect of the oscillation of muon neutrinos is the appearance of tau neutrinos. Direct detection of $\nu_\tau$ in the atmospheric neutrino flux provides an unambiguous confirmation of neutrino oscillations. $\nu_\mu$ changing to $\nu_e$ is the sub-dominant $\nu_\mu$ oscillation mode, which is studied at SK to determine mass hierarchy. Currently, $\nu_\tau$ interactions form the biggest background to the mass hierarchy signal in the SK analysis. SK uses machine learning techniques of neural networks to segregate $\nu_\tau$ charged-current interactions from the interactions of the atmospheric muon and electron neutrinos. This poster will discuss improvements in the $\nu_\tau$ identification algorithm and discuss corresponding improvements in the search for tau neutrinos and the suppression of mass heirarchy backgrounds.
| In-person participation | Yes |
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