Speaker
Ali Ajmi
(HBNI)
Description
The primary physics signal events in the Iron Calorimeter at India-based Neutrino Observatory are the $\nu_\mu$ charged current (CC) interactions with a
well defined muon track. Apart from these events, the Iron Calorimeter can also detect other types of neutrino interactions, i.e. the electron neutrino charged current interactions and the neutral current events. It is possible to have a dataset containing mostly $\nu_e$CC events, by imposing appropriate selection cuts on the events. The $\nu_\mu$CC and the neutral current events form the background to
these events. This study uses Monte Carlo generated neutrino events, to design the necessary selection cuts to obtain
a $\nu_e$CC rich dataset. An optimized set of constraints are developed which balance the need for improving the purity
of the sample and having a large enough event sample. Depending on the constraints used, one can obtain a neutrino data sample with the purity of $\nu_e$ events varying between 55\% to 70\%.
additional information
For details, on may refer to our paper: JINST 10 (2015) 04, P04006.
Author
Ali Ajmi
(HBNI)
Co-author
Sankagiri Umasankar
(IIT Bombay)
