Library Event Matching event classification algorithm for electron neutrino interactions in the NOνA detectors

Abstract

We describe the Library Event Matching classification algorithm implemented for use in the NOνA ν_μ→ν_e oscillation measurement. Library Event Matching, developed in a different form by the earlier MINOS experiment, is a powerful approach in which input trial events are compared to a large library of simulated events to find those that best match the input event. A key feature of the algorithm is that the comparisons are based on all the information available in the event, as opposed to higher-level derived quantities. The final event classifier is formed by examining the details of the best-matched library events. We discuss the concept, definition, optimization, and broader applications of the algorithm as implemented here. Library Event Matching is well-suited to the monolithic, segmented detectors of NOνA and thus provides a powerful technique for event discrimination.

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