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

TL;DR

This paper presents the implementation of the Library Event Matching algorithm for classifying electron neutrino interactions in NOvA detectors, leveraging detailed event comparisons to improve discrimination accuracy.

Contribution

The paper introduces a detailed implementation of the Library Event Matching algorithm tailored for NOvA, enhancing event classification by utilizing comprehensive event information.

Findings

Effective discrimination of electron neutrino events in NOvA

Utilization of all available event information improves classification accuracy

Algorithm is adaptable to monolithic, segmented detectors

Abstract

We describe the Library Event Matching classification algorithm implemented for use in the NOvA $\nu_\mu \rightarrow \nu_e$ 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 NOvA and thus provides a powerful technique for event discrimination.