📝 SummarXiv

Abstract

Fundamental particle physics is a key part of an undergraduate physics curriculum, but can be challenging to incorporate into teaching laboratories. We present an undergraduate laboratory experiment that enables students to work with real data from the MicroBooNE liquid-argon time projection chamber to search for the existence of a sterile neutrino: a new, fourth, neutrino state. This search has galvanized physicists for decades, as the existence of sterile neutrinos could play a critical role in understanding fundamental processes in the early universe, provide viable dark matter candidates, and offer a natural explanation for the origin of neutrino masses. From an experimental point of view, anomalies observed in several neutrino experiments provide tantalizing hints of their existence. The analysis presented here, whilst based on real data, has been adapted as a pedagogical tool for an undergraduate teaching laboratory, in which students are asked to develop an understanding of neutrino oscillation theory, analyse a MicroBooNE data sample, and apply statistical methods to search for a potential sterile neutrino. The analysis incorporates machine learning techniques to improve event classification. Students are encouraged to explore these and other methods to optimize their results.