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© 2017 Emily Hudson. All rights reserved. This work is freely available courtesy of the author. It may only be used for non-commercial, educational, and research purposes. For all other uses, including reproduction and distribution, please contact the copyright holder.

Degree Name

Bachelor of Arts


Physics & Astronomy Department

First Advisor

Carol Guess


The purpose of this project was to develop pulse shape discrimination (PSD) methods that would be applied to background measurements for the Mitchell Institute Neutrino Experiment at Reactor, or MivER, collaboration. The purpose of the MivER experiment is to detect coherent elastic neutrino-nucleus scattering (CEvNS). Pulse shape discrimination is an analysis method used to distinguish between different particles by the shapes of their waveforms. I wrote my analysis code in Python while my research partner wrote her code in C++. We tried a variety of PSD methods. In one method, we curve fit the waveform to various functions and distributions (Gaussian, a piecewise function of two Gaussians, and Landau, among others) while looking at various parameters of the fits. Another method we applied was charge pulse integration, in which we integrated the area of the waveform's curve. My code was tested on simulated data from a CAEN DT5800 desktop digital detector emulator. The charge pulse integration code worked the best for distinguishing between two types of simulated waveforms. If taken further, my Python code would be further developed and tested on real data.

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