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Samantha Pagan

Publications and source records attributed to Samantha Pagan.

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Performance of a SiPM-based, plastic scintillator muon veto prototype for CUPID

CUPID will be a next-generation experiment searching for neutrinoless double beta decay in the inverted mass ordering regime. The reduction of backgrounds in the region of interest is critical to the performance of the experiment. Despite its underground location, muon-induced events will be a non-negligible source of background for CUPID, and their mitigation will be critical in reaching CUPID's target sensitivity. This mitigation will be achieved with a muon veto system, which must fit within the physical constraints of the existing infrastructure while maximizing geometrical coverage. We present the design, construction, and characterization of prototypes for a modular system of plastic scintillator panels with embedded plastic wavelength-shifting fibers connected to silicon photomultipliers for the CUPID muon veto. The 100$\, \times \,$50$\, \times \, $2.5\,cm$^3$ panel prototype presented here exhibited a light yield of ($55.9 \,\pm \,1.5$)\,p.e./MeV with a position reconstruction resolution of 25$\,\times \,$25\,cm$^2$. This design also achieves a muon detection efficiency of $(98\,\pm \,1)\%$. We compare the light yield, uniformity, and position reconstruction potential of different prototype designs.

physics.ins-det

Astronomy as a Field: A Guide for Aspiring Astrophysicists

This book was created as part of the SIRIUS B VERGE program to orient students to astrophysics as a broad field. The 2023-2024 VERGE program and the printing of this book is funded by the Women and Girls in Astronomy Program via the International Astronomical Union's North American Regional Office of Astronomy for Development and the Heising-Simons Foundation; as a result, this document is written by women in astronomy for girls who are looking to pursue the field. However, given its universal nature, the material covered in this guide is useful for anyone interested in pursuing astrophysics professionally.

astro-ph.IM

Using Machine Learning to Select High-Quality Measurements

We describe the use of machine learning algorithms to select high-quality measurements for the Mu2e experiment. This technique is important for experiments with backgrounds that arise due to measurement errors. The algorithms use multiple pieces of ancillary information that are sensitive to measurement quality to separate high-quality and low-quality measurements.

physics.data-an