4 papers
New Deep Learning Data Analysis Method for PROSPECT using GAPE: Genetic Algorithm Powered Evolution
M. Adriamirado, A. B. Balantekin, C. Bass +40
We propose a genetic algorithm powered evolution (GAPE) method to create deep learning solutions for energy and position estimation for reactor antineutrino interactions in the Pre…
Sensitivity of nEXO to Xe Charged-Current Interactions: Background-free Searches for Solar Neutrinos and Fermionic Dark Matter
G. Richardson, B. G. Lenardo, D. Gallacher +135
We study the sensitivity of nEXO to solar neutrino charged-current interactions, XeCs, as well as analogous interactions predicted by mo…
A prototype reactor-antineutrino detector based on Li-doped pulse-shaping-discriminating plastic scintillator
O. Benevides Rodrigues, E. P. Bernard, N. S. Bowden +26
An aboveground 60-kg reactor-antineutrino detector prototype, comprised of a 2-dimensional array of 36 Li-doped pulse shape sensitive plastic scintillator bars, is described.…
Machine Learning for Single-Ended Event Reconstruction in PROSPECT Experiment
M. Andriamirado, A. B. Balantekin, C. D. Bass +43
The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, was a segmented antineutrino detector that successfully operated at the High Flux Isotope Reactor in Oak Ridge,…