High Energy Physics is entering an exciting period with new insights into many of the fundamental mysteries of the universe, especially with developments in "big data" analyses. Continuous exploration of new, cutting-edge technologies and techniques is required to unravel these mysteries for scientific discovery. One of these mysteries lies also in neutrino physics and known as the short-baseline anomalies. The Short Baseline Neutrino (SBN) program aims to elucidate the nature of this anomaly with three detectors, SBND, MicroBooNE, and ICARUS. Analysis of neutrino data collected from these detectors involves a combination of complex fitting procedures and statistical correction techniques used to produce the sensitivity contours in a multi-dimensional parameter space. This prescription is known as the Feldman-Cousins unified approach which is very computationally expensive. This talk will focus on the development and deployment of new tools and algorithms that melds high-performance computing (HPC) and techniques for big data analysis to enable this computationally expensive physics studies to be completed on time scales that are not currently feasible.
|Fermilab report number||FERMILAB-SLIDES-20-057-ND-SCD|