<span class="var-sub_title">Enabling Neutrino and Antineutrino Appearance Observation Measurements with HPC Facilities</span> SC18 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Enabling Neutrino and Antineutrino Appearance Observation Measurements with HPC Facilities

Authors: Norm Buchanan (Colorado State University), Steven Calvez (Colorado State University), Pengfei Ding (Fermi National Accelerator Laboratory), Derek Doyle (Colorado State University), Alex Himmel (Fermi National Accelerator Laboratory), Burt Holzman (Fermi National Accelerator Laboratory), Jim Kowalkowski (Fermi National Accelerator Laboratory), Andrew Norman (Fermi National Accelerator Laboratory), Alex Sousa (University of Cincinnati), Marc Paterno (Fermi National Accelerator Laboratory), Saba Sehrish (Fermi National Accelerator Laboratory), Brandon White (Fermi National Accelerator Laboratory), Christopher Green (Fermi National Accelerator Laboratory)

Abstract: When fitting to data with low statistics and near physical boundaries, extra measures need to be taken to ensure proper statistical coverage. The method NOvA uses is called the Feldman-Cousins procedure, which entails fitting thousands of independent pseudoexperiments to generate acceptance intervals that are then used to correct our fits. The scale required by the Feldman-Cousins procedure makes it extremely computationally intensive. In past analyses, it has taken up to several weeks to complete, bottlenecking our final results. Here, I present recent work by members of the NOvA experiment and the SciDAC4 collaboration to enable the use of the supercomputing facilities at NERSC to process our Feldman-Cousins corrections over 50x faster, allowing us to perform more studies, increase the precision of our fits, and produce results quickly.

Best Poster Finalist (BP): no

Poster: pdf
Poster summary: PDF

Back to Poster Archive Listing