Developing High-Performance-Computing Applications for Liquid Argon Neutrino Detectors

PI Andrzej Szelc, The University of Manchester

Liquid argon time projection chambers (LArTPCs), including the Short Baseline Near Detector (SBND) under construction at Fermilab, are a quickly growing detector technology. They are set to answer the biggest questions in neutrino physics by measuring the interactions of these ghost-like particles with unprecedented precision. This precision results from the high resolution of LArTPCs and the large number of neutrino interactions these detectors register. However, it will also create a formidable computing challenge to simulate, reconstruct, and process the data the SBND detector will acquire. To address this challenge, this project aims to use leadership computing resources to simulate and reconstruct neutrino interactions and the cosmic ray backgrounds that contaminate the detector readout. The team will develop tools to enable fast reprocessing and quick turnaround times, which are needed to optimize the performance of the reconstruction and the precision of detector simulations. Instead of a simulation processing campaign lasting for months, it could be completed in days on the ALCF’s Theta supercomputer. This will permit many more iterations of data processing that will lead to more precise scientific analyses and broaden the range of physics topics covered.