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Reconstruction for Liquid Argon TPC Neutrino Detectors Using Parallel Architectures by Berkman, Sophie; Cerati, Giuseppe; Gravelle, Brian; Norris, Boyana; Hall, Allison Reinsvold; Wang, Michael is a scholarly article available to read on EtoBox.

What is Reconstruction for Liquid Argon TPC Neutrino Detectors Using Parallel Architectures about?

Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is becoming more difficult as the detectors increase in size to reach their physics goals. In liquid argon time projection chambers (TPCs) the charged particles from neutrino interactions produce ionization electrons which drift in an electric field towards a series of collection wires, and the signal on the wires is used to reconstruct the interaction. The MicroBooNE detector currently collecting data at Fermilab has 8000 wires, and planned future experiments like DUNE will have 100 times more, which means that the time required to reconstruct an event will scale accordingly. Modernization of liquid argon TPC reconstruction code, including vectorization, parallelization and code portability to GPUs, will help to mitigate these challenges. The liquid argon TPC hit finding algorithm within the \texttt{LArSoft}\xspace framework used across multiple experiments has been vectorized and parallelized. This increases the speed of the algorithm on the order of ten times within a standalone version on Intel architectur

Author

Berkman, Sophie; Cerati, Giuseppe; Gravelle, Brian; Norris, Boyana; Hall, Allison Reinsvold; Wang, Michael

Published

2020

Language

EN