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DOE OSTI · 2429217

Real-Time Anomaly Detection for Charge-Based Triggering in LArTPCs

Chung, Seokju
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Abstract

Modern particle detectors, including liquid argon time projection chambers (LArTPCs), collect a vast amount of data, making it impractical to save everything for offline analysis. As a result, these experiments need to employ different down-selection techniques during data acquisition, referred to as triggering. In this talk, I will present a framework that would enable real-time, data-driven triggering for LArTPCs, using anomaly detection algorithms implemented on Field-Programmable Gate Arrays (FPGAs). Drawing on a study that makes use of collected charge data from the MicroBooNE LArTPC Public Dataset, I will discuss the overall performance of such algorithms and potential applications for future neutrino experiments.

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43 PARTICLE ACCELERATORS72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

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BibTeXRIS

Chung, Seokju. 2024-08-09. Real-Time Anomaly Detection for Charge-Based Triggering in LArTPCs. https://doi.org/10.2172/2429217

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