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DTSTART:20250101T000000
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DTSTART;TZID=UTC:20251204T160000
DTEND;TZID=UTC:20251204T170000
DTSTAMP:20260414T183328
CREATED:20251201T184348Z
LAST-MODIFIED:20251201T184348Z
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SUMMARY:Speaker: Brinden Carlson (University of Florida) - Title: Machine Learning Reconstruction Enhancing SBND's Neutrino Physics Program
DESCRIPTION:Research Progress Meeting \nDate: December 4\, 2025 \nTime: 4:00- 5:00 pm \nLocation: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]  \nSpeaker: Brinden Carlson (University of Florida) \nTitle: Machine Learning Reconstruction Enhancing SBND’s Neutrino Physics Program \nAbstract: The Short-Baseline Near Detector (SBND) is a 100-ton Liquid Argon Time Projection Chamber (LArTPC) neutrino detector in the Booster Neutrino Beam at Fermilab\, part of the Short-Baseline Neutrino program. I will present my work developing and deploying SPINE\, an end-to-end machine learning reconstruction algorithm for neutrino events in LArTPCs. SPINE provides high-quality particle identification and interaction clustering\, enabling precision neutrino-argon cross-section measurements and high-quality neutrino selections for oscillation analyses. I will demonstrate SPINE’s impact through a muon neutrino charged current inclusive selection\, comparing traditional reconstruction methods to the SPINE-based approach\, and discuss how this reconstruction capability supports the SBN program’s physics goals for both cross-section measurements and oscillation analyses. \nhttps://lbnl.zoom.us/j/98854322464?pwd=K2tKUm1VZjRlV1J5RHE3cXdHQzRxdz09 \nMeeting ID: 988 5432 2464\n\nPasscode: 142239
URL:https://rpm.physics.lbl.gov/event/speaker-brinden-carlson-university-of-florida-title-machine-learning-reconstruction-enhancing-sbnds-neutrino-physics-program/
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