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DTSTART;TZID=America/Los_Angeles:20250613T120000
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DTSTAMP:20260425T084625
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SUMMARY:INPA Seminar Speaker-Bear Carlson (University of Florida)- Title: Machine-Learning-Based Data Reconstruction Chain for the Short Baseline Near Detector
DESCRIPTION:Date: June 13\,  2025 \nTime: 12:00 pm – 1:00 pm \nLocation: Sessler Conference Room – 50A-5132  [Hybrid and In-Person] \nSpeaker: Bear Carlson (University of Florida) \nTitle: Machine-Learning-Based Data Reconstruction Chain for the Short Baseline Near Detector \nAbstract: The Short-Baseline Near Detector (SBND) is a 100-ton scale Liquid Argon Time Projection Chamber (LArTPC) neutrino detector positioned in the Booster Neutrino Beam (BNB) at Fermilab\, as part of the Short-Baseline Neutrino (SBN) program. Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data. SBND data can therefore be reconstructed using an end-to-end\, ML-based data reconstruction chain for LArTPCs. The reconstruction chain is a multi-task network cascade that combines point-level feature extraction using Sparse Convolutional Neural Networks (CNN) and particle superstructure formation using Graph Neural Networks (GNN). I will first introduce the SBN program and its physics goals. I then demonstrate the expected reconstruction performance on SBND and its role in physics measurements. \n  \nJoin Zoom Meeting\nhttps://lbnl.zoom.us/j/95016696011?pwd=Tk1XOW1Xd3RYRnlsc2tEYmRWZlVVZz09 \nMeeting ID: 950 1669 6011 \nPasscode: 247722
URL:https://inpa.lbl.gov/event/inpa-seminar-speaker-tba-3/
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