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DTSTART;TZID=America/Chicago:20261116T160000
DTEND;TZID=America/Chicago:20261116T170000
DTSTAMP:20261114T024706Z
SUMMARY:HEP Seminar: Justin Mueller: "Searching for Muon-Neutrino Disappearance at ICARUS: Leveraging Machine Learning for Event Reconstruction"
UID:648170@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The ICARUS collaboration\, as part of the Short-Baseline Neutrino (SBN) Program at Fermilab\, has completed its first oscillation analysis with the Booster Neutrino Beam (BNB): a single-detector search for muon-neutrino disappearance in the context of a 3+1 sterile neutrino model\, using data collected in 2022–2023. Two independent reconstruction frameworks were used to select charged-current events with a single muon\, at least one proton\, and no pions in the final state\, and no statistically significant disappearance is observed at the 600 m ICARUS baseline. One of these frameworks is SPINE\, an end-to-end machine-learning-based reconstruction that goes from raw liquid argon time projection chamber (LArTPC) images to complete particle-level descriptions of each neutrino interaction\, enabling a high-efficiency\, high-purity selection. In this talk\, I will describe how SPINE works and how it was integrated into the analysis\, including its performance relative to traditional approaches. Upcoming joint SBND–ICARUS analyses will build on this result\, constraining flux and interaction model uncertainties with a near detector and further leveraging ML-based reconstruction. I will close by discussing how these reconstruction advances are positioned to extend the physics reach of LArTPC experiments\, including SBN and DUNE.  Justin Mueller\, Research Associate\, Fermilab  Host: Susan Dittmer
LOCATION:Technological Institute\, F160\, 2145 Sheridan Road\, Evanston\, IL 60208
TRANSP:OPAQUE
URL:https://planitpurple.northwestern.edu/event/648170
CREATED:20241011T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20261105T193351Z
PRIORITY:0
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