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X-WR-CALDESC:Events for LBNL Physics Division Research Progress Meetings
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DTSTART:20260101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260108T160000
DTEND;TZID=UTC:20260108T170000
DTSTAMP:20260414T112419
CREATED:20260102T183558Z
LAST-MODIFIED:20260106T214613Z
UID:3041-1767888000-1767891600@rpm.physics.lbl.gov
SUMMARY:Speaker: Livio Calivers (University of Bern) - Title: Light Detection for Modular Liquid Argon Neutrino Detectors: From Concept to Beam Data in the DUNE Near Detector
DESCRIPTION:Research Progress Meeting \nDate: January 8\, 2026 \nTime: 4:00- 5:00 pm \nLocation: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]  \nSpeaker: Livio Calivers\, University of Bern \nTitle: Light Detection for Modular Liquid Argon Neutrino Detectors: From Concept to Beam Data in the DUNE Near Detector \nAbstract: The Deep Underground Neutrino Experiment (DUNE) aims to perform precision measurements of neutrino oscillations\, which require stringent control of systematic uncertainties at the Near Detector. A major challenge arises from the severe interaction pile-up in liquid-argon time projection chambers operating near the origin of the intense neutrino beam. This talk describes how fast scintillation-light detection is exploited to enhance event reconstruction and interaction timing in the modular Liquid Argon Near Detector (ND-LAr). The design of the ArCLight system is presented—a fully dielectric\, SiPM-based light detector integrated directly into the TPC drift field\, providing efficient photon collection with minimal inactive material. Results from the DUNE 2×2 Demonstrator operated in the NuMI beam at Fermilab include the observation of neutrino interactions and a demonstrated sub-4 ns timing resolution\, sufficient to resolve the accelerator bunch structure and enable in-spill interaction separation. \nhttps://lbnl.zoom.us/j/98854322464?pwd=K2tKUm1VZjRlV1J5RHE3cXdHQzRxdz09 \nMeeting ID: 988 5432 2464\n\nPasscode: 142239
URL:https://rpm.physics.lbl.gov/event/speaker-livio-calivers-university-of-bern-title-light-detection-for-modular-liquid-argon-neutrino-detectors-from-concept-to-beam-data-in-the-dune-near-detector/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260113T160000
DTEND;TZID=UTC:20260113T170000
DTSTAMP:20260414T112419
CREATED:20260105T173222Z
LAST-MODIFIED:20260105T173222Z
UID:3045-1768320000-1768323600@rpm.physics.lbl.gov
SUMMARY:Speaker: Matthias Vigl (Technical University of Munich) - Title: Machine-Learning Scaling Laws for LHC Physics: How Scale Unlocks Breakthrough Gains in Physics Sensitivity
DESCRIPTION:Research Progress Meeting \nDate: January 13\, 2026 \nTime: 4:00- 5:00 pm \nLocation: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]  \nSpeaker: Matthias Vigl (Technical University of Munich) \nTitle: Machine-Learning Scaling Laws for LHC Physics: How Scale Unlocks Breakthrough Gains in Physics Sensitivity \nAbstract: High Energy Physics and deep learning have historically taken different routes to data processing: in collider physics\, performance has been driven by deep\, hand-engineered pipelines that encode decades of domain knowledge\, while modern machine learning has advanced primarily through scale\, leveraging large datasets and increasingly generic model architectures. While machine learning has long been embedded in the HEP analysis pipeline\, the rate of improvement has remained slower than the rapid\, scale-driven progress observed in industry.\nThis talk contrasts physics-driven and scale-driven approaches to data processing and shows how foundation-model principles (scaling laws\, transfer learning\, and end-to-end optimization) can be applied to HEP analyses. Compute-optimal scaling laws are derived for the state-of-the-art ATLAS jet flavor tagger and validated by training models two orders of magnitude beyond previous compute regimes\, yielding predictable performance improvements in line with industry-scale models. When translated into physics sensitivity for flagship ATLAS analyses such as HH(4b) at the High-Luminosity LHC\, these gains correspond to improvements equivalent to multiple years of data taking\, motivating a shift toward large-scale ML model training and deployment within LHC experiments.\n \nJoin Zoom Meeting\nhttps://lbnl.zoom.us/j/95679892182?pwd=RU5xU2dDRFNabnR1U3pQMklkYWFIdz09 \nMeeting ID: 956 7989 2182 \nPasscode: 169037
URL:https://rpm.physics.lbl.gov/event/speaker-matthias-vigl-technical-university-of-munich-title-machine-learning-scaling-laws-for-lhc-physics-how-scale-unlocks-breakthrough-gains-in-physics-sensitivity/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260122T160000
DTEND;TZID=UTC:20260122T170000
DTSTAMP:20260414T112419
CREATED:20260115T202313Z
LAST-MODIFIED:20260115T202313Z
UID:3053-1769097600-1769101200@rpm.physics.lbl.gov
SUMMARY:Speaker: Daniel Kodroff (LBNL) - Title: New Results on Solar Neutrinos and Light Dark Matter Searches with the LUX-ZEPLIN Experiment
DESCRIPTION:Research Progress Meeting \nDate: January 22\, 2026 \nTime: 4:00- 5:00 pm \nLocation: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]  \nSpeaker: Daniel Kodroff\, LBNL \nTitle: New Results on Solar Neutrinos and Light Dark Matter Searches with the LUX-ZEPLIN Experiment \nAbstract: LUX-ZEPLIN (LZ) is a direct detection dark matter experiment led by Berkeley Lab. Located nearly a mile underground at the Sanford Underground Research Facility in South Dakota\, USA\, LZ employs a 7 tonne active volume of liquid xenon in a dual-phase time projection chamber (TPC). In this talk\, I will discuss the status of the experiment and present recent results on searches for dark matter candidates and coherent elastic neutrino nucleus scattering (CEvNS) from Boron-8 solar neutrinos. I will then discuss the implications of these measurements and the experiment’s future prospects. \nhttps://lbnl.zoom.us/j/98854322464?pwd=K2tKUm1VZjRlV1J5RHE3cXdHQzRxdz09 \nMeeting ID: 988 5432 2464\n\nPasscode: 142239
URL:https://rpm.physics.lbl.gov/event/speaker-daniel-kodroff-lbnl-title-new-results-on-solar-neutrinos-and-light-dark-matter-searches-with-the-lux-zeplin-experiment/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260129T160000
DTEND;TZID=UTC:20260129T170000
DTSTAMP:20260414T112419
CREATED:20260120T183506Z
LAST-MODIFIED:20260120T183506Z
UID:3056-1769702400-1769706000@rpm.physics.lbl.gov
SUMMARY:Speaker: Vladimir Tishchenko (Brookhaven National Laboratory) - Title: The Muon g-2 Experiment: A Precision Test of the Standard Model
DESCRIPTION:Research Progress Meeting \nDate: January 29\, 2026 \nTime: 4:00- 5:00 pm \nLocation: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]  \nSpeaker: Vladimir Tishchenko\, Brookhaven National Laboratory \nTitle: The Muon g-2 Experiment: A Precision Test of the Standard Model \nAbstract: The anomalous magnetic moment of the muon\, aμ\, is among the most precisely measured quantities in particle physics and a powerful probe of physics within and beyond the Standard Model. The Muon g-2 Experiment at Fermilab was motivated by a long-standing ~3.5σ discrepancy between theory and experiment and aimed to improve the experimental precision by a factor of four. In 2025\, the collaboration reported its final result based on six years of data\, reaching a precision of 127 parts per billion. This talk will summarize the experimental method\, key systematic challenges\, and the final measurement\, and discuss its implications for ongoing efforts at the precision frontier. \nhttps://lbnl.zoom.us/j/98854322464?pwd=K2tKUm1VZjRlV1J5RHE3cXdHQzRxdz09 \nMeeting ID: 988 5432 2464\n\nPasscode: 142239
URL:https://rpm.physics.lbl.gov/event/speaker-vladimir-tishchenko-brookhaven-national-laboratory-title-the-muon-g-2-experiment-a-precision-test-of-the-standard-model/
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