Neutrino Physics and Machine Learning 2023

Session

Session 7

25 Aug 2023, 09:00

Tufts University

27. Towards Self-Supervised Learning for Neutrino Experiments (remote)

Radi Radev (CERN)

25/08/2023, 09:00

Individual Talk

Deep learning models for reconstruction in LArTPC neutrino data have become ubiquitous and have been successfully applied to real analyses. These models usually have to be trained from scratch depending on the task and do not take into account symmetries or systematic uncertainties.

Following advances in contrastive learning we show how such a method can be applied to sparse 3D LArTPC data,...

9. Machine Learning Applications for the neutrinoless double-beta decay search with LEGEND

Ann-Kathrin Schuetz (Lawrence Berkeley National Laboratory)

25/08/2023, 09:35

Collaboration Talk

The Large Enriched Germanium Experiment for Neutrinoless double-beta Decay (LEGEND) project searches for the lepton-number-violating neutrinoless double-beta (0vbb) decay of Ge-76. By utilizing High Purity Germanium (HPGe) detectors enriched with Ge-76 and immersing them directly into liquid argon (LAr), LEGEND combines the superior energy resolution of germanium detectors with the...

8. Faithful Pulse Shape Analysis for Germanium Detectors using Feature Importance Supervision

Katharina Kilgus (Universität Tübingen)

25/08/2023, 10:35

Individual Talk

Experiments using the 76Ge isotope have set leading limits in the search for neutrinoless double beta decay, offering insights into the nature of neutrinos and the universe. The LEGEND experiment employs High Purity Germanium (HPGe) detectors for this purpose and dramatically reduces backgrounds using Pulse Shape Analysis (PSA). To enhance the analysis, we propose the implementation of a...

23. Machine Learning in KamLAND-Zen: An Old Detector Learning New ML Tricks

Hasung Song (Boston University)

25/08/2023, 11:10

Collaboration Talk

The KamLAND-Zen experiment is a multi-purpose neutrino detector in central Japan, with a broad neutrino science program. KLZ has produced world-leading results in the study of solar, geo, and astophysical neutrinos. Recently, KLZ has also set the world-leading limit on the majorana neutrino mass, the first such limit in the Inverted Mass Ordering region. Machine learning plays a key role in...

37. MAJORANA demonstrator data release

Aobo Li (Boston University)

25/08/2023, 11:55

33. Closing

Kazuhiro Terao (SLAC)

25/08/2023, 12:10

14. NuDot and Machine Learning

Masooma Sarfraz

Individual Talk

(Submitted as a poster request)
NuDot is a monolithic ton-scale liquid scintillator research and development testbed. Presently, NuDot aims to reduce one of the dominant backgrounds in modern and future neutrinoless double beta decay (0νββ) searches: the solar neutrino background. It will demonstrate the ability to separate the Cherenkov emission by MeV electrons from the scintillation...