Neutrino Physics and Machine Learning 2026

Session

Applications: Detector Calibration & Systematic Uncertainties

15 Jun 2026, 15:50

The Interdisciplinary Science and Engineering Building (UC Irvine)

20. Machine Learning to Constrain Optical Parameters at Liquid Scintillator Detectors

Ms Sanya Arora (University of California, Berkeley)

15/06/2026, 15:50

Experimental Applications

Applications in Experiments

Monolithic liquid scintillator detectors are searching for neutrinoless double beta decay, a theorized process that would confirm the Majorana nature of neutrinos. The production and propagation of photons in the detection medium depend on various optical properties, such as light yield, attenuation lengths and re-emission/absorption spectra. These must all be separately characterized,...

49. Efficient Calibration of Scintillation Time Constants via Bayesian Optimization (BO)

Po-Wei Huang (University of Oxford)

15/06/2026, 16:15

Experimental Applications

Applications in Experiments

Accurate characterization of scintillation emission profiles is essential for robust event reconstruction in liquid scintillator detectors. The SNO+ Collaboration has developed an innovative framework employing Bayesian optimization (BO) to calibrate these timing profiles using internal radioactive backgrounds. Our results demonstrate that BO achieves convergence in at least an order of...

17. Improving Detector Systematic Uncertainties Through Data-Driven Machine Learning

Harry Hausner (Fermilab)

15/06/2026, 16:40

Experimental Applications

Applications in Experiments

Detector simulation in liquid argon time projection chambers (LArTPCs) is a constant challenge. In particular the modeling of electrons response on wires is highly nontrivial. However, new machine learning techniques exist which can be leveraged to ameliorate these concerns. We present a novel methodology to attempt to learn from cosmic muon data in the ICARUS detector how reconstructed wire...

59. The Status of the RENE Experiment

Dr Sang Yong KIM (Chonnam National University)

Experimental Applications

AI/ML R&D

The Reactor Experiment for Neutrinos and Exotics (RENE) is a pioneering initiative aimed at investigating the existence of sterile neutrinos within the Δm²≈2 eV² parameter space, motivated by the observed Reactor Antineutrino Anomaly. The experimental setup consists of a cylindrical target volume containing 270 liters of gadolinium-loaded liquid scintillator (Gd-LS), surrounded by a...