Neutrino Physics and Machine Learning (NPML 2025)

Session

AI//ML for Detector Physics Modeling

30 Oct 2025, 13:00

Koshiba Hall (University of Tokyo)

52. Determining a TPC Electric Field using Physics-Informed Continuous Normalizing Flows

Ivy Li

30/10/2025, 13:00

Long talk (25min. + 10min. Q/A)

Noble element time projection chambers (TPCs) have enabled searches for neutrino physics both within and beyond the Standard Model, but these rare event searches are limited by electric field distortions on event position reconstruction. Traditional data-driven field distortion corrections lack smoothness and differentiability, require extensive calibration data, and often do not follow...

46. PMT Timing Calibration in Large Liquid Scintillator Detectors with In Situ Radioactive Backgrounds

Scott DeGraw

30/10/2025, 13:35

Short talk (15min. + 5 min. Q/A)

Event reconstruction in large liquid scintillator neutrino detectors, such as SNO+, rely on hit times from large numbers of photomultiplier tubes (PMTs). Standard methods of PMT timing calibrations involve dedicated hardware with deployed or in situ light sources. A calibration using in situ radioactive backgrounds present in regular physics data would allow vastly more frequent calibrations...

4. LUCiD: a Light-based Unified Calibration and trackIng Differentiable simulation

Omar Alterkait

30/10/2025, 13:55

Long talk (25min. + 10min. Q/A)

Next-generation monolithic Water Cherenkov detectors aim to probe fundamental questions in neutrino physics. These measurements demand unprecedented precision in detector calibration and event reconstruction, pushing beyond the capabilities of traditional techniques. We present a novel framework for differentiable simulation of Water Cherenkov detectors that enables end-to-end optimization...

34. Uncertainty propagation with a LArTPC differentiable simulator

Pierre Granger

30/10/2025, 14:30

Long talk (25min. + 10min. Q/A)

Liquid argon time projection chambers (LArTPCs) are highly attractive for particle detection because of their tracking resolution and calorimetric reconstruction capabilities. Developing high-quality simulators for such detectors is very challenging because conventional approaches to describe different detector parameters or processes ignore their entanglement (ie, calibrations are done one at...

24. Towards data application of simultaneously calibrating multiple detector effects using differentiable simulation

Yifan Chen

30/10/2025, 15:05

Short talk (15min. + 5 min. Q/A)

Missing correlations and potential biases in detector calibrations are one major challenge mitigating data—simulation differences. To address this, we propose to use gradients, enabled by differentiable simulation, for efficient and effective optimization of the detector physics parameters. We developed an auto-differentiation enabled simulation of a liquid argon time projection chamber using...