Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors

no code implementations • 1 Feb 2021 • Francois Drielsma, Kazuhiro Terao, Laura Dominé, Dae Heun Koh

Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data.

Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data

no code implementations • 2 Jul 2020 • Francois Drielsma, Qing Lin, Pierre Côte de Soux, Laura Dominé, Ran Itay, Dae Heun Koh, Bradley J. Nelson, Kazuhiro Terao, Ka Vang Tsang, Tracy L. Usher

The optimized algorithm is then applied to the related task of clustering particle instances into interactions and yields a mean ARI of 99. 2 % for an interaction density of $\sim\mathcal{O}(1)\, m^{-3}$.

Clustering