8 citations · 15 across the 2 of their papers we have counts for
5 papers
Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors
Francois Drielsma, Kazuhiro Terao, Laura Dominé +1
Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data. Unlike previous efforts which tack…
Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers
Dae Heun Koh, Pierre Côte de Soux, Laura Dominé +6
Liquid Argon Time Projection Chambers (LArTPCs) are high resolution particle imaging detectors, employed by accelerator-based neutrino oscillation experiments for high precision ph…
Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data
Francois Drielsma, Qing Lin, Pierre Côte de Soux +7
Liquid Argon Time Projection Chambers (LArTPCs) are a class of detectors that produce high resolution images of charged particles within their sensitive volume. In these images, th…
A New Concept for Kilotonne Scale Liquid Argon Time Projection Chambers
M. Auger, R. Berner, Y. Chen +25
We develop a novel approach for a Time Projection Chamber (TPC) concept suitable for deployment in kilotonne scale detectors, with a charge-readout system free from reconstruction…
Analytical model of a 3D beam dynamics in a wakefield device
Dae Heun Koh, Stanislav S. Baturin
In this paper we suggest an analytic model, and derive simple formulas, for the beam dynamics in a wakefield structure of arbitrary cross-section. The results could be applied to e…