NuGraph2: A Graph Neural Network for Neutrino Physics Event Reconstruction

arXiv:2403.11872v1 Announce Type: cross
Abstract: Liquid Argon Time Projection Chamber (LArTPC) detector technology offers a wealth of high-resolution information on particle interactions, and leveraging that information to its full potential requires sophisticated automated reconstruction techniques. This article describes NuGraph2, a Graph Neural Network (GNN) for low-level reconstruction of simulated neutrino interactions in a LArTPC detector. Simulated neutrino interactions in the MicroBooNE detector geometry are described as heterogeneous graphs, with energy depositions on each detector plane forming nodes on planar subgraphs. …

abstract article arxiv automated cs.lg event gnn graph graph neural network hep-ex information interactions low network neural network particle physics physics.data-an projection technology type wealth