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Found 4 papers, 0 papers with code
Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector
As the size of a table increases with detector volume for a fixed resolution, this method scales poorly for future larger detectors.
Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers
This work contributes to the development of an end-to-end optimizable full data reconstruction chain for LArTPCs, in particular pixel-based 3D imaging detectors including the near detector of the Deep Underground Neutrino Experiment.
Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data
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 $\sim\mathcal{O}(1)\, m^{-3}$.
Point Proposal Network for Reconstructing 3D Particle Endpoints with Sub-Pixel Precision in Liquid Argon Time Projection Chambers
Using as a benchmark the PILArNet public LArTPC data sample in which the voxel resolution is 3mm/voxel, our algorithm successfully predicted 96. 8% and 97. 8% of 3D points within a distance of 3 and 10~voxels from the provided true point locations respectively.
