Corpus ID: 219260369

PILArNet: Public Dataset for Particle Imaging Liquid Argon Detectors in High Energy Physics

@article{Adams2020PILArNetPD,
  title={PILArNet: Public Dataset for Particle Imaging Liquid Argon Detectors in High Energy Physics},
  author={Corey Adams and Kazuhiro Terao and Taritree Wongjirad},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.01993}
}
Rapid advancement of machine learning solutions has often coincided with the production of a test public data set. Such datasets reduce the largest barrier to entry for tackling a problem -- procuring data -- while also providing a benchmark to compare different solutions. Furthermore, large datasets have been used to train high-performing feature finders which are then used in new approaches to problems beyond that initially defined. In order to encourage the rapid development in the analysis… Expand
3 Citations
Point Proposal Network for Reconstructing 3D Particle Positions with Sub-Pixel Precision in Liquid Argon Time Projection Chambers
TLDR
A simple algorithm is demonstrated to cluster 3D voxels into individual track-like particle trajectories with a clustering efficiency, purity, and Adjusted Rand Index of 96 %, 93 %, and 91 % respectively. Expand
A Living Review of Machine Learning for Particle Physics
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This living review is a nearly comprehensive list of citations for those developing and applying deep learning approaches to experimental, phenomenological, or theoretical analyses, and will be updated as often as possible to incorporate the latest developments. Expand
Convolutional Neural Networks for Shower Energy Prediction in Liquid Argon Time Projection Chambers
Abstract: When electrons with energies ofO (100) MeV pass through a liquid argon time projection chamber (LArTPC), they deposit energy in the form of electromagnetic showers. Methods to reconstructExpand

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