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High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high-energy physics.
LHC analysis-specific datasets with Generative Adversarial Networks
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Focal loss for dense object detection. In Proceedings of the IEEE international conference on computer vision . 2980–2988
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sPHENIX Software repositories https://github.com/sPHENIX-Collaboration
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Technical Design Report: sPHENIX experiment at RHIC
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Yasir Alanazi, Nobuo Sato, Tianbo Liu, W Melnitchouk, Michelle P Kuchera, Evan Pritchard, Michael Robertson, Ryan Strauss, Luisa Velasco, and Yaohang Li. 2020 · 2020
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cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data. In Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques (New York, NY, USA, 2020-09-30) (PACT ’20) . Association for Computing Machinery, 3–15
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Science Requirements and Detector Concepts for the Electron-Ion Collider: EIC Yellow Report
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Scientific computing plan for the ECCE detector at the Electron Ion Collider
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Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints
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Fast Error-Bounded Lossy HPC Data Compression with SZ. In 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2016-05). 730–739
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Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder. In 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) . 1094–1099
Yi Huang, Yihui Ren, Shinjae Yoo, and Jin Huang. 2021 · 2021
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MGARD+: Optimizing Multilevel Methods for Error-Bounded Scientific Data Reduction
Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, and Scott Klasky. [n. d.] · 2021
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Multilevel Techniques for Compression and Reduction of Scientific Data—The Multivariate Case
Mark Ainsworth, Ozan Tugluk, Ben Whitney, and Scott Klasky. [n. d.]
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LHC Machine
Lyndon Evans and Philip Bryant. [n. d.]
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Reducing the Dimensionality of Data with Neural Networks
G. E. Hinton and R. R. Salakhutdinov. [n. d.]
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Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. [n. d.] · 2075
Closest in time.