JetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physics

Journal Article · Mon Oct 30 00:00:00 UTC 2023 · Journal of Open Source Software

DOI: https://doi.org/10.21105/joss.05789 · OSTI ID:2305635

Kansal, Raghav  ^[1]; Pareja, Carlos  ^[2]; Hao, Zichun  ^[3]; Duarte, Javier  ^[2]

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1. Univ. of California, San Diego, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
2. Univ. of California, San Diego, CA (United States)
3. California Institute of Technology (CalTech), Pasadena, CA (United States)

JetNet is a Python package that aims to increase accessibility and reproducibility for machinelearning (ML) research in high energy physics (HEP), primarily related to particle jets. Basedon the popular PyTorch ML framework, it provides easy-to-access and standardized interfacesfor multiple heterogeneous HEP datasets and implementations of evaluation metrics, lossfunctions, and more general utilities relevant to HEP.

• Research Organization: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), High Energy Physics (HEP)
• Grant/Contract Number: AC02-07CH11359; SC0021187; SC0021396
• OSTI ID: 2305635
• Report Number(s): FERMILAB-PUB--23-0885-V; oai:inspirehep.net:2719606
• Journal Information: Journal of Open Source Software, Journal Name: Journal of Open Source Software Journal Issue: 90 Vol. 8; ISSN 2475-9066
• Publisher: Open Source Initiative - NumFOCUSCopyright Statement
• Country of Publication: United States
• Language: English