Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics
Published in Machine Learning: Science and Technology, 2025
Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrates how data collected by the CMS experiment at the Large Hadron Collider can be useful in pre-training foundation models for HEP. Specifically, we introduce the AspenOpenJets (AOJs) dataset, consisting of approximately 178 M high pt jets derived from CMS 2016 Open Data. We show how pre-training the OmniJet-α foundation model on AOJs improves performance on generative tasks with significant domain shift: generating boosted top and QCD jets from the simulated JetClass dataset. In addition to demonstrating the power of pre-training of a jet-based foundation model on actual proton–proton collision data, we provide the ML-ready derived AOJs dataset for further public use.
Recommended citation: Amram, O., et al., Reyes-González, H. (2025). 'Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics.' Mach. Learn.: Sci. Technol. 6, 030601.
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