STI Publications - View Publication Form #17184
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Publication Information
| Title | Machine learning-based jet and event classification at the Electron-Ion Collider and applications to hadron structure and spin physics | ||||
| Abstract | We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at the relatively low EIC energies, focusing on (i) identifying the quark flavor of the jet and (ii) identifying the hard-scattering process. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current RHIC program, including the extraction of (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant for the detector design including particle identification, charge information, and minimum transverse mome | ||||
| Author(s) | James Mulligan, Felix Ringer, Kyle Lee, Feng Yuan, M. Ploskon | ||||
| Publication Date | March 2023 | ||||
| Document Type | Journal Article | ||||
| Primary Institution | Thomas Jefferson National Accelerator Facility, Newport News | ||||
| Affiliation | Theory & Comp Physics / THEORY CENTER / THEORY CENTER | ||||
| Funding Source | Nuclear Physics (NP) | ||||
| Proprietary? | No | ||||
| This publication conveys | Technical Science Results | ||||
| Document Numbers |
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| Associated with an experiment | No | ||||
| Associated with EIC | Yes | ||||
| Supported by Jefferson Lab LDRD Funding | No |
Journal Article
| Journal Name | Journal of High Energy Physics |
| Refereed | No |
| Volume | |
| Issue | |
| Page(s) | 85 |
Attachments/Datasets/DOI Link
| Document(s) |
Machine_learning_based_event_and_jet_identification_at_the_Electron_Ion_Collider-2.pdf
(STI Document)
JHEP03(2023)085.pdf
(Accepted Manuscript)
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| DOI Link | |
| Dataset(s) | (none) |
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