STI Publications - View Publication Form #19800

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Publication Information
Title Diffusion model approach to simulating electron-proton scattering events
Abstract Generative AI is a fast-growing area of research offering various avenues for exploration in high-energy nuclear physics. In this work, we explore the use of generative models for simulating electron-proton collisions relevant to experiments like CEBAF and the future Electron-Ion Collider (EIC). These experiments play a critical role in advancing our understanding of nucleons and nuclei in terms of quark and gluon degrees of freedom. The use of generative models for simulating collider events faces several challenges such as the sparsity of the data, the presence of global or event-wide constraints, and steeply falling particle distributions. In this work, we focus on the implementation of diffusion models for the simulation of electron-proton scattering events at EIC energies. Our results demonstrate that diffusion models can accurately reproduce relevant observables such as momentum distributions and correlations of particles, momentum sum rules, and the leading electron kinematics,
Author(s) Jianwei Qiu, Nobuo Sato, Felix Ringer , Peter Devlin
Publication Date July 2024
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
JLAB Number: JLAB-THY-23-3945 OSTI Number: 2407241
LANL Number: Other Number: DOE/OR/23177-7245
Associated with an experiment No
Associated with EIC No
Supported by Jefferson Lab LDRD Funding No
Journal Article
Journal Name Physical Review D
Refereed No
Volume 110
Issue
Page(s) 016030
Attachments/Datasets/DOI Link
Document(s)
PhysRevD.110.016030.pdf (Accepted Manuscript)
DOI Link
Dataset(s) (none)
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