Authors
C. Allaire, Université Paris-Saclay
R. Ammendola, Sezione di Roma Tor Vergata
E.-C. Aschenauer, Brookhaven National Lab
M. Balandat, Meta
M. Battaglieri, National Institute for Nuclear Physics
J. Bernauer, Stony Brook University
M. Bondì, National Institute for Nuclear Physics
N. Branson, Drexel University
T. Britton, Jefferson Lab
A. Butter, Laboratory Nuclear and High-Energy Physics
I. Chahrour, University of Michigan
P. Chatagnon, Jefferson Lab
E. Cisbani, National Institute for Nuclear Physics
E. W. Cline, Stony Brook University
S. Dash, Indian Institute of Technology Bombay
C. Dean, MIT
W. Deconinck, University of Manitoba
A. Deshpande, Brookhaven National Lab
M. Diefenthaler, Jefferson Lab
R. Ent, Jefferson Lab
C. Fanelli, Jefferson Lab
M. Finger, Charles University
M. Finger Jr.
E. Fol, CERN
S. Furletov, Jefferson Lab
Y. Gao, Brookhaven National Lab
J. Giroux, William & Mary
N. C. Gunawardhana Waduge, University of Virginia
O. Hassan, University of Manitoba
P. L. Hegde, Central University of Karnataka
R. J. Hernandez-Pinto, Ciudad Universitaria
A. Hiller Blin, Tübingen University
T. Horn, The Catholic University of America
J. Huang, Brookhaven National Lab
A. Jalotra, University of Jammu
D. Jayakodige, Hampton University
B. Joo, Oak Ridge National Laboratory
M. Junaid, University of Regina
N. Kalantarians, Virginia Union University
P. Karande, Lawrence Livermore National Laboratory
B. Kriesten, Center for Nuclear Femtography
R. Kunnawalkam Elayavalli, Vanderbilt University
Y. Li, Old Dominion UniversityFollow
M. Lin, Brookhaven National Lab
F. Liu, Oak Ridge National Laboratory
S. Liuti, University of Virginia
G. Matousek, Duke University
M. McEneaney, Duke University
D. McSpadden, Jefferson Lab
T. Menzo, University of Cincinnati
T. Miceli, Fermilab
V. Mikuni, Berkeley Laboratory
R. Montgomery, University of Glasgow
B. Nachman, Lawrence Berkeley National Laboratory
R. R. Nair, National Centre for Nuclear Research
J. Niestroy, William & Mary
S. A. Ochoa Oregon, Ciudad Universitaria
J. Oleniacz, Warsaw University of Technology
J. D. Osborn, Brookhaven National Lab
C. Paudel, Florida International University
C. Pecar, Duke University
C. Peng, Argonne National Laboratory
G. N. Perdue, Fermilab
W. Phelps, Jefferson Lab
M. L. Purschke, Brookhaven National Lab
H. Rajendran, Central University of Karnataka
K. Rajput, Jefferson Lab
Y. Ren, Lawrence Berkeley National Laboratory
D. F. Renteria-Estrada, Ciudad Universitaria
D. Richford, Baruch College
B. J. Roy, Nuclear Physics Division
D. Roy, Rutgers University
A. Saini, Fermilab
N. Sato, Jefferson Lab
T. Satogata, Old Dominion UniversityFollow
G. Sborlini, Universidad de Salamanca
M. Schram, Jefferson Lab
D. Shih, Rutgers University
J. Singh, Panjab University
R. Singh, Brookhaven National Laboratory
A. Siodmok, Jagiellonian University
J. Stevens, William & Mary
P. Stone, William & Mary
L. Suarez, William & Mary
K. Suresh, University of Regina
A. -N. Tawfik, Future University in Egypt
F. Torales Acosta, Lawrence Berkeley National Laboratory
N. Tran, Fermilab
R. Trotta, The Catholic University of America
F. J. Twagirayezu, University of California
R. Tyson, University of Glasglow
S. Volkova, Pacific Northwest National Laboratory
A. Vossen, Jefferson Lab
E. Walter, William & Mary
D. Whiteson, University of California Irvine
M. Williams, MIT
S. Wu, University of Manitoba
N. Zachariou, University of York
P. Zurita, Universidad Complutense de Madrid
DOI
10.1007/s41781-024-00113-4
Publication Title
Computing and Software for Big Science
Abstract
The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.
Rights
© 2024 The Authors.
This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Data Availability
Article states: "The datasets and lecture materials used in our tutorials are publicly available on the EIC Community website at https://eic.ai/community, which includes all relevant educational resources."
Original Publication Citation
Allaire, C., Ammendola, R., Aschenauer, E. C., Balandat, M., Battaglieri, M., Bernauer, J., Bondi, M., Branson, N., Britton, T., Butter, A., Chahrour, I., Chatagnon, P., Cisbani, E., Cline, E. W., Dash, S., Dean, C., Deconinck, W., Deshpande, A., Diefenthaler, M., . . . Zurita, P. (2024). Artificial intelligence for the Electron-Ion Collider (AI4EIC). Computing and Software for Big Science, 8(1), 1-21, Article 5. https://doi.org/10.1007/s41781-024-00113-4
Repository Citation
Allaire, C., Ammendola, R., Aschenauer, E. C., Balandat, M., Battaglieri, M., Bernauer, J., Bondi, M., Branson, N., Britton, T., Butter, A., Chahrour, I., Chatagnon, P., Cisbani, E., Cline, E. W., Dash, S., Dean, C., Deconinck, W., Deshpande, A., Diefenthaler, M., . . . Zurita, P. (2024). Artificial intelligence for the Electron-Ion Collider (AI4EIC). Computing and Software for Big Science, 8(1), 1-21, Article 5. https://doi.org/10.1007/s41781-024-00113-4
ORCID
0000-0002-8081-3815 (Satogata)
