Artificial Intelligence for the Electron Ion Collider (AI4EIC)

Allaire, C. et al. (2024) Artificial Intelligence for the Electron Ion Collider (AI4EIC). Computing and Software for Big Science, 8, 5. (doi: 10.1007/s41781-024-00113-4)

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 and 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.

• Item Type: Articles
• Keywords: QCD, Artificial Intelligence, Deep learning, Machine learning, ePIC, Physics, EIC
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Tyson, Mr Richard and Montgomery, Dr Rachel
• Authors: Allaire, C., Ammendola, R., Aschenauer, E.-C., Balandat, M., Battaglieri, M., Bernauer, J., Bondì, 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., Ent, R., Fanelli, C., Finger, M., Finger, M., Fol, E., Furletov, S., Gao, Y., Giroux, J., Gunawardhana Waduge, N. C., Hassan, O., Hegde, P. L., Hernández-Pinto, R. J., Hiller Blin, A., Horn, T., Huang, J., Jalotra, A., Jayakodige, D., Joo, B., Junaid, M., Kalantarians, N., Karande, P., Kriesten, B., Kunnawalkam Elayavalli, R., Li, Y., Lin, M., Liu, F., Liuti, S., Matousek, G., McEneaney, M., McSpadden, D., Menzo, T., Miceli, T., Mikuni, V., Montgomery, R., Nachman, B., Nair, R.R., Niestroy, J., Ochoa Oregon, S.A., Oleniacz, J., Osborn, J.D., Paudel, C., Pecar, C., Peng, C., Perdue, G.N., Phelps, W., Purschke, M.L., Rajendran, H., Rajput, K., Ren, Y., Renteria-Estrada, D.F., Richford, D., Roy, B. J., Roy, D., Saini, A., Sato, N., Satogata, T., Sborlini, G., Schram, M., Shih, D., Singh, J., Singh, R., Siodmok, A., Stevens, J., Stone, P., Suarez, L., Suresh, K., Tawfik, A.-N., Torales Acosta, F., Tran, N., Trotta, R., Twagirayezu, F. J., Tyson, R., Volkova, S., Vossen, A., Walter, E., Whiteson, D., Williams, M., Wu, S., Zachariou, N., and Zurita, P.
• College/School: College of Science and Engineering > School of Physics and Astronomy
• Journal Name: Computing and Software for Big Science
• Publisher: Springer
• ISSN: 2510-2036
• ISSN (Online): 2510-2044
• Copyright Holders: Copyright: © The Author(s) 2024
• First Published: First published in Computing and Software for Big Science 8: 5
• Publisher Policy: Reproduced under a Creative Commons licence