Towards an Event-Level Analysis in Hadronic Physics Using Generative AI-Based Surrogates
Published in 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI), 2025
Hadronic physics analyses traditionally aggregate events into binned observables before comparing with theory, which loses information. This paper uses generative surrogate models to make analysis at the level of individual events computationally tractable.
Recommended citation: T. Alghamdi, Jitao Xu, N. Ramachandra, N. Sato, Y. Li. (2025). "Towards an Event-Level Analysis in Hadronic Physics Using Generative AI-Based Surrogates." 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI).