A survey of machine learning-based physics event generation
Old Dominion University（欧道明大学）；Jefferson Lab（杰斐逊实验室）；Shandong University（山东大学）
英文摘要：
Event generators in high-energy nuclear and particle physics play an important role in facilitating studies of particle reactions. We survey the state-of-the-art of machine learning (ML) efforts at building physics event generators. We review ML generative models used in ML-based event generators and their specific challenges, and discuss various approaches of incorporating physics into the ML model designs to overcome these challenges. Finally, we explore some open questions related to super-resolution, fidelity, and extrapolation for physics event generation based on ML technology.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
