报告题目：An introduction to machine learning physics

报告嘉宾：Akio Tomiya(富谷昭夫)，东京女子大学 副教授

报告时间：2024年8月28日 14:00-16:00

报告地点：吉林大学中心校区物理楼333会议室

嘉宾简介

　　Professor Akio Tomiya got a PhD in Osaka U, 2015. Passing through his postdoc carriers at CCNU (2015-2018), RIKEN/BNL (2018-2021) and assistant and associate professor positions at IPUT Osaka (2021-2024), he is currently working at Tokyo Woman’s Christian University as afaculty associate professor, since 2024. He has so far received several awards and approved research fundings as a PI: The 2019 (14th) Particle Medal Encouragement Award; The 2023 (29th) Physical Society of Japan Paper; Transformative Research Areas (A) [Japan]; Early-Career Scientists [in Japan]; Grants-in-Aid for Scientific Research (C) [Japan]. His works have also been published in books: “Deep learning and physics”, Springer, 2021; three related books in Japanese. He is a member of lattice QCD simulation teams, HotQCD, JLQCD, and Tsukuba university, and has published one paper in Phys. Rev. Lett.

报告简介

　　In this talk, I briefly introduce recent progress on machine learning physics and lattice QCD. Deep learning utilizes neural networks, and the application of neural networks in physics is referred to as machine learning physics. With the rising popularity of ChatGPT, it's noteworthy that the core technology behind it is the Transformer. I introduce the symmetry covariant transformer, which can be used in simulations of physical systems. I will also touch on our ongoing work to apply this technology to lattice QCD simulations.

举办单位：

36365线路检测中心

吉林大学理论物理中心