2022-12-19

UTAPwiki/セミナー/初期宇宙・相対論速報

Title: Introduction of machine learning and its application to physics of the universe. (Sequel of his talk on 11/28) †

Speaker: Takumi Hayashi †

With the improvement of knowledge of information science and computation power of machine, the role of machine learning(ML) is growing in various field, also in physics. In my last talk, I reviewed the basics of ML and the models widely used. In this talk, I will complete the remaining part, introduction of the application of ML to the physics familiar to us. Especially I focus on the estimation of the quasi-normal modes of a blackhole ringdown, and show the comparison between ML and other traditional methods such as matched filtering, HHT, AR-model.

[1] Giuseppe Carleo, Rev. Mod. Phys. 91, 045002 (2019), [arXiv:1903.10563].
[2] H. Nakano et al, Phys. Rev. D 99, 124032 (2019) [arXiv:1811.06443].