Joint Physics Dept.–Inst. for Space Weather Sci. Colloquium

February 19, Thursday (** SPECIAL DAY**)

What kinds of problems in solar physics and space weather are well solved by deep learning?

Prof. Yong-Jae Moon

Kyung Hee Univ., South Korea

(Solar Physics, Host: Haimin Wang)

Room: ECE 202

**Special Time: 1pm - 2pm with 12:45 pm teatime

**ZOOM Meeting ID for those who cannot attend in-person:

955 9399 6954

(APPROVAL by Prof Ahn REQUIRED for APPH/MTSE PhD Students to attend online)

*Password: check email or request from kenahn@njit.edu

In this talk, I introduce our recent deep learning applications to solar and space weather data. We have successfully applied novel deep learning methods to the following applications:

(1) image translations between solar images such as solar far side magnetograms, (2) improvement of empirical models, (3) inversion problem, (4) super resolution, (5) pixel-to-pixel translation, (6) reduction of simulation times, (7) 2D to 3D conversion, and (8) space weather forecasting.

We also discuss the applications of symbolic regression and GPT for space weather.