Conveners
Invited talks - Physics and Astronomy 1-2
- Hyung Do Kim (Seoul National University)
Prof.
Sunghoon Jung
(Seoul National University)
07/11/2019, 15:45
ML has a deep potential to extend our ability to understand Nature, beyond common knowledge. As the very first steps to realize it, we use ML to seek for answers to one of the not-well-solved problems in particle physics. Our focus is not only to improve the solution, but to develop ways to figure out what the network has learned.
Dr
Sven Krippendorf
(Ludwig Maximilian University of Munich)
07/11/2019, 16:05
In this talk, I will review how ultralight axion-like particles can be constrained using X-ray observations of bright localized sources (AGNs, Quasars) in and behind galaxy clusters. To find axion-like particles in these settings corresponds to finding their characteristic pattern (quasi-sinusoidal oscillations) in noisy data. Using ML-techniques we are able to improve the search sensitivity...
Prof.
Hyung Do Kim
(Seoul National University)
07/11/2019, 16:35
Prof.
Hwidong Yoo
(Seoul National University)
07/11/2019, 16:55
최근들어 딥러닝 기술은 기초 과학 분야에도 광범위하게 연구되고 있다. 이를 통해 얻어진 지식 및 기술이 차세대 연구 시스템 및 환경을 변화시키고 결과를 획기적으로 향상시키기 위해 다양하게 적용될 것으로 기대되고 있다. 현재 고에너지 물리 실험분야에서 활발하게 연구되고 있는 딥러닝 관련 연구에 대해 소개하고 향후 기대 효과에 대해 논의 한다.
