The Bulletin of The Korean Astronomical Society (천문학회보)
- Volume 43 Issue 1
- /
- Pages.40.3-40.3
- /
- 2018
- /
- 1226-2692(pISSN)
Applications of machine learning methods in KMTNet data quality assurance and detecting microlensing events
- Shin, Min-Su (Korea Astronomy and Space Science Institute) ;
- Lee, Chung-Uk (Korea Astronomy and Space Science Institute) ;
- Kim, Hyoun-Woo (Korea Astronomy and Space Science Institute)
- Published : 2018.05.08
Abstract
We present results from our two experiments of using machine learning algorithms in processing and analyzing the KMTNet imaging data. First, density estimation and clustering methods find meaningful structures in the metric space of imaging quality measurements described by photometric quantities. Second, we also develop a method to separate out light curves of reliable microlensing event candidates from spurious events, estimating reliability scores of the candidates.
Keywords