Machine-learning Selection of Optical Transients in Subaru/Hyper Suprime-Cam Survey

12 Sep 2016 Mikio Morii Shiro Ikeda Nozomu Tominaga Masaomi Tanaka Tomoki Morokuma Katsuhiko Ishiguro Junji Yamato Naonori Ueda Naotaka Suzuki Naoki Yasuda Naoki Yoshida

We present an application of machine-learning (ML) techniques to source selection in the optical transient survey data with Hyper Suprime-Cam (HSC) on the Subaru telescope. Our goal is to select real transient events accurately and in a timely manner out of a large number of false candidates, obtained with the standard difference-imaging method... (read more)

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  • INSTRUMENTATION AND METHODS FOR ASTROPHYSICS