Photometry of Saturated Stars with Machine Learning

Photometry of Saturated Stars with Machine Learning
Dominek Winecki (Dept. of Computer Science and Engineeering, The Ohio State University), Christopher S. Kochanek (Dept. of Astronomy, The Ohio State University)
arXiv:2404.15405v1 Announce Type: new
Abstract: We develop a deep neural network (DNN) to obtain photometry of saturated stars in the All-Sky Automated Survey for Supernovae (ASAS-SN). The DNN can obtain unbiased photometry for stars from g=4 to 14 mag with a dispersion (15%-85% 1sigma range around median) of 0.12 mag for saturated (garXiv:2404.15405v1 Announce Type: new
Abstract: We develop a deep neural network (DNN) to obtain photometry of saturated stars in the All-Sky Automated Survey for Supernovae (ASAS-SN). The DNN can obtain unbiased photometry for stars from g=4 to 14 mag with a dispersion (15%-85% 1sigma range around median) of 0.12 mag for saturated (g