Photometry of Saturated Stars with Machine Learning

arXiv:2404.15405v1 Announce Type: cross
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<11.5 mag) stars. More importantly, the light curve of a non-variable saturated star has a median dispersion of only 0.037 mag. The DNN light curves are, in many …

abstract arxiv astro-ph.im astro-ph.sr automated cs.cv deep neural network dnn machine machine learning median network neural network stars supernovae survey type unbiased