DEEPCR on ACS/WFC: Cosmic-Ray Rejection for HST ACS/WFC Photometry


DEEPCR is a deep-learning-based cosmic-ray rejection algorithm previously demonstrated to be superior to state-of-the-art LACosmic on Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS)/WFC F606W imaging data. In this research note, we present a new DEEPCR model for use on all filters of HST ACS/WFC. We train and test the model with ACS/WFC F435W, F606W, and F814W images, covering the entire spectral range of the ACS optical channel. The global model demonstrates near 100% detection rates of CRs in extragalactic fields and globular clusters and 91% in resolved galaxy fields. We further confirm the global applicability of the model by comparing its performance against single-filter models that were trained simultaneously and by testing the global model on data from another filter which was not previously used for training.

Research Notes of the American Astronomical Society