White dwarfs from machine learning

On the other hand, existing astronomical algorithms are essentially classification algorithms, with sample incompleteness being a critical weakness. In our study, we propose the WD Network (WDNet) algorithm, which is a new object detection algorithm that integrates multiple advanced technologies and can directly locate WDs in images. WDNet overcomes the degradation issue of WDs and detected 31,065 candidates in 80,448 images.

The candidates exhibit a wide range of types, including DA, DB, DC, DQ, and DZ, with surface gravity within 7.8dex~8.4dex, effective temperatures within 10000K~56000K, colors within -1<u-g<1 and -0.8<g-r<0.4, and reduced proper motion within 20~35mag. In the future, WDNet will conduct large-scale searches using the Chinese Space Station Telescope and Sloan Digital Sky Survey V.