A blue horizontal-branch star detector based on SDSS images

Abstract The blue horizontal-branch (BHB) stars are horizontal-branch stars bluer than the RR Lyrae instability strip in the Hertzsprung–Russell diagram, serving as ideal tracers for studying the structure and evolution of the Milky Way. With the accumulated photometric image data from the Sloan Digital Sky Survey (SDSS), we attempt to use object detection techniques to directly locate the position of BHB stars from the images. Given that BHB stars appear extremely tiny in images captured by the SDSS telescope, many existing object detection algorithms are unsuitable for detecting such tiny objects. In this study, we propose a blue horizontal-branch star detector (BHBDet), the first object detection algorithm with six detection heads designed for stellar detection. BHBDet achieves a precision of $80.4\%$, a recall of $91.1\%$, and an $F_{1}$ score of $85.4\%$, significantly outperforming popular algorithms with three detection heads. Among 109696 images containing at least 11 million objects, we detected 49852 BHB candidates. These candidates exhibit reduced proper motions primarily ranging from 5–$20$ mas yr$^{-1}$, and colors primarily within $-1.5 < u - g < 2$, $-2 < g - r < 0.5$, $-2 < r - i < 1$, and $-2 < i - z < 2$. We further estimated the atmosphere parameters for these candidates, which primarily fall within $7000 < T_{\mathrm{eff}} < 12000$ K, $3 < \log g < 5$ dex, and $-3 < {\rm [Fe/H]} < -1$ dex. We also find that approximately $30\%$ of the candidates are located beyond $35$ kpc, with some exceeding $100$ kpc. By applying Balmer line profile cuts, we confirmed 2093 BHB stars from those with the spectra provided by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope. We have published this catalog online to further enrich the BHB population and advance the research on the structure of the Milky Way.