Photometric Identification and Dynamical Purification of Blue Horizontal-branch Stars in DESI MWS DR1

Abstract

Blue horizontal-branch (BHB) stars are ideal tracers for mapping the structure of the Galactic stellar halo. However, traditional spectroscopic identification is limited by data quality and sample size, while broadband photometric methods often achieve only moderate completeness and purity. Building upon the color-space BHB identification method of G. Hu et al., we synthesize SkyMapper (u, v, g, z) photometry from DESI MWS DR1 spectroscopy and identify 9237 BHB candidates in the (g − z)0–(u − v)0 color space using the HDBSCAN clustering algorithm. We then construct a kernel density estimation (KDE) Bayesian probability model with capture–recapture (C–R) prior to assign posterior membership probabilities, achieving a probability-weighted purity of 88.9% and completeness of 94.2%. Applying an escape-velocity cut based on the Galactic gravitational potential, we remove 1461 contaminants with unphysical kinematic parameters, yielding a clean photometric BHB sample Sc of 7776 stars (retention rate Rkeep = 84.2%). Systematic analysis of the contaminants reveals that they are predominantly faint sources (g ∼ 20 mag) with very low signal-to-noise ratios (SNRs; median SNR < 5). When the BHB color–luminosity relation is incorrectly applied to these objects, their space velocities are amplified beyond the Galactic escape limit, confirming that the escape-velocity filter essentially acts as a physical detector of low-SNR-driven distance inflation.