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

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 broad-band photometric methods often achieve only moderate completeness and purity. Building upon the color-space BHB identification method of, we synthesize SkyMapper (u,v,g,z) photometry from DESI MWS DR1 spectroscopy and identify 9,237 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 1,461 contaminants with unphysical kinematic parameters, yielding a clean photometric BHB sample S c of 7,776 stars (retention rate R keep = 84.2%). Systematic analysis of the contaminants reveals that they are predominantly faint sources (g about20 mag) with very low signal-to-noise ratios (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.