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 broad-band photometric methods often achieve only moderate completeness and purity. Building upon the color-space BHB identification method of \citet{2025ApJS..278...62H}, 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 𝒮c of 7,776 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 (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.
Related
- The Pristine Survey. XXX. Mapping substructures in the inner and outer halo with blue horizontal branch stars
- Two Kepler red-giant eclipsing binaries as lower red-giant branch benchmarks for asteroseismic scaling relations. Dynamical masses and radii from JKTEBOP and PHOEBE-2 modeling
- Identification of Magnetic Reconnection in Plasma Turbulence Using a Dual-branch Lightweight Hybrid Convolutional Neural Network
- Infrared spectroscopy of the longest-period Galactic Mira variables from Palomar Gattini-IR: Identification of a candidate thermally pulsing Super-Asymptotic Giant Branch star
- Morphological Identification of Dynamical Regimes in MHD Turbulence with ScaleAware-JEPA
BibTeX
@misc{zhang2026photometric,
title = {{Photometric Identification and Dynamical Purification of Blue Horizontal Branch Stars in DESI MWS DR1}},
author = {Shuai Zhang and Xiaolong Wang and Kai Xiao and Guozhen Hu and Wenyuan Cui and Ce Cai and Shuai Feng and Jie Ju},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.15031},
eprint = {2610.15031},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.15031},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Photometric Identification and Dynamical Purification of Blue Horizontal Branch Stars in DESI MWS DR1
AU - Shuai Zhang
AU - Xiaolong Wang
AU - Kai Xiao
AU - Guozhen Hu
AU - Wenyuan Cui
AU - Ce Cai
AU - Shuai Feng
AU - Jie Ju
PY - 2026
DA - 2026/10/10
PB - arXiv
DO - 10.48550/arxiv.2610.15031
UR - https://arxiv.org/abs/2610.15031
AB - 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 \citet{2025ApJS..278...62H}, 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∼20~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.
ER -