MSFA-Net applies multi-scale convolutions and soft frequency attention to LAMOST spectra, achieving high-precision BHB identification and adding 3583 new candidates to the catalog.
VVV Survey of Blue Horizontal-Branch Stars in the Bulge-Halo Transition Region of the Milky Way
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We characterize the population of blue horizontal-branch (BHB) stars in the bulge-halo transition region of the Milky Way using the VISTA Variables in the V\'ia L\'actea (VVV) ESO Public Survey data. The selection of BHB stars is made using the globular cluster M22 as a reference standard, and constructing color-magnitude and color-color diagrams with specific cuts in the $ZYJHK_s$ near-infrared (IR) passbands. A total of 12,554 BHB stars were detected, in a region within $-10.0^{\circ} \leq \ell \leq 10.2^{\circ}$ and $-10.2^{\circ} \leq b \leq -8.0^{\circ}$. We provide accurate coordinates and near-IR photometry for this sample of BHB stars. We searched for over-densities of stars with sizes similar to those of known globular clusters and stellar streams. By comparing real data with Monte Carlo simulations, we conclude that the few over-densities detected are of low significance. We also constructed $K_s$-band light curves for the BHB stars to study their variability. Taking an average of 52 epochs to calculate periods and amplitudes, we identify hundreds of candidate eclipsing binaries and a dozen pulsating stars. Finally, we made some comparisons with results obtained in a previous study for RR Lyrae variable stars in this same region.
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astro-ph.SR 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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MSFA-Net: An Advanced Deep Learning Model for Identifying Blue Horizontal-Branch Stars from LAMOST DR12
MSFA-Net applies multi-scale convolutions and soft frequency attention to LAMOST spectra, achieving high-precision BHB identification and adding 3583 new candidates to the catalog.