Data-driven Spectroscopic Estimates of Absolute Magnitude, Distance, and Binarity: Method and Catalog of 16,002 O- and B-type Stars from LAMOST

Abstract

We present a data-driven method to estimate absolute magnitudes for O- and B-type stars from the LAMOST spectra, which we combine with Gaia DR2 parallaxes to infer distance and binarity. The method applies a neural network model trained on stars with precise Gaia parallax to the spectra and predicts K s -band absolute magnitudes with a precision of 0.25 mag, which corresponds to a precision of 12% in spectroscopic distance. For distant stars (e.g., >5 kpc), the inclusion of constraints from spectroscopic significantly improves the distance estimates compared to inferences from Gaia parallax alone. Our method accommodates for emission-line stars by first identifying them via principal component analysis reconstructions and then treating them separately for the estimation. We also take into account unresolved binary/multiple stars, which we identify through deviations in the spectroscopic from the geometric inferred from Gaia parallax. This method of binary identification is particularly efficient for unresolved binaries with near equal-mass components and thus provides a useful supplementary way to identify unresolved binary or multiple-star systems. We present a catalog of spectroscopic , extinction, distance, flags for emission lines, and binary classification for 16,002 OB stars from LAMOST DR5. As an illustration, we investigate the of the enigmatic LB-1 system, which Liu et al. had argued consists of a B star and a massive stellar-mass black hole. Our results suggest that LB-1 is a binary system that contains two luminous stars with comparable brightness, and the result is further supported by parallax from the Gaia eDR3.