Double-lined Spectroscopic Binaries from the LAMOST Low-Resolution Survey

TL;DR

This paper presents a data-driven spectral model to identify double-lined spectroscopic binaries in the LAMOST survey, detecting over 4800 candidates and deriving their physical and orbital parameters using multi-epoch data.

Contribution

The study introduces a novel spectral fitting approach for SB2 detection in low-resolution spectra and provides comprehensive physical and orbital parameters for identified binaries.

Findings

Detected over 4800 SB2 candidates from 2.6 million objects.

Most candidates are FGK-type binaries with high mass ratio and large radial velocity separation.

Provided orbital solutions for 44 candidates with multiple observational epochs.

Abstract

We report on a data-driven spectral model that we have developed for the identification of double-lined spectroscopic binary stars (SB2s) in the LAMOST low-resolution survey (R$\sim$1800). Employing simultaneous fitting with both single-star and binary-star models, we detected over 4800 SB2 candidates, where both components are detectably contributing to the spectrum, from an initial pool of 2.6 million objects. Tests show that our model favors FGK-type main-sequence binaries with high mass ratio ($q\geq$ 0.7) and large radial velocity separation ($\Delta \rm RV \geq$ 100~km$\,$s$^{-1}$). Almost all of these candidates are positioned above the main sequence in the color-magnitude diagram, indicating their binary nature. Additionally, we utilized various observational data, including spectroscopy, photometry, parallax, and extinction, to determine multiple physical parameters such as the effective temperature, age, metallicity, radial velocity, mass, mass ratio, stellar radius, along with their associated uncertainties for these SB2 candidates. For the 44 candidates with seven or more observational epochs, we provide complete orbital solutions. We make available catalogs containing various stellar parameters for identified SB2 systems.