New Single-lined Spectroscopic Binaries Identified from the LAMOST Medium-resolution Spectroscopic Survey

Abstract A typical single-lined spectroscopic binary (SB1) consists of two stars with almost the same age but markedly different masses and physical properties. SB1s are essential for obtaining the statistical properties of stars and constraining stellar evolutionary models, particularly when orbital parameters are well determined. In this study, we first carry out a data-cleaning step on a sample of LAMOST Medium-Resolution Spectroscopic Survey stars with a sufficient number of observations and perform an F 2 test, obtaining 7775 radial velocity variables. After removing false positives and crossmatching with variable and double-lined spectroscopic binary (SB2) catalogs, we exclude known astrophysical variables and SB2s, leaving 6106 SB1 candidates. We estimate initial periods using the Heck–Manfroid–Mersch method combined with Monte Carlo simulations and then fit each source with both an orbital model and a trend model, selecting between them via the Snedecor F- test of nested models. For orbital models, we accept the least- χ 2 solution if it satisfies F 2 < 3.1, s > 10, phase _ gap _ max < 0.3, σ v / K < 0.25 and passes the Markov Chain Monte Carlo–based robustness tests. For trend cases, we discard zeroth-order fits and require F 2 < 3.1. In total, we obtain 623 accepted solutions, of which 337 SB1s are new relative to existing catalogs.

Authors

Publication Details

Journal
The Astrophysical Journal Supplement Series
Published
2026-01-30
DOI
https://doi.org/10.3847/1538-4365/ae2bfc
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

New Single-lined Spectroscopic Binaries Identified from the LAMOST Medium-resolution Spectroscopic Survey

Fang Xia, Yue Chen, Tong 童 Ye 叶, Yanning 燕宁 Fu 傅
The Astrophysical Journal Supplement Series
Stellar, planetary, and galactic studies
article

New Single-lined Spectroscopic Binaries Identified from the LAMOST Medium-resolution Spectroscopic Survey

Fang Xia, Yue Chen, Tong 童 Ye 叶, Yanning 燕宁 Fu 傅
article en

Abstract

Abstract A typical single-lined spectroscopic binary (SB1) consists of two stars with almost the same age but markedly different masses and physical properties. SB1s are essential for obtaining the statistical properties of stars and constraining stellar evolutionary models, particularly when orbital parameters are well determined. In this study, we first carry out a data-cleaning step on a sample of LAMOST Medium-Resolution Spectroscopic Survey stars with a sufficient number of observations and perform an F 2 test, obtaining 7775 radial velocity variables. After removing false positives and crossmatching with variable and double-lined spectroscopic binary (SB2) catalogs, we exclude known astrophysical variables and SB2s, leaving 6106 SB1 candidates. We estimate initial periods using the Heck–Manfroid–Mersch method combined with Monte Carlo simulations and then fit each source with both an orbital model and a trend model, selecting between them via the Snedecor F- test of nested models. For orbital models, we accept the least- χ 2 solution if it satisfies F 2 < 3.1, s > 10, phase _ gap _ max < 0.3, σ v / K < 0.25 and passes the Markov Chain Monte Carlo–based robustness tests. For trend cases, we discard zeroth-order fits and require F 2 < 3.1. In total, we obtain 623 accepted solutions, of which 337 SB1s are new relative to existing catalogs.

The Astrophysical Journal Supplement SeriesVol. 282(2)
Openalex Percentile: Top 69%
Stellar, planetary, and galactic studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.