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Table · dataset · 2025

Spectroscopic binaries from LAMOST MRS DR9

Listed in IVOA Registry (Virtual Observatory)

We utilize a hybrid approach that integrates the traditional cross-correlation function (CCF) and machine learning to detect spectroscopic multiple star systems, specifically focusing on double-line spectroscopic binaries (SB2s).

Description

Based on the ninth data release (DR9) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), which includes a medium-resolution survey (MRS) containing 29,920,588 spectra, we identify 27,164 double-line and 3124 triple-line spectra, corresponding to 7096 SB2 candidates and 1903 triple-line spectroscopic binary (SB3) candidates, respectively, representing about 1% of the selected data set from LAMOST-MRS DR9.

Notably, 70.1% of the SB2 candidates and 89.6% of the SB3 candidates are newly identified. Compared to using only the traditional CCF technique, our method significantly improves the efficiency of detecting SB2s, saving time on visual inspections by a factor of 4.

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Catalogue records · 2

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Stated by source
Optical
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Astronomical sciences 71%
Provenance · 1 source records, 9 field assertions
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IVOA Registry (Virtual Observatory)ivo://cds.vizier/j/apjs/276/1111 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:astronomymapping · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[modality].ivoa_waveband:opticalsource · IVOA Registryconnector:ivoa_registry@1.0.0
descriptionsource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_description
license_textsource · IVOA Registryconnector:ivoa_registry@1.0.0
publication_datesource · IVOA Registryconnector:ivoa_registry@1.0.0
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updated_datesource · IVOA Registryconnector:ivoa_registry@1.0.0