The Gaia-ESO survey: New spectroscopic binaries in the Milky Way

The survey (GES) is a large public spectroscopic survey that acquired spectra for more than stars across all major components of the Milky Way. In addition to atmospheric parameters and stellar abundances that have been derived in previous papers of this series, the GES spectra allow us to detect spectroscopic binaries with one (SB1), two (SB2), or more (SB$n 3$) components. The present paper discusses the statistics of GES SB$n 2$ after analysing GIRAFFE HR10 and HR21 spectra, amounting to unique Milky Way field targets. Cross-correlation functions (CCFs) have been re-computed thanks to a dozen spectral masks probing a range of effective temperatures ($ kelvin < T_ eff kelvin $), surface gravities ($1.0 < g < 4.7$), and metallicities ($-2.6 < Fe H < 0.3$). By optimising the mask choice for a given spectrum, the newly computed, so-called (NArrow CRoss-correlation Experiment) CCFs are narrower and allow more stellar components to be unblended than standard masks. The (Detection Of Extrema) extremum-finding code then selects the individual components and provides their radial velocities. From the sample of HR10 and HR21 spectra corresponding to objects the present study leads to the detection of SB2, ten SB3 (three of them being tentative), and two tentative SB4. In particular, compared to our previous study, the CCFs allowed us to multiply the number of SB2 candidates by $ The colour-magnitude diagram reveals, as expected, the shifted location of the SB2 main sequence. A comparison between the SB identified in DR3 and the ones detected in the present work was performed and the complementarity of the two censuses is discussed. An application to the mass-ratio determination is presented, and the mass-ratio distribution of the GES SB2 is discussed. When accounting for the SB2 detection rate, an SB2 frequency of $ percent $ is derived within the present stellar sample of mainly FGK-type stars. As primary outliers identified within the GES data, SB$n$ spectra produce a wealth of information and useful constraints for the binary population synthesis studies.