Radial velocity (RV) is among the most fundamental physical quantities obtainable from stellar spectra and is rather important in the analysis of time-domain phenomena. LAMOST Medium-resolution Survey (MRS) DR7 contains five million single-exposure stellar spectra with spectral resolution R ∼ 7500. However, the temporal variation of the RV zero-points (RVZPs) of the MRS, which makes the RVs from multiple epochs inconsistent, has not been addressed. In this paper, we measure the RVs of 3.8 million single-exposure spectra (for 0.6 million stars) with signal-to-noise ratios (S/N) higher than 5 based on the cross-correlation function method, and propose a robust method to self-consistently determine the RVZPs exposure by exposure for each spectrograph with the help of Gaia DR2 RVs. Such RVZPs are estimated for 3.6 million RVs and can reach a mean precision of ∼0.38 km s⁻¹. The result of the temporal variation of RVZPs indicates that our algorithm is efficient and necessary before we use the absolute RVs to perform time-domain analyses. Validating the results with APOGEE DR16 shows that our absolute RVs can reach an overall precision of 0.84/0.80 km s⁻¹ in the blue/red arm at 50 < S/N < 100 and of 1.26/1.99 km s⁻¹ at 5 < S/N < 10. The cumulative distribution function of the standard deviations of multiple RVs (N _obs ≥ 8) for 678 standard stars reaches 0.45/0.54, 1.07/1.39, and 1.45/1.86 km s⁻¹ in the blue/red arm at the 50%, 90%, and 95% levels, respectively. Catalogs of the RVs, RVZPs, and selected candidate RV standard stars are available at https://github.com/hypergravity/paperdata.

Astronomy & Astrophysics (A&A) is an international journal which publishes papers on all aspects of astronomy and astrophysics

Phase II of the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST)-Kepler/K2 survey (LK–MRS), initiated in 2018, aims at collecting medium-resolution spectra (R ∼ 7500; hereafter MRS) for more than 50,000 stars with multiple visits (∼60 epochs) over a period of 5 yr (2018 September to 2023 June). We selected 20 footprints distributed across the Kepler field and six K2 campaigns, with each plate containing a number of stars ranging from ∼2000 to ∼3000. During the first year of observations, the LK–MRS has already visited 13 plates 223 times over 40 individual nights, and collected ∼280,000 and ∼369,000 high-quality spectra in the blue and red wavelength ranges, respectively. The atmospheric parameters and radial velocities for ∼259,000 spectra of 21,053 targets were successfully calculated by the LAMOST stellar parameter pipeline. The internal uncertainties for the effective temperature, surface gravity, metallicity, and radial velocity are found to be 100 K, 0.15 dex, 0.09 dex, and 1.00 km s⁻¹, respectively, when derived from a medium-resolution LAMOST spectrum with a signal-to-noise ratio (S/N) in the g band of 10. All of the uncertainties decrease as S/N increases, but they stabilize for S/N > 100. We found 14,997, 20,091, and 1514 stars in common with the targets from the LAMOST low-resolution survey (LRS), Gaia, and the Apache Point Observatory Galactic Evolution Experiment (APOGEE), respectively, corresponding to fractions of ∼70%, ∼95%, and ∼7.2%. In general, the parameters derived from LK–MRS spectra are consistent with those obtained from the LRS and APOGEE spectra, but the scatter increases as the surface gravity decreases when comparing with the measurements from APOGEE. A large discrepancy is found with the Gaia values of the effective temperature. Comparisons of the radial velocities of LK–MRS to Gaia and LK–MRS to APOGEE nearly follow a Gaussian distribution with means of μ ∼ 1.10 and 0.73 km s⁻¹, respectively. We expect that the results from the LK–MRS spectra will shed new light on binary stars, asteroseismology, stellar activity, and other research fields.

The LAMOST-Kepler (LK-) project was initiated to use the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) to make spectroscopic follow-up observations for the targets in the field of the Kepler mission. The Kepler field is divided into 14 subfields that are adapted to the LAMOST circular field with a diameter of 5°. During the regular survey phase of LAMOST, the LK-project took data from 2012 June to 2017 June and covered all 14 subfields at least twice. In particular, we describe in this paper the second Data Release of the LK-project, including all spectra acquired through 2015 May–2017 June together with the first round observations of the LK-project from 2012 June to 2014 September. The LK-project now counts 227,870 spectra of 156,390 stars, among which we have derived atmospheric parameters ( , T _eff, and [Fe/H]) and heliocentric radial velocity for 173,971 spectra of 126,172 stars. These parameters were obtained with the most recent version of the LAMOST Stellar Parameter Pipeline v 2.9.7. Nearly one half, namely 76,283 targets, are observed both by the LAMOST and Kepler telescopes. These spectra, establishing a large spectroscopy library, will be useful for the entire astronomical community, particularly for planetary science and stellar variability on Kepler targets.

We developed a convolutional neural network model to distinguish the double-lined spectroscopic binaries (SB2s) from others based on single-exposure medium-resolution spectra (R ∼ 7500). The training set consists of a large set of mock spectra of single stars and binaries synthesized based on the MIST stellar evolutionary model and ATLAS9 atmospheric model. Our model reaches a novel theoretic false-positive rate by adding a proper penalty on the negative sample (e.g., 0.12% and 0.16% for the blue/red arm when the penalty parameter Λ = 16). Tests show that the performance is as expected and favors FGK-type main-sequence (MS) binaries with high mass ratio (q ≥ 0.7) and large radial velocity separation (Δv ≥ 50 km s⁻¹). Although the real false-positive rate cannot be estimated reliably, validating on eclipsing binaries identified from Kepler light curves indicates that our model predicts low binary probabilities at eclipsing phases (0, 0.5, and 1.0) as expected. The color–magnitude diagram also helps illustrate its feasibility and capability of identifying FGK MS binaries from spectra. We conclude that this model is reasonably reliable and can provide an automatic approach to identify SB2s with period ≲10 days. This work yields a catalog of binary probabilities for over 5 million spectra of 1 million sources from the LAMOST medium-resolution survey (MRS) and a catalog of 2198 SB2 candidates whose physical properties will be analyzed in a follow-up paper. Data products are made publicly available online, as well as our Github website.