Fang Zuo

We present a clean, homogeneous, and AI-ready stellar dataset assembled from LAMOST DR11 low-resolution spectra, tailored for data-driven models. This dataset contains 111,417 high-quality spectra for 91,542 AFGK-type stars, with stellar labels such as T _eff , log g , [Fe/H], [ α /M], stellar mass, and absolute G -band magnitude. It reaches a metallicity of [Fe/H] ∼ −3.8 dex, significantly below the LAMOST pipeline’s lower limit of −2.5 dex, and covers T _eff ≈ 3800–13,000 K, log g ≈ 0.1–5.0 dex, [ α /M] from −0.4 to 0.6 dex, mass from 0.4 to 6.0 M _⊙ , and M _G from −4.0 to 8.0 mag. Self-consistency validation using neural networks confirms the reliability of stellar labels and shows only minor differences between the adopted and network-predicted parameters. By combining this dataset with the 5105 M-type stars from our previous work, we trained a neural network model and applied it to the complete set of LAMOST DR12 AFGKM-type spectra, obtaining stellar parameters for 9 million spectra. The model yields precise estimates that agree well with APOGEE and Gaia estimates, with uncertainties of about 55 K in T _eff , 0.10 dex in log g , 0.07 dex in [Fe/H], 0.02 dex in [ α /M], a relative error of about 4.2% in stellar mass, and 0.13 mag in M _G . Distances inferred from M _G show a relative error of 7.4%. This work delivers a public, AI-ready dataset and a value-added catalog for LAMOST DR12, extends investigations of very metal-poor stars toward lower metallicities, and supports direct, efficient estimation of stellar parameters, mass, and distance from large spectroscopic surveys.

To enhance the efficiency, scalability, and cross-survey applicability of stellar parameter inference in large spectroscopic datasets, we present a modular, parallelized Python framework with automated error estimation, built on the LAMOST Atmospheric Parameter Pipeline (LASP) originally implemented in IDL. Rather than a direct code translation, this framework refactors LASP with two complementary modules: LASP-CurveFit, a new implementation of the LASP fitting procedure that runs on a CPU, preserving legacy logic while improving data I/O and multithreaded execution efficiency; and LASP-Adam-GPU, a GPU-accelerated method that introduces grouped optimization by constructing a joint residual function over multiple observed and model spectra, enabling high-throughput parameter inference across tens of millions of spectra. Applied to 10 million LAMOST spectra, the framework reduces runtime from 84 to 48 hr on the same CPU platform and to 7 hr on an NVIDIA A100 GPU, while producing results consistent with those from the original pipeline. The inferred errors agree well with the parameter variations from repeat observations of the same target (excluding radial velocities), while the official empirical errors used in LASP are more conservative. When applied to DESI DR1, our effective temperatures and surface gravities agree better with APOGEE than those from the DESI pipeline, particularly for cool giants, while the latter performs slightly better in radial velocity and metallicity. These results suggest that the framework delivers reliable accuracy, efficiency, and transferability, offering a practical approach to parameter inference in large spectroscopic surveys. The code and DESI-based catalog are available via DOI: 10.12149/101679 and DOI: 10.12149/101675 , respectively.

In this research, we conducted systematic photometric, spectroscopic, and theoretical modeling analyses of two δ Scuti stars—KIC 12602250 and KIC 5768203—that pulsate only in radial modes. We collected their relevant photometric and spectroscopic parameters from multiple catalogs and estimated the absolute luminosities of both stars. Using high-precision time-series data from Kepler and TESS, we performed in-depth analysis of the periodic modulation in pulsation frequency phases, successfully determining the orbital periods and companion mass distribution ranges for these binary systems. Additionally, we thoroughly investigated the temporal evolution characteristics of pulsation periods and amplitudes. Based on calculations using Modules for Experiments in Stellar Astrophysics stellar evolution models, we determined that KIC 12602250 has a mass of M = 1.6 6 − 0.07 + 0.05 M ⊙ with metallicity Z = 0.03 9 − 0.010 + 0.018 and is currently in the main-sequence evolutionary stage. For KIC 5768203, we derived precise parameters through rigorous constraints: mass M = 2.09 ± 0.01M _⊙, metallicity Z = 0.024 ± 0.003, and radius R = 3.19 ± 0.01R _⊙. Theoretical models reveal that this star has already crossed the first main-sequence turn-off point and entered the late-main-sequence evolutionary stage. Through comparative studies with typical High Amplitude δ Scuti stars, we believe that the primary reason for the low radial pulsation amplitudes in these two stars likely stems from their specific evolutionary states.

The discrepancies between theoretical and observed spectra, and the systematic differences between various spectroscopic parameter estimates, complicate the determination of atmospheric parameters of M-type stars. In this work, we present an empirical sample of 5105 M-type star spectra with homogeneous atmospheric parameter labels through stellar-label transfer and sample cleaning. We addressed systematic discrepancies in spectroscopic parameter estimates by adopting recent results for Gaia EDR3 stars as a reference standard. Then, we used a density-based spatial clustering of applications with noise to remove unreliable samples in each subgrid of parameters. To confirm the reliability of the stellar labels, a five-layer neural network was utilized, randomly partitioning the samples into training and testing sets. The standard deviations between the predicted and actual values in the testing set are 14 K for T _eff, 0.06 dex for logg, and 0.05 dex for [M/H], respectively. In addition, we conducted an internal cross validation to enhance validation and obtained precisions of 11 K, 0.05 dex, and 0.05 dex for T _eff, logg, and [M/H], respectively. A grid of 1365 high-signal-to-noise ratio (S/N) spectra and their labels, selected from the empirical sample, was utilized in the stellar parameter pipeline for M-type stars of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), producing an almost seamless Kiel distribution diagram for LAMOST DR10 and DR11 data. The atmospheric parameters for M-type stars from LAMOST DR11 show improved precision compared to the data from DR9, with improvements (for spectra with S/N higher than 10) from 118 to 67 K in T _eff, 0.2 to 0.07 dex in logg, and 0.29 to 0.14 dex in [M/H].

The discrepancies between theoretical and observed spectra, and the systematic differences between various spectroscopic parameter estimates, complicate the determination of atmospheric parameters of M-type stars. In this work, we present an empirical sample of 5105 M-type star spectra with homogeneous atmospheric parameter labels through stellar-label transfer and sample cleaning. We addressed systematic discrepancies in spectroscopic parameter estimates by adopting recent results for Gaia EDR3 stars as a reference standard. Then, we used a density-based spatial clustering of applications with noise to remove unreliable samples in each subgrid of parameters. To confirm the reliability of the stellar labels, a 5-layer neural network was utilized, randomly partitioning the samples into training and testing sets. The standard deviations between the predicted and actual values in the testing set are 14 K for Teff , 0.06 dex for log g, and 0.05 dex for [M/H], respectively. In addition, we conducted an internal cross-validation to enhance validation and obtained precisions of 11 K, 0.05 dex, and 0.05 dex for Teff , log g, and [M/H], respectively. A grid of 1365 high Signal-to-Noise ratio (S/N) spectra and their labels, selected from the empirical sample, was utilized in the stellar parameter pipeline for M-Type stars (LASPM) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), producing an almost seamless Kiel distribution diagram for LAMOST DR10 and DR11 data. The atmospheric parameters for M-type stars from LAMOST DR11 show improved precision compared to the data from DR9, with improvements (for spectra with S/N higher than 10) from 118 to 67 K in Teff , 0.2 to 0.07 dex in log g, and 0.29 to 0.14 dex in [M/H].

In Data Release 9 of LAMOST, we present measurements of v sin i for a total of 121,698 stars measured using the Medium Resolution Spectrograph (MRS) and 80,108 stars using the Low Resolution Spectrograph (LRS). These values were obtained through a χ ² minimization process, comparing LAMOST spectra with corresponding grids of synthetically broadened spectra. Due to the resolution and the spectral range of LAMOST, v sin i measurements are limited to stars with an effective temperature (T _eff) ranging from 5000 to 8500 K for MRS and 7000 to 9000 K for LRS. The detectable v sin i for MRS is set between 27 and 350 km s⁻¹, and for LRS between 110 and 350 km s⁻¹. This limitation is because the convolved reference spectra become less informative beyond 350 km s⁻¹. The intrinsic precision of v sin i, determined from multiepoch observations, is approximately ∼4.0 km s⁻¹ for MRS and ∼10.0 km s⁻¹ for LRS at a signal-to-noise ratio greater than 50. Our v sin i values show consistency with those from APOGEE17, displaying a scatter of 8.79 km s⁻¹. They are also in agreement with measurements from the Gaia DR3 and Sun et al. catalogs. An observed trend in LAMOST MRS data is the decrease in v sin i with a drop in T _eff, particularly transiting around 7000 K for dwarfs and 6500 K for giants, primarily observed in stars with near-solar abundances.

In Data Release 9 of LAMOST, we present measurements of v sin i for a total of 121,698 stars measured using the Medium Resolution Spectrograph (MRS) and 80,108 stars using the Low Resolution Spectrograph (LRS). These values were obtained through a chi^2 minimisation process, comparing LAMOST spectra with corresponding grids of synthetically broadened spectra. Due to the resolution and the spectral range of LAMOST, v sin i measurements are limited to stars with effective temperature (Teff) ranging from 5000 K to 8500 K for MRS and 7000 K to 9000 K for LRS. The detectable v sin i for MRS is set between 27 km/s and 350 km/s , and for LRS between 110 km/s and 350 km/s, This limitation is because the convolved reference spectra become less informative beyond 350 km/s. The intrinsic precisions of v sin i , determined from multi-epoch observations, is approximately 4.0 km/s for MRS and 10.0 km/s for LRS at signal-to-noise ratio (S/N) greater than 50. Our v sin i values show consistence with those from APOGEE17, displaying a scatter of 8.79 km/s. They are also in agreement with measurements from the Gaia DR3 and SUN catalogs. An observed trend in LAMOST MRS data is the decrease in v sin i with dropping Teff, particularly transiting around 7000 K for dwarfs and 6500 K for giants, primarily observed in stars with near-solar abundances.

Based on luminosity contributions, we develop a spectroscopic modelling method to derive atmospheric parameters of component stars in binary systems. The method is designed for those spectra of binaries which show double-lined features due to the radial velocities differences between the component stars. We first derive the orbital parameters and the stellar radii by solving the light and radial velocity curves. Then the luminosity contributions in different phases can be calculated. The synthesised double-lined spectra model is constructed by superposing theoretical single-star spectra according to the luminosity contributions. Finally, we derive the atmospheric parameters of each component star by the model fitting method. For multi-epoch double-lined spectra observed by the Large sky Area Multi-Object Spectroscopic Telescope (LAMOST) Medium Resolution Survey ($R \sim 7500$), our method gives robust results for detached eclipsing binary systems observed in different orbital phases. Furthermore, this method can also be applied to other spectroscopic data with different resolutions as long as the systems are detached eclipsing binaries with nearly spherical stars.

We identify 20 F-type Herbig stars and provide a list of 22 pre-main-sequence candidates from LAMOST DR8. The effective temperature, distance, extinction, stellar luminosity, mass, age, and radius are derived for each Herbig star based on optical spectra, photometry, Gaia EDR3 parallaxes, and pre-main-sequence evolutionary tracks. According to spectral energy distribution, 19 F-type Herbig stars belong to Class II YSOs, and one belongs to the flat-spectrum class. Four have Spitzer IRS spectra, of which three show extremely weak polycyclic aromatic hydrocarbon emissions, and three with both amorphous and crystalline silicate emissions share similar parameters and are at the same evolutionary stage. We detect a solar-nearby outbursting EXor Herbig star J034344.48+314309.3, a possible precursor of a Herbig Ae star. Intense emission lines of H i, He i, O i, Na i, and Ca ii originating from the rapid accretion during the outbursts are detected in its optical spectra, and silicate emission features are detected in its infrared spectrum. We also conduct a statistical analysis of the disk properties of all known Herbig stars using the defined infrared spectral indices ( α J − K S and α K S − W 3 ). The proportion of Herbig stars with moderate infrared excesses decreases as effective temperature increases. The majority of the precursors (F, G, or K type) have moderate infrared excesses. Hotter Herbig stars tend to have a larger proportion with large infrared excesses. The trends may be due to the fact that hotter stars have larger areas of re-emitting dust, although there is some scatter due to the particularities of each disk.

The LAMOST II survey began in the fall of 2018, and LAMOST formally released the obtained medium-resolution spectra (MRS) as well as catalogs of stellar parameters and radial velocities (RV) derived from the MRS in the seventh LAMOST data release (DR7). Compared with the RVs and parameters from high-resolution SDSS14/APOGEE spectra, nearly no RV discrepancy was found, with only dispersion around one km s⁻¹. The T _eff of MRS was 27.79 K systematically lower than that of APOGEE, and the 1σ difference was approximately 60.40 K. For metallicity, the [Fe/H] of the MRS was 0.11 dex poorer than that of APOGEE, with a dispersion of 0.07 dex. More apparently, the offset of log g was 0.14 dex, and the scatter was 0.23 dex. The gravities of APOGEE have been corrected through seismological data. Similarly, in this study, we tried to calibrate LAMOST MRS log g with the Kepler data for red clump stars and red giant branch stars based on two fitted calibration relations. In addition, we found log g of a small fraction late-K type giants mistakenly measured as dwarfs, and vice versa, on the HR diagram generated with LAMOST T _eff and Gaia absolute magnitudes. This was because the MRS parameters were measured from blue band spectra only. The measurements of log g for late-K stars can be significantly improved by adding red spectra.