We present the determination of stellar parameters and individual elemental abundances for 6 million stars from $\sim$8 million low-resolution ($R\sim1800$) spectra from LAMOST DR5. This is based on a modeling approach that we dub $The$ $Data$--$Driven$ $Payne$ ($DD$--$Payne$), which inherits essential ingredients from both {\it The Payne} \citep{Ting2019} and $The$ $Cannon$ \citep{Ness2015}. It is a data-driven model that incorporates constraints from theoretical spectral models to ensure the derived abundance estimates are physically sensible. Stars in LAMOST DR5 that are in common with either GALAH DR2 or APOGEE DR14 are used to train a model that delivers stellar parameters ($T_{\rm eff}$, $\log g$, $V_{\rm mic}$) and abundances for 16 elements (C, N, O, Na, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, and Ba) when applied to LAMOST spectra. Cross-validation and repeat observations suggest that, for ${\rm S/N}_{\rm pix}\ge 50$, the typical internal abundance precision is 0.03--0.1\,dex for the majority of these elements, with 0.2--0.3\,dex for Cu and Ba, and the internal precision of $T_{\rm eff}$ and $\log g$ is better than 30\,K and 0.07\,dex, respectively. Abundance systematics at the $\sim$0.1\,dex level are present in these estimates, but are inherited from the high-resolution surveys' training labels. For some elements, GALAH provides more robust training labels, for others, APOGEE. We provide flags to guide the quality of the label determination and to identify binary/multiple stars in LAMOST DR5. The abundance catalogs are publicly accessible via \href{url}{http://dr5.lamost.org/doc/vac}.
We have studied the zero-point offset of Gaia early Data Release 3 (EDR3) parallaxes based on a sample of 0.3 million giant stars built from the LAMOST data with distance accuracy better than 8.5\%. The official parallax zero-point corrections largely reduce the global offset in the Gaia EDR3 parallaxes: the global parallax offsets are $-$27.9 $μ$as and $-$26.5 $μ$as (before correction) and $+$2.6 $μ$as and $+$2.9 $μ$as (after correction) for the five- and six-parameter solutions, respectively. The bias of the raw parallax measurements is significantly dependent on the $G$ magnitudes, spectral…
The LAMOST survey has acquired low-resolution spectra (R=1,800) for 5 million stars across the Milky Way, far more than any current stellar survey at a corresponding or higher spectral resolution. It is often assumed that only very few elemental abundances can be measured from such low-resolution spectra, limiting their utility for Galactic archaeology studies. However, Ting et al. (2017) used ab initio models to argue that low-resolution spectra should enable precision measurements of many elemental abundances, at least in theory. Here we verify this claim in practice by measuring the relativ…
I combine duplicate spectroscopic stellar parameter estimates in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 6 Low Resolution Spectral Survey A, F, G, and K Type stellar parameter catalog. Combining repeat measurements results in a factor of two improvement in the precision of the spectroscopic stellar parameter estimates. Moreover, this trivializes the process of performing coordinate-based cross-matching with other catalogs. Similarly, I combine duplicate stellar abundance estimates for the Xiang et al. catalog which was produced using LAMOST Data Rele…
Large stellar surveys are revealing the chemodynamical structure of the Galaxy across a vast spatial extent. However, the many millions of low-resolution spectra observed to date are yet to be fully exploited. We employ The Cannon, a data-driven approach to estimating abundances, to obtain detailed abundances from low-resolution (R = 1800) LAMOST spectra, using the GALAH survey as our reference. We deliver five (for dwarfs) or six (for giants) estimated abundances representing five different nucleosynthetic channels, for 3.9 million stars, to a precision of 0.05 - 0.23 dex. Using wide binary p…
The fundamental stellar atmospheric parameters T_eff and log g and 13 chemical abundances are derived for medium-resolution spectroscopy from LAMOST Medium-Resolution Survey (MRS) data sets with a deep-learning method. The neural networks we designed, named as SPCANet, precisely map LAMOST MRS spectra to stellar parameters and chemical abundances. The stellar labels derived by SPCANet are with precisions of 119 K for T_eff and 0.17 dex for log g. The abundance precision of 11 elements including [C/H], [N/H], [O/H], [Mg/H], [Al/H], [Si/H], [S/H], [Ca/H], [Ti/H], [Cr/H], [Fe/H], and [Ni/H] are 0…
Carbon stars, enhanced in carbon and neutron-capture elements, provide wealth of information about the nucleosynthesis history of the Galaxy. In this work, we present the first ever detailed abundance analysis of carbon star LAMOSTJ091608.81+230734.6 and a detailed abundance analysis of neutron-capture elements for the object LAMOSTJ151003.74+305407.3. Updates on the abundances of elements C, O, Mg, Ca, Cr, Mn and Ni for LAMOSTJ151003.74+305407.3 are also presented. Our analysis is based on high resolution spectra obtained using Hanle Echelle Spectrograph (HESP) attached to the Himalayan Chand…
We present the results of the high-resolution (R$\sim$60,000) spectroscopic analysis of the star LAMOSTJ045019.27+394758.7 (hereafter J045) from the list of carbon stars of LAMOST DR2. From our analysis, we find that J045 does not exhibit the spectral characteristics of carbon stars. It is found to be a metal-poor ( [Fe/H] = $-$1.05) giant that shows very unusual elemental abundances, particularly for N, Na, V, and Zn. J045 shows $α$-elements (Mg, Si, Ca) with near-solar values ($<$[$α$/Fe]$>$ = 0.09) in contrast to Galactic stars that show [$α$/Fe] in the range 0.2 to 0.3 dex. In J045, Sc and…
We present a new analysis of the LAMOST DR1 survey spectral database performed with the code SP_Ace, which provides the derived stellar parameters T$_{\rm eff}$, log (g), [Fe/H], and [$α$/Fe] for 1,097,231 stellar objects. We tested the reliability of our results by comparing them to reference results from high spectral resolution surveys. The expected errors can be summarized as $\sim$120 K in T$_{\rm eff}$, $\sim$0.2 in log (g), $\sim$0.15 dex in [Fe/H], and $\sim$0.1 dex in [$α$/Fe] for spectra with S/N$>$40, with some differences between dwarf and giant stars. SP_Ace provides error estimat…
We report the discovery of an extremely metal-poor (EMP) giant, LAMOST J110901.22+075441.8, which exhibits large excess of r-process elements with [Eu/Fe] ~ +1.16. The star is one of the newly discovered EMP stars identified from LAMOST low-resolution spectroscopic survey and the high-resolution follow-up observation with the Subaru Telescope. Stellar parameters and elemental abundances have been determined from the Subaru spectrum. Accurate abundances for a total of 23 elements including 11 neutron-capture elements from Sr through Dy have been derived for LAMOST J110901.22+075441.8. The abund…
We measure carbon and nitrogen abundances to $\lesssim$ 0.1 dex for 450,000 giant stars from their low-resolution (R$\sim$1800) LAMOST DR2 survey spectra. We use these [C/M] and [N/M] measurements, together with empirical relations based on the APOKASC sample, to infer stellar masses and implied ages for 230,000 of these objects to 0.08 dex and 0.2 dex respectively. We use The Cannon, a data-driven approach to spectral modeling, to construct a predictive model for LAMOST spectra. Our reference set comprises 8125 stars observed in common between the APOGEE and LAMOST surveys, taking seven APOGE…
The LAMOST Medium-Resolution Spectroscopic Survey (LAMOST-MRS) provides an unprecedented opportunity for detecting multi-line spectroscopic systems. Based on the method of Cross-Correlation Function (CCF) and successive derivatives, we search for spectroscopic binaries and triples and derive their radial velocities (RVs) from the LAMOST-MRS spectra. A Monte-Carlo simulation is adopted to estimate the RV uncertainties. After examining over 1.3 million LAMOST DR7 MRS blue arm spectra, we obtain 3,133 spectroscopic binary (SB) and 132 spectroscopic triple (ST) candidates, which account for 1.2% o…
We present estimates of stellar age and mass for 0.93 million Galactic disk main sequence turn-off and sub-giant stars from the LAMOST Galactic Spectroscopic Surveys. The ages and masses are determined by matching with stellar isochrones using Bayesian algorithm, utilizing effective temperature $T_{\rm eff}$, absolute magnitude ${\rm M}_V$, metallicity [Fe/H] and $α$-element to iron abundance ratio [$α$/Fe] deduced from the LAMOST spectra. Extensive examinations suggest the age and mass estimates are robust. The overall sample stars have a median error of 34 per cent for the age estimates, and…
The LAMOST survey has provided 9 million spectra in its Data Release 5 (DR5) at R$\sim$1800. Extracting precise stellar labels is crucial for such a large sample. In this paper, we report the implementation of the Stellar LAbel Machine (SLAM), which is a data-driven method based on Support Vector Regression (SVR), a robust non-linear regression technique. Thanks to the capability to model highly non-linear problems with SVR, SLAM generally can derive stellar labels over a wide range of spectral types. This gives it a unique capability compared to other popular data-driven methods. To illustrat…
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), also known as the Guoshoujing Telescope, is a major national scientific facility for astronomical research located in Xinglong, China. Beginning with a pilot survey in 2011, LAMOST has been surveying the night sky for more than 10 years. The LAMOST survey covers various objects in the Universe, from normal stars to peculiar ones, from the Milky Way to other galaxies, and from stellar black holes and their companions to quasars that ignite ancient galaxies. Until the latest data release 8, the LAMOST survey has released spe…
Standard stellar evolution model predicts a severe depletion of lithium (Li) abundance during the first dredge up process (FDU). Yet a small fraction of giant stars are still found to preserve a considerable amount of Li in their atmospheres after the FDU. Those giants are usually identified as Li-rich by a widely used criterion, A(Li) > 1.5 dex. A large number of works dedicated to searching for investigating this minority of the giant family, and the amount of Li-rich giants, has been largely expanded on, especially in the era of big data. In this paper, we present a catalog of Li-rich giant…
Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) acquired tens of millions of low-resolution stellar spectra. The large amount of the spectra result in the urgency to explore automatic atmospheric parameter estimation methods. There are lots of LAMOST spectra with low signal-to-noise ratios (SNR), which result in a sharp degradation on the accuracy of their estimations. Therefore, it is necessary to explore better estimation methods for low-SNR spectra. This paper proposed a neural network-based scheme to deliver atmospheric parameters, LASSO-MLPNet. Firstly, we adopt a polyn…
We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution, wavelength coverage) of the LAMOST and MUSE instruments, we adopt the Data-Driven Payne (DD-Payne) model used on LAMOST observations and apply it to stars observed in MUSE fields. Remarkably, in spite of instrumental differences, according to the cross-validation of 27 LAMOST-MUSE common stars, we are able to determine stellar labels with precision better than 75K in $T_{\rm eff}$, 0.15 d…
Accurate determination of stellar atmospheric parameters and elemental abundances is crucial for Galactic archeology via large-scale spectroscopic surveys. In this paper, we estimate stellar atmospheric parameters -- effective temperature T_{\rm eff}, surface gravity log g and metallicity [Fe/H], absolute magnitudes M_V and M_{Ks}, α-element to metal (and iron) abundance ratio [α/M] (and [α/Fe]), as well as carbon and nitrogen abundances [C/H] and [N/H] from the LAMOST spectra with amultivariate regressionmethod based on kernel-based principal component analysis, using stars in common with oth…
A small fraction of giants possess photospheric lithium(Li) abundance higher than the value predicted by the standard stellar evolution models, and the detailed mechanisms of Li enhancement are complicated and lack a definite conclusion. In order to better understand the Li enhancement behaviors, a large and homogeneous Li-rich giants sample is needed. In this study, we designed a modified convolutional neural network model called Coord-DenseNet to determine the A(Li) of Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) low-resolution survey (LRS) giant spectra. The precision …
We present a detailed analysis of the selection function of the LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC). LSS-GAC was designed to obtain low resolution optical spectra for a sample of more than 3 million stars in the Galactic anti-centre. The second release of value-added catalogues of the LSS-GAC (LSS-GAC DR2) contains stellar parameters, including radial velocity, atmospheric parameters, elemental abundances and absolute magnitudes deduced from 1.8 million spectra of 1.4 million unique stars targeted by the LSS-GAC between 2011 and 2014. For many studies using this d…
Basing on the large volume \textit{Gaia} Early Data Release 3 and LAMOST Data Release 5 data, we estimate the bias-corrected binary fractions of the field late G and early K dwarfs. A stellar locus outlier method is used in this work, which works well for binaries of various periods and inclination angles with single epoch data. With a well-selected, distance-limited sample of about 90 thousand GK dwarfs covering wide stellar chemical abundances, it enables us to explore the binary fraction variations with different stellar populations. The average binary fraction is 0.42$\pm$0.01 for the whol…
We present a catalog of stellar age and mass estimates for a sample of 640\,986 red giant branch (RGB) stars of the Galactic disk from the LAMOST Galactic Spectroscopic Survey (DR4). The RGB stars are distinguished from the red clump stars utilizing period spacing derived from the spectra with a machine learning method based on kernel principal component analysis (KPCA). Cross-validation suggests our method is capable of distinguishing RC from RGB stars with only 2 per cent contamination rate for stars with signal-to-noise ratio (SNR) higher than 50. The age and mass of these RGB stars are det…
The correlation between host star iron abundance and the exoplanet occurrence rate is well-established and arrived at in several studies. Similar correlations may be present for the most abundant elements, such as carbon and oxygen, which also control the dust chemistry of the protoplanetary disk. In this paper, using a large number of stars in the Kepler field observed by the LAMOST survey, it has been possible to estimate the planet occurrence rate with respect to the host star carbon abundance. Carbon abundances are derived using synthetic spectra fit of the CH G-band region in the LAMOST s…
We present homogeneous abundance analysis of over 20 elements for 385 very metal-poor (VMP) stars based on the LAMOST survey and follow-up observations with the Subaru Telescope. It is the largest high-resolution VMP sample (including 363 new objects) studied by a single program, and the first attempt to accurately determine evolutionary stages for such a large sample based on Gaia parallaxes. The sample covers a wide metallicity range from [Fe/H]=-1.7 down to [Fe/H]=-4.3, including over 110 objects with [Fe/H]<-3.0. The expanded coverage in evolutionary status makes it possible to define abun…
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. The LAMOST Medium-Resolution Survey (MRS) DR7 contains 5 million single-exposure stellar spectra at spectral resolution $R\sim7\,500$. However, the temporal variation of the RV zero-points (RVZPs) of the MRS survey, which makes the RVs from multiple epochs inconsistent, has not been addressed. In this paper, we measure the RVs of the 3.8 million single-exposure spectra (for 0.6 million stars) with signal-to-noise ratio (SNR) hi…
RV variable stars are important in astrophysics. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic survey has provided ~ 6.5 million stellar spectra in its Data Release 4 (DR4). During the survey, ~ 4.7 million unique sources were targeted and ~ 1 million stars observed repeatedly. The probabilities of stars being RV variables are estimated by comparing the observed radial velocity variations with the simulated ones. We build a catalog of 80,702 RV variable candidates with probability greater than 0.60 by analyzing the duplicate-observed multi-epoch sources c…
Testing Chemical Tagging with LAMOST: Intrinsic Abundance Dispersion of Subgiant Stars in the Galactic Disk
National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台）；Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University（北京师范大学前沿交叉科学研究院）；School of Astronomy and Space Science, University of Chinese Academy of Sciences（中国科学院大学天文与空间科学学院）；Purple Mountain Observatory, Chinese Academy of Sciences（中国科学院紫金山天文台）；Department of Astronomy, Beijing Normal University（北京师范大学天文学系）
We report on the observations of two ultra metal-poor (UMP) stars with [Fe/H]~-4.0 including one new discovery. The two stars are studied in the on-going and quite efficient project to search for extremely metal-poor (EMP) stars with LAMOST and Subaru. Detailed abundances or upper limits of abundances have been derived for 15 elements from Li to Eu based on high-resolution spectra obtained with Subaru/HDS. The abundance patterns of both UMP stars are consistent with the "normal-population" among the low-metallicity stars. Both of the two program stars show carbon-enhancement without any excess…
Since September 2018, LAMOST starts a new 5-year medium-resolution spectroscopic survey (MRS) using bright/gray nights. We present the scientific goals of LAMOST-MRS and propose a near optimistic strategy of the survey. A complete footprint is also provided. Not only the regular medium-resolution survey, but also a time-domain spectroscopic survey is being conducted since 2018 and will be end in 2023. According to the detailed survey plan, we expect that LAMOST-MRS can observe about 2 million stellar spectra with ~7500 and limiting magnitude of around G=15 mag. Moreover, it will also provide a…
We download the LAMOST DR8 low resolution catalog 6,478,063 AFGK tpye stars and plot the figures of effective temperature, gravitational acceleration, and metal abundance. Some small and medium mass stars are evolved from pre-main sequence or main sequence stage to planetary nebula stage or white dwarf stage by the stellar evolution code \texttt{MESA}. We analyze the observed statistical data and model calculation results, and then obtain some basic conclusions preliminarily. Most red giant and asymptotic giant stars with log$g$ less than 0.85 have poor metal abundance. Most hot A type main-se…
Morphological and chemical structures of M33 are investigated with LAMOST DR7 survey. Physical parameters, extinction, chemical composition of He, N, O, Ne, S, Cl, Ar (where available), and radial velocities were determined for 110 nebulae (95 H\ii\ regions and 15 PNe) in M33. Among them, 8 PNe and 55 H\ii\ regions in M33 are newly discovered. We obtained the following O abundance gradients: $-$0.199$_{-0.030}^{+0.030}$ dex $R_{25}^{-1}$ (based on 95 H\ii\ regions), $-$0.124$_{-0.036}^{+0.036}$ dex $R_{25}^{-1}$ (based on 93 H\ii\ regions), and $-$0.207$_{-0.174}^{+0.160}$ dex $R_{25}^{-1}$ (b…
Mapping lithium evolution for evolved stars will provide restrictions and constraints on the fundamental stellar interior physical processes, which further shed light on our understanding of the theory of stellar structure and evolution. Based on a sample of 1,848 giants with known evolutionary phases and lithium abundances from the LAMOST-\kepler{} and LAMOST-\emph{K}2 fields, we construct mass-radius diagrams to characterize the evolutionary features of lithium. The stars at red giant branch (RGB) phase show natural depletion along with their stellar evolution, particularly, there is no obvi…
The Actinide-Boost Star LAMOST J122216.85-063345.2: A Detailed R-process Abundance Study with Gemini-S/GHOST
Korea Astronomy and Space Science Institute（韩国天文与空间科学研究院）；Chungnam National University（忠南国立大学）；NSF NOIRLab（美国国家光学红外天文实验室）；Tohoku University of Community Service and Science（东北公益文化大学）；Joint Institute for Nuclear Astrophysics– Center for the Evolution of the Elements (JINA-CEE)（核天体物理学联合研究所-元素演化中心）；University of Notre Dame（圣母大学）；Gemini Observatory/NSFʼs NOIRLab（Gemini 天文台/美国国家光学红外天文实验室）；Instituto de Astrofísica de La Plata, CONICET–UNLP, and Facultad de Ciencias Astronómicas y Geofísicas, UNLP（拉普拉塔天体物理研究所、阿根廷国家科学研究委员会-拉普拉塔国立大学及拉普拉塔国立大学天文与地球物理科学学院）
Tsinghua University-Ma Huateng Telescopes for Survey (TMTS), located at Xinglong Station of NAOC, has a field of view upto 18 deg^2. The TMTS has started to monitor the LAMOST sky areas since 2020, with the uninterrupted observations lasting for about 6 hours on average for each sky area and a cadence of about 1 minute. Here we introduce the data analysis and preliminary scientific results for the first-year observations, which covered 188 LAMOST plates ( about 1970 deg^2). These observations have generated over 4.9 million uninterrupted light curves, with at least 100 epochs for each of them.…
A General Framework for Radial Velocity Calibration in Low-Resolution Spectroscopic Surveys: Correcting Wavelength-Dependent and Global Systematics with Application to LAMOST DR9
Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University（北京师范大学天文与前沿科学研究院）；School of Physics and Astronomy, Beijing Normal University（北京师范大学物理与天文学院）；Yunnan University（云南大学）
We cross-matched 1.3 million white dwarf (WD) candidates from Gaia EDR3 with spectral data from LAMOST DR7 within 3 arcsec. Applying machine learning described in our previous work, we spectroscopically identified 6,190 WD objects after visual inspection, among which 1,496 targets were firstly confirmed. 32 detailed classes were adopted for them, including but not limited to DAB and DB+M. We estimated the atmospheric parameters for the DA and DB type WD using Levenberg-Marquardt least-squares algorithm (LM). Finally, a catalog of WD spectra from LAMOST was provided online.
We report on the elemental abundances of the carbon-enhanced metal-poor (CEMP) star J2217+2104 discovered by our metal-poor star survey with LAMOST and Subaru. This object is a red giant having extremely low Fe abundance ([Fe/H]=-4.0) and very large enhancement of C, N, and O with excesses of Na, Mg, Al, and Si. This star is a new example of a small group of such CEMP stars identified by previous studies. We find a very similar abundance pattern for O-Zn in this class of objects that shows enhancement of elements up to Si and normal abundance of Ca and Fe-group elements. Whereas the C/N ratio …
Identify ~20,000 Li-rich Giants in the LAMOST Low-Resolution Survey
Nanjing Institute of Astronomical Optics & Technology, Chinese Academy of Sciences（中国科学院南京天文光学技术研究所）；CAS Key Laboratory of Astronomical Optical & Technology, Nanjing Institute of Astronomical Optics & Technology（中国科学院南京天文光学技术研究所天文光学与技术重点实验室）；University of Chinese Academy of Sciences（中国科学院大学）；CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台光学天文重点实验室）；School of Astronomy and Space Science, University of Chinese Academy of Sciences（中国科学院大学天文学与空间科学学院）；School of Physics and Astronomy, Beijing Normal University（北京师范大学物理与天文学院）；Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University（北京师范大学天文与前沿科学研究院）
We developed a convolutional neural network (CNN) model to distinguish the double-lined spectroscopic binaries (SB2s) from others based on single exposure medium-resolution spectra ($R\sim 7,500$). 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 exp…
Based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) medium-resolution spectroscopic survey (MRS), we report the discovery of nine super Li-rich unevolved stars with A(Li) $>$ 3.8 dex. These objects show unusually high levels of lithium abundances up to three times higher than the meteoritic value of 3.3 dex, which indicates that they must have experienced a history of lithium enrichment. It is found that seven of our program stars are fast rotators with $vsini>9$ km\,s$^{-1}$, which suggests that the accretion of circumstellar matter may be the main contributor to t…
We present a catalog of 166 spectroscopically identified hot subdwarf stars from LAMOST DR1, 44 of which show the characteristics of cool companions in their optical spectra. Atmospheric parameters of 122 non-composite spectra subdwarf stars were measured by fitting the profiles of hydrogen (H) and helium (He) lines with synthetic spectra from non-LTE model atmospheres. Most of the sdB stars scatter near the Extreme Horizontal Branch in the $T_{\rm eff}-\log{g}$ diagram and two well defined groups can be outlined. A clustering of He-enriched sdO stars appears near $T_{\rm eff}=45\,000$ K and $…
We present a value-added catalog containing stellar parameters estimated from 7.10 million low-resolution spectra for 5.16 million unique stars with spectral signal-to-noise ratios (SNRs) higher than 10 obtained by the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) Galactic spectroscopic surveys. The catalog presents values of stellar atmospheric parameters (effective temperature $T_{\mathrm{eff}}$, surface gravity $\log g$, metallicity [Fe/H]/[M/H]), $α$-element to metal abundance ratio [$α$/M], carbon and nitrogen to iron abundance ratios [C/Fe] and [N/Fe] and 14 bands' a…
