arXiv subjects

Maosheng Xiang

Publications and source records attributed to Maosheng Xiang.

At least 19 recordsLinked to original sources

arXiv2026

PhDLspec: physical-prior embedded deep learning method for spectroscopic determination of stellar labels in high-dimensional parameter space

Unlocking the full physical information encoded in low-resolution spectra poses a significant challenge for astronomical survey analysis. Such a task demands modeling spectra and optimizing astrophysical parameters in high-dimensional space, as a consequence of line blending. Here we present PhDLspec -- a deep learning framework embedded with physical priors for stellar spectra modeling and analysis. By imposing differential spectra derived from ab initio stellar atmospheric model calculation on a transformer framework, PhDLspec can rigorously and precisely model stellar spectra by simultaneously taking into account more than 30 physical parameters, at a computational speed hundreds of times faster than ab initio model calculation. With such a flexible stellar modeling approach, PhDLspec can effectively derive ~30 stellar labels from a low-resolution spectrum using affordable optimization techniques. Application to LAMOST spectra (R~1800) yields stellar elemental abundances in good agreement with high-resolution spectroscopic surveys, following essential calibrations to correct systematic biases in elemental abundance estimates using wide binaries and reference high-resolution datasets. We provide a catalog of 25 elemental abundances for 116,611 subgiant stars with precise age estimates. The successful application of PhDLspec to LAMOST spectra for high-dimensional parameter determination sheds light on similar challenges faced by other surveys and disciplines.

astro-ph.GA↗

arXiv2026

A Tale of Two Dust Disks in Our Milky Way

Cosmic dust plays a vital role in stellar and galactic formation and evolution, but its three-dimensional structure in the Milky Way has remained unclear due to insufficient precise reddening and distance measurements. Although early studies typically adopted a single-disk model, we detect two distinct components at Galactocentric distances of 5-14 kpc, enabled by photometric, spectroscopic, and astrometric measurements of over 5 million stars. The thin dust disk's scale height increases radially from 60 to 200 pc, while the thick disk grows from 300 to 800 pc. For the first time, we find the thin and thick dust disk correlates spatially with molecular and atomic hydrogen disk, respectively. The thin, thick, and combined disks have scale lengths of 9.6+1.2-1.1 kpc, 4.2+0.4-0.3 kpc, and 6.6+0.3-0.3 kpc, respectively. The gas-to-dust ratio shows an exponential radial gradient, increasing from around 60 at 5 kpc to around 470 at 14 kpc. These findings provide new insights into dust morphology in the Galaxy and raise fundamental questions that require further investigation.

astro-ph.GA↗

arXiv2025

A large, long-lived, slowly-expanding superbubble across the Perseus Arm

Stellar feedback is a crucial mechanism in galactic evolution, as demonstrated by the widespread bubbles observed with JWST. In this study, we combine data from Gaia and LAMOST to obtain a sample of young O-B2 stars with full three-dimensional velocity information. Focusing on the largest known superbubble in the Milky Way, we identify groups of O-B2 stars at its periphery, exhibiting a transverse velocity of 25.8 km/s and an expansion velocity of 6.2 km/s. Using these velocities, we calculate a crossing time t_cross ~ 20 Myr and an expansion timescale t_expansion ~ 80 Myr. We estimate a survival timescale t_survival ~ 250 Myr and a supernova interval t_SN ~ 0.1 Myr. Together with the Galactic shear timescale t_shear ~ 30 Myr, these values satisfy t_SN < t_shear < t_survival. The energy and momentum from supernovae are sufficient to sustain the bubble's growth against ambient pressure. This indicates that repeated supernovae replenish energy faster than shear and turbulent distort the cavity. Our analysis classifies the Giant Oval Cavity as a large, quasi-stationary superbubble, similar to the Phantom Bubble observed by JWST, stabilised by the interplay between stellar feedback and Galactic disk dynamics.

astro-ph.GA↗

arXiv2025

Planets Across Space and Time (PAST). VIII : Kinematic Characterization and Identification of Radial Velocity Variables for the LAMOST-Gaia-TESS Stars

The Transiting Exoplanet Survey Satellite (TESS) has discovered over 6700 nearby exoplanets candidates using the transit method through its all-sky survey. Characterizing the kinematic properties and identifying variable stars for the TESS stellar sample is crucial for revealing the correlations between the properties of planetary systems and the properties of stars (e.g., Galactic components, age, chemistry, dynamics, radiation). Based on data from TESS, Gaia DR3, and LAMOST DR10, we present a catalog of kinematic properties (i.e., Galactic positions, velocities, orbits, Galactic components, and kinematic age) as well as other basic stellar parameters for $\sim 660,000$ TESS stars. Our analysis of the kinematic catalog reveals that stars belonging to different Galactic components (i.e., thin disk, thick disk, halo and 12 streams in the disk) display distinctive kinematic and chemical properties. We also find that hot planets with period less then 10 days in the TESS sample favor thin disk stars compared to thick disk stars, consistent with previous studies. Furthermore, using the LAMOST multiple-epoch observations, we identify 41,445 stars exhibiting significant radial velocity variations, among which 7,846 are classified as binary stars. By fitting the radial velocity curves, we further derive orbital parameters (e.g., mass ratio, orbital period and eccentricity) for 297 binaries. The observed decreasing orbital eccentricity with shorting period reveals evidence of tidal circularization. The catalogs constructed in this work have laid a solid foundation for future work on the formation and evolution of stellar and planetary systems in different Galactic environments.

astro-ph.EP↗

arXiv2025

An all-sky 3D dust map Based on Gaia and LAMOST

We present a comprehensive 3D dust reddening map covering the entire Milky Way, constructed by combining reddening estimates based on LAMOST low-resolution spectra (E(B$-$V)$_{\rm LAMOST}$) with those derived from $Gaia$ XP spectra (E(B$-$V)$_{\rm XP}$), along with revised $Gaia$ distances. E(B$-$V)$_{\rm LAMOST}$ values of $\sim$ 4.6 million unique sources were obtained with the standard-pair analysis using LAMOST DR11 stellar parameters and synthesized $B/V$-band photometry from $Gaia$ XP spectra, showing a typical precision of $\sim$ 0.01 mag. The E(B$-$V)$_{\rm XP}$ from the catalog of \citet{zhang2023}, which was derived using forward modeling of $Gaia$ XP spectra, were cross-validated with E(B$-$V)$_{\rm LAMOST}$, leading to the selection of $\sim$ 150 million high-reliability measurements. The combined dataset achieves a median precision of $\sim$ 0.03 mag for E(B$-$V). To model the reddening -- distance relationship along various lines-of-sight, we implemented a parametric approach that accounts for contributions from the local bubble, diffuse interstellar-medium, and multiple potential molecular clouds. The sky was adaptively partitioned based on stellar density, resulting in angular resolutions ranging from 3.4$^{\prime}$ to 58$^{\prime}$, with about half of the sky having a resolution better than 6.9$^{\prime}$. The reddening precision of our 3D map for individual stars reaches $\sim$ 0.01 mag in most regions at $|b| > 20^\circ$, but degrades to 0.01-0.05 mag at $|b| < 20^\circ$. The map reaches a maximum distance of 3-5 kpc in high-extinction regions with $|b| < 5^\circ$, and extends to 10-15 kpc elsewhere. An interactive platform and Python package have been developed for utilization of the 3D dust map. Available online: https://nadc.china-vo.org/data/dustmaps/.

astro-ph.GA↗

arXiv2025

Spectroscopic ages for 4 million main-sequence dwarf stars from LAMOST DR10 estimated with data-driven approach

Stellar age determination for large samples of stars opens new avenues for a broad range of astronomical sciences. While precise stellar ages for evolved stars have been derived from large ground- and space-based stellar surveys, reliable age determination for cool main-sequence dwarf stars remains a challenge. In this work, we set out to estimate the age of dwarf stars from the LAMOST spectra with a data-driven approach. We build a training set by using wide binaries that the primary component has reliable isochrone age estimate thus gives the age of the secondary. This training set is further supplemented with field stars and cluster stars whose ages are known. We then train a data-driven model for inferring age from their spectra with the XGBoost algorithm. Given a spectral signal-to-noise ratio greater than 50, the age estimation precise to 10% to 25% for K-type stars, as younger stars have larger relative errors. Validations suggest that the underlying information used for our age estimation is largely attributed to the LAMOST spectral features of chemical abundances. It means our result is a manifestation of stellar chemical clock effectively acted on LAMOST spectra ($R\simeq1800$). Applying our model to the LAMOST DR10 yields a massive age catalog for $\sim4$ million dwarf stars. Statistical properties, such as the age distribution, age-abundance and age-stellar activity relations of the sample stars are discussed. The catalog is publicly accessible and can be helpful for extensive sciences from detection and characterization of Earth-like planets to Galactic archaeology.

astro-ph.SR↗

arXiv2025

Intergalactic Wandering Stars in the Local Universe: Theoretical Predictions for Their Distance and Luminosity Distribution

Intergalactic wandering stars (IWSs) within 10 Mpc remain a poorly explored area of astronomy. Such stars, if they exist, are supposed to be wandering objects as they are not bounded by the gravitational potential of any galaxy. We set out to conduct dedicated studies for unraveling such a wandering stellar population. As the first paper of the series, in the present work we model the distance distribution and luminosity function of IWSs formed via the Hills mechanism of the Galactic central massive black hole (GCMBH). We implement a numerical simulation to generate IWSs taking the ejection history of the GCMBH and the stellar evolution process into consideration, and present their luminosity function in the distance range of 200kpc - 10Mpc. Our results suggest that a few hundred thousand IWSs have been generated by the GCMBH via the Hills mechanism in the past 14 billion years. These IWSs have an apparent magnitude peaking at 30 to 35 mag in SDSS $r-$band, which are hard to detect. However, a few thousand of them at the bright end are detectable by upcoming wide-field deep surveys, such as China Space Station Telescope (CSST) and Vera Rubin Observatory (LSST). The forthcoming discovery of such a wandering stellar population will open a door for precise understanding of the matter constitution of the nearby intergalactic space and the dynamical history of galaxies in the local universe.

astro-ph.GA↗

arXiv2025

Additional Evidence for the Existence of a Primordial Disk System

The origin of very metal-poor (VMP; [Fe/H] $\leq -2.0$) stars on planar orbits has been the subject of great attention since their first discovery. However, prior to the release of the Gaia BP/RP (XP) spectra, and large photometric samples such as SkyMapper, SAGES, J-PLUS and S-PLUS, most studies have been limited due to their small sample sizes or strong selection effects. Here, we cross-match photometric metallicities derived from Gaia XP synthetic photometry and geometric distances from Bailer-Jones et al., and select 12,000 VMP stars (1604 dwarfs and 10,396 giants) with available high-quality astrometry. After calculating dynamical parameter estimates using \texttt{AGAMA}, we employ the non-negative matrix factorization technique to the $v_ϕ$ distribution across bins in $Z_{\rm max}$ (the maximum height above or below the Galactic plane during the stellar orbit). We find three primary populations of the selected VMP stars: halo, disk system, and the Gaia Sausage/Enceladus (GSE) structure. The fraction of disk-like stars decreases with increasing $Z_{\rm max}$ (as expected), although it is still $\sim 20$\% for stars with $Z_{\rm max}$ $\sim 3 $ kpc. Similar results emerge from the application of the Hayden criterion, which separates stellar populations on the basis of their orbital inclination angles relative to the Galactic plane. We argue that such high fractions of disk-like stars indicate that they are an independent component, rather than originating solely from Galactic building blocks or heating by minor mergers. We suggest that most of these VMP stars are members of the hypothesized ``primordial" disk.

astro-ph.GA↗

arXiv2025

Homogeneous Stellar Atmospheric Parameters and 22 Elemental Abundances for FGK Stars Derived From LAMOST Low-resolution Spectra with DD-Payne

A deep understanding of our Galaxy desires detailed decomposition of its stellar populations via their chemical fingerprints. This requires precise stellar abundances of many elements for a large number of stars. Here we present an updated catalog of stellar labels derived from LAMOST low-resolution spectra in a physics-sensible and rigorous manner with DD-Payne, taking labels from high-resolution spectroscopy as training set. The catalog contains atmospheric parameters for 6.4 million stars released in LAMOST DR9, and abundances for 22 elements, namely, C, N, O, Na, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, Ni, Sr, Y, Zr, Ba, La, Ce, Nd, Sm, and Eu, for nearly 3.6 million stars with spectral signal-to-noise ratio (SNR) higher than 20. The [Fe/H] is valid down to $\sim$-4.0, while elemental abundance ratios [X/Fe] are mostly valid for stars with [Fe/H] $\gtrsim-2.0$. Measurement errors in these labels are sensitive to and almost inversely proportional with SNR. For stars with S/N>50, we achieved a typical error of 30 K in Teff, 0.07 dex in $\log g$, $\sim0.05$ dex in abundances for most elements with atomic number smaller than Sr, and 0.1--0.2 dex for heavier elements. Homogenization to the label estimates is carried out via dedicated internal and external calibration. In particular, the non-local thermal equilibrium effect is corrected for the [Fe/H] estimates, the Teff is calibrated to the infrared flux method scale, and the $\log~g$ is validated with asteroseismic measurements. The elemental abundances are internally calibrated using wide binaries, eliminating systematic trend with effective temperature. The catalog is publicly available.

astro-ph.SR↗

arXiv2025

Metallicities of 20 Million Giant Stars Based on Gaia XP spectra

We design an uncertainty-aware cost-sensitive neural network (UA-CSNet) to estimate metallicities from dereddened and corrected Gaia BP/RP (XP) spectra for giant stars. This method accounts for both stochastic errors in the input spectra and the imbalanced density distribution in [Fe/H] values. With a specialized architecture and training strategy, the UA-CSNet improves the precision of the predicted metallicities, especially for very metal-poor (VMP; $\rm [Fe/H] \leq -2.0$) stars. With the PASTEL catalog as the training sample, our model can estimate metallicities down to $\rm [Fe/H] \sim -4$. We compare our estimates with a number of external catalogs and conduct tests using star clusters, finding overall good agreement. We also confirm that our estimates for VMP stars are unaffected by carbon enhancement. Applying the UA-CSNet, we obtain reliable and precise metallicity estimates for approximately 20 million giant stars, including 360,000 VMP stars and 50,000 extremely metal-poor (EMP; $\rm [Fe/H] \leq -3.0$) stars. The resulting catalog is publicly available at https://doi.org/10.12149/101604. This work highlights the potential of low-resolution spectra for metallicity estimation and provides a valuable dataset for studying the formation and chemo-dynamical evolution of our Galaxy.

astro-ph.SR↗

arXiv2025

Finding Quasars Behind the Galactic Plane: Spectroscopic Identifications of ~1300 New Quasars at |b|<=20 degree from LAMOST DR10

Quasars behind the Galactic plane (GPQs) are excellent tracers to probe the chemistry and kinematics of the interstellar/intergalactic medium (ISM/IGM) of the Milky Way along sight lines via absorption line spectroscopy. Moreover, the quasars located at low Galactic latitudes will fill the gap in the spatial distribution of known quasars near the Galactic plane, and can be used to construct an astrometric reference frame for accurate measurements of proper motions (PMs) of stars, and substructures of the Milky Way. We started a survey of background quasars in the low Galactic latitude region since the LAMOST phase II survey in 2017. Quasar candidates have been selected from the optical and infrared photometric data of Pan-STARRS1 and WISE surveys based on their variability and color properties. In this paper, we present a sample of 1982 spectroscopically confirmed GPQs with |b| <= 20 degree based on LAMOST Data Release 10 (DR10). Among them, 1338 are newly discovered. Most GPQs are located around 240<l<90 degree, and the spatial distributions are non-uniform. These GPQs have a magnitude distribution with a peak at i-mag 19.0, and mostly around 18.0-19.5mag. The peak of redshift distributions is around ~1.5, and most GPQs have redshifts between 0.3 and 2.5. Our finding demonstrates the potential discovery space for the GPQs from the spectroscopic surveys and the promising applications for future research.

astro-ph.GA↗

arXiv2025

Stellar Loci. VIII. Photometric Metallicities for 100 Million Stars Based on Synthetic Gaia Colors

We apply the stellar locus method to synthetic $(BP-RP)_{XPSP}$ and $(BP-G)_{XPSP}$ colors derived from corrected Gaia BP/RP (XP) spectra to obtain precise estimates of metallicity for about 100 million stars in the Milky Way (34 million giants in the color range $0.6 < (BP-RP)_0 < 1.75$ and 65 million dwarfs in the color range $0.2 < (BP-RP)_0 < 1.5$). The sub milli-magnitude precision of the derived synthetic stellar colors enables estimates of metallicity for stars as low as [Fe/H] $\sim -4$. Multiple validation tests indicate that the typical metallicity precision is between 0.05 -- 0.1 dex for both dwarfs and giants at [Fe/H] = 0 as faint as G $\sim$ 16, and decreases to 0.15 -- 0.25 dex at [Fe/H] = $-$2.0. For $-4.0 < $[Fe/H]$< -3.0$, the typical metallicity precision decreases to on the order of 0.4 -- 0.5 dex, based on the results from the reference sample. Our achieved precision is comparable to or better than previous efforts using the entire XP spectra, and about three times better than our previous work based on Gaia EDR3 colors. This opens up new opportunities for investigations of stellar populations, the formation and chemical evolution of the Milky Way, the chemistry of stars and star clusters, and the identification of candidate stars for subsequent high-resolution spectroscopic follow-up. The catalog is publicly available at https://doi.org/10.12149/101548.

astro-ph.SR↗

arXiv2025

Complementary Subspace Low-Rank Adaptation of Vision-Language Models for Few-Shot Classification

Vision language model (VLM) has been designed for large scale image-text alignment as a pretrained foundation model. For downstream few shot classification tasks, parameter efficient fine-tuning (PEFT) VLM has gained much popularity in the computer vision community. PEFT methods like prompt tuning and linear adapter have been studied for fine-tuning VLM while low rank adaptation (LoRA) algorithm has rarely been considered for few shot fine-tuning VLM. The main obstacle to use LoRA for few shot fine-tuning is the catastrophic forgetting problem. Because the visual language alignment knowledge is important for the generality in few shot learning, whereas low rank adaptation interferes with the most informative direction of the pretrained weight matrix. We propose the complementary subspace low rank adaptation (Comp-LoRA) method to regularize the catastrophic forgetting problem in few shot VLM finetuning. In detail, we optimize the low rank matrix in the complementary subspace, thus preserving the general vision language alignment ability of VLM when learning the novel few shot information. We conduct comparison experiments of the proposed Comp-LoRA method and other PEFT methods on fine-tuning VLM for few shot classification. And we also present the suppression on the catastrophic forgetting problem of our proposed method against directly applying LoRA to VLM. The results show that the proposed method surpasses the baseline method by about +1.0\% Top-1 accuracy and preserves the VLM zero-shot performance over the baseline method by about +1.3\% Top-1 accuracy.

cs.CV↗

arXiv2024

The formation and survival of the Milky Way's oldest stellar disk

It remains a mystery when our Milky Way first formed a stellar disk component that survived and maintained its disk structure from subsequent galaxy mergers. We present a study of the age-dependent structure and star formation rate of the Milky Way's disk using high-alpha stars with significant orbital angular momentum that have precise age determinations. Our results show that the radial scale length is nearly independent of age, while the vertical scale height experienced dramatic evolution. A disk-like geometry presents even for populations older than 13 Gyr, with the scale height-to-length ratio dropping below 0.5 for populations younger than 12.5 Gyr. We dub the oldest population that has maintained a disk geometry - apparently formed over 13 Gyr ago - PanGu. With an estimated present-day stellar mass of $2 \times 10^9$ $M_\odot$, PanGu is presumed to be a major stellar component of our Galaxy in the earliest epoch. The total present-day stellar mass of the whole high-alpha disk is $2 \times 10^{10}$ $M_\odot$, mostly formed during a distinct star formation rate peak of 11 $M_\odot$ per year around 11 Gyrs ago. A comparison with Milky Way analogs in the TNG50 simulations implies that our Galaxy has experienced an exceptionally quiescent dynamical history, even before the Gaia-Enceladus merger.

astro-ph.GA↗

arXiv2024

The Age-Dependent Vertical Actions of Young Stars in the Galaxy

Stars in the Galactic disk are born on cold, nearly circular orbits with small vertical excursions. After their birth, their orbits evolve, driven by small- or large-scale perturbations in the Galactic disk's gravitational potential. Here, we study the vertical motions of young stars over their first few orbital periods, using a sample of OBA stars from \textit{Gaia} E/DR3, which includes radial velocities and ages $τ$ from LAMOST. We constructed a parametric model for the time evolution of the stellar orbits' mean vertical actions $J_z$ as a function of Galactocentric radius, $R_{\mathrm{GC}}$. Accounting for data uncertainties, we use Markov Chain Monte Carlo (MCMC) analysis in annuli of Galactocentric radius to constrain the model parameters. Our best-fit model shows a remarkably linear increase of vertical actions with age across all Galactocentric radii examined. Orbital \textit{heating} by random scattering could offer a straightforward interpretation for this trend. However, various other dynamical aspects of the Galactic disk, such as stars being born in a warped disk, might offer alternative explanations that could be tested in the future.

astro-ph.GA↗

arXiv2024

Autonomous Disentangling for Spectroscopic Surveys

A suite of spectroscopic surveys is producing vast sets of stellar spectra with the goal of advancing stellar physics and Galactic evolution by determining their basic physical properties. A substantial fraction of these stars are in binary systems, but almost all large-survey modeling pipelines treat them as single stars. For sets of multi-epoch spectra, spectral disentangling is a powerful technique to recover or constrain the individual components' spectra of a multiple system. So far, this approach has focused on small samples or individual objects, usually with high resolution ($R \gtrsim 10.000$) spectra and many epochs ($\gtrsim 8$). Here, we present a disentangling implementation that accounts for several aspects of few-epoch spectra from large surveys: that vast sample sizes require automatic determination of starting guesses; that some of the most extensive spectroscopic surveys have a resolution of only $\approx 2,000$; that few epochs preclude unique orbit fitting; that one needs effective regularisation of the disentangled solution to ensure resulting spectra are smooth. We describe the implementation of this code and show with simulated spectra how well spectral recovery can work for hot and cool stars at $R \approx 2000$. Moreover, we verify the code on two established binary systems, the ``Unicorn'' and ``Giraffe''. This code can serve to explore new regimes in survey disentangling in search of massive stars with massive dark companions, e.g. the $\gtrsim 200,000$ hot stars of the SDSS-V survey.

astro-ph.SR↗

arXiv2024

Filter Design for Estimation of Stellar Metallicity: Insights from Experiments with Gaia XP Spectra

We search for an optimal filter design for the estimation of stellar metallicity, based on synthetic photometry from Gaia XP spectra convolved with a series of filter-transmission curves defined by different central wavelengths and bandwidths. Unlike previous designs based solely on maximizing metallicity sensitivity, we find that the optimal solution provides a balance between the sensitivity and uncertainty of the spectra. With this optimal filter design, the best precision of metallicity estimates for relatively bright ($G \sim 11.5$) stars is excellent, $σ_{\rm [Fe/H]} = 0.034$\,dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapper\,$v$). By selecting hundreds of high-probabability member stars of the open cluster M67, our analysis reveals that the intrinsic photometric-metallicity scatter of these cluster members is only 0.036\,dex, consistent with this level of precision. Our results clearly demonstrate that the internal precision of photometric-metallicity estimates can be extremely high, even providing the opportunity to perform chemical tagging for very large numbers of field stars in the Milky Way. This experiment shows that it is crucial to take into account uncertainty alongside the sensitivity when designing filters for measuring the stellar metallicity and other parameters.

astro-ph.SR↗

arXiv2024

Reconstructing Intrinsic Stellar Noise with Stellar Atmospheric Parameters and Chromospheric Activity

Accurately characterizing intrinsic stellar photometric noise induced by stellar astrophysics, such as stellar activity, granulation, and oscillations, is of crucial importance for detecting transiting exoplanets. In this study, we investigate the relation between the intrinsic stellar photometric noise, as quantified by the Kepler rrmsCDPP measurement, and the level of stellar chromospheric activity, as indicated by the S-index of Ca II HK lines derived from the LAMOST spectra. Our results reveal a clear positive correlation between S-index and rrmsCDPP, and the correlation becomes more significant at higher activity levels and on longer timescales. We have therefore built an empirical relation between rrmsCDPP and S-index as well as Teff, logg, [Fe/H], and apparent magnitude with the XGBoost regression algorithm, using the LAMOST-Kepler common star sample as the training set. This method achieves a precision of ~20 ppm for inferring the intrinsic noise from the S-index and other stellar labels on a 6-hour integration duration. We have applied this empirical relation to the full LAMOST DR7 spectra database, and obtained the intrinsic noise predictions for 1,358,275 stars. The resultant catalog is publicly available and expected to be valuable for optimizing target selection for future exoplanet-hunting space missions, such as the Earth 2.0 mission.

astro-ph.SR↗