Stellar Library Research Articles

Estimating Stellar Atmospheric Parameters and [α/Fe] for LAMOST O-M-type Stars Using a Spectral Emulator

In this paper, we developed a spectral emulator based on the Mapping Nearby Galaxies at Apache Point Observatory Stellar Library (MaStar) and a grouping optimization strategy to estimate effective temperature (T eff), surface gravity (log g), metallicity ([Fe/H]), and the abundance of alpha elements with respect to iron ([α/Fe]) for O-M-type stars within the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) low-resolution spectra. The primary aim is to use a rapid spectral-fitting method, specifically the spectral emulator with the grouping optimization strategy, to create a comprehensive catalog for stars of all types within LAMOST, addressing the shortcomings in parameter estimations for both cold and hot stars present in the official LAMOST AFGKM-type catalog. This effort is part of our series of studies dedicated to establishing an empirical spectral library for LAMOST. Experimental results demonstrate that our method is effectively applicable to parameter prediction for LAMOST, with the single-machine processing time within 70 hr. We observed that the internal error dispersions for T eff, log g, [Fe/H], and [α/Fe] across different spectral types lie within the ranges of 15–594 K, 0.03–0.27 dex, 0.02–0.10 dex, and 0.01–0.04 dex, respectively, indicating a good consistency. A comparative analysis with external data highlighted deficiencies in the official LAMOST catalog and issues with MaStar parameters, as well as potential limitations of our method in processing spectra with strong emission lines and bad pixels. The derived atmospheric parameters as a part of this work are available via doi:10.12149/101402.

Scylla. II. The Spatially Resolved Star Formation History of the Large Magellanic Cloud Reveals an Inverted Radial Age Gradient

The proximity of the Magellanic Clouds provides the opportunity to study interacting dwarf galaxies near a massive host, and spatial trends in their stellar population properties in particular, with a unique level of detail. The Scylla pure parallel program has obtained deep (80% complete to >1 mag below the ancient main-sequence turnoff), homogeneous two-filter Hubble Space Telescope imaging sampling the inner star-forming disk of the Large Magellanic Cloud (LMC), the perfect complement to shallower, contiguous ground-based surveys. We harness this imaging together with extant archival data and fit lifetime star formation histories (SFHs) to resolved color–magnitude diagrams of 111 individual fields, using three different stellar evolutionary libraries. We validate per-field recovered distances and extinctions, as well as the combined global LMC age–metallicity relation and SFH against independent estimates. We find that the present-day radial age gradient reverses from an inside-out gradient in the inner disk to an outside-in gradient beyond ∼2 disk scale lengths, supported by ground-based measurements. The gradients become relatively flatter at earlier look-back times, while the location of the inversion remains constant over an order of magnitude in look-back time, from ∼1 to 10 Gyr. This suggests at least one mechanism that predates the recent intense LMC–Small Magellanic Cloud interaction. We compare observed radial age trends to other late-type galaxies at fixed stellar mass and discuss similarities and differences in the context of potential drivers, implying strong radial migration in the LMC.

Deriving the star formation histories of galaxies from spectra with simulation-based inference

High-resolution galaxy spectra encode information about the stellar populations within galaxies. The properties of the stars, such as their ages, masses, and metallicities, provide insights into the underlying physical processes that drive the growth and transformation of galaxies over cosmic time. We explore a simulation-based inference (SBI) workflow to infer from optical absorption spectra the posterior distributions of metallicities and the star formation histories (SFHs) of galaxies (i.e. the star formation rate as a function of time). We generated a dataset of synthetic spectra to train and test our model using the spectroscopic predictions of the MILES stellar population library and non-parametric SFHs. We reliably estimate the mass assembly of an integrated stellar population with well-calibrated uncertainties. Specifically, we reach a score of $0.97\,R^2$ for the time at which a given galaxy from the test set formed $50<!PCT!>$ of its stellar mass, obtaining samples of the posteriors in only $\,s. We then applied the pipeline to real observations of massive elliptical galaxies, recovering the well-known relationship between the age and the velocity dispersion, and show that the most massive galaxies ($ km/s) built up to 90<!PCT!> of their total stellar masses within $1$\,Gyr of the Big Bang. The inferred properties also agree with the state-of-the-art inversion codes, but the inference is performed up to five orders of magnitude faster. This SBI approach coupled with machine learning and applied to full spectral fitting makes it possible to address large numbers of galaxies while performing a thick sampling of the posteriors. It will allow both the deterministic trends and the inherent uncertainties of the highly degenerated inversion problem to be estimated for large and complex upcoming spectroscopic surveys, such as DESI, WEAVE, or 4MOST.

Toward an Auditory Virtual Observatory

The large ecosystem of observations generated by major space telescope missions can be remotely analyzed using interoperable virtual observatory technologies. In this context of astronomical big data analysis, sonification has the potential of adding a complementary dimension to visualization, enhancing the accessibility of the archives, and offering an alternative strategy to be used when overlapping issues are found in purely graphical representations. This article presents a collection of sonification and musification prototypes that explore the case studies of the MILES and STELIB stellar libraries from the Spanish Virtual Observatory and the Kepler and TESS light curve databases from the Space Telescope Science Institute archive. Using automation and deep learning algorithms, it offers a “palette” of resources that could be used in future developments oriented toward an auditory virtual observatory proposal. The work includes a user study with quantitative and qualitative feedback from specialized and nonspecialized users analyzing the use of sine waves and musical instrument mappings for revealing overlapped lines in galaxy transmission spectra, confirming the need for training and prior knowledge for the correct interpretation of accurate sonifications, and providing potential guidelines to inspire future designs of widely accepted auditory representations for outreach purposes.

Stellar spectral template library construction based on generative adversarial networks

Stellar spectral template libraries play an important role in the automated analysis of stellar spectra. Synthetic template libraries cover a very large parameter space but suffer from poor matching with observed spectra. In this study, we propose a synthetic-to-observed spectral translation (SOST) method based on generative adversarial networks. The SOST method is able to calibrate synthetic spectra by converting them to the corresponding observed spectra. We applied this method to Kurucz synthetic spectra and observed spectra data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). After that, we constructed a stellar spectral library with uniform and broad parameter distributions using the SOST-corrected Kurucz synthetic spectra. Our stellar spectral template library contains 2431 spectra spanning a parameter space of 3500–8000 K for effective temperature (Teff), 0.0–5.0 dex for surface gravity (log g), and −2.0–0.5 dex for metallicity ([Fe/H]). The spectra in the library have a resolution of R ∼ 1800 and cover the wavelength range 3900–8700 Å. In order to verify the accuracy of this template library, we used the template library and the template-matching algorithm to derive the parameters of the PASTEL database. Compared to measurements using the original synthetic template library, the accuracies of the three parameters, Teff, log g, and [Fe/H], are improved, from 140 K, 0.31 dex, and 0.21 dex to 121 K, 0.26 dex, and 0.13 dex, respectively. In addition, we re-parameterised more than six million stellar spectra released by LAMOST DR8.

GalaPy: A highly optimised C++/Python spectral modelling tool for galaxies

Bolstered by upcoming data from new-generation observational campaigns, we are about to enter a new era in the study of how galaxies form and evolve. The unprecedented quantity of data that will be collected from distances that have only marginally been grasped up to now will require analytical tools designed to target the specific physical peculiarities of the observed sources and handle extremely large datasets. One powerful method to investigate the complex astrophysical processes that govern the properties of galaxies is to model their observed spectral energy distributions (SEDs) at different stages of evolution and times throughout the history of the Universe. To address these challenges, we have developed GalaPy, a new library for modelling and fitting SEDs of galaxies from the X-ray to the radio band, as well as the evolution of their components and dust attenuation and reradiation. On the physical side, GalaPy incorporates both empirical and physically motivated star formation histories (SFHs), state-of-the-art single stellar population synthesis libraries, a two-component dust model for attenuation, an age-dependent energy conservation algorithm to compute dust reradiation, and additional sources of stellar continuum such as synchrotron, nebular and free-free emission, as well as X-ray radiation from low-and high-mass binary stars. On the computational side, GalaPy implements a hybrid approach that combines the high performance of compiled C++with the user-friendly flexibility of Python. Also, it exploits an object-oriented design via advanced programming techniques. GalaPy is the fastest SED-generation tool of its kind, with a peak performance of almost 1000 SEDs per second. The models are generated on the fly without relying on templates, thus minimising memory consumption. It exploits a fully Bayesian parameter space sampling, which allows for the inference of parameter posteriors and thereby facilitates the study of the correlations between the free parameters and the other physical quantities that can be derived from modelling. The application programming interface (API) and functions of GalaPy are under continuous development, with planned extensions in the near future. In this first work, we introduce the project and showcase the photometric SED fitting tools already available to users. GalaPy is available on the Python Package Index (PyPI) and comes with extensive online documentation and tutorials.

SMARTY: The mileS Moderate resolution neAr-infRared sTellar librarY

Abstract Most of the observed galaxies cannot be resolved into individual stars and are studied through their integrated spectrum using simple stellar populations (SSPs) models, with stellar libraries being a key ingredient in building them. Spectroscopic observations are increasingly being directed towards the near-infrared (NIR), where much is yet to be explored. SSPs in the NIR are still limited, and there are inconsistencies between different sets of models. One of the ways to minimize this problem is to have reliable NIR stellar libraries. The main goal of this work is to present smarty (mileS Moderate resolution neAr-infRared sTellar librarY) a ∼0.9 − 2.4 μm stellar spectral library composed of 31 stars observed with the Gemini Near-IR Spectrograph (GNIRS) at the 8.1 m Gemini North telescope and make it available to the community. The stars were chosen from the miles library, for which the atmospheric parameters are reliable (and well tested), to populate different regions of the Hertzsprung-Russell (HR) diagram. Furthermore, five of these stars have NIR spectra available that we use to assess the quality of smarty. The remaining 26 stars are presented for the first time in the NIR. We compared the observed smarty spectra with synthetic and interpolated spectra, finding a mean difference of $\sim 20\%$ in the equivalent widths and ∼1% in the overall continuum shape in both sets of comparisons. We computed the spectrophotometric broadband magnitudes and colours and compared them with the 2MASS ones, resulting in mean differences up to 0.07 and 0.10 mag in magnitudes and colours, respectively. In general, a small difference was noted between the smarty spectra corrected using the continuum from the interpolated and the theoretical stars.

The Near-infrared Ca ii Triplet as a Stellar Activity Indicator: A Library and Comparative Study

We have established and released a new stellar index library of the Ca ii triplet, which serves as an indicator for characterizing the chromospheric activity of stars. The library is based on data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS) Data Release 9. To better reflect the chromospheric activity of stars, we have defined new indices R and R +. The library includes measurements of R and R + for each Ca ii infrared triplet (IRT) from 699,348 spectra of 562,863 F, G, and K-type solar-like stars with a signal-to-noise ratio higher than 100, as well as the stellar atmospheric parameters and basic information inherited from the LAMOST LRS catalog. We compared the differences between the three individual indices of the Ca ii triplet and also conducted a comparative analysis of Rλ8542+ to the Ca ii H and K S and RHK+ index databases. We observe the fraction of less active stars decreases with T eff and the fraction of more active stars first decreases with decreasing temperature and turns to increase with decreasing temperature at 5800 K. We also find that a significant fraction of stars that show a high activity index in both Ca ii H and K and IRT are binaries with low activity; some of them could be discriminated in the Ca ii H and K S index and Rλ8542+ space. This new stellar library serves as a valuable resource for studying chromospheric activity in stars and can be used to improve our comprehension of stellar magnetic activity and other astrophysical phenomena.

Carbon- and Oxygen-rich stars in MaStar: identification and classification

Abstract Carbon- and Oxygen-rich stars populating the Thermally-Pulsing Asymptotic Giant Branch (TP-AGB) phase of stellar evolution are relevant contributors to the spectra of ∼1 Gyr old populations. Atmosphere models for these types are uncertain, due to complex molecules and mass-loss effects. Empirical spectra are then crucial, but samples are small due to the short (∼3 Myr) TP-AGB lifetime. Here we exploit the vastness of the MaNGA Stellar library MaStar (∼60, 000 spectra) to identify C,O-rich type stars. We define an optical colour selection with cuts of (g − r) > 2 and (g − i) < 1.55(g − r) − 0.07, calibrated with known C- and O- rich spectra. This identifies C-,O-rich stars along clean, separated sequences. An analogue selection is found in V, R, I bands. Our equation identifies C-rich and O-rich spectra with predictive performance metric F1-scores of 0.72 and 0.74 (over 1), respectively. We finally identify 41 C- and 87 O-rich type AGB stars in MaStar, 5 and 49 of which do not have a SIMBAD counterpart. We also detect a sample of non-AGB, dwarf C-stars. We further design a fitting procedure to classify the spectra into broad spectral types, by using as fitting templates empirical C and O-rich spectra. We find remarkably good fits for the majority of candidates and categorise them into C- and O-rich bins following existing classifications, which correlate to effective temperature. Our selection models can be applied to large photometric surveys (e.g. Euclid, Rubin). The classified spectra will facilitate future evolutionary population synthesis models.

Less is less: Photometry alone cannot predict the observed spectral indices of z ~ 1 galaxies from the LEGA-C spectroscopic survey

Aims. We test whether we can predict optical spectra from deep-field photometry of distant galaxies. Our goal is to perform a comparison in data space, highlighting the differences between predicted and observed spectra. Methods. The Large Early Galaxy Astrophysics Census (LEGA-C) provides high-quality optical spectra of thousands of galaxies at redshift 0.6 < z < 1. Broadband photometry of the same galaxies, drawn from the recent COSMOS2020 catalog, is used to predict the optical spectra with the spectral energy distribution (SED) fitting code Prospector and the MILES stellar library. The observed and predicted spectra are compared in terms of two age and metallicity-sensitive absorption features (HδA and Fe4383). Results. The global bimodality of star-forming and quiescent galaxies in photometric space is recovered with the model spectra. However, the presence of a systematic offset in the Fe4383 line strength and the weak correlation between the observed and modeled line strength imply that accurate age or metallicity determinations cannot be inferred from photometry alone. Conclusions. For now we caution that photometry-based estimates of stellar population properties are determined mostly by the modeling approach and not the physical properties of galaxies, even when using the highest-quality photometric datasets and state-of-the-art fitting techniques. When exploring a new physical parameter space (i.e. redshift or galaxy mass) high-quality spectroscopy is always needed to inform the analysis of photometry.

The JWST Resolved Stellar Populations Early Release Science Program. IV. The Star Formation History of the Local Group Galaxy WLM

We present the first star formation history (SFH) and age–metallicity relation (AMR) derived from resolved stellar populations imaged with the JWST NIRCam instrument. The target is the Local Group star-forming galaxy WLM at 970 kpc. The depth of the color–magnitude diagram (CMD) reaches below the oldest main sequence turnoff with a signal-to-noise ratio = 10 at M F090W = + 4.6 mag. This is the deepest CMD for any galaxy that is not a satellite of the Milky Way. We use Hubble Space Telescope (HST) optical imaging that overlaps with the NIRCam observations to directly evaluate the SFHs derived based on data from the two great observatories. The JWST and HST-based SFHs are in excellent agreement. We use the metallicity distribution function measured from stellar spectra to confirm the trends in the AMRs based on the JWST data. Together, these results confirm the efficacy of recovering an SFH and AMR with the NIRCam F090W−F150W filter combination, and validate the sensitivity and accuracy of stellar evolution libraries in the near-infrared relative to the optical for SFH recovery work. From the JWST data, WLM shows an early onset to star formation, followed by an extended pause post-reionization before star formation reignites, which is qualitatively similar to what has been observed in the isolated galaxies Leo A and Aquarius. Quantitatively, 15% of the stellar mass formed in the first Gyr, while only 10% formed over the next ∼5 Gyr. The stellar mass then rapidly doubled in ∼2.5 Gyr, followed by constant star formation over the last ∼5 Gyr.

The updated BaSTI stellar evolution models and isochrones – IV. α-Depleted calculations

ABSTRACT This is the fourth paper of our new release of the BaSTI (a Bag of Stellar Tracks and Isochrones) stellar model and isochrone library. Following the updated solar-scaled, α-enhanced, and white dwarf model libraries, we present here α-depleted ([α/Fe] = −0.2) evolutionary tracks and isochrones, suitable to study the α-depleted stars discovered in Local Group dwarf galaxies and in the Milky Way. These calculations include all improvements and updates of the solar-scaled and α-enhanced models, and span a mass range between 0.1 and 15 M⊙, and 21 metallicities between [Fe/H] = −3.20 and +0.45 with a helium-to-metal enrichment ratio ΔY/ΔZ = 1.31, homogeneous with the solar-scaled and α-enhanced models. The isochrones – available in several photometric filters – cover an age range between ∼20 Myr and 14.5 Gyr, including the pre-main-sequence phase. We have compared our isochrones with independent calculations of α-depleted stellar models, available for the same α-element depletion adopted in the present investigation. We have also discussed the effect of an α-depleted heavy element distribution on the bolometric corrections in different wavelength regimes. Our α-depleted evolutionary tracks and isochrones are publicly available at our BaSTI website.

SPar: Estimating Stellar Parameters from Multiband Photometries with Empirical Stellar Libraries

Abstract Modern large-scale photometric surveys have provided us with multiband photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (T eff) and metallicities ([Fe/H]), absolute magnitudes (M G ), distances (d), and reddening values (E(G BP − G RP)) is fundamental to study the stellar populations, structure, kinematics, and chemistry of the Galaxy. This work constructed an empirical stellar library that maps the stellar parameters to multiband photometries from a data set with Gaia parallaxes, LAMOST atmospheric parameters, and optical to near-infrared photometry from several photometric surveys. Based on the stellar library, we developed a new algorithm, SPar (Stellar Parameters from multiband photometry), which fits the multiband stellar photometries to derive the stellar parameters (T eff, [Fe/H], M G , d, and E(G BP − G RP)) of the individual stars. The algorithm is applied to the multiband photometric measurements of a sample of stars selected from the SMSS survey, which have stellar parameters derived from the spectroscopic surveys. The stellar parameters derived from multiband photometries by our algorithm are in good agreement with those from the spectroscopic surveys. The typical differences between our results and the literature values are 170 K for T eff, 0.23 dex for [Fe/H], 0.13 mag for M G , and 0.05 mag for E(G BP − G RP). The algorithm proved to be robust and effective and will be applied to the data of future large-scale photometric surveys such as the Mephisto and CSST surveys.

SMILES SSPs: a library of semi-empirical MILES stellar population models with variable [α/Fe] abundances

ABSTRACT We present a new library of semi-empirical stellar population models that are based on the empirical MILES and semi-empirical sMILES stellar libraries. The models span a large range of age and metallicity, in addition to an [α/Fe] coverage from −0.2 to +0.6 dex, at MILES resolution (FWHM = $2.5\,$ Å) and wavelength coverage ($3540.5-7409.6\,$ Å). These models are aimed at exploring abundance ratios in the integrated light from stellar populations in star clusters and galaxies. Our approach is to build SSPs from semi-empirical stars at particular [α/Fe] values, thus producing new SSPs at a range of [α/Fe] values from sub-solar to super-solar. We compare these new SSPs with previously published and well-used models and find similar abundance pattern predictions, but with some differences in age indicators. We illustrate a potential application of our new SSPs, by fitting them to the high signal-to-noise data of stacked SDSS galaxy spectra. Age, metallicity, and [α/Fe] trends were measured for galaxy stacks with different stellar velocity dispersions and show systematic changes, in agreement with previous analyses of subsets of those data. These new SSPs are made publicly available.

New Generation Stellar Spectral Libraries in the Optical and Near-infrared. I. The Recalibrated UVES-POP Library for Stellar Population Synthesis* * Recalibrated spectra are available at https://sl.voxastro.org/.

We present reprocessed flux-calibrated spectra of 406 stars from the UVES-POP stellar library in the wavelength range 320–1025 nm, which can be used for stellar population synthesis. The spectra are provided in the two versions having spectral resolving power R = 20,000 and R = 80,000. Raw spectra from the ESO data archive were re-reduced using the latest version of the UVES data reduction pipeline with some additional algorithms that we developed. The most significant improvements in comparison with the original UVES-POP release are (i) an updated echelle order merging, which eliminates “ripples” present in the published spectra; (ii) a full telluric correction; (iii) merging of nonoverlapping UVES spectral setups taking into account the global continuum shape; (iv) a spectrophotometric correction and absolute flux calibration; and (v) estimates of the interstellar extinction. For 364 stars from our sample, we computed atmospheric parameters T eff, surface gravity log g, metallicity [Fe/H], and α-element enhancement [α/Fe] by using a full-spectrum fitting technique based on a grid of synthetic stellar atmospheres and a novel minimization algorithm. We also provide projected rotational velocity and radial velocity v rad estimates. The overall absolute flux uncertainty in the reprocessed data set is better than 2%, with subpercent accuracy for about half of the stars. A comparison of the recalibrated UVES-POP spectra with other spectral libraries shows a very good agreement in flux; at the same time, Gaia DR3 BP/RP spectra are often discrepant with our data, which we attribute to spectrophotometric calibration issues in Gaia DR3.

Understanding the Chemical Evolution of Blue Edge-on Low Surface Brightness Galaxies

We present a sample of 330 blue edge-on low surface brightness galaxies (ELSBGs). To understand the chemical evolution of ELSBGs, we derived the gas-phase abundance and the [α/Fe] ratio. Compared with star-forming galaxies, ELSBGs show a flatter trend in the mass–metallicity (M *–Z) relation, which suggests that the oxygen abundance enhancement is inefficient. We focused on 77 ELSBGs with H i data and found that the closed-box model cannot explain their gas fraction and metallicity relation, which implies that infall and/or outflow is needed. We derived the [α/Fe] ratio of normal ELSBG (<109.5 M ⊙) and massive ELSBG (> = 109.5 M ⊙) using single stellar population grids from the MILES stellar library. The mean [α/Fe] ratios are 0.18 and 0.4 for normal ELSBG and massive ELSBG, respectively. We suggest that the long timescales of star formation and/or metal-rich gas outflow events caused by SNe Ia winds are likely to be responsible for the α-enhancement of massive ELSBGs.

The Stellar Spectra Factory (SSF) Based on SLAM

An empirical stellar spectral library with large coverage of stellar parameters is essential for stellar population synthesis and studies of stellar evolution. In this work, we present Stellar Spectra Factory (SSF), a tool to generate empirical-based stellar spectra from arbitrary stellar atmospheric parameters. The relative flux-calibrated empirical spectra can be predicted by SSF given arbitrary effective temperature, surface gravity, and metallicity. SSF constructs the interpolation approach based on the Stellar LAbel Machine, using ATLAS-A library, which contains spectra covering from O type to M type, as the training data set. SSF is composed of four data-driven sub-models to predict empirical stellar spectra. Sub-model SSF-N can generate spectra from A to K type and some M giant stars, covering 3700 < T eff < 8700 K, 0 < < dex, and −1.5 < [M/H] < 0.5 dex. Sub-model SSF-gM is mainly used to predict M giant spectra with 3520 < T eff < 4000 K and −1.5 < [M/H] < 0.4 dex. Sub-model SSF-dM is for generating M dwarf spectra with 3295 < T eff < 4040 K, −1.0 < [M/H] < 0.1 dex. Sub-model SSF-B can predict B-type spectra with 9000 < T eff < 24,000 K and −5.2 < M G < 1.5 mag. The accuracy of the predicted spectra is validated by comparing the flux of predicted spectra to those with same stellar parameters selected from the known spectral libraries, MILES and MaStar. The averaged difference of flux over optical wavelength between the predicted spectra and the corresponding ones in MILES and MaStar is less than 5%. More verification is conducted between the magnitudes calculated from the integration of the predicted spectra and the observations in PS1 and APASS bands with the same stellar parameters. No significant systematic difference is found between the predicted spectra and the photometric observations. The uncertainty is 0.08 mag in the r band for SSF-gM when comparing with the stars with the same stellar parameters selected from PS1. The uncertainty becomes 0.31 mag in the i band for SSF-dM when comparing with the stars with the same stellar parameters selected from APASS.

All Spectral Type LAMOST Spectra Library (ATLAS)

We present an empirical stellar spectra library, ATLAS, with resolution R ∼ 1800 and wavelength coverage from 3800–8700 Å. These spectra are homogeneously observed by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope and have been released in its DR5. ATLAS is separated into two groups, ATLAS-A and -T. The former contains 5584 spectra covering spectral types from O- to M-type and some special types such as A supergiant, blue horizontal-branch, and carbon stars. All of the spectra have absolutely calibrated fluxes at certain characteristic wavelengths corresponding to the optical passbands with accuracy better than 2.9% by comparing with PanSTARRS1 g-, r-, and i-band photometry. In addition, greater than 1% systematic uncertainty from the fundamental calibration should be considered separately. ATLAS-A contains 5342 spectra with spectral energy distribution effective temperature, surface gravity, and metallicity and 242 spectra with only the effective temperature and surface gravity. These parameters are consistent with the spectroscopic derived parameters of the same stars. Compared to current empirical libraries, ATLAS-A contains more cool giant stars, which may play a critical role in understanding the evolution of galaxies. ATLAS-T, on the other hand, contains 1118 spectral templates averaging over spectra with similar stellar parameters from ATLAS-A. It smooths out some special features in the individual spectra and can be used as a “standard” atlas of stellar spectra. Containing stellar spectra with almost all normal types, ATLAS may not only be a complete training data set for stellar spectra parameter determination but also an ideal legacy for stellar population synthesis.

Chemical characterisation of the X-shooter Spectral Library (XSL): [Mg/Fe] and [Ca/Fe] abundances

Context. The X-shooter Spectral Library (XSL) is a large empirical stellar library used as a benchmark for the development of stellar population models. The inclusion of α-element abundances is crucial to disentangling the chemical evolution of any stellar system. Aims. The aim of this paper is to provide a catalogue of high-precision, accurate magnesium and calcium abundances from a wide variety of stars that are well distributed in the Hertzsprung-Russell (HR) diagram. Methods. We originally performed an analysis of the derived Mg and Ca abundances for medium-resolution spectra of 611 stars from the XSL Data Release 2. For this purpose, we used the GAUGUIN automated abundance estimation code to fit the ultraviolet-blue (UVB) and visible (VIS) spectra. We tested the consistency of the atmospheric parameters and chemical abundances with the Gaia DR3 and the AMBRE Project datasets. Results. We finally obtained precise [Mg/Fe] and [Ca/Fe] abundances for 192 and 217 stars, respectively, from which 174 stars have measurements in both elements. The stars cover a broad effective temperature range of 4000 &lt; Teff &lt; 6500 K, surface gravity of 0.3 &lt; log(g) &lt; 4.8 cm s−2, and metallicity of −2.5 &lt; [Fe/H] &lt; +0.4 dex. We find an excellent agreement with the abundance estimates from the AMBRE:HARPS and the Gaia-RVS (Radial Velocity Spectrometer) analysis. Moreover, the resulting abundances reproduce a plateau in the metal-poor regime followed by a decreasing trend even at supersolar metallicities, as predicted by Galactic chemical evolution models. Conclusions. This catalogue is suitable for improving the modelling of evolutionary stellar population models with empirical α enhancements, which could significantly contribute to the analysis of external galaxies’ abundances in the near future.

On the impact of spectral template uncertainties in synthetic stellar populations

ABSTRACTUncertainties in stellar population models, both in terms of stellar evolution and stellar spectra, translate into uncertainties in our interpretation of stellar populations in galaxies, since stars are the source of most of the light we receive from them. Observations by JWST are revealing high-redshift galaxies in great detail, which must then be compared to models. One significant source of uncertainty is in the stellar spectra used to generate composite spectra of stellar populations, which are then compared to data. Confidence in theoretical models is important to enable reliable determination of the properties of these galaxies such as their ages and star formation history. Here, we present a comparison of spectral synthesis carried out with six different stellar spectral libraries using the Binary Population and Spectral Synthesis framework. In photometric colours, the differences between theoretical libraries are relatively small (&amp;lt;0.10 mag), similar to typical observational uncertainties on individual galaxy observations. Differences become more pronounced when detailed spectroscopic properties are examined. Predictions for spectral line indices can vary significantly, with equivalent widths differing by a factor of 2 in some cases. With these index strengths, some of the libraries yield predictions of ages and metallicities which are unphysical. Many spectral libraries lack wavelength coverage in the ultraviolet, which is of growing importance in the era of JWST observations of distant galaxies, whose flux is dominated by hot, young stars.