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L. Casamiquela

Publications and source records attributed to L. Casamiquela.

At least 19 recordsLinked to original sources

Gaia FGK benchmark stars: Abundances of n-capture elements of the third version

In the current era, in which an unprecedented wealth of data are available for the study of the Milky Way, Gaia benchmark stars (GBSs) have become an established reference and calibration sample. Studies of stellar structure and evolution and of the chemical history of our Galaxy generally rely on large spectroscopic surveys and their output catalogs. In this context, deriving precise and accurate stellar parameters and chemical abundances is of paramount importance. This study provides the determination of neutron (n)-capture element abundances and extends the set of chemical abundances available for the third GBS release (GBSv3). Based on the compilation of high-resolution spectra assembled for GBSv3 and consistent with the spectral analysis adopted for the chemical abundances of GBSv3, we used the public iSpec code to derive heavy element abundances. We inferred homogeneous abundances of n-capture elements across the GBSv3 sample using an in-depth line assessment tailored to different groups identified through a clustering algorithm that accounts for the diversity in stellar parameters and metallicities. This approach addresses key challenges in the spectral analysis of these elements, including the paucity of usable lines, weak line strengths, saturation effects, and sensitivity to atomic data. The assessment yielded reliable measurements, establishing an extended and robust reference scale in good agreement with the literature. This compilation of n-capture abundances is based on the GBS sample's accurate atmospheric parameters and the analysis of a large sample of stellar spectra per star, which provides a reliable and homogeneous spectral analysis. It also supports the use of chemical abundances as precise tracers of the Milky Ways star formation history and chemical evolution and constitutes a legacy sample for the calibration of current and future spectroscopic surveys.

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Stellar age determination using deep neural networks: Isochrone ages for 1.3 million stars, based on BaSTI, MIST, PARSEC, Dartmouth and SYCLIST evolutionary grids

We aim to develop a model-driven deep learning approach to age determination, by training neural networks on stellar evolutionary grids. Contrary to the usual data-driven deep learning approach of using prior age estimates as training data, our method has the potential for a wider and less biased range of application. The low computational cost of deep learning methods compared to bayesian isochrone-fitting allows for a broad analysis of large spectroscopic catalogues. We train multilayer perceptrons on different stellar evolutionary grids to map [M/H], MG, (GBP - GRP) to stellar age $τ$. We combine Gaia photometry and parallaxes, metallicities and $α$ elements from spectroscopic surveys and extinction maps, which are passed through the neural networks to estimate stellar ages. We apply our method to the LAMOST DR10, GALAH DR3 & DR4 and APOGEE DR17 spectroscopic surveys, for which we estimate the ages using the BaSTI tracks, along with other stellar evolutionary models. We leverage this novel technique to study, for the first time, differences in age estimates from several evolutionary grids applied on very large datasets. In addition, we date 13 open clusters and one globular cluster and find a median absolute deviation with literature ages of 0.20 Gyr. Along with the stellar ages catalogues from our estimates, we release NEST (Neural Estimator of Stellar Times), a python package to estimate stellar age based on this work, as well as a web interface. We show that, when using the same evolutionary grid, our method retrieves the same ages as a bayesian approach like SPInS, for only a fraction of the computational cost, with a 60,000 speedup factor for a typical star. This model-driven deep learning technique thus opens up the way for broad galactic archeology studies on the largest datasets available today and in the near future with upcoming surveys such as 4MOST.

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Why the Northern Hemisphere Needs a 30-40 m Telescope and the Science at Stake: Resolved Stellar Populations Studies in M31 and its Satellites

A 30 m class optical/near-IR telescope in the Northern Hemisphere, equipped for diffraction-limited imaging and high-resolution, multi-object spectroscopy of faint stars, would enable a transformational investigation of the formation and evolution of M31 and its satellite system - on par with what Gaia, the HST, and other major photometric and spectroscopic facilities have achieved for the Milky Way (MW) and its satellites. The unprecedented detail obtained for our home system has reshaped our understanding of the assembly of the MW disk, halo, and bulge, and that of its satellites, which now serve as a benchmark for galaxy formation and evolution models. Extending this level of insight to the M31 system - that of the nearest massive spiral and the only one for which such a comprehensive, resolved stellar population study is feasible - will allow us to address a fundamental question: how representative is the MW and its satellite system within the broader context of galaxy evolution?

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Gaia FGK Benchmark Stars: spectral library, metallicities and abundances of $α$ and Fe-peak elements of the third version

The accurate determination of chemical abundances in stars plays a pivotal role in understanding stellar structure and evolution, nucleosynthesis, and the chemical enrichment history of the Milky Way. Benchmark stars with precise and accurate atmospheric parameters and abundances are indispensable for calibrating spectroscopic surveys and testing stellar atmosphere models. This study focuses on the compilation of high-quality spectra and the determination of LTE chemical abundances of iron-peak and $α$ elements for the third version of the Gaia FGK Benchmark Stars (GBSv3). We compiled spectra of the GBSv3 from public archives and complemented these with our own observations. We use fundamental atmospheric parameters from Soubiran et al. 2024 to derive the chemical abundances and perform a spectroscopic analysis using the public code iSpec. We compile a homogeneous spectral library of high-resolution (42,000) and high signal-to-noise ($>100$) normalised spectra for 202 stars: including the 192 GBSv3, 9 stars with indirect measurement of the angular diameter from previous GBS versions, and the Sun. Using four radiative transfer codes, we derive chemical abundances of 13 chemical species (Fe I, Fe II, Mg I, Si I, Ca I, Ti I, Ti II, Sc II, V I, Cr I, Mn I, Co I, Ni I). We make an in-depth study of several sources of error. The GBSv3 contributes to the legacy samples of spectroscopic reference stars with improved statistics and homogeneity. This work offers the community a homogeneous spectral library and robust reference abundances for iron-peak and $α$ elements, supported by an extensive analysis of the associated uncertainties.

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Open clusters in the outer disc studied with MEGARA@GTC Auner 1 and Berkeley 102

Open clusters offer crucial insights into stellar nucleosynthesis and the chemical evolution of the Galactic disc, as their ages and distances can be determined with higher accuracy compared to field stars. In this study, we investigate the outermost regions of the Milky Way disc using two previously unstudied open clusters -Auner 1 and Berkeley 102- located at Galactocentric distances of approximately 14 kpc in largely uncharted areas of the Galaxy. We obtained medium-resolution spectra (R > 18,700) using the MEGARA integral-field unit (IFU) spectrograph on the 10.4 m Gran Telescopio Canarias (GTC), targeting red giant member stars in both clusters. From these spectra, we derived radial velocities, stellar atmospheric parameters, and chemical abundances for six elements: Fe, Ca, Co, Ni, Ba, and Eu. Additionally, we provide updated estimates of the clusters' ages and distances. Both clusters are old (3.2 +- 0.7 Ga), distant (d ~ 8 kpc), and lie below the Galactic plane (Z Gal ~ -0.7 kpc), with moderate extinction (AV ~ 1.3 mag). We find that Auner 1 has a metallicity of [Fe/H] = -0.30 +- 0.09 and Berkeley 102 of [Fe/H] = -0.35 +- 0.06, consistent with other clusters at similar Galactocentric radii and indicating minimal azimuthal variation in metallicity. The [X/Fe] abundance ratios align with expected trends, although [Ca/Fe] is slightly higher in both clusters, and [Eu/Fe] is notably enhanced in Berkeley 102 ([Eu/Fe] = 0.64 +- 0.05). Our findings highlight the effectiveness of GTC/MEGARA in IFU mode for Galactic archaeology and emphasize the need for further medium-to-high resolution spectroscopic studies of remote open clusters to refine models of the outer Galactic disc's chemical evolution.

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New stellar age estimates using SPInS based on Gaia DR3 photometry and LAMOST DR8 abundances

Reliable stellar age estimates are fundamental for testing several problems in modern astrophysics, in particular since they set the time scales of Galactic dynamical and chemical evolution. In this study, we determine ages using only Gaia DR3 photometry and parallaxes, in combination with interstellar extinction maps, spectroscopic metallicities and $α$ abundances from the latest data release (DR8) of the LAMOST survey. In contrast with previous age estimates, we do not use spectroscopic effective temperatures or surface gravities, thus relying on the excellent precision and accuracy of the Gaia photometry. We use a new version of the publicly available SPInS code with improved features, including the on-the-fly computation of the autocorrelation time and the automatic convergence evaluation. We determine reliable age estimates for 35,096 and 243,768 sub-giant and main-sequence turn-off stars in the LAMOST DR8 low- and medium-resolution surveys with typical uncertainties smaller than 10%. In addition, we successfully test our method on more than 4,000 stars of 14 well-studied open and globular star clusters covering a wide range of ages, confirming the reliability of our age and uncertainty estimates.

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Transferring spectroscopic stellar labels to 217 million Gaia DR3 XP stars with SHBoost

In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest regressor (xgboost), trained on spectroscopic data, capable of producing output parameters with reliable uncertainties from Gaia DR3 data (most notably the low-resolution XP spectra), without ground-based spectroscopic observations. Using Shapley additive explanations, we interpret how the predictions for each star are influenced by each data feature. For the training and testing of the network, we used high-quality parameters obtained from the StarHorse code for a sample of around eight million stars observed by major spectroscopic stellar surveys, complemented by curated samples of hot stars, very metal-poor stars, white dwarfs, and hot sub-dwarfs. The training data cover the whole sky, all Galactic components, and almost the full magnitude range of the Gaia DR3 XP sample of more than 217 million objects that also have reported parallaxes. We have achieved median uncertainties of 0.20 mag in V-band extinction, 0.01 dex in logarithmic effective temperature, 0.20 dex in surface gravity, 0.18 dex in metallicity, and $12\%$ in mass (over the full Gaia DR3 XP sample, with considerable variations in precision as a function of magnitude and stellar type). We succeeded in predicting competitive results based on Gaia DR3 XP spectra compared to classical isochrone or spectral-energy distribution fitting methods we employed in earlier works, especially for parameters $A_V$ and $T_{\rm eff}$, along with the metallicity values. Finally, we showcase some potential applications of this new catalogue, including extinction maps, metallicity trends in the Milky Way, and extended maps of young massive stars, metal-poor stars, and metal-rich stars). [abridged]

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OCCASO V. Chemical-abundance trends with Galactocentric distance and age

Context. Open clusters provide valuable information on stellar nucleosynthesis and the chemical evolution of the Galactic disc, as their age and distances can be measured more precisely with photometry than for field stars. Aims. Our aim is to study the chemical distribution of the Galactic disc using open clusters by analysing the existence of gradients with Galactocentric distance, azimuth or height from the plane and dependency with age. Methods. High-resolution spectra (R>60 000) of 194 stars belonging to 36 open clusters are used to determine atmospheric parameters and chemical abundances with two independent methods: equivalent widths and spectral synthesis. The sample has been complemented with 63 clusters with high-resolution spectroscopy from literature. Results. We measure local thermodynamic equilibrium abundances for 21 elements: α (Mg, Si, Ca, and Ti), odd-Z (Na and Al), Fe-peak (Fe, Sc, V, Cr, Mn, Co, Ni, Cu, and Zn), and neutron-capture (Sr, Y, Zr, Ba, Ce, and Nd). We also provide non-local thermodynamic equilibrium abundances for elements when corrections are available. We find inner disc young clusters enhanced in [Mg/Fe] and [Si/Fe] compared to other clusters of their age. For [Ba/Fe] we report an age trend flattening for older clusters (age<2.5 Ga). The studied elements follow the expected radial gradients as a function of their nucleosynthesis groups, which are significantly steeper for the oldest systems. For the first time, we investigate the existence of an azimuthal gradient, finding some hints of its existence among the old clusters (age>2 Ga).

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How Gaia sheds light on the Milky Way star cluster population

Star clusters are among the first celestial objects catalogued by early astronomers. As simple and coeval populations, their study has been instrumental in charting the properties of the Milky Way and providing insight into stellar evolution through the 20th century. Clusters were traditionally spotted as local stellar overdensities in the plane of the sky. In recent decades, for a limited number of nearby clusters, it became possible to identify cluster members through their clustering in proper motion space. With its astrometric data of unprecedented precision, the Gaia mission has completely revolutionised our ability to discover and characterise Milky Way star clusters, to map their large-scale distribution, and to investigate their internal structure. In this review we focus on the population of open clusters, residing in the Galactic disc. We summarise the current state of the Gaia-updated cluster census and studies of young clusters and associations. We discuss recent developments in techniques for cluster detection and age estimation. We also review results enabled by Gaia data concerning the dynamical evolution of gravitationally bound clusters and their stellar inventory.

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Exploring the dependence of chemical traits on metallicity: chemical trends for red giant stars with asteroseismic ages

Given the massive spectroscopic surveys and the Gaia mission, the Milky Way has turned into a unique laboratory to be explored using abundance ratios that show a strong dependency with time. Within this framework, the data provided through asteroseismology serve as a valuable complement. Yet, it has been demonstrated that chemical traits can not be used as universal relations across the Galaxy. To complete this picture, it is important to investigate the dependence on metallicity of the chemical ratios employed for inferring stellar ages. We aim to explore different combinations of neutron-capture, odd-Z and $α$ elements as a function of age, particularly focusing on their metallicity dependence for a sample of 74 giant field stars. Using UVES observations, we derive atmospheric parameters and high-precision line by line chemical abundances (<0.04 dex) for the entire set of spectra. Stellar ages are inferred from astereoseismic information. By fitting chemical-age trends for three different metallicity groups, we estimated their dependence on metallicity. We found that the stronger chemical-age relations ([Zr/$α$]) are not necessarily the ratios with the smaller dependence on metallicity ([Ce/$α$] and [Ce/Eu]). We confirm the [n-capture/$α$]-age trends for evolved stars, wherein the most significant correlation is evident in stars with solar-metallicity, gradually diminishing in stars with lower iron content. The lack of homogeneity within the metallicity range highlights the intricate nature of our Galaxy's star formation history and yield production. Metallicity dependence in s-process element yields and the impact of radial stellar migration challenge the reliability of using chemical abundances alone to date stars. These discoveries raise doubts about universally valid chemical clocks applicable across the entire Galaxy and its diverse metallicity ranges.

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Spectroscopic age estimates for APOGEE red-giant stars: Precise spatial and kinematic trends with age in the Galactic disc

Over the last few years, many studies have found an empirical relationship between the abundance of a star and its age. Here we estimate spectroscopic stellar ages for 178 825 red-giant stars observed by the APOGEE survey with a median statistical uncertainty of 17%. To this end, we use the supervised machine learning technique XGBoost, trained on a high-quality dataset of 3060 red-giant and red-clump stars with asteroseismic ages observed by both APOGEE and Kepler. After verifying the obtained age estimates with independent catalogues, we investigate some of the classical chemical, positional, and kinematic relationships of the stars as a function of their age. We find a very clear imprint of the outer-disc flare in the age maps and confirm the recently found split in the local age-metallicity relation. We present new and precise measurements of the Galactic radial metallicity gradient in small age bins between 0.5 and 12 Gyr, confirming a steeper metallicity gradient for $\sim2-5$ Gyr old populations and a subsequent flattening for older populations mostly produced by radial migration. In addition, we analyse the dispersion about the abundance gradient as a function of age. We find a clear power-law trend (with an exponent $β\approx0.15$) for this relation, indicating a relatively smooth radial migration history in the Galactic disc over the past $7-9$ Gyr. Departures from this power law may possibly be related to the Gaia Enceladus merger and passages of the Sagittarius dSph galaxy. Finally, we confirm previous measurements showing a steepening in the age-velocity dispersion relation at around $\sim9$ Gyr, but now extending it over a large extent of the Galactic disc (5 kpc $<R_{\rm Gal}<13$ kpc). [Abridged]

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The multiplicity fraction in 202 open clusters from Gaia

In this study, we estimate the fraction of binaries with high mass ratios for 202 open clusters in the extended solar neighbourhood (closer than 1.5 kpc from the Sun). This is one of the largest homogeneous catalogues of multiplicity fractions in open clusters to date, including the unresolved and total (close-binary) multiplicity fractions of main-sequence systems with mass ratio larger than $0.6_{-0.15}^{+0.05}$. The unresolved multiplicity fractions are estimated applying a flexible mixture model to the observed Gaia colour-magnitude diagrams of the open clusters. Then we use custom Gaia simulations to account for the resolved systems and derive the total multiplicity fractions. The studied open clusters have ages between 6.6 Myr and 3.0 Gyr and total high-mass-ratio multiplicity fractions between 6% and 80%, with a median of 18%. The multiplicity fractions increase with the mass of the primary star, as expected. The average multiplicity fraction per cluster displays an overall decreasing trend with the open cluster age up to ages about 100 Myr, above which the trend increases. Our simulations show that most of this trend is caused by complex selection effects (introduced by the mass dependence of the multiplicity fraction and the magnitude limit of our sample). Furthermore, the multiplicity fraction is not significantly correlated with the clusters' position in the Galaxy. The spread in multiplicity fraction decreases significantly with the number of cluster members (used as a proxy for cluster mass). We also find that the multiplicity fraction decreases with metallicity, in line with recent studies using field stars.

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A machine learning-based tool for open cluster membership determination in Gaia DR3

Membership studies characterising open clusters with Gaia data, most using DR2, are so far limited at magnitude G = 18 due to astrometric uncertainties at the faint end. Our goal is to extend current open cluster membership lists with faint members and to characterise the low-mass end, which members are important for many applications, in particular for ground-based spectroscopic surveys. We use a deep neural network architecture to learn the distribution of highly reliable open cluster member stars around known clusters. After that, we use the trained network to estimate new open cluster members based on their similarities in a high-dimensional space, five-dimensional astrometry plus the three photometric bands. Due to the improved astrometric precisions of Gaia DR3 with respect to DR2, we are able to homogeneously detect new faint member stars (G > 18) for the known open cluster population. Our methodology can provide extended membership lists for open clusters down to the limiting magnitude of Gaia, which will enable further studies to characterise the open cluster population, e.g. estimation of their masses, or their dynamics. These extended membership lists are also ideal target lists for forthcoming ground-based spectroscopic surveys.

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Ultracool dwarfs in Gaia DR3

Aims. In this work we use the Gaia DR3 set of ultracool dwarf candidates and complement the Gaia spectrophotometry with additional photometry in order to characterise its global properties. This includes the inference of the distances, their locus in the Gaia colour-absolute magnitude diagram and the (biased through selection) luminosity function in the faint end of the Main Sequence. We study the overall changes in the Gaia RP spectra as a function of spectral type. We study the UCDs in binary systems, attempt to identify low-mass members of nearby young associations, star forming regions and clusters, and analyse their variability properties. Results. We detect 57 young, kinematically homogeneous groups some of which are identified as well known star forming regions, associations and clusters of different ages. We find that the primary members of 880 binary systems with a UCD belong mainly to the thin and thick disk components of the Milky Way. We identify 1109 variable UCDs using the variability tables in the Gaia archive, 728 of which belong to the star forming regions defined by HMAC. We define two groups of variable UCDs with extreme bright or faint outliers. Conclusions. The set of sources identified as UCDs in the Gaia archive contains a wealth of information that will require focused follow-up studies and observations. It will help to advance our understanding of the nature of the faint end of the Main Sequence and the stellar/substellar transition.

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Gaia DR3: Apsis III -- Non-stellar content and source classification

Context. As part of the third Gaia data release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5 deg. Results. Gaia DR3 includes 1591 million sources with DSC classifications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 squared degree, where the extinction is evaluated by TGE.

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Gaia Data Release 3: Analysis of the Gaia BP/RP spectra using the General Stellar Parameterizer from Photometry

We present the General Stellar Parameterizer from Photometry (GSP-Phot), which is part of the astrophysical parameters inference system (Apsis). GSP-Phot is designed to produce a homogeneous catalogue of parameters for hundreds of millions of single non-variable stars based on their astrometry, photometry, and low-resolution BP/RP spectra. These parameters are effective temperature, surface gravity, metallicity, absolute $M_G$ magnitude, radius, distance, and extinction for each star. GSP-Phot uses a Bayesian forward-modelling approach to simultaneously fit the BP/RP spectrum, parallax, and apparent $G$ magnitude. A major design feature of GSP-Phot is the use of the apparent flux levels of BP/RP spectra to derive, in combination with isochrone models, tight observational constraints on radii and distances. We carefully validate the uncertainty estimates by exploiting repeat Gaia observations of the same source. The data release includes GSP-Phot results for 471 million sources with $G<19$. Typical differences to literature values are 110 K for $T_{\rm eff}$ and 0.2-0.25 for $\log g$, but these depend strongly on data quality. In particular, GSP-Phot results are significantly better for stars with good parallax measurements ($\varpi/σ_varpi>20$), mostly within 2kpc. Metallicity estimates exhibit substantial biases compared to literature values and are only useful at a qualitative level. However, we provide an empirical calibration of our metallicity estimates that largely removes these biases. Extinctions $A_0$ and $A_{\rm BP}$ show typical differences from reference values of 0.07-0.09 mag. MCMC samples of the parameters are also available for 95% of the sources. GSP-Phot provides a homogeneous catalogue of stellar parameters, distances, and extinctions that can be used for various purposes, such as sample selections (OB stars, red giants, solar analogues etc.).

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Gaia Data Release 3: Astrophysical parameters inference system (Apsis) I -- methods and content overview

Gaia Data Release 3 contains a wealth of new data products for the community. Astrophysical parameters are a major component of this release. They were produced by the Astrophysical parameters inference system (Apsis) within the Gaia Data Processing and Analysis Consortium. The aim of this paper is to describe the overall content of the astrophysical parameters in Gaia Data Release 3 and how they were produced. In Apsis we use the mean BP/RP and mean RVS spectra along with astrometry and photometry, and we derive the following parameters: source classification and probabilities for 1.6 billion objects, interstellar medium characterisation and distances for up to 470 million sources, including a 2D total Galactic extinction map, 6 million redshifts of quasar candidates and 1.4 million redshifts of galaxy candidates, along with an analysis of 50 million outlier sources through an unsupervised classification. The astrophysical parameters also include many stellar spectroscopic and evolutionary parameters for up to 470 million sources. These comprise Teff, logg, and m_h (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (up to 5 million), diffuse interstellar band analysis (0.5 million), activity indices (2 million), H-alpha equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). This catalogue is the most extensive homogeneous database of astrophysical parameters to date, and it is based uniquely on Gaia data.

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Gaia Data Release 3: Apsis II -- Stellar Parameters

The third Gaia data release contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the Gaia prism spectra (BP and RP) and the spectrograph (RVS). This data release opens a new window on the chemo-dynamical properties of stars in our Galaxy, essential knowledge for understanding the structure, formation, and evolution of the Milky Way. To provide insight into the physical properties of Milky Way stars, we used these data to produce a uniformly-derived, all-sky catalog of stellar astrophysical parameters (APs): Teff, logg, [M/H], [$α$/Fe], activity index, emission lines, rotation, 13 chemical abundance estimates, radius, age, mass, bolometric luminosity, distance, and dust extinction. We developed the Apsis pipeline to infer APs of Gaia objects by analyzing their astrometry, photometry, BP/RP, and RVS spectra. We validate our results against other literature works, including benchmark stars, interferometry, and asteroseismology. Here we assessed the stellar analysis performance from Apsis statistically. We describe the quantities we obtained, including our results' underlying assumptions and limitations. We provide guidance and identify regimes in which our parameters should and should not be used. Despite some limitations, this is the most extensive catalog of uniformly-inferred stellar parameters to date. These comprise Teff, logg, and [M/H] (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (5 million), diffuse interstellar band analysis (1/2 million), activity indices (2 million), H{$α$} equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). More precise and detailed astrophysical parameters based on epoch BP, RP, and RVS are planned for the next Gaia data release.

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