Search

Making use of the APOGEE DR17 catalogue with high quality data for 143 509 red giant branch stars we explore the strength of different mechanisms that causes a star to radially migrate in the Milky Way stellar disc. At any position in the disc we find stars that are more metal-rich than the local interstellar medium. This is surprising and normally attributed to the migration of these stars after their formation inside their current Galactocentric radius. Such stars are prime candidates for studying the strength of different migratory processes. We specifically select two types of metal-rich stars: (i) super metal-rich stars (⁠|$\mathrm{[Fe/H]}\gt 0.2$|⁠) and (ii) stars that are more metal-rich than their local environment. For both, we explore the distribution of orbital parameters and ages as evidence of their migration history. We find that most super metal-rich stars have experienced some amount of churning as they have orbits with |$R_g\gtrsim 5 \,{\rm kpc}$|⁠. Furthermore, about half of the super metal-rich stars are on non-circular orbits (⁠|$\mathrm{ecc} \gt 0.15$|⁠) and therefore also have experienced blurring. The metallicity of young stars in our sample is generally the same as the metallicity of the interstellar medium, suggesting they have not radially migrated yet. Stars with lower metallicity than the local environment have intermediate to old ages. We further find that super metal-rich stars have approximately the same age distribution at all Galactocentric radii, which suggests that radial migration is a key mechanism responsible for the chemical compositions of stellar populations in the Milky Way. [ABSTRACT FROM AUTHOR]

Cosmological N -body simulations of galaxies operate at the level of 'star particles' with a mass resolution on the scale of thousands of solar masses. Turning these simulations into stellar mock catalogues requires 'upsampling' the star particles into individual stars following the same phase-space density. In this paper, we introduce two new upsampling methods. First, we describe GalaxyFlow , a sophisticated upsampling method that utilizes normalizing flows to both estimate the stellar phase-space density and sample from it. Secondly, we improve on existing upsamplers based on adaptive kernel density estimation (KDE), using maximum likelihood estimation to fine-tune the bandwidth for such algorithms in a way that improves both the density estimation accuracy and upsampling results. We demonstrate our upsampling techniques on a neighbourhood of the Solar location in two simulated galaxies: Auriga 6 and h277. Both yield smooth stellar distributions that closely resemble the stellar densities seen in the Gaia DR3 catalogue. Furthermore, we introduce a novel multimodel classifier test to compare the accuracy of different upsampling methods quantitatively. This test confirms that GalaxyFlow more accurately estimates the density of the underlying star particles than methods based on KDE, at the cost of being more computationally intensive. [ABSTRACT FROM AUTHOR]

Context. Various stellar objects experience a velocity kick at some point in their evolution. These include neutron stars and black holes at their birth, or binary systems when one of the two components goes supernova. For most of these objects, the magnitude of the kick and its impact on the object dynamics remains a topic of debate. Aims. We investigate how kicks alter the velocity distribution of objects born in the Milky Way disc, both immediately after the kick and at later times, and whether these kicks are encoded in the observed population of Galactic neutron stars. Methods. We simulated the Galactic trajectories of point masses on circular orbits in the disc after being perturbed by an isotropic kick, with a Maxwellian distribution where σ = 265 km s−1. Then, we simulated the motion of these point masses for 200 Myr. These trajectories were then evaluated, either for the Milky Way population as a whole or for those passing within two kiloparsecs of the Sun, to get the time evolution of the velocities. Results. During the first 20 Myr, the bulk velocity of kicked objects becomes temporarily aligned with the cylindrical radius, implying an anisotropy in the velocity orientations. Beyond this age, the velocity distribution shifts towards lower values and settles to a median of ∼200 km s−1. Around the Sun, the distribution also loses its upper tail, primarily due to unbound objects escaping the Galaxy. We compared this to the velocities of Galactic pulsars and find that pulsars show a similar evolution with characteristic age. Conclusions. The shift in the velocity distribution is due to bound objects spending most of their orbits at larger radii after the kick. They are, therefore, decelerated by the Galactic potential. We find the same deceleration for nearby objects and the total population, and conclude that it is also observed in Galactic pulsars. Because of this effect, the (scalar) speeds of old neutron stars provide little information about their kicks at birth. [ABSTRACT FROM AUTHOR]

Context. The study of the Milky Way is living a golden era thanks to the enormous high-quality datasets delivered by Gaia, and space asteroseismic and ground-based spectroscopic surveys. However, the current major challenge to reconstructing the chronology of the Milky Way is the difficulty to derive precise stellar ages for large samples of stars. The colour–magnitude diagram (CMD) fitting technique offers an alternative to individual age determinations to derive the star formation history (SFH) of complex stellar populations. Aims. Our aim is to obtain a detailed dynamically evolved SFH (deSFH) of the solar neighbourhood, and the age and metallicity distributions that result from it. We define deSFH as the amount of mass transformed into stars, as a function of time and metallicity, in order to account for the population of stars contained in a particular volume. Methods. We present a new package to derive SFHs from CMD fitting tailored to work with Gaia data, called CMDft.Gaia, and we use it to analyse the CMD of the Gaia Catalogue of Nearby Stars (GCNS), which contains a complete census of the (mostly thin disc) stars currently within 100 pc of the Sun. Results. We present an unprecedentedly detailed view of the evolution of the Milky Way disc at the solar radius. The bulk of star formation started 11–10.5 Gyr ago at metallicity around solar, and continued with a slightly decreasing metallicity trend until 6 Gyr ago. Between 6 and 4 Gyr ago, a notable break in the age–metallicity distribution is observed, with three stellar populations with distinct metallicities (sub-solar, solar, and super-solar), possibly indicating some dramatic event in the life of our Galaxy. Star formation then resumed 4 Gyr ago with a somewhat bursty behaviour, metallicity near solar and average star formation rate higher than in the period before 6 Gyr ago. The derived metallicity distribution closely matches precise spectroscopic data, which also show stellar populations deviating from solar metallicity. Interestingly, our results reveal the presence of intermediate-age populations exhibiting both a metallicity typical of the thick disc, approximately [M/H] ≃ −0.5, and super-solar metallicity. Conclusions. The many tests performed indicate that, with high-precision photometric and distance data such as that provided by Gaia, CMDft.Gaia is able to achieve a precision of ≲10% and an accuracy better than 6% in the dating of stellar populations, even at old ages. A comparison with independent spectroscopic metallicity information shows that metallicity distributions are also determined with high precision, without imposing any a priori metallicity information in the fitting process. This opens the door to obtaining detailed and robust information on the evolution of the stellar populations of the Milky Way over cosmic time. As an example, we provide in this paper an unprecedentedly detailed view of the age and metallicity distributions of the stars within 100 pc of the Sun. [ABSTRACT FROM AUTHOR]

Context. The morphology of open clusters plays a major role in the study of their dynamic evolution. The study of their morphological coherence, namely, the three-dimensional (3D) difference between the inner and outer morphologies of open clusters, allows us to obtain a better understanding of the morphological evolution of open clusters. Aims. We aim to investigate the morphological coherence of 132 open clusters with up to 1 kpc from the Sun in the three-dimensional (3D) space within the heliocentric cartesian coordinate frame. The 132 open clusters have a 3D core-shell structure and conform to the ellipsoidal model, with all of them coming from a catalog of publicly available clusters in the literature. Methods. We employed the ellipsoid fitting method to delineate the 3D spatial structure of the sample clusters, while using the morphological dislocation (MD) defined in our previous work and the ellipticity ratio (ER) of the clusters' inner and outer structures to characterize the morphological coherence of the sample clusters. Results. The results show an inverse correlation between the ER of the sample clusters and the number of their members, indicating that sample clusters with a much more elliptical external morphology than internal shape generally tend to host a large number of members. Meanwhile, a slight shrinking of the MD of the sample clusters with their members' number may shed light on the significant role of the gravitational binding of the sample clusters in maintaining their morphological stability. Moreover, there are no correlations between the MD and ER of the sample clusters and their age. They are also not significantly correlated with the X-axis, the Y-axis, their orbital eccentricities, and the radial and vertical forces on them. However, the ER of the sample clusters displays some fluctuations in the distributions between it and the above covariates, implying that the morphologies of the sample clusters are sensitive to the external environment if sample effects are not taken into account. Finally, the analysis of the 3D spatial shapes of sample clusters with a small ER or a large ER demonstrates that the number of members lays an important foundation for forming a dense internal system for sample clusters. At the same time, the MD of the sample clusters can serve well as an indicator of their morphological stability, which is built upon a certain amount of member stars. Conclusions. We present a new insight into the morphological coherence of open clusters, attributed to the combination of their gravitational binding capacity and external environmental perturbations. [ABSTRACT FROM AUTHOR]

We present several machine learning (ML) models developed to efficiently separate stars formed in situ in Milky Way-type galaxies from those that were formed externally and later accreted. These models, which include examples from artificial neural networks, decision trees, and dimensionality reduction techniques, are trained on a sample of disc-like, Milky Way-mass galaxies drawn from the artemis cosmological hydrodynamical zoom-in simulations. We find that the input parameters which provide an optimal performance for these models consist of a combination of stellar positions, kinematics, chemical abundances ([Fe/H] and [α/Fe]), and photometric properties. Models from all categories perform similarly well, with area under the precision–recall curve (PR-AUC) scores of ≃ 0.6. Beyond a galactocentric radius of 5 kpc, models retrieve |$\gt 90~{{\ \rm per\ cent}}$| of accreted stars, with a sample purity close to 60 per cent, however the purity can be increased by adjusting the classification threshold. For one model, we also include host galaxy-specific properties in the training, to account for the variability of accretion histories of the hosts, however this does not lead to an improvement in performance. The ML models can identify accreted stars even in regions heavily dominated by the in-situ component (e.g. in the disc), and perform well on an unseen suite of simulations (the auriga simulations). The general applicability bodes well for application of such methods on observational data to identify accreted substructures in the Milky Way without the need to resort to selection cuts for minimizing the contamination from in-situ stars. [ABSTRACT FROM AUTHOR]

In order to constrain the evolutionary history of the Milky Way, we hunt for faint RR Lyrae stars (RRLs) using Dark Energy Camera data from the High cadence Transient Survey and the Halo Outskirts With Variable Stars survey. We report the detection of |$\sim$| 500 RRLs, including previously identified stars and |$\sim$| 90 RRLs not yet reported. We identify nine new RRLs beyond 100 kpc from the Sun, most of which are classified as fundamental-mode pulsators. The periods and amplitudes of the distant RRLs do not place them in either one of the two classical Oosterhoff groups, but in the Oosterhoff intermediate region. We detect two groups of clumped distant RRLs with similar distances and equatorial coordinates, which we interpret as an indication of their association with undiscovered bound or unbound satellites. We study the halo density profile using spheroidal and ellipsoidal (⁠|$q=0.7$|⁠) models, following a Markov chain Monte Carlo methodology. For a spheroidal halo, our derived radial profile is consistent with a broken power law with a break at |$18.1^{+2.1}_{-1.1}$| kpc separating the inner and the outer halo, and an outer slope of |$-4.47^{+0.11}_{-0.18}$|⁠. For an ellipsoidal halo, the break is located at |$24.3^{+2.6}_{-3.2}$| kpc and the outer slope is |$-4.57^{+0.17}_{-0.25}$|⁠. The break in the density profile is a feature visible in different directions of the halo. The similarity of these radial distributions with previous values reported in the literature seems to depend on the regions of the sky surveyed (direction and total area) and halo tracer used. Our findings are compatible with simulations and observations that predict that the outer regions of Milky Way-like galaxies are mainly composed of accreted material. [ABSTRACT FROM AUTHOR]

Large-scale astrophysics data sets present an opportunity for new machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional searches. To this end, we demonstrate how Classification Without Labels (CWoLa), a weakly supervised anomaly detection method, can help identify cold stellar streams within the more than one billion Milky Way stars observed by the Gaia satellite. CWoLa operates without the use of labelled streams or knowledge of astrophysical principles. Instead, it uses a classifier to distinguish between mixed samples for which the proportions of signal and background samples are unknown. As a proof of concept, we demonstrate that this computationally lightweight strategy is able to detect both simulated streams and the known stream GD-1 in data. Originally designed for high-energy collider physics, this technique may have broad applicability within astrophysics as well as other domains interested in identifying localized anomalies.

With the plentiful information available in the Gaia BP/RP spectra, there is significant scope for applying discriminative models to extract stellar atmospheric parameters and abundances. We describe an approach to leverage an 'Uncertain Neural Network' model trained on APOGEE data to provide high-quality predictions with robust estimates for per-prediction uncertainty. We report median formal uncertainties of 0.068 dex, 69.1 K, 0.14 dex, 0.031 dex, 0.040 dex, and 0.029 dex for [Fe/H], T eff, log  g , [C/Fe], [N/Fe], and [α/M], respectively. We validate these predictions against our APOGEE training data, LAMOST, and Gaia GSP- phot stellar parameters, and see a strong correlation between our predicted parameters and those derived from these surveys. We investigate the information content of the spectra by considering the 'attention' our model pays to different spectral features compared to expectations from synthetic spectra calculations. Our model's predictions are applied to the Gaia data set, and we produce a publicly available catalogue of our model's predictions. [ABSTRACT FROM AUTHOR]

The oldest stars in the Milky Way (born in the first few billion years) are expected to have a high density in the inner few kpc, spatially overlapping with the Galactic bulge. We use spectroscopic data from the Pristine Inner Galaxy Survey (PIGS) to study the dynamical properties of ancient, metal-poor inner Galaxy stars. We compute distances using starhorse , and orbital properties in a barred Galactic potential. With this paper, we release the spectroscopic AAT/PIGS catalogue (13 235 stars). We find that most PIGS stars have orbits typical for a pressure-supported population. The fraction of stars confined to the inner Galaxy decreases with decreasing metallicity, but many very metal-poor stars (VMP; [Fe/H] <−2.0) stay confined (⁠|$\sim 60~{{\ \rm per \, cent}}$| stay within 5 kpc). The azimuthal velocity vϕ also decreases between [Fe/H] = −1.0 and −2.0, but is constant for VMP stars (at ∼+40 km s−1). The carbon-enhanced metal-poor (CEMP) stars in PIGS appear to have similar orbital properties compared to normal VMP stars. Our results suggest a possible transition between two spheroidal components – a more metal-rich, more concentrated, faster rotating component, and a more metal-poor, more extended and slower/non-rotating component. We propose that the former may be connected to pre-disc in-situ stars (or those born in large building blocks), whereas the latter may be dominated by contributions from smaller galaxies. This is an exciting era where large metal-poor samples, such as in this work (as well as upcoming surveys, e.g. 4MOST), shed light on the earliest evolution of our Galaxy. [ABSTRACT FROM AUTHOR]

Context. The emergence of the disc in our Galaxy and the relation between thick and thin disc formation and evolution is still a matter of debate. The chemo-dynamical characterization of disc stars is key to resolving this question, particularly at parameter regimes, where both disc components overlap, such as the region around [Fe/H] ∼ −0.7 corresponding to the thin disc's metal-poor end. Aims. In this paper, we re-assess the recent detection of a metal-poor extension of stars moving with thin-disc-like rotational velocities between −2 < [Fe/H] < −0.7, carried out on the basis of metallicity estimates obtained from photometric data and their rotational velocity distributions. Methods. We explored the chemo-dynamical properties of metal-poor stars from the recent Gaia third data release (DR3), which includes the first catalog of metallicity estimates from the Radial Velocity Spectrometer (RVS) experiment. We complemented them with the two largest high-resolution (λ/dλ >  20 000) spectroscopic surveys available: the GALAH DR3 and the APOGEE DR17. Results. We confirm that there are high-angular-momentum stars moving in thin-disc-like orbits, that is, with a high angular momentum of Lz/Jtot >  0.95, and close to the Galactic plane, |Zmax|< 750 pc, reaching metallicity values down to [Fe/H] ∼ −1.5. We also find tentative evidence for stars moving on such orbits at lower metallicities, down to [Fe/H] ∼ −2.5, albeit in smaller numbers. Based on their chemical trends, thin-disc-like stars with [Fe/H] < −1 would have formed in a medium that is less chemically evolved than the bulk of the thick disc. Stars with chemical abundances typical of the thin disc appear at metallicities between −1 < [Fe/H] < −0.7. [ABSTRACT FROM AUTHOR]

From the chemodynamical properties of tidal debris in the Milky Way, it has been inferred that the dwarf satellites that have been disrupted had different chemical abundances from their present-day counterparts of similar mass that survive today, specifically, they had lower [Fe/H] and higher [Mg/Fe]. Here we use the A rtemis simulations to study the relation between the chemical abundances of disrupted progenitors of MW-mass galaxies and their stellar mass, and the evolution of the stellar mass–metallicity relations (MZR) of this population with redshift. We find that these relations have significant scatter, which correlates with the accretion redshifts (z acc) of satellites, and with their cold gas fractions. We investigate the MZRs of dwarf populations accreted at different redshifts and find that they have similar slopes, and also similar with the slope of the MZR of the surviving population (≈0.32). However, the entire population of disrupted dwarfs displays a steeper MZR, with a slope of ≈0.48, which can be explained by the changes in the mass spectrum of accreted dwarf galaxies with redshift. We find strong relations between the (mass-weighted) 〈 z acc〉 of the disrupted populations and their global chemical abundances (〈[Fe/H]〉 and 〈[Mg/Fe]〉), which suggests that chemical diagnostics of disrupted dwarfs can be used to infer the types of merger histories of their hosts. For the case of the MW, our simulations predict that the bulk of the disrupted population was accreted at 〈 z acc〉 ≈ 2, in agreement with other findings. We also find that disrupted satellites form and evolve in denser environments, closer to their hosts, than their present-day counterparts. [ABSTRACT FROM AUTHOR]

We present an update to Via Machinae , an automated stellar stream-finding algorithm based on the deep learning anomaly detector ANODE. Via Machinae identifies stellar streams within Gaia , using only angular positions, proper motions, and photometry, without reference to a model of the Milky Way potential for orbit integration or stellar distances. This new version, Via Machinae 2.0 , includes many improvements and refinements to nearly every step of the algorithm, that altogether result in more robust and visually distinct stream candidates than our original formulation. In this work, we also provide a quantitative estimate of the false positive rate of Via Machinae 2.0 by applying it to a simulated Gaia -mock catalogue based on galaxia , a smooth model of the Milky Way that does not contain substructure or stellar streams. Finally, we perform the first full-sky search for stellar streams with Via Machinae 2.0 , identifying 102 streams at high significance within the Gaia Data Release 2, of which only 10 have been previously identified. While follow-up observations for further confirmation are required, taking into account the false positive rate presented in this work, we expect approximately 90 of these stream candidates to correspond to real stellar structures. [ABSTRACT FROM AUTHOR]

Low-mass (sub)stellar objects represent the low end of the initial mass function, the transition to free-floating planets and a prominent interloper population in the search for high-redshift galaxies. To what accuracy can photometry only classify these? JWST/NIRCam has several advantages over Hubble Space Telescope (HST)/WFC3 near-infrared (NIR): more filters, a greater wavelength range, and greater spatial resolution. Here, we present a catalogue of (sub)stellar dwarfs identified in the cosmic evolution early release science survey (CEERS). We identify 518 stellar objects down to mF200W 28 using half-light radius, a full three magnitudes deeper than typical HST/WFC3 images. A k-means nearest neighbour (kNN) algorithm identifies and types these sources, using four HST/WFC3 and four NIRCam filters, trained on IRTF / spex spectra of nearby brown dwarfs. The kNN with four neighbours classifies well within two subtypes: e.g. M2±2, achieving ∼95 per cent precision and recall. In CEERS, we find 9 M8±2, 2 L6±2, 1 T4±2, and 15 T8±2. We compare the observed long wavelength NIRCam colours – not used in the kNN – to those expected for brown dwarf atmospheric models. The NIRCam F356W−F444W and F410M−F444W colours are redder by a magnitude for the type assigned by the kNN, hinting at a wider variety of atmospheres for these objects. We find a 300–350 pc scale height for M6±2 dwarfs plus a second structural component and a 150–200 pc scale height for T6±2 type dwarfs, consistent with literature values. A single M8±2 dwarf is spectroscopically confirmed at 4 kpc distance. [ABSTRACT FROM AUTHOR]

RR Lyrae are a well-known class of pulsating horizontal branch stars widely used as tracers of old, metal-poor stellar populations. However, mounting observational evidence shows that a significant fraction of these stars may be young and metal-rich. Here, through detailed binary stellar evolution modelling, we show that all such metal-rich RR Lyrae can be naturally produced through binary interactions. Binary companions of these RR Lyrae stars formed through binary interactions partly strip their progenitor's envelopes during a preceding red giant phase. As a result, stripped horizontal branch stars become bluer than their isolated stellar evolution counterparts and thus end up in the instability strip. In contrast, in the single evolution scenario, the stars can attain such colours only at large age and low metallicity. While binary-made RR Lyrae can possess any ages and metallicities, their Galactic population is relatively young (1 – |$9\, {\rm Gyr}$|⁠) and dominated by the thin disc and the bulge. We show that Galactic RR Lyrae from binary evolution are produced at rates compatible with the observed metal-rich population and have consistent G -band magnitudes, Galactic kinematics, and pulsation properties. Furthermore, these systems dominate the RR Lyrae population in the solar neighbourhood. We predict that all metal-rich RR Lyrae have an A, F, G, or K-type companion with a long orbital period (⁠|$P \gtrsim 1000\, {\rm d}$|⁠). Observationally characterizing the orbital periods and masses of such stellar companions will provide valuable new constraints on mass and angular momentum-loss efficiency for Sun-like accretors and the nature of RR Lyrae populations. [ABSTRACT FROM AUTHOR]

Estimating precise metallicity of M dwarfs is a well-known difficult problem due to their complex spectra. In this work, we empirically calibrate the metallicity using wide binaries with a F, G, or K dwarf and a M dwarf companion. With 1308 FGK+M wide binaries well observed by LAMOST, we calibrated M dwarf's [Fe/H] by using the Stellar LAbel Machine (SLAM) model, a data-driven method based on support vector regression. The [Fe/H] labels of the training data are from FGK companions in range of [−1,0.5] dex. The T effs are based on APOGEE, spanning [3100, 4400] K. The uncertainties in SLAM estimates of [Fe/H] and T eff are ∼0.15 dex and ∼40 K, respectively, at snri >100, where snri is the signal-to-noise ratio (SNR) at i band of M dwarf spectra. We applied the trained SLAM model to determine the [Fe/H] and T eff for ∼630 000 M dwarfs with low-resolution spectra in LAMOST DR9. Compared to other literature also using FGK+M wide binaries for calibration, our [Fe/H] estimates show no bias but a scatter of ∼0.14–0.18 dex. However, the [Fe/H] compared to APOGEE shows a systematic difference of ∼0.10–0.15 dex with a scatter of ∼0.15–0.20 dex. While the T eff compared to APOGEE has a bias of 3 K with a scatter of 62 K, it is systematically higher by 180 K compared to other calibrations based on the bolometric temperature. Finally, we calculated the ζ index for 1308 M dwarf secondaries and presents a moderate correlation between ζ and [Fe/H]. [ABSTRACT FROM AUTHOR]

Large-scale astrophysics data sets present an opportunity for new machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional searches. To this end, we demonstrate how Classification Without Labels (CWoLa), a weakly supervised anomaly detection method, can help identify cold stellar streams within the more than one billion Milky Way stars observed by the Gaia satellite. CWoLa operates without the use of labelled streams or knowledge of astrophysical principles. Instead, it uses a classifier to distinguish between mixed samples for which the proportions of signal and background samples are unknown. As a proof of concept, we demonstrate that this computationally lightweight strategy is able to detect both simulated streams and the known stream GD-1 in data. Originally designed for high-energy collider physics, this technique may have broad applicability within astrophysics as well as other domains interested in identifying localized anomalies. [ABSTRACT FROM AUTHOR]

In general, the atypical high velocity of some stars in the Galaxy can only be explained by invoking acceleration mechanisms related to extreme astrophysical events in the Milky Way. Using astrometric data from Gaia and the photometric information in 12 filters of the S-PLUS, we performed a kinematic, dynamical, and chemical analysis of 64 stars with Galactocentric velocities higher than 400 |$\mathrm{km\, s}^{-1}$|⁠. All the stars are gravitationally bound to the Galaxy and exhibit halo kinematics. Some of the stars could be remnants of structures such as the Sequoia and the Gaia-Sausage/Enceladus. Supported by orbital and chemical analysis, we identified Gaia DR3 5401875170994688896 as a star likely to be originated at the centre of the Galaxy. Application of a machine learning technique to the S-PLUS photometric data allows us to obtain very good estimates of magnesium abundances for this sample of high-velocity stars. [ABSTRACT FROM AUTHOR]

The iMaNGA project uses a forward-modelling approach to compare the predictions of cosmological simulations with observations from SDSS-IV/MaNGA. We investigate the dependency of age and metallicity radial gradients on galaxy morphology, stellar mass, stellar surface mass density (Σ*), and environment. The key of our analysis is that observational biases affecting the interpretation of MaNGA data are emulated in the theoretical iMaNGA sample. The simulations reproduce the observed global stellar population scaling relations with positive correlations between galaxy mass and age/metallicity quite well and also produce younger stellar populations in late-type in agreement with observations. We do find interesting discrepancies, though, that can inform the physics and further development of the simulations. Ages of spiral galaxies and low-mass ellipticals are overestimated by about 2–4 Gyr. Radial metallicity gradients are steeper in iMaNGA than in MaNGA, a discrepancy most prominent in spiral and lenticular galaxies. Also, the observed steepening of metallicity gradients with increasing galaxy mass is not well matched by the simulations. We find that the theoretical radial profiles of surface mass density Σ* are steeper than in observations except for the most massive galaxies. In both MaNGA and iMaNGA [Z/H] correlates with Σ*, however, the simulations systematically predict lower [Z/H] by almost a factor of 2 at any Σ*. Most interestingly, for galaxies with stellar mass log  M * ≤ 10.80 M⊙, the MaNGA data reveal a positive correlation between galaxy radius and [Z/H] at fixed Σ*, which is not recovered in iMaNGA. Finally, the dependence on environmental density is negligible in both the theoretical iMaNGA and the observed MaNGA data. [ABSTRACT FROM AUTHOR]

Context. The inner Galaxy is a complex environment, and the relative contributions of different formation scenarios to its observed morphology and stellar properties are still debated. The different components are expected to have different spatial, kinematic, and metallicity distributions, and a combination of photometric, spectroscopic, and astrometric large-scale surveys is needed to study the formation and evolution of the Galactic bulge. Aims. The Blanco DECam Bulge Survey (BDBS) provides near-ultraviolet to near-infrared photometry for approximately 250 million unique stars over more than 200 square degrees of the southern Galactic bulge. By combining BDBS photometry with the latest Gaia astrometry, we aim to characterize the chemodynamics of red clump stars across the BDBS footprint using an unprecedented sample size and sky coverage. Methods. Our field of view of interest is |ℓ| ≤ 10°, −10° ≤b ≤ −3°. We constructed a sample of approximately 2.3 million red clump giants in the bulge with photometric metallicities, BDBS photometric distances, and proper motions. Photometric metallicities are derived from a (u − i)0 versus [Fe/H] relation; astrometry, including precise proper motions, is from the third data release (DR3) of the ESA satellite Gaia. We studied the kinematics of the red clump stars as a function of sky position and metallicity by investigating proper-motion rotation curves, velocity dispersions, and proper-motion correlations across the southern Galactic bulge. Results. By binning our sample into eight metallicity bins in the range of −1.5 dex < [Fe/H] < +1 dex, we find that metal-poor red clump stars exhibit lower rotation amplitudes, at ∼29 km s−1 kpc−1. The peak of the angular velocity is ∼39 km s−1 kpc−1 for [Fe/H] ∼ −0.2 dex, exhibiting declining rotation at higher [Fe/H]. The velocity dispersion is higher for metal-poor stars, while metal-rich stars show a steeper gradient with Galactic latitude, with a maximum dispersion at low latitudes along the bulge minor axis. Only metal-rich stars ([Fe/H] ≳ −0.5 dex) show clear signatures of the bar in their kinematics, while the metal-poor population exhibits isotropic motions with an axisymmetric pattern around Galactic longitude ℓ = 0. Conclusions. This work describes the largest sample of bulge stars with distance, metallicity, and astrometry reported to date, and shows clear kinematic differences with metallicity. The global kinematics over the bulge agrees with earlier studies. However, we see striking changes with increasing metallicity, and, for the first time, kinematic differences for stars with [Fe/H]>  − 0.5, suggesting that the bar itself may have kinematics that depends on metallicity. [ABSTRACT FROM AUTHOR]

Context. In June 2022, Gaia DR3 provided the astronomy community with about one million spectra from the Radial Velocity Spectrometer (RVS) covering the CaII triplet region. In the next Gaia data releases, we anticipate the number of RVS spectra to successively increase from several 10 million spectra to eventually more than 200 million spectra. Thus, stellar spectra are projected to be produced on an 'industrial scale', with numbers well above those for current and anticipated ground-based surveys. However, one-third of the published spectra have 15 ≤ S /N ≤ 25 per pixel such that they pose problems for classical spectral analysis pipelines, and therefore, alternative ways to tap into these large datasets need to be devised. Aims. We aim to leverage the versatility and capabilities of machine learning techniques for supercharged stellar parametrisation by combining Gaia-RVS spectra with the full set of Gaia products and high-resolution, high-quality ground-based spectroscopic reference datasets. Methods. We developed a hybrid convolutional neural network (CNN) that combines the Gaia DR3 RVS spectra, photometry (G, G_BP, G_RP), parallaxes, and XP coefficients to derive atmospheric parameters (Teff, log(g) as well as overall [M/H]) and chemical abundances ([Fe/H] and [α/M]). We trained the CNN with a high-quality training sample based on APOGEE DR17 labels. Results. With this CNN, we derived homogeneous atmospheric parameters and abundances for 886 080 RVS stars that show remarkable precision and accuracy compared to external datasets (such as GALAH and asteroseismology). The CNN is robust against noise in the RVS data, and we derive very precise labels down to S/N =15. We managed to characterise the [α/M] - [M/H] bimodality from the inner regions to the outer parts of the Milky Way, which has never been done using RVS spectra or similar datasets. Conclusions. This work is the first to combine machine learning with such diverse datasets and paves the way for large-scale machine learning analysis of Gaia-RVS spectra from future data releases. Large, high-quality datasets can be optimally combined thanks to the CNN, thereby realising the full power of spectroscopy, astrometry, and photometry. [ABSTRACT FROM AUTHOR]

We present an initial-final mass relation derived from the spectroscopically complete volume-limited 40 pc sample of white dwarfs. The relation is modelled using population synthesis methods to derive an initial stellar population which can be fit to the observed mass distribution of white dwarfs. The population synthesis accounts for binary evolution, where higher mass white dwarfs are more likely to be merger products than their lower mass counterparts. Uncertainties are accounted from the initial mass function, stellar metallicity, and age of the Galactic disc. We also consider biases induced by the spectral type of the white dwarf where pure-hydrogen atmosphere white dwarfs are likely to have more accurate masses, whilst the full white dwarf sample will have fewer biases arising from spectral evolution. We provide a four-piece segmented linear regression using Monte Carlo methods to sample the 1-σ range of uncertainty on the initial stellar population. The derived initial-final mass relation provides a self-consistent determination of the progenitor mass for white dwarfs in the Solar neighbourhood which will be useful to study the local stellar formation history. [ABSTRACT FROM AUTHOR]

The merger locations of binary neutron stars (BNSs) encode their galactic kinematics and provide insights into their connection to short gamma-ray bursts (SGRBs). In this work, we use the sample of Galactic BNSs with measured proper motions to investigate their kinematics and predict their merger locations. Using a synthetic image of the Milky Way and its Galactic potential we analyse the BNS mergers as seen from an extragalactic viewpoint and compare them to the location of SGRBs on and around their host galaxies. We find that the Galactocentric transverse velocities of the BNSs are similar in magnitude and direction to those of their Local Standards of Rest, which implies that the present-day systemic velocities are not isotropically oriented and the peculiar velocities might be as low as those of BNS progenitors. Both systemic and peculiar velocities fit a lognormal distribution, with the peculiar velocities being as low as ∼22–157 km s−1. We also find that the observed BNS sample is not representative of the whole Galactic population, but rather of systems born around the Sun's location with small peculiar velocities. When comparing the predicted BNS merger locations to SGRBs, we find that they cover the same range of projected offsets, host-normalized offsets, and fractional light. Therefore, the spread in SGRB locations can be reproduced by mergers of BNSs born in the Galactic disc with small peculiar velocities, although the median offset match is likely a coincidence due to the biased BNS sample. [ABSTRACT FROM AUTHOR]

The radial metallicity distribution of the Milky Way's disc is an important observational constraint for models of the formation and evolution of our Galaxy. It informs our understanding of the chemical enrichment of the Galactic disc and the dynamical processes therein, particularly radial migration. We investigate how the metallicity changes with guiding radius in the thin disc using a sample of red giant stars with robust astrometric, spectroscopic, and asteroseismic parameters. Our sample contains 668 stars with guiding radii 4 < R g < 11 kpc and asteroseismic ages covering the whole history of the thin disc with precision |${\approx} 25 {{\, \rm per\ cent}}$|⁠. We use MCMC analysis to measure the gradient and its intrinsic spread in bins of age and construct a hierarchical Bayesian model to investigate the evolution of these parameters independently of the bins. We find a smooth evolution of the gradient from ≈−0.07 dex kpc−1 in the youngest stars to ≈−0.04 dex kpc−1 in stars older than 10 Gyr, with no break at intermediate ages. Our results are consistent with those based on asteroseismic ages from CoRoT , with that found in Cepheid variables for stars younger than 1 Gyr, and with open clusters for stars younger than 6 Gyr. For older stars we find a significantly lower metallicity in our sample than in the clusters, suggesting a survival bias favouring more metal-rich clusters. We also find that the chemical evolution model of Chiappini '09 is too metal poor in the early stages of disc formation. Our results provide strong new constraints for the growth and enrichment of the thin disc and radial migration, which will facilitate new tests of model conditions and physics. [ABSTRACT FROM AUTHOR]

The Gaia -Sausage/Enceladus (GS/E) structure is an accretion remnant that comprises a large fraction of the Milky Way's stellar halo. We study GS/E using high-purity samples of kinematically selected stars from APOGEE DR16 and Gaia. Employing a novel framework to account for kinematic selection biases using distribution functions, we fit density profiles to these GS/E samples and measure their masses. We find that GS/E has a shallow density profile in the inner Galaxy, with a break between 15 and 25 kpc beyond which the profile steepens. We also find that GS/E is triaxial, with axis ratios 1:0.55:0.45 (nearly prolate), and the major axis is oriented about 80° from the Sun–Galactic centre line and 16° above the plane. We measure a stellar mass for GS/E of |$1.45\, ^{+0.92}_{-0.51}\, \mathrm{(stat.)}\, ^{+0.13}_{-0.37} \mathrm{(sys.)}\ \times 10^{8}$| M⊙. Our mass estimate is lower than others in the literature, a finding we attribute to the excellent purity of the samples we work with. We also fit a density profile to the entire Milky Way stellar halo, finding a mass in the range of 6.7–8.4 × 108 M⊙, and implying that GS/E could make up as little as 15–25 per cent of the mass of the Milky Way stellar halo. Our lower stellar mass combined with standard stellar mass-to-halo mass relations implies that GS/E constituted a minor 1:8 mass-ratio merger at the time of its accretion. [ABSTRACT FROM AUTHOR]

Short-period Galactic white dwarf binaries detectable by Laser Interferometer Space Antenna are the only guaranteed persistent sources for multimessenger gravitational-wave astronomy. Large-scale surveys in the 2020s present an opportunity to conduct preparatory science campaigns to maximize the science yield from future multimessenger targets. The Nancy Grace Roman Space Telescope Galactic Bulge Time-Domain Survey will (in its Reference Survey design) image seven fields in the Galactic Bulge approximately 40 000 times each. Although the Reference Survey cadence is optimized for detecting exoplanets via microlensing, it is also capable of detecting short-period white dwarf binaries. In this paper, we present forecasts for the number of detached short-period binaries the Roman Galactic Bulge Time-Domain Survey will discover and the implications for the design of electromagnetic surveys. Although population models are highly uncertain, we find a high probability that the baseline survey will detect of the order of ∼5 detached white dwarf binaries. The Reference Survey would also have a |${\gtrsim} 20\,{\rm per\,cent}$| chance of detecting several known benchmark white dwarf binaries at the distance of the Galactic Bulge. [ABSTRACT FROM AUTHOR]

The gravitational wave (GW) signals from the Galactic population of cataclysmic variables (CVs) have yet to be carefully assessed. Here, we estimate these signals and evaluate their significance for Laser Interferometer Space Antenna (LISA). First, we find that at least three known systems are expected to produce strong enough signals to be individually resolved within the first four years of LISA 's operation. Secondly, CVs will contribute significantly to the LISA Galactic binary background, limiting the mission's sensitivity in the relevant frequency band. Third, we predict a spike in the unresolved GW background at a frequency corresponding to the CV minimum orbital period. This excess noise may impact the detection of other systems near this characteristic frequency. Fourth, we note that the excess noise spike amplitude and location associated with P min ∼ 80 min can be used to measure the CV space density and period bounce location with complementary and simple GW biases compared to the biases and selection effects plaguing samples selected from electromagnetic signals. Our results highlight the need to explicitly include the Galactic CV population in the LISA mission planning, both as individual GW sources and generators of background noise, as well as the exciting prospect of characterising the CV population through their GW emission. [ABSTRACT FROM AUTHOR]

The gravitational interactions between the Milky Way and in-falling satellites offer a wealth of information about the formation and evolution of our Galaxy. In this paper, we explore the high-dimensionality of the GALAH DR3 plus Gaia eDR3 data set to identify new tidally stripped candidate stars of the nearby star cluster Omega Centauri (⁠|$\omega \, \mathrm{Cen}$|⁠). We investigate both the chemical and dynamical parameter space simultaneously, and identify cluster candidates that are spatially separated from the main cluster body, in regions where contamination by halo field stars is high. Most notably, we find candidates for |$\omega \, \mathrm{Cen}$| scattered in the halo extending to more than 50° away from the main body of the cluster. Using a grid of simulated streams generated with |$\omega \, \mathrm{Cen}$| -like orbital properties, we then compare the on sky distribution of these candidates to the models. The results suggest that if |$\omega \, \mathrm{Cen}$| had a similar initial mass as its present day mass, then we can place a lower limit on its time of accretion at tacc > 7 Gyr ago. Alternatively, if the initial stellar mass was significantly larger, as would be expected if |$\omega \, \mathrm{Cen}$| is the remnant core of a dwarf Galaxy, then we can constrain the accretion time to tacc > 4 Gyr ago. Taken together, these results are consistent with the scenario that |$\omega \, \mathrm{Cen}$| is the remnant core of a disrupted dwarf galaxy. [ABSTRACT FROM AUTHOR]

We develop, validate and apply a forward model to estimate stellar atmospheric parameters (T eff, log  g , and [Fe/H]), revised distances and extinctions for 220 million stars with XP spectra from Gaia DR3. Instead of using ab initio stellar models, we develop a data-driven model of Gaia XP spectra as a function of the stellar parameters, with a few straightforward built-in physical assumptions. We train our model on stellar atmospheric parameters from the LAMOST survey, which provides broad coverage of different spectral types. We model the Gaia XP spectra with all of their covariances, augmented by 2MASS and WISE photometry that greatly reduces degeneracies between stellar parameters, yielding more precise determinations of temperature and dust reddening. Taken together, our approach overcomes a number of important limitations that the astrophysical parameters released in Gaia DR3 faced, and exploits the full information content of the data. We provide the resulting catalogue of stellar atmospheric parameters, revised parallaxes, and extinction estimates, with all their uncertainties. The modelling procedure also produces an estimate of the optical extinction curve at the spectral resolution of the XP spectra (R ∼ 20–100), which agrees reasonably well with the R (V) = 3.1 CCM model. Remaining limitations that will be addressed in future work are that the model assumes a universal extinction law, ignores binary stars and does not cover all parts of the Hertzsprung–Russell Diagram (e.g. white dwarfs). [ABSTRACT FROM AUTHOR]

This is the third paper in a series that attempts to observe a clear signature of the Galactic bar/bulge using kinematic observations of the bulge stellar populations in low foreground extinction windows. We report on the detection of ∼100 000 new proper motions in four fields covering the far side of the Galactic bar/bulge, at negative longitudes. Our proper motions have been obtained using observations from the Advance Camera for Surveys (ACS), on board of the Hubble Space Telescope (HST), with a time-baseline of 8–9 years, which has produced accuracies better than 0.5 mas yr−1 for a significant fraction of the stellar populations with F 814 W < 23 mag. Interestingly, as shown in previous works, the Hess diagrams show a strikingly similar proper motion distribution to fields closer to the Galactic center and consistent with an old stellar population. The observed kinematics point to a significant bulge rotation, which seems to predominate even in fields as far as l ≃ −8°, and is also reflected in the changes of the velocity ellipsoid in the l, b plane as a function of distance. [ABSTRACT FROM AUTHOR]

Context. Metal-poor stars are key for studying the formation and evolution of the Galaxy. Evidence of the early mergers that built up the Galaxy remains in the distributions of abundances, kinematics, and orbital parameters of its stars. Several substructures resulting from these mergers have been tentatively identified in the literature. Aims. We conducted a global analysis of the chemodynamic properties of metal-poor stars. Our aim is to identify signs of accreted and in situ stars in different regions of the parameter space and investigate their differences and similarities. Methods. We selected a sample of about 6600 metal-poor stars with [Fe/H] ≤ −0.8 from DR3 of the GALAH survey. We used unsupervised machine learning to separate stars in a parameter space made of two normalised orbital actions, plus [Fe/H] and [Mg/Fe], without additional a priori cuts on stellar properties. Results. We divided the halo stars into four main groups. All groups exhibit a significant fraction of in situ contamination. Accreted stars of these groups have very similar chemical properties, except the group of stars with very retrograde orbits. This points to at most two main sources of accreted stars in the current sample, the major one related to Gaia-Enceladus and another possibly related to Thamnos and/or Sequoia. Gaia-Enceladus stars are r-process enriched at low metallicities, but a contribution of the s-process appears with increasing metallicity. A flat trend of [Eu/Mg] as a function of [Fe/H] suggests that only core-collapse supernovae contributed to r-process elements in Gaia-Enceladus. Conclusions. To better characterise accreted stars in the low-metallicity regime, high precision abundances and guidance from chemical evolution models are needed. It is possible that the in situ contamination in samples of accreted stars has been underestimated. This can have important consequences for attempts to estimate the properties of the original systems. [ABSTRACT FROM AUTHOR]

High-velocity stars in the Milky Way are related to extreme astrophysical phenomena. In this work, we characterize 28 stars with Galactocentric velocities higher than 400  |$\mathrm{km\, s^{-1}}$| observed in the Javalambre Photometric Local Universe Survey Data Release 2 (J-PLUS DR2) survey. We combine J-PLUS photometry with astrometric data from the Gaia DR3 catalogue to analyse the kinematics, dynamics, and fundamental stellar parameters of these stars. Our results indicate that most of the 28 stars have typical behaviour and properties of halo stars, and some of them could be related to the disk population. Some of the halo stars may belong to known structures that originated from mergers of other systems with the Milky Way. [ABSTRACT FROM AUTHOR]

Most stars in our Galaxy form in stellar aggregates, which can become long-lived structures called open clusters (OCs). Along their dynamical evolution, their gradual depletion leave some imprints on their structure. In this work, we employed astrometric, photometric, and spectroscopic data from the Gaia DR3 catalogue to uniformly characterize a sample of 60 OCs. Structural parameters (tidal, core, and half-light radii, respectively, rt , rc , and rh), age, mass (M clu), distance, reddening, Jacobi radius (RJ), and half-light relaxation time (trh) are derived from radial density profiles and astrometrically decontaminated colour–magnitude diagrams. Ages and Galactocentric distances (RG) range from 7.2 |$\, \lesssim \,$| log(t.yr |$^{-1})\, \lesssim \,$| 9.8 and 6 |$\, \lesssim \, R_G$| (kpc) |$\, \lesssim \,$| 12. Analytical expressions derived from N -body simulations are also employed to estimate the OC initial mass (M ini) and mass loss due to dynamical effects. Both rc and the tidal filling ratio, rh / RJ , decrease with the dynamical age (=  t / trh), indicating the shrinking of the OCs' internal structure as consequence of internal dynamical relaxation. This dependence seems differentially affected by the external tidal field, since OCs at smaller RG tend to be dynamically older and have smaller M clu/ M ini ratios. For |$R_G\lesssim 8\,$| kpc, the rh / RJ ratio presents a slight positive correlation with RG. Beyond this limit, there is a dichotomy in which more massive OCs are more compact and less subject to tidal stripping compared to those less massive and looser OCs at similar RG. Besides, the rt / RJ ratio also correlates positively with RG. [ABSTRACT FROM AUTHOR]

Measuring the density profile of dark matter in the Solar neighbourhood has important implications for both dark matter theory and experiment. In this work, we apply autoregressive flows to stars from a realistic simulation of a Milky Way-type galaxy to learn – in an unsupervised way – the stellar phase space density and its derivatives. With these as inputs, and under the assumption of dynamic equilibrium, the gravitational acceleration field and mass density can be calculated directly from the Boltzmann equation without the need to assume either cylindrical symmetry or specific functional forms for the galaxy's mass density. We demonstrate our approach can accurately reconstruct the mass density and acceleration profiles of the simulated galaxy, even in the presence of Gaia -like errors in the kinematic measurements. [ABSTRACT FROM AUTHOR]

The spectral energy distribution (SED) from the X-ray to far-IR is used to characterize active galactic nuclei (AGNs) having obscuring dusty material. A sample of 73 AGNs, with redshifts of z < 2.5, is subdivided based on the optical spectra into subgroups of type 1 and 2 AGNs and no-AGN. The x-cigale code is used to produce the SEDs of these galaxies, fitting them with their observed flux densities. Accordingly, this code provides estimates of the physical properties, including the stellar mass, dust-to-gas mass ratio, far-UV attenuation, star-formation rate, and luminosity. All these properties and luminosity components, namely stellar, AGN, X-ray, and dust luminosities, are characterized versus the redshift. With the caveat that the sample is flux-limited and thus is affected by Malmquist bias, the results show that these properties increase as a function of redshift with various variation rates for each galaxy group, except for the far-UV attenuation of type 1 AGNs, which shows a slight reduction with redshift. The stellar, AGN, and X-ray luminosities show tight correlations with the intrinsic AGN luminosity, which is, in principle, attributed to the intrinsic AGN accretion power acting as a fuelling source. This power has an impact on most other correlations versus the redshift when the intrinsic AGN luminosity increases with redshift. Owing to their different emission sources, these luminosities make different fractional contributions to the total luminosity. The stellar luminosity, where the dust luminosity is the most effective, has the highest contribution of all galaxy groups, while the AGN luminosity has the lowest. [ABSTRACT FROM AUTHOR]

We present the first release of the MaNGA Stellar Library (MaStar), which is a large, well-calibrated, high-quality empirical library covering the wavelength range 3622-10354 Å at a resolving power of R ∼ 1800. The spectra were obtained using the same instrument as used by the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) project, by piggybacking on the Sloan Digital Sky Survey (SDSS-IV)/Apache Point Observatory Galaxy Evolution Experiment 2-N (APOGEE-2N) observations. Compared to previous empirical libraries, the MaStar library will have a higher number of stars and a more comprehensive stellar-parameter coverage, especially of cool dwarfs, low-metallicity stars, and stars with different [α/Fe], achieved by a sophisticated target-selection strategy that takes advantage of stellar-parameter catalogs from the literature. This empirical library will provide a new basis for stellar-population synthesis and is particularly well suited for stellar-population analysis of MaNGA galaxies. The first version of the library contains 8646 high-quality per-visit spectra for 3321 unique stars. Compared to photometry, the relative flux calibration of the library is accurate to 3.9% in g-r, 2.7% in r-i, and 2.2% in i-z. The data are released as part of SDSS Data Release 15. We expect the final release of the library to contain more than 10,000 stars.

Context. To take full advantage of upcoming large-scale spectroscopic surveys, it will be necessary to parameterize millions of stellar spectra in an effcient way. Machine learning methods, especially convolutional neural networks (CNNs), will be among the main tools geared at achieving this task. Aims. We aim to prepare the groundwork for machine learning techniques for the next generation of spectroscopic surveys, such as 4MOST and WEAVE. Our goal is to show that CNNs can predict accurate stellar labels from relevant spectral features in a physically meaningful way. The predicted labels can be used to investigate properties of the Milky Way galaxy. Methods. We built a neural network and trained it on GIRAFFE spectra with their associated stellar labels from the sixth internal Gaia-ESO data release. Our network architecture contains several convolutional layers that allow the network to identify absorption features in the input spectra. The internal uncertainty was estimated from multiple network models. We used the t-distributed stochastic neighbor embedding tool to remove bad spectra from our training sample. Results. Our neural network is able to predict the atmospheric parameters Te and log(g) as well as the chemical abundances [Mg/Fe], [Al/Fe], and [Fe/H] for 36 904 stellar spectra. The training precision is 37K for Te, 0.06 dex for log(g), 0.05 dex for [Mg/Fe], 0.08 dex for [Al/Fe], and 0.04 dex for [Fe/H]. Network gradients reveal that the network is inferring the labels in a physically meaningful way from spectral features. We validated our methodology using benchmark stars and recovered the properties of different stellar populations in the Milky Way galaxy. Conclusions. Such a study provides very good insights into the application of machine learning for the analysis of large-scale spectroscopic surveys, such as WEAVE and 4MOST MilkyWay disk and bulge low- and high-resolution (4MIDABLE-LR and -HR). The community will have to put substantial efforts into building proactive training sets for machine learning methods to minimize any possible systematics. [ABSTRACT FROM AUTHOR]

Aims. We examined the Gaia DR3 GSP-Phot and GSP-Spec parameters of known K- and M-type stars of Class I luminosity to make a comparison with the parameters collected from the literature to assess their accuracy and their potential in setting stellar classifications of intrinsically bright late-types that have been unknown thus far. Gaia DR3 GSP-Phot and GSP-Spec parameters were generated by the astrophysical parameters inference software (Apsis). Methods. In the Gaia DR3 catalog, there are about 40,000 entries with Apsis parameters that are similar to those of known red supergiants (RSGs), good parallaxes, and infrared 2MASS and WISE data. In using parallactic distances, infrared photometry, and variability information, only 203 new entries were found with luminosities and temperatures similar to that of known RSGs and G-band amplitudes smaller than 0.5 mag. Their low-resolution BP/RP spectra were compared with an empirically built spectral library of BP/RP spectra of known bright late-type stars, including C-rich, S-type, O-rich asymptotic giant branch stars (AGBs) and RSGs, to obtain their spectral types. Results. Among them, 15 S-type stars were identified based on peculiar absorption features attributed to ZrO and LaO visible in their BP/RP spectra, along with 1 S/C star and 9 C-rich stars by their strong CN absorption bands. K- and M-types can be reproduced with an accuracy of two subtypes. In addition, 20 new RSGs have been confirmed, of which 6 have bolometric magnitudes that are brighter than those of the AGB limit: 2MASS J21015501+4517205, 2MASS J16291280-4956384, 2MASS J10192621-5818105, 2MASS J20230860+3651450, 2MASS J17084131−4026595, and 2MASS J16490055−4217328. The flag for C-rich stars of the Gaia DR3 LPV pipeline is erroneously positive for some RSGs and, thus, a visual inspection of the BP/RP spectra is mandatory. [ABSTRACT FROM AUTHOR]

Context. With its origin coming from several sources (Big Bang, stars, cosmic rays) and given its strong depletion during its stellar lifetime, the lithium element is of great interest as its chemical evolution in the Milky Way is not well understood at present. To help constrain stellar and galactic chemical evolution models, numerous and precise lithium abundances are necessary for a large range of evolutionary stages, metallicities, and Galactic volume. Aims. In the age of stellar parametrization on industrial scales, spectroscopic surveys such as APOGEE, GALAH, RAVE, and LAMOST have used data-driven methods to rapidly and precisely infer stellar labels (atmospheric parameters and abundances). To prepare the ground for future spectroscopic surveys such as 4MOST and WEAVE, we aim to apply machine learning techniques to lithium measurements and analyses. Methods. We trained a convolution neural network (CNN), coupling Gaia-ESO Survey iDR6 stellar labels (Teff, log(g), [Fe/H], and A(Li)) and GIRAFFE HR15N spectra, to infer the atmospheric parameters and lithium abundances for ∼40 000 stars. The CNN architecture and accompanying notebooks are available online via GitHub. Results. We show that the CNN properly learns the physics of the stellar labels, from relevant spectral features through a broad range of evolutionary stages and stellar parameters. The lithium feature at 6707.8 Å is successfully singled out by our CNN, among the thousands of lines in the GIRAFFE HR15N setup. Rare objects such as lithium-rich giants are found in our sample. This level of performance is achieved thanks to a meticulously built, high-quality, and homogeneous training sample. Conclusions. The CNN approach is very well adapted for the next generations of spectroscopic surveys aimed at studying (among other elements) lithium, such as the 4MIDABLE-LR/HR (4MOST Milky Way disk and bulge low- and high-resolution) surveys. In this context, the caveats of machine-learning applications should be appropriately investigated, along with the realistic label uncertainties and upper limits for abundances. [ABSTRACT FROM AUTHOR]

Context. Determining ages of stars for reconstructing the history of the Milky Way remains one of the most difficult tasks in astrophysics. This involves knowing when it is possible to relate the stellar mass with its age and when it is not. The young α-rich (YAR) stars present such a case in which we are still not sure about their ages because they are relatively massive, implying young ages, but their abundances are α-enhanced, which implies old ages. Aims. We report the results from new observations from a long-term radial-velocity-monitoring campaign complemented with high-resolution spectroscopy, as well as new astrometry and seismology of a sample of 41 red giants from the third version of APOKASC, which includes YAR stars. The aim is to better characterize the YAR stars in terms of binarity, mass, abundance trends, and kinematic properties. Methods. The radial velocities of HERMES, APOGEE, and Gaia were combined to determine the binary fraction among YAR stars. In combination with their mass estimate, evolutionary status, chemical composition, and kinematic properties, it allowed us to better constrain the nature of these objects. Results. We found that stars with M < 1 M⊙ were all single, whereas stars with M > 1 M⊙ could be either single or binary. This is in agreement with theoretical predictions of population synthesis models. Studying their [C/N], [C/Fe], and [N/Fe], trends with mass, it became clear that many YAR stars do not follow the APOKASC stars, favoring the scenario that most of them are the product of mass transfer. Our sample further includes two likely undermassive stars, that is to say of such as low mass that they cannot have reached the red clump within the age of the Universe, unless their low mass is the signature of mass loss in previous evolutionary phases. These stars do not show signatures of currently being binaries. Both YAR and undermassive stars might show some anomalous APOGEE abundances for the elements N, Na, P, K, and Cr; although, higher-resolution optical spectroscopy might be needed to confirm these findings. Conclusions. Considering the significant fraction of stars that are formed in pairs and the variety of ways that makes mass transfer possible, the diversity in properties in terms of binarity, and chemistry of the YAR and undermassive stars studied here implies that most of these objects are likely not young. [ABSTRACT FROM AUTHOR]

The advent of large-scale stellar spectroscopic surveys naturally leads to the implementation of machine learning techniques to isolate, for example, small sub-samples of potentially interesting stars from the full data set. A recent example is the application of the t-SNE statistical method to ∼600 000 stellar spectra from the GALAH survey in order to identify a sample of candidate extremely metal-poor (EMP; [Fe/H] ≤ –3) stars. We report the outcome of low-resolution spectroscopic follow-up of 83 GALAH EMP candidates that lack any previous metallicity estimates. Overall, the statistical selection is found to be efficient (∼one-third of the candidates have [Fe/H] ≤ –2.75) with low contamination (<10 per cent have [Fe/H] > –2), and with a metallicity distribution function that is consistent with previous work. Five stars are found to have [Fe/H] ≤ –3.0, one of which is a main sequence turnoff star. Two other stars are revealed as likely carbon-enhanced metal-poor (CEMP) stars of type CEMP- s , and a known carbon star is re-identified. The results indicate that the statistical selection approach employed was successful, and therefore it can be applied to forthcoming even larger stellar spectroscopic surveys with the expectation of similar positive outcomes. [ABSTRACT FROM AUTHOR]

MEGARA (Multi Espectrógrafo en Gran Telescopio Canarias de Alta Resolución para Astronomía) is the optical integral-field and multi-object spectrograph at the Gran Telescopio Canarias. We have created MEGASTAR , an empirical library of stellar spectra obtained using MEGARA at high resolution, |$R=20\, 000$| (full width at half-maximum), available in two wavelength ranges: one centred on Hα, from 6420 to 6790 Å; and the other centred on the Ca  ii triplet, from 8370 to 8885 Å (HR-R and HR-I volume phase holographic (VPH)-grating configurations). In this work, we use MEGASTAR spectra, a combination of these two short wavelength intervals, to estimate the stellar parameters, namely the effective temperature, surface gravity, and metallicity (and their associated errors), for a sample of 351 MEGASTAR members with spectral types earlier than B2. We applied a χ2-technique by comparing MEGASTAR data with theoretical stellar models. For those stars with stellar parameters derived in the literature, we obtained a good agreement between the published parameters and ours. In addition to the stellar parameters, we also provide several products, such as the rectified spectra, radial velocities, and stellar indices, for this sample of stars. In the near future, we will use MEGASTAR spectra and their derived stellar parameters to compute stellar population evolutionary synthesis models, which will contribute to a better interpretation of star cluster and galactic spectra obtained with MEGARA. [ABSTRACT FROM AUTHOR]

The third data release of Gaia has provided low-resolution spectra for ∼100 000 white dwarfs (WDs) that, together with the excellent photometry and astrometry, represent an unrivalled benchmark for the study of this population. In this work, we first built a highly complete volume-limited sample consisting in 12 718 WDs within 100 pc from the Sun. The use of Virtual Observatory Spectral energy distribution Analyzer tool allowed us to perform an automated fitting of their spectral energy distributions to different atmospheric models. In particular, the use of spectrally derived Javalambre-Physics of the Accelerating Universe Astrophysical Survey photometry from Gaia spectra led to the classification of DA and non-DA WDs with an accuracy >90 per cent, tested in already spectroscopically labelled objects. The excellent performance achieved was extended to practically the whole population of WDs with effective temperatures above 5500 K. Our results show that while the A branch of the Gaia WD Hertzsprung–Russell diagram is practically populated by DA WDs, the B branch is largely formed by non-DAs (65 per cent). The remaining 35 per cent of DAs within the B branch implies a second peak at ∼0.8 M⊙ in the DA mass distribution. Additionally, the Q branch and its extension to lower temperatures can be observed for both DA and non-DA objects due to core crystallization. Finally, we derived a detailed spectral evolution function, which confirms a slow increase of the fraction of non-DAs as the effective temperature decreases down to 10 500 K, where it reaches a maximum of 36 per cent and then decreases for lower temperatures down to ∼31 per cent. [ABSTRACT FROM AUTHOR]

Nearby galaxies provide populations of stellar and non-stellar sources at a common distance and in quantifiable environments. All are observed through the Milky Way foreground, with varying degrees of contamination that depend on observed Galactic latitude and the distance and size of the target galaxy. This work uses Gaia Data Release 3 (DR3) to identify foreground sources via astrometric measurements and thus quantify foreground contamination for a large sample of nearby galaxies. There are approximately half a million Gaia  sources in the directions of 1401 galaxies listed in the Local Volume Galaxy catalogue (D < 11 Mpc), excluding the largest Local Group galaxies. About two-thirds of the Gaia  sources have astrometric properties consistent with foreground sources; these sources are brighter, redder, and less centrally concentrated than non-foreground sources. Averaged over galaxies, foreground sources make up 50 per cent of Gaia  sources at projected radius r 50 = 1.06 a 26, where a 26 is the angular diameter at the B = 26.5 isophote. Foreground sources make up 50 per cent of Gaia  sources at apparent magnitude m G , 50 = 20.50. This limit corresponds to the tip of the red giant branch absolute magnitude at D = 450 kpc, and to the globular cluster luminosity function peak absolute magnitude at 5 Mpc. Gaia  data provide a powerful tool for removing foreground contamination in stellar population studies of nearby galaxies, although Gaia  foreground removal will be incomplete beyond distances of 5 Mpc. [ABSTRACT FROM AUTHOR]

We present a sub-arcsec cross-match of Gaia Data Release 3 (DR3) against the INT Galactic Plane Surveys (IGAPS) and the United Kingdom Infrared Deep Sky Survey (UKIDSS). The resulting cross-match of Galactic Plane Surveys (XGAPS) provides additional precise photometry (U RGO, g, r, i , Hα, J, H , and K) to the Gaia photometry. In building the catalogue, proper motions given in Gaia DR3 are wound back to match the epochs of the IGAPS constituent surveys (INT Photometric HαSurvey of the Northern Galactic Plane, IPHAS, and the UV-Excess Survey of the Northern Galactic Plane, UVEX) and UKIDSS, ensuring high-proper motion objects are appropriately cross-matched. The catalogue contains 33 987 180 sources. The requirement of >3σ parallax detection for every included source means that distances out to 1–1.5 kpc are well covered. In producing XGAPS, we have also trained a Random Forest classifier to discern targets with problematic astrometric solutions. Selection cuts based on the classifier results can be used to clean colour-magnitude and colour–colour diagrams in a controlled and justified manner, as well as producing subsets of astrometrically reliable targets. We provide XGAPS as a 111 column table. Uses of the catalogue include the selection of Galactic targets for multi-object spectroscopic surveys as well as identification of specific Galactic populations. [ABSTRACT FROM AUTHOR]

Binary black holes are the primary endpoint of massive stars. Their properties provide a unique opportunity to constrain binary evolution, which remains poorly understood. We predict the main properties of binary black holes and their merger products in/around the Milky Way. We present the first combination of a high-resolution cosmological simulation of a Milky Way-mass galaxy with a binary population synthesis model in this context. The hydrodynamic simulation, taken from the FIRE project, provides a cosmologically realistic star formation history for the galaxy, its stellar halo, and satellites. During post-processing, we apply a metallicity-dependent evolutionary model to the star particles to produce individual binary black holes. We find that 7 × 105 binary black holes have merged in the model Milky Way, and 1.2 × 106 binaries are still present, with a mean mass of 28M⊙. Because the black hole progenitors are strongly biased towards low-metallicity stars, half reside in the stellar halo and satellites and a third were formed outside the main galaxy. The numbers and mass distribution of the merged systems is broadly compatible with the LIGO/Virgo detections. Our simplified binary evolution models predict that LISA will detect more than 20 binary black holes, but that electromagnetic observations will be challenging. Our method will allow for constraints on the evolution of massive binaries based on comparisons between observations of compact objects and the predictions of varying binary evolution models. We provide online data of our star formation model and binary black hole distribution.

The oldest stars in the Milky Way (MW) bear imprints of the Galaxy's early assembly history. We use FIRE cosmological zoom-in simulations of three MW-mass disc galaxies to study the spatial distribution, chemistry, and kinematics of the oldest surviving stars (z form ≳ 5) in MW-like galaxies. We predict the oldest stars to be less centrally concentrated at z = 0 than stars formed at later times as a result of two processes. First, the majority of the oldest stars are not formed in situ but are accreted during hierarchical assembly. These ex situ stars are deposited on dispersion-supported, halo-like orbits but dominate over old stars formed in situ in the solar neighbourhood, and in some simulations, even in the galactic centre. Secondly, old stars formed in situ are driven outwards by bursty star formation and energetic feedback processes that create a time-varying gravitational potential at z ≳ 2, similar to the process that creates dark matter cores and expands stellar orbits in bursty dwarf galaxies. The total fraction of stars that are ancient is more than an order of magnitude higher for sight lines away from the bulge and inner halo than for inward-looking sight lines. Although the task of identifying specific stars as ancient remains challenging, we anticipate that million-star spectral surveys and photometric surveys targeting metal-poor stars already include hundreds of stars formed before z = 5. We predict most of these targets to have higher metallicity (-3 < [Fe/H] < -2) than the most extreme metal-poor stars.

We present the first large-scale study that demonstrates how ages can be determined for large samples of stars through Galactic chemical evolution. Previous studies found that the elemental abundances of a star correlate directly with its age and metallicity. Using this knowledge, we derive ages for 214 577 stars in GALAH DR3 using only overall metallicities and chemical abundances. Stellar ages are estimated via the machine learning algorithm XGBoost for stars belonging to the Milky Way disc with metallicities in the range −1 < [Fe/H] < 0.5, using main-sequence turn-off stars as our training set. We find that stellar ages for the bulk of GALAH DR3 are precise to 1–2 Gyr using this method. With these ages, we replicate many recent results on the age-kinematic trends of the nearby disc, including the solar neighbourhood's age–velocity dispersion relationship and the larger global velocity dispersion relations of the disc found using Gaia and GALAH. These results show that chemical abundance variations at a given birth radius are small, and that strong chemical tagging of stars directly to birth clusters may prove difficult with our current elemental abundance precision. Our results highlight the need to measure abundances for as many nucleosynthetic production sites as possible in order to estimate reliable ages from chemistry. Our methods open a new door into studies of the kinematic structure and evolution of the disc, as ages may potentially be estimated to a precision of 1–2 Gyr for a large fraction of stars in existing spectroscopic surveys. [ABSTRACT FROM AUTHOR]

We present GECKOS (Generalising Edge-on galaxies and their Chemical bimodalities, Kinematics, and Outflows out to Solar environments), a new ESO VLT/MUSE large program. The main aim of GECKOS is to reveal the variation in key physical processes of disk formation by connecting Galactic Archaeology with integral field spectroscopic observations of nearby galaxies. Edge-on galaxies are ideal for this task: they allow us to disentangle the assembly history imprinted in thick disks and provide the greatest insights into outflows. The GECKOS sample of 35 nearby edge-on disk galaxies is designed to trace the assembly histories and properties of galaxies across a large range of star formation rates, bulge-to-total ratios, and boxy and non-boxy bulges. GECKOS will deliver spatially resolved measurements of stellar abundances, ages, and kinematics, as well as ionised gas metallicities, ionisation param- eters, pressure, and inflow and outflow kinematics; all key parameters for building a complete chemodynamical picture of disk galaxies. With these data, we aim to extend Galactic analysis methods to the wider galaxy population, reaping the benefits of detailed Milky Way studies, while probing the diverse mechanisms of galaxy evolution. [ABSTRACT FROM AUTHOR]