Beyond Gaia DR3: tracing the [α/M] − [M/H] bimodality from the Inner to the outer Milky Way disc with Gaia RVS and Convolutional Neural-Networks

Gaia DR3 provided the community with one million RVS spectra covering the CaII triplet region, similarly to the RAVE spectra. One third of the spectra have a signal-to-noise ratio from 15 to 25 per pixel. Gaia also provides XP spectra/coefficients in DR3. We aim to leverage versatility/capabilities of machine learning techniques for combining the full set of Gaia products for supercharged stellar parametrization. We developed a hybrid Convolutional Neural-Network (CNN)to derive atmospheric parameters (Teff, log(g), and [M/H]) and chemical abundances ([Fe/H] and [α/M]). Our CNN is designed to effectively combine the Gaia DR3 RVS spectra, photometry (G, Bp, Rp), parallaxes, and XP coefficients and is able to extract formation from non-spectral inputs to supplement the limited spectral coverage of the RVS spectrum. We trained CNN with high-quality training sample based on APOGEE DR17 labels. The atmospheric parameters we provide thanks to CNN out-perform the spectroscopic ones provided by the Gaia Collaboration both in terms of uncertainties and comparison with external high-quality data-sets. CNN is extremely robust to noise in RVS data, and very precise labels are derived down to S/N = 15. We provide atmospheric parameters and abundances for 841 300 stars homogeneous being the first machine-learning catalog to combine such diverse datasets. We managed to characterize the [α/M] − [M/H] bimodality from the inner regions to the outer part of the Milky Way, which has never been characterized using RVS spectra or similar datasets. This study set the path for the machine-learning analysis of Gaia-RVS spectra for the next data releases. Large high-quality datasets and archives can be ideally combined thanks to CNN,releasing the full power of spectroscopy, astrometry, and photometry

Observational constraints on the origin of the elements. VI. Origin and evolution of neutron-capture elements as probed by the Gaia-ESO survey

Most heavy elements beyond the iron peak are synthesized via neutron capture processes. The nature of the astrophysical sites of neutron capture processes is still very unclear. In this work we explore the observational constraints of the chemical abundances of s-process and r-process elements on the sites of neutron-capture processes by applying Galactic chemical evolution (GCE) models to the data from Gaia-ESO large spectroscopic stellar survey. For the r-process, the [Eu/Fe]-[Fe/H] distribution suggests a short delay time of the site that produces Eu. Other independent observations (e.g., NS-NS binaries), however, suggest a significant fraction of long delayed ($>1$Gyr) neutron star mergers (NSM). When assuming NSM as the only r-process sites, these two observational constraints are inconsistent at above 1$\sigma$ level. Including short delayed r-process sites like magneto-rotational supernova can resolve this inconsistency. For the s-process, we find a weak metallicity dependence of the [Ba/Y] ratio, which traces the s-process efficiency. Our GCE model with up-to-date yields of AGB stars qualitatively reproduces this metallicity dependence, but the model predicts a much higher [Ba/Y] ratio compared to the data. This mismatch suggests that the s-process efficiency of low mass AGB stars in the current AGB nucleosynthesis models could be overestimated.Comment: 14 pages, 11 figures, accepted by MNRA

Dissecting stellar chemical abundance space with t-SNE

In the era of large-scale Galactic astronomy and multi-object spectroscopic stellar surveys, the sample sizes and the number of available stellar chemical abundances have reached dimensions in which it has become difficult to process all the available information in an effective manner. In this paper we demonstrate the use of a dimensionality-reduction technique (t-distributed stochastic neighbour embedding; t-SNE) for analysing the stellar abundance-space distribution. While the non-parametric non-linear behaviour of this technique makes it difficult to estimate the significance of any abundance-space substructure found, we show that our results depend little on parameter choices and are robust to abundance errors. By reanalysing the high-resolution high-signal-to-noise solar-neighbourhood HARPS-GTO sample with t-SNE, we find clearer chemical separations of the high- and low-[α/Fe] disc sequences, hints for multiple populations in the high-[α/Fe] population, and indications that the chemical evolution of the high-[α/Fe] metal-rich stars is connected with the super-metal-rich stars. We also identify a number of chemically peculiar stars, among them a high-confidence s-process-enhanced abundance-ratio pair (HD 91345/HD 126681) with very similar ages and v X and v Y velocities, which we suggest have a common birth origin, possibly a dwarf galaxy. Our results demonstrate the potential of abundance-space t-SNE and similar methods for chemical-tagging studies with large spectroscopic surveys

Estimating stellar birth radii and the time evolution of Milky Way’s ISM metallicity gradient

We present a semi-empirical, largelymodel-independent approach for estimatingGalactic birth radii, rbirth, for Milky Way disc stars. The technique relies on the justifiable assumption that a negative radial metallicity gradient in the interstellar medium (ISM) existed for most of the disc lifetime. Stars are projected back to their birth positions according to the observationally derived age and [Fe/H] with no kinematical information required. Applying our approach to the AMBRE:HARPS and HARPS–GTO local samples, we show that we can constrain the ISM metallicity evolution with Galactic radius and cosmic time, [Fe/H]ISM(r, t), by requiring a physically meaningful rbirth distribution. We find that the data are consistent with an ISM radial metallicity gradient that flattens with time from ~− 0.15 dex kpc−1 at the beginning of disc formation, to its measured present-day value (−0.07 dex kpc−1). We present several chemokinematical relations in terms of mono-rbirth populations. One remarkable result is that the kinematically hottest stars would have been born locally or in the outer disc, consistent with thick disc formation from the nested flares of mono-age populations and predictions from cosmological simulations. This phenomenon can be also seen in the observed age–velocity dispersion relation, in that its upper boundary is dominated by stars born at larger radii. We also find that the flatness of the local age–metallicity relation (AMR) is the result of the superposition of the AMRs of mono-rbirth populations, each with a well-defined negative slope. The solar birth radius is estimated to be 7.3 ± 0.6 kpc, for a current Galactocentric radius of 8 kpc

Single-lined Spectroscopic Binary Star Candidates from a Combination of the RAVE and Gaia DR2 Surveys

The combination of the final version of the Radial Velocity Experiment (RAVE) spectroscopic survey data release 6 with radial velocities (RVs) and astrometry from Gaia DR2 allows us to identify and create a catalog of single-lined binary star candidates (SB1), their inferred orbital parameters, and to inspect possible double-lined binary stars (SB2). A probability function for the detection of RV variations is used for identifying SB1 candidates. The estimation of orbital parameters for main-sequence dwarfs is performed by matching the measured RVs with theoretical velocity curves sampling the orbital parameter space. The method is verified by studying a mock sample from the SB 9 catalog. Studying the boxiness and asymmetry of the spectral lines allows us to identify possible SB2 candidates, while matching their spectra to a synthetic library indicates probable properties of their components. From the RAVE catalog we select 37,664 stars with multiple RV measurements and identify 3838 stars as SB1 candidates. Joining Rave and Gaia DR2 yields 450,646 stars with RVs measured by both surveys and 27,716 of them turn out to be SB1 candidates, which is an increase by an order of magnitude over previous studies. For main-sequence dwarf candidates we calculate their most probable orbital parameters: orbital periods are not longer than a few years and primary components have masses similar to the solar mass. All our results are available in the electronic version.Funding for RAVE has been provided by: the Leibniz-Institut für Astrophysik Potsdam (AIP); the Australian Astronomical Observatory; the Australian National University; the Australian Research Council; the French National Research Agency; the German Research Foundation (SPP 1177 and SFB 881); the European Research Council (ERC-StG 240271 Galactica); the Istituto Nazionale di Astrofisica at Padova; The Johns Hopkins University; the National Science Foundation of the USA (AST-0908326); the W. M. Keck foundation; the Macquarie University; the Netherlands Research School for Astronomy; the Natural Sciences and Engineering Research Council of Canada; the Slovenian Research Agency (core funding No. P1-0188); the Swiss National Science Foundation; the Science & Technology Facilities Council of the UK; Opticon; Strasbourg Observatory; and the Universities of Basel, Groningen, Heidelberg and Sydney. T.Z. thanks the Research School of Astronomy & Astrophysics in Canberra for support through a Distinguished Visitor Fellowship

Single-lined Spectroscopic Binary Star Candidates from a Combination of the RAVE and Gaia DR2 Surveys

The combination of the final version of the Radial Velocity Experiment (RAVE) spectroscopic survey data release 6 with radial velocities (RVs) and astrometry from Gaia DR2 allows us to identify and create a catalog of single-lined binary star candidates (SB1), their inferred orbital parameters, and to inspect possible double-lined binary stars (SB2). A probability function for the detection of RV variations is used for identifying SB1 candidates. The estimation of orbital parameters for main-sequence dwarfs is performed by matching the measured RVs with theoretical velocity curves sampling the orbital parameter space. The method is verified by studying a mock sample from the SB 9 catalog. Studying the boxiness and asymmetry of the spectral lines allows us to identify possible SB2 candidates, while matching their spectra to a synthetic library indicates probable properties of their components. From the RAVE catalog we select 37,664 stars with multiple RV measurements and identify 3838 stars as SB1 candidates. Joining Rave and Gaia DR2 yields 450,646 stars with RVs measured by both surveys and 27,716 of them turn out to be SB1 candidates, which is an increase by an order of magnitude over previous studies. For main-sequence dwarf candidates we calculate their most probable orbital parameters: orbital periods are not longer than a few years and primary components have masses similar to the solar mass. All our results are available in the electronic version

Stellar Astrophysics and Exoplanet Science with the Maunakea Spectroscopic Explorer (MSE)

The Maunakea Spectroscopic Explorer (MSE) is a planned 11.25-m aperture facility with a 1.5 square degree field of view that will be fully dedicated to multi-object spectroscopy. A rebirth of the 3.6m Canada-France-Hawaii Telescope on Maunakea, MSE will use 4332 fibers operating at three different resolving powers (R ~ 2500, 6000, 40000) across a wavelength range of 0.36-1.8mum, with dynamical fiber positioning that allows fibers to match the exposure times of individual objects. MSE will enable spectroscopic surveys with unprecedented scale and sensitivity by collecting millions of spectra per year down to limiting magnitudes of g ~ 20-24 mag, with a nominal velocity precision of ~100 m/s in high-resolution mode. This white paper describes science cases for stellar astrophysics and exoplanet science using MSE, including the discovery and atmospheric characterization of exoplanets and substellar objects, stellar physics with star clusters, asteroseismology of solar-like oscillators and opacity-driven pulsators, studies of stellar rotation, activity, and multiplicity, as well as the chemical characterization of AGB and extremely metal-poor stars.Comment: 31 pages, 11 figures; To appear as a chapter for the Detailed Science Case of the Maunakea Spectroscopic Explore

The sixth data release of the Radial Velocity Experiment (RAVE). I. Survey description, spectra and radial velocities

The Radial Velocity Experiment (RAVE) is a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A). The 6th and final data release (DR6 or FDR) is based on 518387 observations of 451783 unique stars. RAVE observations were taken between 12 April 2003 and 4 April 2013. Here we present the genesis, setup and data reduction of RAVE as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in RAVE DR6. Furthermore, we present derived spectral classification and radial velocities for the RAVE targets, complemented by cross matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km/s, while 95% of the objects have radial velocities better than 4.0 km/s. Stellar atmospheric parameters, abundances and distances are presented in subsequent publication. The data can be accessed via the RAVE Web (http://rave-survey.org) or the Vizier database.Comment: 32 pages, 11 figures, accepted for publication to A

The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

The eighteenth data release of the Sloan Digital Sky Surveys (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs, or "Mappers": Milky Way Mapper (MWM), Black Hole Mapper (BHM), and Local Volume Mapper (LVM). This data release contains extensive targeting information for the two multi-object spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration- and scientifically-focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.Comment: Accepted to ApJ