The Gaia-ESO Survey: Homogenisation of stellar parameters and elemental abundances

The Gaia-ESO Survey is a public spectroscopic survey that targeted ≳105 stars covering all major components of the Milky Way from the end of 2011 to 2018, delivering its final public release in May 2022. Unlike other spectroscopic surveys, Gaia-ESO is the only survey that observed stars across all spectral types with dedicated, specialised analyses: from O (Teff ~ 30 000–52 000 K) all the way to K-M (≳3500 K). The physics throughout these stellar regimes varies significantly, which has previously prohibited any detailed comparisons between stars of significantly different types. In the final data release (internal data release 6) of the Gaia-ESO Survey, we provide the final database containing a large number of products, such as radial velocities, stellar parameters and elemental abundances, rotational velocity, and also, for example, activity and accretion indicators in young stars and membership probability in star clusters for more than 114 000 stars. The spectral analysis is coordinated by a number of working groups (WGs) within the survey, each specialised in one or more of the various stellar samples. Common targets are analysed across WGs to allow for comparisons (and calibrations) amongst instrumental setups and spectral types. Here we describe the procedures employed to ensure all survey results are placed on a common scale in order to arrive at a single set of recommended results for use by all survey collaborators. We also present some general quality and consistency checks performed on the entirety of the survey results.This work was partly supported by the European Union FP7 programme through ERC grant number 320360 and by the Leverhulme Trust through grant RPG-2012-541. We acknowledge the support from INAF and Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR) in the form of the grant “Premiale VLT 2012”. L. Magrini and M. Van der Swaelmen acknowledge support by the WEAVE Italian consortium, and by the INAF Grant “Checs”. A.J. Korn acknowledges support by the Swedish National Space Agency (SNSA). A. Lobel acknowledges support in part by the Belgian Federal Science Policy Office under contract no. BR/143/A2/BRASS and by the European Union Framework Programme for Research and Innovation Horizon 2020 (2014-2020) under the Marie Sklodowska-Curie grant Agreement No. 823734. D.K. Feuillet was partly supported by grant no. 2016-03412 from the Swedish Research Council. D. Montes acknowledges financial support from the Agencia Estatal de Investigacion of the Ministerio de Ciencia, Innovation through project PID2019-109522GB-C54 /AEI/10.13039/501100011033. E. Marfil acknowledges financial support from the European Regional Development Fund (ERDF) and the Gobierno de Canarias through project ProID2021010128. J.I. Gonzalez Hernandez acknowledges financial support from the Spanish Ministry of Science and Innovation (MICINN) project PID2020-117493GB-I00. M. Bergemann is supported through the Lise Meitner grant from the Max Planck Society and acknowledges support by the Collaborative Research centre SFB 881 (projects A5, A10), Heidelberg University, of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). This project has received funding from the European Research Council (ERC) under the European Union, Horizon 2020 research and innovation programme (Grant agreement No. 949173). P. Jofré acknowledges financial support of FONDECYT Regular 1200703 as well as Nucleo Mile-nio ERIS NCN2021_017. R. Smiljanic acknowledges support from the National Science Centre, Poland (2014/15/B/ST/03981). S.R. Berlanas acknowledges support by MCIN/AEI/10.13039/501100011033 (contract FJC 2020-045785-I) and NextGeneration EU/PRTR and MIU (UNI/551/2021) through grant Margarita Salas-ULL. T. Bensby acknowledges financial support by grant No. 2018-04857 from the Swedish Research Council. T. Merle is supported by a grant from the Foundation ULB. T. Morel are grateful to Belgian F.R.S.-FNRS for support, and are also indebted for an ESA/PRODEX Belspo contract related to the Gaia Data Processing and Analysis Consortium and for support through an ARC grant for Concerted Research Actions financed by the Federation Wallonie-Brussels. W. Santos acknowledges FAPERJ for a Ph.D. fellowship. H.M. Tabernero acknowledges financial support from the Agencia Estatal de Investigation of the Ministerio de Ciencia, Innovation through project PID2019-109522GB-C51/AEI/10.13039/501100011033

The Gaia-ESO Public Spectroscopic Survey: Motivation, implementation, GIRAFFE data processing, analysis, and final data products

Context. The Gaia-ESO Public Spectroscopic Survey is an ambitious project designed to obtain astrophysical parameters and elemental abundances for 100 000 stars, including large representative samples of the stellar populations in the Galaxy, and a well-defined sample of 60 (plus 20 archive) open clusters. We provide internally consistent results calibrated on benchmark stars and star clusters, extending across a very wide range of abundances and ages. This provides a legacy data set of intrinsic value, and equally a large wide-ranging dataset that is of value for the homogenisation of other and future stellar surveys and Gaia's astrophysical parameters. Aims. This article provides an overview of the survey methodology, the scientific aims, and the implementation, including a description of the data processing for the GIRAFFE spectra. A companion paper introduces the survey results. Methods. Gaia-ESO aspires to quantify both random and systematic contributions to measurement uncertainties. Thus, all available spectroscopic analysis techniques are utilised, each spectrum being analysed by up to several different analysis pipelines, with considerable effort being made to homogenise and calibrate the resulting parameters. We describe here the sequence of activities up to delivery of processed data products to the ESO Science Archive Facility for open use. Results. The Gaia-ESO Survey obtained 202 000 spectra of 115 000 stars using 340 allocated VLT nights between December 2011 and January 2018 from GIRAFFE and UVES. Conclusions. The full consistently reduced final data set of spectra was released through the ESO Science Archive Facility in late 2020, with the full astrophysical parameters sets following in 2022. A companion article reviews the survey implementation, scientific highlights, the open cluster survey, and data products

The Gaia-ESO Public Spectroscopic Survey: Implementation, data products, open cluster survey, science, and legacy

Context. In the last 15 years different ground-based spectroscopic surveys have been started (and completed) with the general aim of delivering stellar parameters and elemental abundances for large samples of Galactic stars, complementing Gaia astrometry. Among those surveys, the Gaia-ESO Public Spectroscopic Survey, the only one performed on a 8m class telescope, was designed to target 100 000 stars using FLAMES on the ESO VLT (both Giraffe and UVES spectrographs), covering all the Milky Way populations, with a special focus on open star clusters. Aims. This article provides an overview of the survey implementation (observations, data quality, analysis and its success, data products, and releases), of the open cluster survey, of the science results and potential, and of the survey legacy. A companion article reviews the overall survey motivation, strategy, Giraffe pipeline data reduction, organisation, and workflow. Methods. We made use of the information recorded and archived in the observing blocks; during the observing runs; in a number of relevant documents; in the spectra and master catalogue of spectra; in the parameters delivered by the analysis nodes and the working groups; in the final catalogue; and in the science papers. Based on these sources, we critically analyse and discuss the output and products of the Survey, including science highlights. We also determined the average metallicities of the open clusters observed as science targets and of a sample of clusters whose spectra were retrieved from the ESO archive. Results. The Gaia-ESO Survey has determined homogeneous good-quality radial velocities and stellar parameters for a large fraction of its more than 110 000 unique target stars. Elemental abundances were derived for up to 31 elements for targets observed with UVES. Lithium abundances are delivered for about 1/3 of the sample. The analysis and homogenisation strategies have proven to be successful; several science topics have been addressed by the Gaia-ESO consortium and the community, with many highlight results achieved. Conclusions. The final catalogue will be released through the ESO archive in the first half of 2022, including the complete set of advanced data products. In addition to these results, the Gaia-ESO Survey will leave a very important legacy, for several aspects and for many years to come

Gaia Early Data Release 3: Structure and properties of the Magellanic Clouds

We compare the Gaia DR2 and Gaia EDR3 performances in the study of the Magellanic Clouds and show the clear improvements in precision and accuracy in the new release. We also show that the systematics still present in the data make the determination of the 3D geometry of the LMC a difficult endeavour; this is at the very limit of the usefulness of the Gaia EDR3 astrometry, but it may become feasible with the use of additional external data. We derive radial and tangential velocity maps and global profiles for the LMC for the several subsamples we defined. To our knowledge, this is the first time that the two planar components of the ordered and random motions are derived for multiple stellar evolutionary phases in a galactic disc outside the Milky Way, showing the differences between younger and older phases. We also analyse the spatial structure and motions in the central region, the bar, and the disc, providing new insights into features and kinematics. Finally, we show that the Gaia EDR3 data allows clearly resolving the Magellanic Bridge, and we trace the density and velocity flow of the stars from the SMC towards the LMC not only globally, but also separately for young and evolved populations. This allows us to confirm an evolved population in the Bridge that is slightly shift from the younger population. Additionally, we were able to study the outskirts of both Magellanic Clouds, in which we detected some well-known features and indications of new ones

The Gaia mission

Gaia is a cornerstone mission in the science programme of the EuropeanSpace Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page. http://www.cosmos.esa.int/gai

Syndromes of Pre-School Psychopathology Reported by Teachers and Caregivers in 14 Societies Using the Caregiver Teacher Report Form (C-TRF)

Caregivers and teachers from 14 societies rated 9,389 1.5 to 5-year-olds on the Caregiver-Teacher Report Form (C-TRF; Achenbach & Rescorla, 2000). General population samples were obtained in Asia; the Middle East; Eastern, Northern, Central, Western, and Southern Europe; and South America. The 2-level 6-syndrome C-TRF model derived on a mostly U.S. sample was tested separately for each society. This model or a slightly modified 2-level 5-syndrome version of the model fit the data for 10 of the 14 societies. The findings generally support use of the C-TRF with children of diverse backgrounds. The multicultural generalizability of C-TRF syndromes suggests that they can be used as taxonomic constructs for preschoolers’ psychopathology, which can facilitate international communication and collaboration between clinicians, researchers, and educators working with young children

The Gaia-ESO Survey: The analysis of the hot-star spectra

Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey that has collected, over a period of six years, spectra of ~105 stars. This survey provides not only the reduced spectra, but also the stellar parameters and abundances resulting from the analysis of the spectra. Aims. The GES dataflow is organised in 19 working groups. Working group 13 (WG13) is responsible for the spectral analysis of the hottest stars (O, B, and A type, with a formal cutoff of Teff > 7000 K) that were observed as part of GES. We present the procedures and techniques that have been applied to the reduced spectra in order to determine the stellar parameters and abundances of these stars. Methods. The procedure used was similar to that of other working groups in GES. A number of groups (called Nodes) each independently analyse the spectra via state-of-the-art techniques and codes. Specific for the analysis in WG13 was the large temperature range covered (Teff ≈ 7000–50 000 K), requiring the use of different analysis codes. Most Nodes could therefore only handle part of the data. Quality checks were applied to the results of these Nodes by comparing them to benchmark stars, and by comparing them to one another. For each star the Node values were then homogenised into a single result: the recommended parameters and abundances. Results. Eight Nodes each analysed part of the data. In total 17 693 spectra of 6462 stars were analysed, most of them in 37 open star clusters. The homogenisation led to stellar parameters for 5584 stars. Abundances were determined for a more limited number of stars. The elements studied are He, C, N, O, Ne, Mg, Al, Si, and Sc. Abundances for at least one of these elements were determined for 292 stars. Conclusions. The hot-star data analysed here, as well as the GES data in general, will be of considerable use in future studies of stellar evolution and open clusters.This work was partly supported by the European Union FP7 programme through ERC grant number 320360 and by the Leverhulme Trust through grant RPG-2012-541. We acknowledge the support from INAF and Ministero dell’ Istruzione, dell’ Université’ e della Ricerca (MIUR) in the form of the grant ‘Premiale VLT 2012’. A.H. acknowledges support by the Spanish Ministerio de Ciencia e Innovación through grants PGC2018-093741-B-C22 and CEX-2019-000920-S. The work of S.R.B, I.N., and S.S.D. is partially supported by the Spanish Government Ministerio de Economía y Competitivad (MINECO/FEDER) under grants PGC2018-093741-B-C21/C22 (MICIU/AEI/FEDER, UE). A.L. acknowledges that his research has been funded in part by the Belgian Federal Science Policy Office under contract No. BR/143/A2/BRASS. The Liège Node is grateful to Belgian F.R.S.-FNRS for various supports. They are also indebted for an ESA/PRODEX Belspo contract related to the Gaia Data Processing and Analysis Consortium and for support through an ARC grant for Concerted Research Actions financed by the Federation Wallonie-Brussels. J.M.A. acknowledges support from the Spanish Government Ministerio de Ciencia through grants AYA2016-75 931-C2-2-P and PGC2018-095049-B-C22. W.S. acknowledges CAPES for a Ph.D. Fellowship. G.H. acknowledges that this research has been partially funded by the Canarian Agency for Economy, Knowledge, and Employment and the European Regional Development Fund (ERDF/EU), under grant with reference ProID2020010016. F.J.E. acknowledges financial support from the Spanish MINECO/FEDER through the grant AYA2017-84089 and MDM-2017-0737 at Centro de Astrobiología (CSIC-INTA), Unidad de Excelencia María de Maeztu, and from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 824064 through the ESCAPE - The European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures project. E.J.A acknowledges funding from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and from MCIU grant PGC2018-095049-B-C21. T.B. acknowledges financial support by grant No. 2018-04857 from the Swedish Research Council. A.J.K. and U.H. acknowledge support from the Swedish National Space Agency (SNSA). R.S. acknowledges support from the National Science Centre (2014/15/B/ST9/03981)

VizieR Online Data Catalog: Gaia-ESO Survey iDR4 calibrators (Pancino+, 2017)

VizieR On-line Data Catalog: J/A+A/598/A5. Originally published in: 2017A&A...598A...5PList of GES iDR4 calibrators. It can be used to select the iDR4 calibrators from the upcoming ESO Phase 3 public release. The columns contain: the GES unique identifier of each star (the CName), based on the object sexagesimal coordinates; the calibration type, which can be GC or OC for clusters, RV for radial velocity standards, BM for benchmark stars, or CR for CoRoT targets; the field name; and the 2MASS J and K magnitudes, when available. (1 data file)