The Gaia-ESO Survey: radial metallicity gradients and age-metallicity relation of stars in the Milky Way disk

We study the relationship between age, metallicity, and alpha-enhancement of FGK stars in the Galactic disk. The results are based upon the analysis of high-resolution UVES spectra from the Gaia-ESO large stellar survey. We explore the limitations of the observed dataset, i.e. the accuracy of stellar parameters and the selection effects that are caused by the photometric target preselection. We find that the colour and magnitude cuts in the survey suppress old metal-rich stars and young metal-poor stars. This suppression may be as high as 97% in some regions of the age-metallicity relationship. The dataset consists of 144 stars with a wide range of ages from 0.5 Gyr to 13.5 Gyr, Galactocentric distances from 6 kpc to 9.5 kpc, and vertical distances from the plane 0 < |Z| < 1.5 kpc. On this basis, we find that i) the observed age-metallicity relation is nearly flat in the range of ages between 0 Gyr and 8 Gyr; ii) at ages older than 9 Gyr, we see a decrease in [Fe/H] and a clear absence of metal-rich stars; this cannot be explained by the survey selection functions; iii) there is a significant scatter of [Fe/H] at any age; and iv) [Mg/Fe] increases with age, but the dispersion of [Mg/Fe] at ages > 9 Gyr is not as small as advocated by some other studies. In agreement with earlier work, we find that radial abundance gradients change as a function of vertical distance from the plane. The [Mg/Fe] gradient steepens and becomes negative. In addition, we show that the inner disk is not only more alpha-rich compared to the outer disk, but also older, as traced independently by the ages and Mg abundances of stars.Comment: accepted for publication in A&

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

Connecting photometric and spectroscopic granulation signals with CHEOPS and ESPRESSO

Context. Stellar granulation generates fluctuations in photometric and spectroscopic data whose properties depend on the stellar type, composition, and evolutionary state. Characterizing granulation is key for understanding stellar atmospheres and detecting planets. Aims. We aim to detect the signatures of stellar granulation, link spectroscopic and photometric signatures of convection for main-sequence stars, and test predictions from 3D hydrodynamic models. Methods. For the first time, we observed two bright stars (Teff = 5833 and 6205 K) with high-precision observations taken simultaneously with CHEOPS and ESPRESSO. We analyzed the properties of the stellar granulation signal in each individual dataset. We compared them to Kepler observations and 3D hydrodynamic models. While isolating the granulation-induced changes by attenuating and filtering the p-mode oscillation signals, we studied the relationship between photometric and spectroscopic observables. Results. The signature of stellar granulation is detected and precisely characterized for the hotter F star in the CHEOPS and ESPRESSO observations. For the cooler G star, we obtain a clear detection in the CHEOPS dataset only. The TESS observations are blind to this stellar signal. Based on CHEOPS observations, we show that the inferred properties of stellar granulation are in agreement with both Kepler observations and hydrodynamic models. Comparing their periodograms, we observe a strong link between spectroscopic and photometric observables. Correlations of this stellar signal in the time domain (flux versus radial velocities, RV) and with specific spectroscopic observables (shape of the cross-correlation functions) are however difficult to isolate due to S/N dependent variations. Conclusions. In the context of the upcoming PLATO mission and the extreme precision RV surveys, a thorough understanding of the properties of the stellar granulation signal is needed. The CHEOPS and ESPRESSO observations pave the way for detailed analyses of this stellar process

Examining the orbital decay targets KELT-9 b, KELT-16 b, and WASP-4 b, and the transit-timing variations of HD 97658 b,

Context. Tidal orbital decay is suspected to occur for hot Jupiters in particular, with the only observationally confirmed case of this being WASP-12 b. By examining this effect, information on the properties of the host star can be obtained using the so-called stellar modified tidal quality factor Q′∗, which describes the efficiency with which the kinetic energy of the planet is dissipated within the star. This can provide information about the interior of the star. Aims. In this study, we aim to improve constraints on the tidal decay of the KELT-9, KELT-16, and WASP-4 systems in order to find evidence for or against the presence of tidal orbital decay. With this, we want to constrain the Q′∗ value for each star. In addition, we aim to test the existence of the transit timing variations (TTVs) in the HD 97658 system, which previously favoured a quadratic trend with increasing orbital period. Methods. Making use of newly acquired photometric observations from CHEOPS (CHaracterising ExOplanet Satellite) and TESS (Transiting Exoplanet Survey Satellite), combined with archival transit and occultation data, we use Markov chain Monte Carlo (MCMC) algorithms to fit three models to the data, namely a constant-period model, an orbital-decay model, and an apsidal-precession model. Results. We find that the KELT-9 system is best described by an apsidal-precession model for now, with an orbital decay trend at over 2 σ being a possible solution as well. A Keplerian orbit model with a constant orbital period provides the best fit to the transit timings of KELT-16 b because of the scatter and scale of their error bars. The WASP-4 system is best represented by an orbital decay model at a 5 σ significance, although apsidal precession cannot be ruled out with the present data. For HD 97658 b, using recently acquired transit observations, we find no conclusive evidence for a previously suspected strong quadratic trend in the data

TOI-1055 b: Neptunian planet characterised with HARPS, TESS, and CHEOPS

Context. TOI-1055 is a Sun-like star known to host a transiting Neptune-sized planet on a 17.5-day orbit (TOI-1055 b). Radial velocity (RV) analyses carried out by two independent groups using nearly the same set of HARPS spectra have provided measurements of planetary masses that differ by ∼2σ. Aims. Our aim in this work is to solve the inconsistency in the published planetary masses by significantly extending the set of HARPS RV measurements and employing a new analysis tool that is able to account and correct for stellar activity. Our further aim was to improve the precision on measurements of the planetary radius by observing two transits of the planet with the CHEOPS space telescope. Methods. We fit a skew normal function to each cross correlation function extracted from the HARPS spectra to obtain RV measurements and hyperparameters to be used for the detrending. We evaluated the correlation changes of the hyperparameters along the RV time series using the breakpoint technique. We performed a joint photometric and RV analysis using a Markov chain Monte Carlo scheme to simultaneously detrend the light curves and the RV time series. Results. We firmly detected the Keplerian signal of TOI-1055 b, deriving a planetary mass of Mb = 20.4-2.5+2.6 MO (∼12%). This value is in agreement with one of the two estimates in the literature, but it is significantly more precise. Thanks to the TESS transit light curves combined with exquisite CHEOPS photometry, we also derived a planetary radius of Rb = 3.490-0.064+0.070 RO (∼1.9%). Our mass and radius measurements imply a mean density of ρb = 2.65-0.35+0.37 g cm-3 (∼14%). We further inferred the planetary structure and found that TOI-1055 b is very likely to host a substantial gas envelope with a mass of 0.41-0.20+0.34 MO and a thickness of 1.05-0.29+0.30 RO. Conclusions. Our RV extraction combined with the breakpoint technique has played a key role in the optimal removal of stellar activity from the HARPS time series, enabling us to solve the tension in the planetary mass values published so far for TOI-1055 b

Human Resource Flexibility as a Mediating Variable Between High Performance Work Systems and Performance

Much of the human resource management literature has demonstrated the impact of high performance work systems (HPWS) on organizational performance. A new generation of studies is emerging in this literature that recommends the inclusion of mediating variables between HPWS and organizational performance. The increasing rate of dynamism in competitive environments suggests that measures of employee adaptability should be included as a mechanism that may explain the relevance of HPWS to firm competitiveness. On a sample of 226 Spanish firms, the study’s results confirm that HPWS influences performance through its impact on the firm’s human resource (HR) flexibility

A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting

This work presents the first application of a non-intrusive reduced order method to model solid interacting with compressible fluid flows to simulate crack initiation and propagation. In the high fidelity model, the coupling process is achieved by introducing a source term into the momentum equation, which represents the effects of forces of the solid on the fluid. A combined single and smeared crack model with the Mohr–Coulomb failure criterion is used to simulate crack initiation and propagation. The non-intrusive reduced order method is then applied to compressible fluid and fractured solid coupled modelling where the computational cost involved in the full high fidelity simulation is high. The non-intrusive reduced order model (NIROM) developed here is constructed through proper orthogonal decomposition (POD) and a radial basis function (RBF) multi-dimensional interpolation method.The performance of the NIROM for solid interacting with compressible fluid flows, in the presence of fracture models, is illustrated by two complex test cases: an immersed wall in a fluid and a blasting test case. The numerical simulation results show that the NIROM is capable of capturing the details of compressible fluids and fractured solids while the CPU time is reduced by several orders of magnitude. In addition, the issue of whether or not to subtract the mean from the snapshots before applying POD is discussed in this paper. It is shown that solutions of the NIROM, without mean subtracted before constructing the POD basis, captured more details than the NIROM with mean subtracted from snapshots

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

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function