Chemical abundances for 23 candidate subgiant stars have been derived with the aim at exploring their usefulness for studies of galactic chemical evolution. High-resolution spectra from ESO CAT-CES ...and NOT-SOFIN covered 16 different spectral regions in the visible part of the spectrum. Some 200 different atomic and molecular spectral lines have been used for abundance analysis of ~30 elemental species. The wings of strong, pressure-broadened metal lines were used for determination of stellar surface gravities, which have been compared with gravities derived from Hipparcos parallaxes and isochronic masses. Stellar space velocities have been derived from Hipparcos and Simbad data, and ages and masses were derived with recent isochrones. Only 12 of the stars turned out to be subgiants, i.e. on the “horizontal” part of the evolutionary track between the dwarf- and the giant stages. The abundances derived for the subgiants correspond closely to those of dwarf stars. With the possible exceptions of lithium and carbon we find that subgiant stars show no “chemical” traces of post-main-sequence evolution and that they are therefore very useful targets for studies of galactic chemical evolution.
Gaia Data Release 3 Andrae, R.; Fouesneau, M.; Sordo, R. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674, Številka:
A27
Journal Article
Recenzirano
Odprti dostop
Context.
The astrophysical characterisation of sources is among the major new data products in the third
Gaia
Data Release (DR3). In particular, there are stellar parameters for 471 million sources ...estimated from low-resolution BP/RP spectra.
Aims.
We present the General Stellar Parameterizer from Photometry (GSP-Phot), which is part of the astrophysical parameters inference system (Apsis). GSP-Phot is designed to produce a homogeneous catalogue of parameters for hundreds of millions of single non-variable stars based on their astrometry, photometry, and low-resolution BP/RP spectra. These parameters are effective temperature, surface gravity, metallicity, absolute
M
G
magnitude, radius, distance, and extinction for each star.
Methods.
GSP-Phot uses a Bayesian forward-modelling approach to simultaneously fit the BP/RP spectrum, parallax, and apparent
G
magnitude. A major design feature of GSP-Phot is the use of the apparent flux levels of BP/RP spectra to derive, in combination with isochrone models, tight observational constraints on radii and distances. We carefully validate the uncertainty estimates by exploiting repeat
Gaia
observations of the same source.
Results.
The data release includes GSP-Phot results for 471 million sources with
G
< 19. Typical differences to literature values are 110 K for
T
eff
and 0.2–0.25 for log
g
, but these depend strongly on data quality. In particular, GSP-Phot results are significantly better for stars with good parallax measurements (
ϖ
/
σ
ϖ
> 20), mostly within 2 kpc. Metallicity estimates exhibit substantial biases compared to literature values and are only useful at a qualitative level. However, we provide an empirical calibration of our metallicity estimates that largely removes these biases. Extinctions
A
0
and
A
BP
show typical differences from reference values of 0.07–0.09 mag. MCMC samples of the parameters are also available for 95% of the sources.
Conclusions.
GSP-Phot provides a homogeneous catalogue of stellar parameters, distances, and extinctions that can be used for various purposes, such as sample selections (OB stars, red giants, solar analogues etc.). In the context of asteroseismology or ground-based interferometry, where targets are usually bright and have good parallax measurements, GSP-Phot results should be particularly useful for combined analysis or target selection.
Aims
. We seek to provide abundances of a large set of light and neutron-capture elements homogeneously analyzed that cover a wide range of metallicity to constrain globular cluster (GC) formation ...and evolution models.
Methods
. We analyzed a large sample of 885 GCs giants from the SDSS IV-Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey. We used the Cannon results to separate the red giant branch and asymptotic giant branch stars, not only allowing for a refinement of surface gravity from isochrones, but also providing an independent
H
-band spectroscopic method to distinguish stellar evolutionary status in clusters. We then used the Brussels Automatic Code for Characterizing High accUracy Spectra (BACCHUS) to derive metallicity, microturbulence, macroturbulence, many light-element abundances, and the neutron-capture elements Nd and Ce for the first time from the APOGEE GCs data.
Results
. Our independent analysis helped us to diagnose issues regarding the standard analysis of the APOGEE DR14 for low-metallicity GC stars. Furthermore, while we confirm most of the known correlations and anticorrelation trends (Na-O, Mg-Al, C-N), we discover that some stars within our most metal-poor clusters show an extreme Mg depletion and some Si enhancement. At the same time, these stars show some relative Al depletion, displaying a turnover in the Mg-Al diagram. These stars suggest that Al has been partially depleted in their progenitors by very hot proton-capture nucleosynthetic processes. Furthermore, we attempted to quantitatively correlate the spread of Al abundances with the global properties of GCs. We find an anticorrelation of the Al spread against clusters metallicity and luminosity, but the data do not allow us to find clear evidence of a dependence of N against metallicity in the more metal-poor clusters.
Conclusions
. Large and homogeneously analyzed samples from ongoing spectroscopic surveys unveil unseen chemical details for many clusters, including a turnover in the Mg-Al anticorrelation, thus yielding new constrains for GCs formation/evolution models.
Gaia Data Release 3 Recio-Blanco, A.; de Laverny, P.; Palicio, P. A. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. A worldwide observational effort ...from the ground has provided, in one century, an extremely heterogeneous collection of chemical abundances for about two million stars in total, with fragmentary sky coverage.
Aims.
This situation is revolutionised by the
Gaia
third data release (DR3), which contains the parametrisation of Radial Velocity Spectrometer (RVS) data performed by the General Stellar Parametriser-spectroscopy, GSP-Spec, module. Here we describe the parametrisation of the first 34 months of
Gaia
RVS observations.
Methods.
GSP-Spec estimates the chemo-physical parameters from combined RVS spectra of single stars, without additional inputs from astrometric, photometric, or spectro-photometric BP/RP data. The main analysis workflow described here, MatisseGauguin, is based on projection and optimisation methods and provides the stellar atmospheric parameters; the individual chemical abundances of N, Mg, Si, S, Ca, Ti, Cr, Fe
I
, Fe
II
, Ni, Zr, Ce and Nd; the differential equivalent width of a cyanogen line; and the parameters of a diffuse interstellar band (DIB) feature. Another workflow, based on an artificial neural network (ANN) and referred to with the same acronym, provides a second set of atmospheric parameters that are useful for classification control. For both workflows, we implement a detailed quality flag chain considering different error sources.
Results.
With about 5.6 million stars, the
Gaia
DR3 GSP-Spec all-sky catalogue is the largest compilation of stellar chemo-physical parameters ever published and the first one from space data. Internal and external biases have been studied taking into account the implemented flags. In some cases, simple calibrations with low degree polynomials are suggested. The homogeneity and quality of the estimated parameters enables chemo-dynamical studies of Galactic stellar populations, interstellar extinction studies from individual spectra, and clear constraints on stellar evolution models. We highly recommend that users adopt the provided quality flags for scientific exploitation.
Conclusions.
The
Gaia
DR3 GSP-Spec catalogue is a major step in the scientific exploration of Milky Way stellar populations. It will be followed by increasingly large and higher quality catalogues in future data releases, confirming the
Gaia
promise of a new Galactic vision.
The Gaia-ESO Survey: Calibration strategy Pancino, E.; Lardo, C.; Altavilla, G. ...
Astronomy and astrophysics (Berlin),
02/2017, Letnik:
598
Journal Article, Web Resource
Recenzirano
Odprti dostop
The Gaia-ESO survey (GES) is now in its fifth and last year of observations and has produced tens of thousands of high-quality spectra of stars in all Milky Way components. This paper presents the ...strategy behind the selection of astrophysical calibration targets, ensuring that all GES results on radial velocities, atmospheric parameters, and chemical abundance ratios will be both internally consistent and easily comparable with other literature results, especially from other large spectroscopic surveys and from Gaia. The calibration of GES is particularly delicate because of (i) the large space of parameters covered by its targets, ranging from dwarfs to giants, from O to M stars; these targets have a large wide of metallicities and also include fast rotators, emission line objects, and stars affected by veiling; (ii) the variety of observing setups, with different wavelength ranges and resolution; and (iii) the choice of analyzing the data with many different state-of-the-art methods, each stronger in a different region of the parameter space, which ensures a better understanding of systematic uncertainties. An overview of the GES calibration and homogenization strategy is also given, along with some examples of the usage and results of calibrators in GES iDR4, which is the fourth internal GES data release and will form the basis of the next GES public data release. The agreement between GES iDR4 recommended values and reference values for the calibrating objects are very satisfactory. The average offsets and spreads are generally compatible with the GES measurement errors, which in iDR4 data already meet the requirements set by the main GES scientific goals.
This article develops a new model depicting how organizations can help customers test out and experience a service prior to purchase and consumption or use. When customers buy a new car, for ...instance, they are allowed to test-drive it to get the feel of it. When customers wish to purchase services, it can be more difficult to provide customers with a “test drive.” In some service situations, service organizations can and do provide “test drives,” but it is suggested that such experiences take place in a simulated setting. This article introduces the notion of hyperreality, the simulated reality of a service experience. It also introduces the concept of the “experience room,” the place where the simulated experience takes place. Based on the existing literature, the authors apply six dimensions of experience rooms to demonstrate how organizations can cocreate value, in conjunction with the customer, through hyperreality in a preservice experience.
Industrial companies today are becoming increasingly service-oriented and therefore need to shift from selling hardware to valuing services and managing customer relationships. A new and particularly ...significant challenge for these companies is how to initiate relationships which is an issue that has received surprisingly limited scientific attention. The aim of this study is to develop a conceptualization that explores the dynamics in the relationship initiation process in service-dominant settings. Narratives from three sellers of professional services, augmented with narratives from a buyer's view, form the empirical basis of the study. The dynamics in the relationship initiation process are clarified with three new concepts: status, converter, and inhibitor. The paper concludes with implications of the new conceptualization and suggestions for future research.
Gaia Data Release 3 Delchambre, L.; Bailer-Jones, C. A. L.; Bellas-Velidis, I. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
As part of the third
Gaia
Data Release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis ...Consortium, which is responsible for the determination of source astrophysical parameters using
Gaia
data. This is the third in a series of three papers describing the work done within CU8 for this release.
Aims.
For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for
Gaia
DR3. We further advise how to use these data products and highlight some limitations.
Methods.
The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |
b
|> 5°.
Results.Gaia
DR3 includes 1591 million sources with DSC classifications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 deg
2
where the extinction is evaluated by TGE.
Conclusions.
Validation shows that results are in good agreement with values from external catalogues; for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while UGC redshifts have a mean error of 0.008 ± 0.037 if evaluated on a clean set of spectra. An internal validation of the OA results further shows that 30 million sources are located in high confidence regions of the clustering map.
Context: As part of the third Gaia Data Release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis ...Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release.
Aims: For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations.
Methods: The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5 degrees.
Results: Gaia DR3 includes 1591 million sources with DSC classifications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0 :013 deg(2) where the extinction is evaluated by TGE.
Conclusions: Validation shows that results are in good agreement with values from external catalogues; for example 90% of the QSOC redshifts have absolute error lower than 0:1 for sources with empty warning flags, while UGC redshifts have a mean error of 0:008 +/- 0:037 if evaluated on a clean set of spectra. An internal validation of the OA results further shows that 30 million sources are located in high confidence regions of the clustering map.
PDF
