J/A+A/639/A127 Age-chemical-clocks-metallicity relations (Casali+, 2020)
The Gaia-ESO survey: the non-universality of the age-chemical-clocks-metallicity
relations in the Galactic disc.
Casali G., Spina L., Magrini L., Karakas A., Kobayashi C., Casey A.R.,
Feltzing S., Van der Swaelmen M., Tsantaki M., Jofre P., Bragaglia A.,
Feuillet D., Bensby T., Biazzo K., Gonneau A., Tautvaisiene G.,
Baratella M., Roccatagliata V., Pancino E., Sousa S., Adibekyan V.,
Martell S., Bayo A., Jackson R.J., Jeffries R.D., Gilmore G., Randich S.,
Alfaro E., Koposov S.E., Korn A.J., Recio-Blanco A., Smiljanic R.,
Franciosini E., Hourihane A., Monaco L., Morbidelli L., Sacco G., Worley C.,
Zaggia S.
<Astron. Astrophys. 639, A127 (2020)>
=2020A&A...639A.127C 2020A&A...639A.127C (SIMBAD/NED BibCode)
ADC_Keywords: Milky Way ; Clusters, open ; Abundances ; Stars, ages
Keywords: stars: abundances - Galaxy: abundances - Galaxy: disc -
Galaxy: evolution - open clusters and associations: general
Abstract:
In the era of large spectroscopic surveys, massive databases of
high-quality spectra coupled with the products of the Gaia satellite
provide tools to outline a new picture of our Galaxy. In this
framework, an important piece of information is provided by our
ability to infer stellar ages, and consequently to sketch a Galactic
timeline.
We aim to provide empirical relations between stellar ages and
abundance ratios for a sample of stars with very similar stellar
parameters to those of the Sun, namely the so-called solar-like stars.
We investigate the dependence on metallicity, and we apply our
relations to independent samples, that is, the Gaia-ESO samples of
open clusters and of field stars.
We analyse high-resolution and high-signal-to-noise-ratio HARPS
spectra of a sample of solar-like stars to obtain precise
determinations of their atmospheric parameters and abundances for 25
elements and/or ions belonging to the main nucleosynthesis channels
through differential spectral analysis, and of their ages through
isochrone fitting.
We investigate the relations between stellar ages and several
abundance ratios. For the abundance ratios with a steeper dependence
on age, we perform multivariate linear regressions, in which we
include the dependence on metallicity, [Fe/H]. We apply our best
relations to a sample of open clusters located from the inner to the
outer regions of the Galactic disc. Using our relations, we are able
to recover the literature ages only for clusters located at
RGC>7kpc. The values that we obtain for the ages of the inner-disc
clusters are much greater than the literature ones. In these clusters,
the content of neutron capture elements, such as Y and Zr, is indeed
lower than expected from chemical evolution models, and consequently
their [Y/Mg] and [Y/Al] are lower than in clusters of the same age
located in the solar neighbourhood. With our chemical evolution model
and a set of empirical yields, we suggest that a strong dependence on
the star formation history and metallicity-dependent stellar yields of
s-process elements can substantially modify the slope of the
[s/α]-[Fe/H]-age relation in different regions of the
Galaxy.
Our results point towards a non-universal relation
[s/α]-[Fe/H]-age, indicating the existence of relations with
different slopes and intercepts at different Galactocentric distances
or for different star formation histories. Therefore, relations
between ages and abundance ratios obtained from samples of stars
located in a limited region of the Galaxy cannot be translated into
general relations valid for the whole disc. A better understanding of
the s-process at high metallicity is necessary to fully understand the
origin of these variations.
Description:
The dataset contains stellar spectra collected by the HARPS
spectrograph. The instrument is installed on the 3.6m telescope at the
La Silla Observatory (Chile) and delivers a resolving power R=115000
over a 383-690nm wavelength range. The HARPS spectra are obtained from
the ESO Archive. The sample comprises 28985 HARPS spectra of 560
solar-like stars with atmospheric parameters within ±200K and
±0.2dex from the solar effective temperature and surface gravity,
respectively. The atmospheric parameters and chemical abundances are
calculated by the qoyllur-quipu (q2) code (https:
//github.com/astroChasqui/q2) through a differential line-by-line
analysis with respect to the spectrum of the Sun. The stellar age is
also estimated using the q2 code that computes a probability
distribution function for age for each star of our sample.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table2.dat 109 560 Atmospheric parameters and stellar ages
determined for the sample of solar-like stars
table3.dat 396 560 Chemical abundances for the sample of
solar-like stars
table1.dat 115 28985 Information about the HARPS spectra of the
sample of solar-like stars
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See also:
J/A+A/572/A33 : Abundances from Gaia-ESO Survey (Mikolaitis+, 2014)
J/A+A/589/A115 : Na and Al abundances of 1303 stars (Smiljanic+, 2016)
J/A+A/601/A70 : GES: pre-main-sequence clusters [Fe/H] (Spina+, 2017)
Byte-by-byte Description of file: table2.dat
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Bytes Format Units Label Explanations
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1- 17 A17 --- Star Star identification
19- 35 F17.13 deg RAdeg ? Right ascension (J2000)
37- 53 F17.13 deg DEdeg ? Declination (J2000)
55- 58 I4 K Teff Effective temperature
60- 64 F5.3 [cm/s2] logg Surface gravity
66- 71 F6.3 [-] [Fe/H] Metallicity
73- 76 F4.2 km/s vt Microturbulence velocity
78- 80 I3 K e_Teff Error of effective temperature
82- 86 F5.3 [cm/s2] e_logg Error on surface gravity
88- 92 F5.3 [-] e_[Fe/H] Error on metallicity
94- 97 F4.2 km/s e_vt Error on microturbulence
99-102 F4.1 Gyr Age ? Stellar age
104-107 F4.2 Gyr e_Age ? Error on stellar age
109 A1 --- Flag [0-1] Flag (G1)
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Byte-by-byte Description of file: table3.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 17 A17 --- Star Star identification
19- 24 F6.3 --- [CI/H] [-1.1/0.4] [CI/H] abundance
26- 30 F5.3 --- e_[CI/H] [0.0/0.6] Error on [CI/H]
32- 37 F6.3 --- [NaI/H] [-1.5/0.6]? [NaI/H] abundance
39- 43 F5.3 --- e_[NaI/H] [0.0/0.4]? Error on [NaI/H]
45- 50 F6.3 --- [MgI/H] [-1.1/0.5] [MgI/H] abundance
52- 56 F5.3 --- e_[MgI/H] [0.0/0.2] Error on [MgI/H]
58- 63 F6.3 --- [AlI/H] [-1.5/0.5] [AlI/H] abundance
65- 69 F5.3 --- e_[AlI/H] [0.0/0.3] Error on [AlI/H]
71- 76 F6.3 --- [SiI/H] [-1.0/0.5] [SiI/H] abundance
78- 82 F5.3 --- e_[SiI/H] [0.0/0.1] Error on [SiI/H]
84- 89 F6.3 --- [SI/H] [-1.1/0.5]? [SI/H] abundance
91- 95 F5.3 --- e_[SI/H] [0.0/0.7]? Error on [SI/H]
97-102 F6.3 --- [CaI/H] [-1.0/0.5] [CaI/H] abundance
104-108 F5.3 --- e_[CaI/H] [0.0/0.2] Error on [CaI/H]
110-115 F6.3 --- [ScI/H] [-1.1/0.6] [ScI/H] abundance
117-121 F5.3 --- e_[ScI/H] [0.0/0.5] Error on [ScI/H]
123-128 F6.3 --- [ScII/H] [-1.2/0.5] [ScII/H] abundance
130-134 F5.3 --- e_[ScII/H] [0.0/0.2] Error on [ScII/H]
136-141 F6.3 --- [TiI/H] [-1.0/0.5] [TiI/H] abundance
143-147 F5.3 --- e_[TiI/H] [0.0/0.2] Error on [TiI/H]
149-154 F6.3 --- [TiII/H] [-1.1/0.5] [TiII/H] abundance
156-160 F5.3 --- e_[TiII/H] [0.0/0.3] Error on [TiII/H]
162-167 F6.3 --- [VI/H] [-1.3/0.5] [VI/H] abundance
169-173 F5.3 --- e_[VI/H] [0.0/0.2] Error on [VI/H]
175-180 F6.3 --- [CrI/H] [-1.3/0.5] [CrI/H] abundance
182-186 F5.3 --- e_[CrI/H] [0.0/0.2] Error on [CrI/H]
188-193 F6.3 --- [CrII/H] [-1.2/0.5] [CrII/H] abundance
195-199 F5.3 --- e_[CrII/H] [0.0/0.3] Error on [CrII/H]
201-206 F6.3 --- [MnI/H] [-1.8/0.6] [MnI/H] abundance
208-212 F5.3 --- e_[MnI/H] [0.0/0.2] Error on [MnI/H]
214-219 F6.3 --- [FeI/H] [-1.2/0.5] [FeI/H] abundance
221-225 F5.3 --- e_[FeI/H] [0.0/0.1] Error on [FeI/H]
227-232 F6.3 --- [FeII/H] [-1.2/0.5] [FeII/H] abundance
234-238 F5.3 --- e_[FeII/H] [0.0/0.2] Error on [FeII/H]
240-245 F6.3 --- [CoI/H] [-1.4/0.7] [CoI/H] abundance
247-251 F5.3 --- e_[CoI/H] [0.0/0.4] Error on [CoI/H]
253-258 F6.3 --- [NiI/H] [-1.3/0.5] [NiI/H] abundance
260-264 F5.3 --- e_[NiI/H] [0.0/0.1] Error on [NiI/H]
266-271 F6.3 --- [CuI/H] [-1.8/0.6] [CuI/H] abundance
273-277 F5.3 --- e_[CuI/H] [0.0/0.5] Error on [CuI/H]
279-284 F6.3 --- [ZnI/H] [-1.2/0.6]? [ZnI/H] abundance
286-290 F5.3 --- e_[ZnI/H] [0.0/0.3]? Error on [ZnI/H]
292-297 F6.3 --- [SrI/H] [-1.3/0.9]? [SrI/H] abundance
299-303 F5.3 --- e_[SrI/H] [0.0/0.2]? Error on [SrI/H]
305-310 F6.3 --- [YII/H] [-1.3/0.9] [YII/H] abundance
312-316 F5.3 --- e_[YII/H] [0.0/0.5] Error on [YII/H]
318-323 F6.3 --- [ZrII/H] [-1.0/1.0]? [ZrII/H] abundance
325-329 F5.3 --- e_[ZrII/H] [0.0/0.4]? Error on [ZrII/H]
331-336 F6.3 --- [BaII/H] [-1.3/0.7] [BaII/H] abundance
338-342 F5.3 --- e_[BaII/H] [0.0/0.2] Error on [BaII/H]
344-349 F6.3 --- [CeII/H] [-1.2/0.7]? [CeII/H] abundance
351-355 F5.3 --- e_[CeII/H] [0.0/0.6]? Error on [CeII/H]
357-362 F6.3 --- [NdII/H] [-1.0/0.5]? [NdII/H] abundance
364-368 F5.3 --- e_[NdII/H] [0.0/0.3]? Error on [NdII/H]
370-375 F6.3 --- [SmII/H] [-1.0/1.0]? [SmII/H] abundance
377-381 F5.3 --- e_[SmII/H] [0.0/0.1]? Error on [SmII/H]
383-388 F6.3 --- [EuII/H] [-1.0/0.7]? [EuII/H] abundance
390-394 F5.3 --- e_[EuII/H] [0.0/0.2]? Error on [EuII/H]
396 A1 --- Flag [0-1] Flag (G1)
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Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 17 A17 --- Star Star identification
19- 58 A40 --- IDspect Spectrum identification
60- 78 A19 "datime" Obs.date Observational date
80- 93 A14 --- ProgID Program ID
95- 99 F5.2 --- Seeing ?=-1 Seeing (1)
101-109 F9.4 s Texp Exposure time
111-115 F5.1 --- S/N Signal-to-noise ratio
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Note (1): seeing -1.00 means value not available.
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Global notes:
Note (G1): Flag as follows:
1 = stars with uncertainties on the atmospheric parameters smaller than 95%
of their distributions.
0 = stars with uncertainties on the atmospheric parameters larger than 95%
of their distributions.
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Acknowledgements:
Giada Casali, casali(at)arcetri.astro.it
(End) G. Casali [Univ. Florence, INAF-OAA], P. Vannier [CDS] 08-Jun-2020