A Homogeneous Comparison between the Chemical Composition of the Large Magellanic Cloud and the Sagittarius Dwarf Galaxy^*

Among the nearby Local Group galaxies, the closest Milky Way (MW) satellites, namely, the Sagittarius (Sgr) dwarf spheroidal galaxy and the Large and Small Magellanic Clouds (LMC and SMC, respectively), provide the opportunity to investigate the evolution of stellar populations in interacting galaxies. The LMC and SMC are two massive (∼10¹⁰ and 10⁹ M_⊙, respectively) irregular galaxies orbiting each other, forming a triple system with the MW. Sgr is the remnant of a dwarf spheroidal galaxy still merging with the MW. The former case allows us to study an ongoing merging event between galaxies with comparable masses, while the latter is a spectacular case of a satellite almost totally disrupted by the tidal field of its (significantly more massive) parent galaxy.

The LMC and Sgr exhibit some similarities in terms of stellar populations, with their stellar content dominated by an intermediate-age population with similar metallicity. The metallicity distributions of these two galaxies are both peaked at [Fe/H] ∼ −0.5/−0.3 dex, as found by several spectroscopic works; see, e.g., Pompéia et al. (2008), Lapenna et al. (2012), Van der Swaelmen et al. (2013), Song et al. (2017), and Nidever et al. (2020) for the LMC, and Monaco et al. (2005), Bellazzini et al. (2006), Sbordone et al. (2007), Carretta et al. (2010), McWilliam et al. (2013), Hasselquist et al. (2017), and Mucciarelli et al. (2017a) for Sgr. The age range of their dominant populations is ∼3–5 Gyr for the LMC (Bekki & Chiba 2005; Harris & Zaritsky 2009; Rubele et al. 2012; Nidever et al. 2020) and ∼6–8 Gyr for Sgr (Layden & Sarajedini 2000; Bellazzini et al. 2006; de Boer et al. 2015). Also, both galaxies have a metal-poor, old stellar component accounting for less than ∼10% of the total stellar content (see, e.g., Monaco et al. 2003; Cole et al. 2005; Hamanowicz et al. 2016; Nidever et al. 2020). However, it is important to note that the available spectroscopic metallicity distributions of Sgr stars sample its central region where the massive metal-poor globular cluster M54 lies. Therefore, these distributions are dominated by the stars of M54 at [Fe/H] < −1.2 dex (see, e.g., Mucciarelli et al. 2017a for further discussions). Moreover, the presence of a metallicity gradient in the main body of Sgr (Hayes et al. 2020) does not allow us to observe a representative sample of the whole galaxy focusing only in the central region.

The violent interactions between the LMC and SMC and between Sgr and the MW have significantly impacted the stellar populations of the LMC and Sgr, contributing to the shape of their star formation histories. The LMC is likely at its first peri-Galactic passage with the MW (Shuter 1992; Byrd et al. 1994; Besla et al. 2007), and it experienced significant tidal gas stripping only recently (∼1.5 Gyr ago; Guglielmo et al. 2014). The gravitational interactions with the SMC started about 4–5 Gyr ago (Bekki et al. 2004; Bekki & Chiba 2005), likely triggering the numerous bursts of star formation in the two galaxies (Harris & Zaritsky 2009; Rubele et al. 2012; Nidever et al. 2020). In particular, the bulk of the stellar content in the LMC is peaked at ∼3–5 Gyr, but a vigorous present-day star formation activity is present, fueled by a remaining large reservoir of Hi. On the other hand, the tidal interaction between Sgr and the more massive MW has disrupted the dwarf galaxy, spreading most of its stellar content and stripping away all the gas (no neutral gas has ever been found in Sgr; Koribalski et al. 1994; Burton & Lockman 1999). The bulk of the Sgr stars formed until ∼6–8 Gyr ago, and probably the star formation was drastically reduced after the first peri-Galactic passage, during which the gas not stripped away was fully converted into stars. This passage had an impact also on the MW disk, triggering an analogous burst in its star formation history (Laporte et al. 2019; Ruiz-Lara et al. 2020).

Some similarities between the chemical composition of the metal-rich component of the LMC and Sgr have already been highlighted (Bonifacio et al. 2000, 2004; Monaco et al. 2005; Hasselquist et al. 2017; Mucciarelli et al. 2017a), especially for the [α/Fe] abundance ratios that in the metal-rich stars of both galaxies are lower than those measured among the MW stars of similar [Fe/H], as expected for galaxies with lower star formation efficiencies (Matteucci & Brocato 1990). Also, subsolar abundance ratios of some iron-peak elements and supersolar abundances for some neutron-capture elements are common features of the metal-rich stars of the LMC and Sgr (Pompéia et al. 2008; Van der Swaelmen et al. 2013). Their similar chemical patterns suggest that they have experienced analogous chemical enrichment histories and that the progenitor of Sgr could be as massive as the LMC (Niederste-Ostholt et al. 2012; de Boer et al. 2014; Gibbons et al. 2017; Mucciarelli et al. 2017a; Carlin et al. 2018).

However, in order to properly highlight similarities and differences between the chemical compositions of the two galaxies, one needs to compare sets of chemical abundances obtained under the same assumptions (see, e.g., Reichert et al. 2020). In fact, the adopted model atmospheres, temperature scale, atomic data, and solar reference abundances can lead to systematics among different chemical analyses, hampering the possibility of a fully meaningful comparison of abundance patterns. The comparisons between the chemical patterns of the LMC and Sgr performed so far are based on analyses that adopted different physical assumptions, limiting our capability to highlight real differences or similarities and allowing us to provide only a qualitative comparison.

In order to bypass this issue, in this study we present a homogeneous and self-consistent chemical analysis of high-resolution spectra for red giant branch (RGB) stars in the LMC, Sgr, and the MW, with the twofold aim of comparing the chemical composition of the LMC and Sgr, keeping the MW abundance pattern as a reference. This study is restricted to the dominant stellar components of the two galaxies, therefore stars with [Fe/H] > −1.0 dex. In particular, we measured chemical abundances for the main groups of elements (light, alpha, iron-peak, neutron-capture elements) to estimate the role played in their chemical evolution by massive stars, exploding either as Type II supernovae (SNe II) or more energetic hypernovae (HNe), and degenerate binary systems, exploding as Type Ia supernovae (SNe Ia) and asymptotic giant branch (AGB) stars.

This paper presents the homogeneous chemical analysis of three samples of high-resolution spectra collected with the optical spectrograph UVES-FLAMES (Pasquini et al. 2002) mounted at the Very Large Telescope of the European Southern Observatory. The observations have been performed adopting the Red Arm 580 UVES setup, with a spectral resolution of 47,000 and a spectral coverage between about 4800 and 6800 Å. All the spectra have been reduced with the dedicated ESO pipelines, ³ including bias subtraction, flat-fielding, wavelength calibration, spectral extraction, and order merging. For each target the individual exposures have been sky-subtracted using the spectra of some close sky regions observed in the same exposure of the science targets.

• 1.  
  LMC data set.—It includes 30 RGB stars belonging to the LMC. Eleven of these stars have been originally selected as possible member stars of some LMC globular clusters but were revealed to be LMC field stars according to their radial velocity and metallicity (both discrepant with respect to those of the close globular cluster). The spectra of the other stars have been retrieved from the ESO archive, selecting UVES-FLAMES observations pointed toward the LMC and considering only giant stars with signal-to-noise ratio (S/N) per pixel larger than ∼20 and with radial velocities between +170 and +380 km s⁻¹, which is the range of radial velocities of the LMC stars (Zhao et al. 2003; Carrera et al. 2008). The LMC spectra have S/N ranging from ∼20 to ∼60 at 6000 Å. The final sample is composed of stars located in different regions of the galaxy, distributed between ∼05 to ∼5° from the LMC center (van der Marel & Cioni 2001). No significant metallicity gradient is expected among the LMC stars within this distance from the center because the mean metallicity of the LMC field stars remains constant within 6° from the LMC center (Carrera et al. 2011).
• 2.  
  Sgr data set.—This data set includes UVES-FLAMES spectra of 14 stars belonging to the upper RGB of the main body of Sgr. Twelve of these stars have already been discussed by Monaco et al. (2005), which, however, provide only the abundances of Fe, Mg, Ca, and Ti, while the remaining 2 stars are from the UVES-FLAMES sample by Carretta et al. (2010). The study of Monaco et al. (2005) included three other RGB stars with [Fe/H] between −1.5 and −1.1 dex, all located within 32 from M54 center but only the most metal-poor considered as a likely member of M54. Our chemical analysis, however, suggests that these three stars are likely members of M54, in virtue of their strong enhancement of Na and Al abundances typical of second-generation stars observed in globular-cluster-like systems (Bastian & Lardo 2018). Therefore, we exclude these stars from our sample, focusing only on the metal-rich ([Fe/H] > −1.0 dex) component of Sgr.
• 3.  
  MW data set.—We defined a reference sample of 14 giant/subgiant MW stars selected from Soubiran et al. (2016) and Smiljanic et al. (2016) and covering the same range of metallicity of the LMC/Sgr targets. The stars belong to both thin and thick disks of the Galaxy, and they have been selected in order to have observations with the Red Arm 580 UVES setup available in the ESO archive and with low color excess (E(B − V) < 0.2 mag).

We highlight that the LMC and Sgr samples include the best spectra, in terms of S/N and spectral resolution, available in the ESO archive for these two galaxies, but they cannot be considered as fully representative of the metallicity distributions of these galaxies. In fact, the LMC sample has been built with stars from different programs and in most cases selected as candidate cluster members. The Sgr stars by Monaco et al. (2005) have been selected along the reddest side of the Sgr RGB in order to maximize the detection of Sgr member stars, hence privileging the most metal-rich stars. The fact that the stars in our Sgr sample have metallicities on average higher than that of the LMC stars (see Section 5) is most likely due to this bias and does not reflect a real difference in the metallicity distributions. We are aware that the samples we are using are small and not fully representative of the complexity of the three galaxies. Currently, a complete chemical screening based on high-resolution spectra can be performed on small samples, but a fully homogeneous comparison of the chemical abundances of different elements in these three galaxies is a crucial starting point also for future observations.

As a first step, effective temperatures (T_eff) and surface gravities ($\mathrm{log}g$) for the observed targets have been derived by using the early third data release of the ESA/Gaia mission (Gaia Collaboration et al. 2016, 2020) and the near-infrared 2MASS survey (Skrutskie et al. 2006).

Gaia eDR3 photometric parameters.—T_eff have been calculated by using the (BP − RP)₀–T_eff transformation provided by Mucciarelli & Bellazzini (2020) and based on the infrared flux method T_eff estimated by González Hernández & Bonifacio (2009). The transformation was calibrated on Gaia DR2 data, but it remains valid also for the new data release. The (BP–RP) colors have been corrected for extinction with an iterative procedure following the scheme proposed by Gaia Collaboration et al. (2018a). The color excess adopted for the Sgr targets is E(B − V) = 0.14 ± 0.03 mag (Layden & Sarajedini 2000). For the LMC targets we used the reddening maps by Skowron et al. (2021). Finally, for the MW sample color excesses are from Schlafly & Finkbeiner (2011). Because color–T_eff relations derived by Mucciarelli & Bellazzini (2020) have a dependence from the stellar metallicity, first we derived T_eff adopting [Fe/H] = −0.5 dex for all the stars (a reasonable value for the LMC/Sgr dominant stellar populations), and subsequently we refined T_eff adopting for any star the appropriate metallicity obtained from the chemical analysis.

Surface gravities have been calculated by adopting the photometric T_eff described above, a stellar mass of 1 M_⊙ (a representative value for the stellar mass of stars belonging to the main LMC and Sgr stellar populations), ⁴ and the G-band bolometric corrections computed according to Andrae et al. (2018). To transform apparent magnitudes into absolute magnitudes, we adopted the distance modulus of (m − M)₀ = 17.10 ± 0.15 mag for Sgr (Monaco et al. 2004) and (m − M)₀ = 18.50 ± 0.02 mag for the LMC (Alves 2004). For the MW stars, their distances have been derived from Gaia eDR3 parallaxes corrected by the offset (+0.029 mas) provided by Gaia Collaboration et al. (2018b). Only for one star in the MW sample is the ratio between parallax and its uncertainty lower than 10, indicating that the distance errors are not symmetrical (Bailer-Jones 2015). According to the typical parallax errors, the derived distance errors are of the order of 0.10 pc.

2MASS/SofI photometric parameters.—For most of the targets we adopted the near-infrared photometry provided by 2MASS, but for the LMC targets observed close to globular clusters we used our own SofI@NTT photometry (which is more precise than 2MASS photometry thanks to the higher spatial resolution) calibrated onto the 2MASS photometric system. T_eff have been obtained using the (J − K)₀–T_eff relation provided by González Hernández & Bonifacio (2009) and defined on the 2MASS photometric system, and adopting the same color excesses discussed above. For $\mathrm{log}g$ the only difference with respect to the procedure based on the Gaia eDR3 photometry is the computation of the K-band bolometric corrections following the prescriptions by Buzzoni et al. (2010).

The two sets of parameters are in good agreement for Sgr and MW stars. For the MW targets the mean differences between 2MASS and Gaia eDR3 parameters are −136 ± 40 K (σ = 150 K) and −0.01 ± 0.02 (σ = 0.09), respectively, for T_eff and log g, while for Sgr targets they are −89 ± 20 K (σ = 72 K) and −0.050 ± 0.006 (σ = 0.02). Instead, for the LMC targets the mean differences are −149 ± 74 K (σ = 405 K) and −0.13 ± 0.06 K (σ = 0.31 K). Applying a 3σ rejection, the mean difference between T_eff from 2MASS and Gaia eDR3 decreases down to −100 ± 58 K (σ = 310 K), but still with a significant scatter.

An additional clue to validate the photometric parameters (and understand which set of parameters is more correct) is to use the standard spectroscopic constraints, namely, the excitation equilibrium to set T_eff (all the Fe i lines provide within the uncertainties the same abundances regardless of the excitation potential χ) and the ionization equilibrium to set log g (neutral and single ionized Fe lines provide within the uncertainties the same average abundance). As demonstrated by Mucciarelli & Bonifacio (2020), the spectroscopic parameters derived following this approach well agree with those derived from the photometry for [Fe/H] > −1.5 dex, while at lower metallicities the spectroscopic parameters are systematically biased and should be avoided (or appropriately corrected following the relations by Mucciarelli & Bonifacio 2020). All the stars discussed in this work have [Fe/H] > −1.1 dex; hence, the spectroscopic method can be used to derive the parameters or to check the photometric ones. Therefore, correct parameters should provide null (within the uncertainties) values for both the slope between the Fe i abundance and χ (σ_χ ) and the difference between the average Fe i and Fe ii abundances (ΔFe).

T_eff from Gaia eDR3 and 2MASS photometries provide values of σ_χ that are null (within ±1σ) for almost all the MW and Sgr targets, indicating that the two photometric T_eff are reliable. For the LMC stars, T_eff from Gaia eDR3 photometry are higher than the 2MASS T_eff by about 200–250 K and providing significant values of σ_χ (at a level of 3σ–4σ or more), at variance to 2MASS T_eff that have σ_χ null at a level of 1σ–2σ. This difference with the spectroscopic T_eff is found also when photometric T_eff are estimated adopting the recent relation provided by Casagrande et al. (2020). This suggests that the Gaia eDR3 T_eff are overestimated, for the LMC targets only. We attribute this different behavior to the high stellar crowding conditions in the LMC, leading to possible problems in the background subtraction for LMC stars.

Spectroscopic parameters.—We decide to use spectroscopic parameters for the targets in all three galaxies, necessary especially for LMC targets owing to the issues with the Gaia eDR3 photometry and the large uncertainties in the 2MASS photometry. In this way we guarantee a homogeneous approach in the determination of the atmospheric parameters for the three samples. An additional hurdle in the spectroscopic determination of the stellar parameters arises from the fact that in giant stars with T_eff < 4200 K, Fe ii lines are more sensitive to T_eff than Fe i lines and ΔFe is more sensitive to T_eff than to $\mathrm{log}g$. Therefore, the usual approach to derive T_eff from excitation equilibrium and log g from ionization equilibrium should be revised, because ΔFe can be canceled or reduced mainly with small changes in T_eff (without significant changes in σ_χ ) and not with large variations in log g. Starting from the photometric parameters, we changed T_eff and log g in order to reduce the large ΔFe observed in some stars and to have simultaneously a value of σ_χ null within ±1σ.

Finally, the microturbolent velocities ξ have been determined by minimizing the slope between the abundances from Fe i lines and the reduced equivalent widths (EWs).

The final atmospheric parameters are listed in Table 1, together with the coordinates, the 2MASS/SofI and Gaia eDR3 photometry, the color excess, and the measured metallicity.

The lines used to derive the chemical abundances have been selected by comparing the observed spectra with synthetic spectra calculated with the code SYNTHE (Kurucz 2005) in order to evaluate the level of blending for each transition. The synthetic spectra have been calculated using the atomic and molecular data listed in the Kurucz/Castelli line lists ⁵ and convoluted with a Gaussian profile in order to reproduce the observed broadening. Model atmospheres have been calculated for any star with the code ATLAS9 (Kurucz 2005) and assuming the stellar parameters derived from the Gaia eDR3 (for Sgr and the MW) or 2MASS/SofI (for the LMC) photometry. Initially we assumed a metallicity of [Fe/H] = −0.5 dex for all the targets. Each line list has been subsequently refined according to the metallicity and the stellar parameters obtained from the chemical analysis.

Chemical abundances for species with unblended lines (Fe, Na, Al, Ca, Ti, Si, Cr, Ni, Zr, Y, and Nd) have been derived from the measured EWs of selected lines by using the code GALA (Mucciarelli et al. 2013).

EWs have been measured with DAOSPEC (Stetson & Pancino 2008) through the wrapper 4DAO (Mucciarelli 2013). A visual inspection on the fitted lines has been performed in order to identify possible lines with an unsatisfactory fit. For these few lines (less than 1% of the total) the EWs have been remeasured using the IRAF task splot.

For the species for which only blended lines (O, Sc, V, Mn, Co, Cu, Ba, La, Eu) or transitions located in noisy/complex spectral regions (Mg, Zn) are available, the chemical abundances have been derived with our own code SALVADOR that performs a χ²-minimization between the observed line and a grid of suitable synthetic spectra calculated on the fly using the code SYNTHE and varying only the abundance of the corresponding element.

Atomic data (excitation potential χ, log gf, damping constants, and hyperfine/isotopic splitting) for the used lines are from the Kurucz/Castelli database, improved for some specific transitions with more recent or more accurate data (see Mucciarelli et al. 2017b, for some additional references). Solar reference abundances are from Grevesse & Sauval (1998) except for oxygen, for which the value quoted by Caffau et al. (2011) is adopted.

In the following, we discuss in detail the procedure adopted to derive chemical abundances for a few problematic species.

• 1.  
  Oxygen: only the forbidden line at 6300.3 Å is available for this element in the optical range. This spectral region is contaminated by several telluric lines. For each target we calculated a synthetic spectrum for the Earth transmission using the code TAPAS (Bertaux et al. 2014), and in the case of contamination of the O line the observed stellar spectrum has been divided by the Earth atmosphere spectrum.Oxygen abundance is derived using spectral synthesis because the forbidden line is blended with an Ni line. In principle, the oxygen abundance can be sensitive to the C and N abundances because of the molecular equilibrium. However, the UVES spectra do not allow us to directly measure these abundances, and the assumption of specific C and N abundances for mixed RGB stars is sensitive to metallicity and stellar mass. We thus adopted solar-scaled C and N abundances, but we checked how O abundance changes for different assumptions of C and N abundances. Indeed, according to the C and N abundances measured for RGB stars brighter than the RGB bump in these galaxies (see, e.g., Smith et al. 2002 for the LMC, Hasselquist et al. 2017 for Sgr, and Gratton et al. 2000 for the MW), [C/Fe] is depleted and [N/Fe] is enhanced. Figure 1 shows for a representative target star the variation of [O/H] as a function of [C/Fe] depletion and corresponding [N/Fe] enhancement. [O/H] is poorly dependent on [N/Fe], while a mild dependence with [C/Fe] is found. In particular, a [C/Fe] depletion and a corresponding enhancement of [N/Fe] by 0.5 dex decreases [O/H] by ∼0.1 dex.
• 2.  
  Magnesium: in the optical range the available Mg lines are those at 5528 and 5711 Å and the triplet at 6318–6319 Å. The first line is dominated by huge pressure-broadening wings, therefore excluded from our line list. The second line is often used in chemical analyses of giant stars. On the other hand, this line is heavily saturated (and often insensitive to the Mg abundance) at [Fe/H] > −1.0 dex and low T_eff (<4500 K). In Figure 2 we show some sets of synthetic spectra around the Mg line at 5711 Å and the Mg triplet at 6318–19 Å for a representative giant star considering three different metallicity ([Fe/H] = −1.0, −0.5, +0.0 dex). The line at 5711 Å becomes more saturated, increasing the metallicity and the Mg abundance, becoming totally insensitive to the abundance variations approaching solar metallicities. Instead, the weaker lines at 6318–19 Å are still sensitive to the Mg abundance until [Fe/H] ∼ 0.0. Therefore, we suggest to avoid the use of the Mg line at 5711 Å in metal-rich giant stars and consider with caution abundances derived from this transition.Only in a few targets (generally with [Fe/H] < −0.9/−0.8 dex) is the Mg line at 5711 Å still sensitive to the abundance and can it be safely used. For all the other stars Mg abundances have been derived from the lines at 6318–6319 Å, using spectral synthesis because these transitions are located on the red wing of a broad autoionization Ca line that affects the continuum location.
• 3.  
  Sodium: the two Na doublets used in this work (at 5682–88 Å and 6154–60 Å) are both affected by departures from local thermodynamic equilibrium. We applied the suitable non-LTE (NLTE) corrections for each line by Lind et al. (2011), of the order of about −0.15 dex for the first doublet and about −0.05 dex for the second one.
• 4.  
  Copper: the only available line is that at 5205.5 Å (the other optical Cu line, at 5782 Å, lies in the gap between the two chips of the 580 setup). At the metallicities/temperatures of our targets, the line is already on the flat part of the curve of growth and basically insensitive to the abundance. Hence, we exclude the abundances of Cu from our analysis, and we discourage using this Cu line for metal-rich giant stars similar to those analyzed here.
• 5.  
  Barium: three Ba ii lines are available in the spectra, located at 5853.7, 6141.7, and 6496.9 Å. The latter transition provides abundances systematically higher than the other two lines for all the targets. We check the atomic parameters of the three Ba ii lines on the solar-flux spectrum by Neckel & Labs (1984), and the line at 6496.9 Å provides Ba abundance 0.2 dex higher than the other lines; therefore, it has been excluded.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

4.1. Error Estimates

Abundance uncertainties have been computed by summing in quadrature the error related to the measurement process and those arising from the adopted atmospheric parameters. The errors due to the measurement have been derived according to the method adopted to obtain the abundances.

Internal errors relative to the EW measurements have been estimated as the line-to-line scatter divided by the rms of the number of used lines. For the elements for which fewer than four lines are available (namely, Al, Na, Y, and Zr) we adopt the standard deviation from Fe i lines as a more realistic estimate of the line-to-line scatter.

O, Mg, Sc, Co, V, Mn, Zn, Ba, La, and Eu are the elements whose abundances are derived from spectral synthesis. The uncertainties of their measurement have been estimated by resorting to Monte Carlo simulation. We created synthetic spectra with representative values for the atmospheric parameters of the analyzed stars, and we injected Poisson noise into them, according to the S/N of the observed spectra. For each line, 200 noisy spectra have been generated and the abundance derived adopting the same procedure used for observed spectra. Finally, we calculated the internal measurement error as the standard deviation of the elemental abundance values derived from the 200 simulations.

The uncertainties arising from the atmospheric parameters have been computed by varying only one parameter at a time, keeping the other ones fixed, and deriving the abundance variation. This method provides a conservative estimate of the uncertainties because it does not take into account the correlations among the parameters. The applied variations are of 100 K, 0.1 dex, and 0.1 km s⁻¹ for T_eff, $\mathrm{log}g$, and ξ, respectively. The variations correspond to the typical uncertainties of the atmospheric parameters.

Since our results are expressed as abundance ratios, also the uncertainties in the Fe abundance have been taken into account. Therefore, the final errors in [Fe/H] and [X/Fe] abundance ratios are calculated as follows:

$$\begin{eqnarray}&&{\sigma }_{[\mathrm{Fe}/{\rm{H}}]}=\sqrt{\displaystyle \frac{{\sigma }_{\mathrm{Fe}}^{2}}{{N}_{\mathrm{Fe}}}+{\left({\delta }_{\mathrm{Fe}}^{{T}_{\mathrm{eff}}}\right)}^{2}+{\left({\delta }_{\mathrm{Fe}}^{\mathrm{log}g}\right)}^{2}+{\left({\delta }_{\mathrm{Fe}}^{\eta }\right)}^{2}}\end{eqnarray} \tag{ 1 }$$

$$\begin{eqnarray}&&\begin{array}{l}{\sigma }_{[{\rm{X}}/\mathrm{Fe}]}\\ =\,\sqrt{\frac{{\sigma }_{{\rm{X}}}^{2}}{{N}_{{\rm{X}}}}+\frac{{\sigma }_{\mathrm{Fe}}^{2}}{{N}_{\mathrm{Fe}}}+{({\delta }_{{\rm{X}}}^{{T}_{\mathrm{eff}}}-{\delta }_{\mathrm{Fe}}^{{T}_{\mathrm{eff}}})}^{2}+{({\delta }_{{\rm{X}}}^{\mathrm{log}g}-{\delta }_{\mathrm{Fe}}^{\mathrm{log}g})}^{2}+{({\delta }_{{\rm{X}}}^{\eta }-{\delta }_{\mathrm{Fe}}^{\eta })}^{2},}\end{array}\end{eqnarray} \tag{ 2 }$$

where σ_X,Fe is the dispersion around the mean of the chemical abundances, N_X,Fe is the number of lines used to derive the abundances, and ${\delta }_{{\rm{X}},\mathrm{Fe}}^{i}$ are the abundance variations obtained modifying the atmospheric parameter i.

This work provides for the first time a fully self-consistent comparison of the abundances for the main groups of elements (light, alpha, iron-peak, neutron-capture elements) among the metal-rich stars in the LMC, Sgr, and the MW. Although these samples cannot be considered as fully representative of the metallicity distributions of the parent galaxies, in particular because of some selection bias in their definition (see Section 2), this work has the main advantage of removing most of the systematics (i.e., solar abundances, atomic data, model atmospheres), affecting the comparison of their abundances.

Tables 2–4 list the measured values of the elemental abundances with their error. In Figures 3–8 we show the results obtained for the three samples, together with the abundances in Galactic field stars from the literature (see caption of Figures 3–8 for references). Only for the works that do not adopt solar values determined with their own line list did we rescale their abundances to our solar reference values. The latter measures are shown as a sanity check to verify that our heterogeneous sample of MW stars reproduces the main MW chemical patterns. Also, the use of both dwarf and giant stars and of different assumptions in the chemical analyses (i.e., atomic data, solar reference values, and model atmospheres, among others) could hamper the direct comparison with the LMC and Sgr abundances derived here. The comparison between our abundances and those from the literature is satisfactory for almost all the elements, while we found offsets of about 0.1–0.2 dex for Na, Al, Co, V and Eu. These differences are mainly explained by the different transitions, atomic parameters, and (in the case of Na) NLTE corrections adopted by different authors. The existence of these offsets enforces the importance of a homogeneous analysis for all the stars.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Table 2. LMC and Sgr Chemical Abundances

ID	$\left[\tfrac{\mathrm{Fe}}{{\rm{H}}}\right]$	err	$\left[\tfrac{\mathrm{Fe}\,{\rm\small{II}}}{{\rm{H}}}\right]$	err	$\left[\tfrac{\mathrm{Na}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Al}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{\rm{O}}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Mg}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Si}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ca}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ti}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Sc}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{\rm{V}}}{\mathrm{Fe}}\right]$	err
LMC
NGC 1754_248	−0.53	0.06	−0.56	0.22	−0.47	0.14	−0.09	0.14	0.25	0.06	−0.08	0.20	0.23	0.10	−0.03	0.13	−0.11	0.17	−0.16	0.05	−0.46	0.17
NGC 1786_2191	−0.29	0.05	−0.31	0.16	−0.36	0.08	−0.18	0.08	0.14	0.06	−0.07	0.06	0.08	0.10	−0.04	0.05	−0.18	0.12	−0.17	0.07	−0.44	0.16
NGC 1786_569	−0.50	0.05	−0.65	0.18	−0.33	0.11	−0.07	0.11	0.28	0.06	0.03	0.13	0.11	0.11	−0.01	0.06	0.01	0.14	−0.13	0.08	−0.34	0.16
NGC 1835_1295	−0.49	0.06	−0.60	0.18	−0.17	0.15	0.02	0.15	0.14	0.08	0.07	0.27	0.13	0.11	0.10	0.07	−0.16	0.14	−0.39	0.08	−0.54	0.16
NGC 1835_1713	−0.58	0.06	−0.64	0.19	−0.11	0.16	−0.13	0.16	0.06	0.08	⋯	⋯	0.21	0.11	0.06	0.10	−0.04	0.15	−0.27	0.14	−0.54	0.17
NGC 1898_2322	−0.43	0.07	−0.42	0.26	−0.43	0.17	−0.07	0.16	0.18	0.08	−0.39	0.28	0.13	0.12	−0.07	0.11	−0.09	0.18	−0.41	0.08	−0.38	0.21
NGC 1978_24	−0.56	0.05	−0.56	0.23	−0.34	0.16	−0.02	0.15	0.17	0.06	−0.24	0.19	0.14	0.10	0.13	0.17	0.08	0.17	−0.19	0.05	−0.40	0.16
NGC 2108_382	−0.55	0.06	−0.52	0.24	−0.43	0.18	0.05	0.17	0.06	0.05	−0.13	0.11	0.18	0.10	0.18	0.12	0.01	0.18	−0.25	0.05	−0.37	0.19
NGC 2108_718	−0.57	0.05	−0.58	0.22	−0.38	0.15	0.08	0.13	0.27	0.05	0.08	0.13	0.20	0.09	0.08	0.09	−0.11	0.18	−0.32	0.09	−0.20	0.18
NGC 2210_1087	−0.52	0.05	−0.61	0.19	−0.26	0.14	−0.06	0.13	0.08	0.05	⋯	⋯	0.17	0.10	−0.06	0.10	−0.14	0.16	−0.25	0.06	−0.12	0.20
2MASS J06112427−6913117	−0.98	0.05	−0.99	0.18	−0.45	0.12	−0.03	0.18	0.24	0.08	0.19	0.18	0.20	0.10	0.14	0.07	−0.03	0.16	−0.10	0.08	0.15	0.18
2MASS J06120862−6911482	−0.91	0.05	−0.93	0.19	−0.56	0.10	−0.16	0.14	0.00	0.09	0.11	0.12	0.18	0.10	0.05	0.07	−0.14	0.16	−0.14	0.09	−0.13	0.17
2MASS J06113433−6904510	−0.56	0.05	−0.63	0.21	−0.35	0.12	0.00	0.11	0.22	0.05	0.05	0.16	0.24	0.11	−0.03	0.07	−0.07	0.15	−0.15	0.07	−0.21	0.16
2MASS J06100373−6902344	−0.62	0.04	−0.76	0.20	−0.48	0.12	−0.27	0.11	0.28	0.05	0.07	0.14	0.05	0.10	−0.06	0.06	−0.05	0.16	−0.13	0.07	−0.35	0.17
2MASS J06122296−6908094	−0.95	0.10	−0.94	0.12	−0.39	0.11	⋯	⋯	0.47	0.11	0.11	0.17	0.12	0.12	0.01	0.04	0.13	0.09	−0.09	0.12	0.08	0.12
2MASS J06092022−6908398	−0.45	0.05	−0.45	0.23	−0.47	0.19	−0.06	0.19	0.23	0.09	−0.20	0.35	0.18	0.11	0.11	0.10	0.06	0.16	−0.30	0.07	−0.25	0.18
2MASS J06103285−6906230	−0.33	0.08	−0.47	0.14	−0.23	0.10	−0.20	0.10	0.11	0.09	0.10	0.13	0.05	0.10	0.01	0.03	−0.08	0.10	−0.24	0.11	−0.10	0.13
2MASS J06122229−6913396	−0.69	0.05	−0.67	0.22	−0.74	0.21	0.00	0.03	0.14	0.06	⋯	⋯	0.28	0.11	−0.04	0.08	−0.22	0.17	−0.24	0.05	−0.66	0.21
2MASS J06114042−6905516	−0.75	0.04	−0.74	0.21	−0.59	0.11	−0.26	0.11	0.38	0.05	−0.03	0.13	0.13	0.10	0.08	0.10	−0.07	0.17	−0.12	0.12	0.03	0.18
2MASS J06110957−6920088	−0.63	0.04	−0.69	0.19	−0.23	0.14	0.03	0.14	0.09	0.06	⋯	⋯	0.24	0.10	0.11	0.11	−0.04	0.16	−0.08	0.07	−0.41	0.17
2MASS J05244805−6945196	−0.84	0.06	−0.81	0.26	−0.49	0.18	0.00	0.06	0.29	0.09	⋯	⋯	0.15	0.12	−0.00	0.14	0.04	0.17	−0.29	0.07	−0.48	0.19
2MASS J05235925−6945050	−0.35	0.05	−0.35	0.20	−0.36	0.21	0.10	0.21	0.11	0.10	−0.29	0.35	0.23	0.14	0.02	0.15	0.08	0.15	−0.17	0.09	−0.31	0.16
2MASS J05225563−6938342	−0.26	0.07	−0.27	0.22	−0.33	0.21	⋯	⋯	0.09	0.10	−0.03	0.25	0.32	0.14	−0.01	0.23	−0.21	0.17	−0.16	0.08	−0.71	0.18
2MASS J05242670−6946194	−0.36	0.05	−0.36	0.26	−0.36	0.18	0.01	0.18	0.13	0.07	⋯	⋯	0.18	0.12	0.01	0.10	−0.05	0.16	−0.17	0.07	−0.50	0.17
2MASS J05225436−6951262	−0.57	0.05	−0.54	0.20	−0.61	0.24	−0.19	0.23	0.26	0.10	−0.15	0.25	0.22	0.12	−0.13	0.09	−0.07	0.15	−0.07	0.09	−0.45	0.18
2MASS J05244501−6944146	−0.72	0.05	−0.82	0.22	−0.44	0.20	−0.04	0.15	0.29	0.09	⋯	⋯	0.22	0.14	−0.00	0.09	−0.04	0.16	−0.27	0.10	−0.32	0.19
2MASS J05235941−6944085	−0.43	0.07	−0.42	0.16	−0.57	0.15	−0.32	0.20	0.17	0.12	−0.02	0.35	0.05	0.12	−0.14	0.14	−0.06	0.12	−0.35	0.15	−0.35	0.18
2MASS J05224137−6937309	−0.58	0.07	−0.59	0.17	−0.51	0.21	−0.03	0.21	0.19	0.11	−0.00	0.25	0.15	0.12	0.02	0.13	−0.03	0.13	−0.05	0.10	−0.49	0.16
2MASS J06143897−6947289	−0.33	0.07	−0.36	0.19	−0.55	0.13	−0.01	0.17	0.05	0.11	⋯	⋯	0.22	0.15	−0.17	0.13	0.02	0.14	−0.20	0.08	−0.36	0.15
2MASS J05224766−6943568	−0.33	0.09	−0.33	0.13	−0.51	0.24	⋯	⋯	0.13	0.13	−0.30	0.21	0.23	0.12	0.04	0.10	−0.10	0.11	−0.39	0.12	−0.42	0.14
Sgr
2300127	−0.73	0.05	−0.77	0.21	−0.60	0.14	−0.26	0.15	0.28	0.08	0.05	0.20	0.08	0.11	0.01	0.12	0.03	0.16	−0.12	0.10	−0.19	0.19
2300196	−0.30	0.06	−0.45	0.22	−0.25	0.17	−0.07	0.16	0.07	0.08	⋯	⋯	0.15	0.10	0.09	0.15	0.03	0.17	−0.22	0.05	−0.34	0.18
2300215	−0.31	0.05	−0.23	0.24	−0.40	0.19	−0.14	0.18	−0.01	0.10	−0.14	0.25	0.08	0.11	0.03	0.16	−0.01	0.16	−0.17	0.07	−0.31	0.16
2409744	−0.20	0.06	−0.31	0.23	−0.44	0.18	−0.26	0.17	0.12	0.06	⋯	⋯	0.06	0.10	0.21	0.18	0.02	0.16	−0.46	0.04	−0.28	0.20
3600230	−0.19	0.05	−0.34	0.22	−0.67	0.16	−0.17	0.15	0.16	0.06	⋯	⋯	−0.03	0.11	−0.12	0.16	−0.18	0.16	−0.31	0.06	−0.44	0.18
3600262	−0.29	0.05	−0.44	0.22	−0.60	0.16	−0.13	0.15	0.14	0.07	−0.44	0.21	0.04	0.10	0.03	0.15	−0.08	0.16	−0.25	0.07	−0.34	0.18
3600302	−0.37	0.05	−0.48	0.21	−0.49	0.15	−0.27	0.14	0.07	0.05	−0.23	0.21	0.01	0.10	0.07	0.14	−0.04	0.16	−0.23	0.06	−0.27	0.19
3800318	−0.36	0.07	−0.41	0.24	−0.22	0.19	0.03	0.18	0.06	0.08	−0.34	0.16	0.20	0.10	0.07	0.17	0.02	0.18	−0.44	0.06	−0.40	0.17
3800558	−0.83	0.06	−0.99	0.15	−0.53	0.05	−0.25	0.07	0.35	0.07	−0.05	0.13	0.00	0.09	0.09	0.08	−0.00	0.13	−0.11	0.06	−0.17	0.10
4214652	−0.27	0.04	−0.46	0.19	−0.59	0.12	−0.26	0.11	0.16	0.07	−0.13	0.14	−0.10	0.09	0.05	0.13	−0.12	0.15	−0.27	0.06	−0.34	0.17
4303773	−0.50	0.05	−0.51	0.23	−0.75	0.14	⋯	⋯	0.10	0.07	−0.16	0.19	0.04	0.10	−0.10	0.13	−0.23	0.17	−0.20	0.06	−0.47	0.18
4304445	−0.42	0.04	−0.57	0.19	−0.51	0.13	−0.21	0.12	0.24	0.04	−0.12	0.11	0.04	0.10	−0.05	0.12	−0.11	0.15	−0.17	0.05	−0.33	0.17
4402285	−0.31	0.05	−0.46	0.20	−0.61	0.16	−0.26	0.13	0.14	0.06	0.01	0.19	0.02	0.09	−0.05	0.13	−0.10	0.15	−0.19	0.05	−0.31	0.17
4408968	−0.08	0.08	−0.15	0.24	−0.71	0.17	−0.44	0.16	−0.03	0.07	−0.30	0.21	0.13	0.09	−0.18	0.16	−0.23	0.16	−0.24	0.06	−0.66	0.17

Download table as:  ASCIITypeset images: 1 2

Table 3. LMC and Sgr Chemical Abundances

ID	$\left[\tfrac{\mathrm{Cr}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Mn}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Co}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ni}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{Zn}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{\rm{Y}}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Zr}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ba}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{La}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Nd}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Eu}}{\mathrm{Fe}}\right]$	err
LMC
NGC 1754_248	−0.16	0.14	−0.47	0.16	−0.15	0.08	−0.150	0.04	−0.58	0.25	−0.49	0.25	−0.07	0.12	0.33	0.09	−0.04	0.09	0.23	0.06	0.40	0.12
NGC 1786_2191	−0.16	0.08	−0.34	0.09	−0.19	0.06	−0.200	0.03	−0.58	0.12	−0.17	0.18	−0.12	0.11	0.48	0.05	0.35	0.05	0.41	0.06	0.49	0.09
NGC 1786_569	−0.08	0.10	−0.28	0.08	−0.04	0.07	−0.160	0.04	−0.36	0.19	−0.24	0.22	0.06	0.13	0.40	0.07	0.29	0.07	0.52	0.08	0.37	0.10
NGC 1835_1295	−0.08	0.13	−0.29	0.15	−0.27	0.19	−0.140	0.04	⋯	⋯	−0.33	0.26	−0.01	0.15	0.24	0.13	0.14	0.09	0.52	0.10	0.11	0.14
NGC 1835_1713	−0.00	0.13	−0.40	0.16	−0.15	0.11	−0.120	0.05	⋯	⋯	−0.27	0.28	0.16	0.16	0.07	0.09	−0.09	0.09	0.43	0.06	0.32	0.13
NGC 1898_2322	−0.14	0.13	−0.27	0.14	−0.18	0.10	−0.120	0.04	⋯	⋯	−0.16	0.25	−0.08	0.15	0.42	0.09	0.30	0.09	0.46	0.06	0.30	0.12
NGC 1978_24	0.08	0.13	−0.23	0.13	−0.10	0.09	−0.140	0.04	−0.32	0.25	0.01	0.25	0.02	0.13	0.22	0.09	0.27	0.07	0.37	0.07	0.48	0.09
NGC 2108_382	0.04	0.13	−0.12	0.15	−0.01	0.10	−0.100	0.04	−0.23	0.18	0.10	0.25	⋯-	⋯	0.58	0.07	0.18	0.07	0.21	0.07	0.55	0.07
NGC 2108_718	−0.11	0.13	−0.16	0.12	0.03	0.07	−0.130	0.04	−0.29	0.18	−0.21	0.23	−0.19	0.14	0.44	0.05	0.20	0.07	0.18	0.06	0.48	0.06
NGC 2210_1087	−0.25	0.12	−0.23	0.13	−0.08	0.08	−0.120	0.04	−0.44	0.18	−0.01	0.22	0.30	0.12	0.34	0.06	0.32	0.07	0.33	0.04	0.44	0.09
2MASS J06112427−6913117	−0.23	0.14	−0.13	0.14	−0.10	0.10	−0.140	0.04	−0.18	0.25	−0.13	0.25	0.14	0.15	−0.20	0.11	0.06	0.12	0.32	0.11	0.85	0.11
2MASS J06120862−6911482	−0.15	0.11	−0.24	0.11	−0.17	0.08	−0.180	0.04	−0.21	0.18	−0.43	0.23	0.06	0.13	0.13	0.07	0.21	0.07	0.35	0.07	0.60	0.14
2MASS J06113433−6904510	−0.10	0.12	−0.17	0.11	−0.15	0.08	−0.140	0.04	−0.19	0.19	−0.31	0.23	−0.15	0.13	0.34	0.05	0.23	0.06	0.24	0.05	0.31	0.08
2MASS J06100373−6902344	−0.10	0.12	−0.33	0.17	−0.15	0.07	−0.190	0.04	−0.44	0.18	−0.36	0.23	−0.02	0.11	0.35	0.07	0.30	0.07	0.31	0.04	0.40	0.10
2MASS J06122296−6908094	0.02	0.07	−0.38	0.10	−0.09	0.08	−0.120	0.04	⋯	⋯	0.28	0.11	⋯-	⋯	0.35	0.10	0.09	0.11	0.16	0.10	0.53	0.16
2MASS J06092022−6908398	0.08	0.12	−0.21	0.18	−0.10	0.17	−0.080	0.06	⋯	⋯	−0.18	0.30	0.26	0.18	0.41	0.17	0.33	0.13	0.43	0.12	0.35	0.15
2MASS J06103285−6906230	−0.11	0.07	−0.19	0.11	−0.24	0.07	−0.190	0.04	−0.49	0.20	−0.05	0.18	−0.03	0.11	0.31	0.09	0.29	0.09	0.36	0.08	0.43	0.13
2MASS J06122229−6913396	−0.10	0.14	−0.43	0.14	−0.12	0.11	−0.120	0.05	−0.05	0.26	−0.34	0.28	−0.21	0.16	−0.45	0.14	0.14	0.08	0.29	0.07	0.71	0.12
2MASS J06114042−6905516	−0.17	0.14	−0.29	0.09	−0.05	0.07	−0.110	0.04	−0.10	0.26	−0.47	0.23	−0.02	0.11	0.35	0.06	0.16	0.07	0.40	0.06	0.49	0.09
2MASS J06110957−6920088	−0.08	0.11	−0.20	0.11	0.02	0.08	−0.070	0.05	−0.28	0.19	0.11	0.25	0.38	0.14	0.65	0.10	0.34	0.09	0.46	0.05	⋯-	⋯
2MASS J05244805−6945196	0.12	0.15	−0.45	0.16	−0.11	0.14	−0.250	0.05	⋯	⋯	−0.05	0.33	0.23	0.17	0.01	0.09	0.26	0.12	0.48	0.08	0.33	0.12
2MASS J05235925−6945050	0.13	0.12	−0.05	0.16	−0.21	0.16	−0.180	0.08	⋯	⋯	−0.09	0.33	⋯-	⋯	0.43	0.17	−0.00	0.13	0.15	0.12	0.05	0.16
2MASS J05225563−6938342	−0.01	0.23	−0.28	0.16	−0.05	0.16	−0.110	0.07	−0.71	0.40	−0.34	0.33	0.03	0.23	0.22	0.17	0.30	0.13	0.57	0.08	⋯-	⋯
2MASS J05242670−6946194	−0.10	0.13	0.19	0.17	−0.18	0.13	−0.160	0.06	⋯-	⋯	−0.22	0.25	0.25	0.29	0.50	0.09	0.31	0.08	0.30	0.08	0.28	0.12
2MASS J05225436−6951262	−0.05	0.13	−0.39	0.24	−0.16	0.14	−0.210	0.06	⋯-	⋯	−0.28	0.29	0.25	0.14	0.03	0.24	−0.15	0.13	0.38	0.09	0.32	0.16
2MASS J05244501−6944146	−0.12	0.14	−0.20	0.13	−0.13	0.10	−0.120	0.05	⋯-	⋯	−0.19	0.27	0.11	0.16	0.32	0.17	0.07	0.12	0.46	0.16	0.57	0.16
2MASS J05235941−6944085	0.21	0.17	−0.33	0.13	−0.21	0.20	−0.180	0.07	⋯-	⋯	⋯-	⋯	0.26	0.26	0.23	0.18	0.20	0.13	0.45	0.08	0.32	0.17
2MASS J05224137−6937309	−0.14	0.17	−0.25	0.17	−0.15	0.11	−0.170	0.06	⋯-	⋯	⋯-	⋯	0.10	0.19	0.28	0.18	0.19	0.13	0.53	0.07	0.23	0.17
2MASS J06143897−6947289	−0.26	0.14	⋯	⋯	−0.09	0.12	−0.140	0.06	⋯-	⋯	−0.45	0.22	−0.07	0.13	0.01	0.18	0.24	0.13	⋯	⋯	0.44	0.16
2MASS J05224766−6943568	0.07	0.12	−0.43	0.18	−0.22	0.15	−0.180	0.06	⋯-	⋯	⋯-	⋯	⋯-	⋯	0.49	0.18	0.15	0.14	0.46	0.11	⋯-	⋯
Sgr
2300127	−0.04	0.14	−0.41	0.10	−0.16	0.07	−0.10	0.04	⋯	⋯	−0.14	0.27	0.16	0.21	0.07	0.08	0.06	0.12	0.16	0.04	0.54	0.11
2300196	0.05	0.11	−0.15	0.11	−0.11	0.11	−0.20	0.05	−0.64	0.24	0.52	0.27	0.42	0.26	0.97	0.10	1.00	0.09	0.68	0.06	0.62	0.12
2300215	0.07	0.13	−0.13	0.12	−0.06	0.11	−0.21	0.06	⋯	⋯	0.09	0.25	0.43	0.28	0.39	0.17	0.62	0.13	0.63	0.06	0.61	0.15
2409744	0.07	0.12	−0.08	0.12	−0.22	0.10	−0.20	0.04	⋯	⋯	0.35	0.24	0.14	0.28	0.69	0.08	0.50	0.08	0.73	0.08	0.56	0.09
3600230	−0.17	0.11	−0.35	0.11	−0.20	0.09	−0.28	0.04	⋯	⋯	−0.04	0.23	0.06	0.22	0.61	0.08	0.41	0.07	0.32	0.05	0.44	0.09
3600262	−0.08	0.11	−0.22	0.12	−0.03	0.10	−0.24	0.04	−0.66	0.25	−0.03	0.24	0.07	0.21	0.50	0.06	0.26	0.07	0.51	0.05	0.39	0.07
3600302	0.00	0.12	−0.11	0.09	−0.04	0.08	−0.18	0.04	−0.29	0.25	0.17	0.22	0.36	0.22	0.68	0.07	0.61	0.07	0.51	0.05	0.48	0.09
3800318	0.07	0.13	0.01	0.20	−0.14	0.14	−0.22	0.04	⋯	⋯	0.34	0.29	0.55	0.28	1.10	0.10	0.90	0.09	0.75	0.06	0.61	0.12
3800558	−0.10	0.10	−0.40	0.11	−0.18	0.09	−0.22	0.03	−0.33	0.19	−0.34	0.19	−0.04	0.19	0.12	0.08	0.14	0.08	0.14	0.07	0.55	0.11
4214652	−0.10	0.09	−0.34	0.12	−0.19	0.10	−0.25	0.04	−0.48	0.19	−0.15	0.21	0.03	0.20	0.48	0.09	0.38	0.08	0.32	0.05	0.47	0.11
4303773	−0.26	0.13	−0.51	0.12	−0.21	0.11	−0.23	0.04	−0.45	0.25	−0.59	0.26	−0.21	0.22	0.03	0.10	−0.07	0.09	0.20	0.08	0.42	0.12
4304445	−0.07	0.10	−0.22	0.08	−0.10	0.07	−0.19	0.04	−0.50	0.18	−0.20	0.22	0.04	0.20	0.43	0.06	0.48	0.06	0.33	0.05	0.52	0.07
4402285	−0.09	0.12	−0.26	0.10	−0.16	0.07	−0.20	0.03	−0.28	0.25	−0.10	0.22	0.08	0.20	0.49	0.07	0.48	0.07	0.58	0.06	0.66	0.08
4408968	−0.13	0.12	−0.15	0.12	−0.28	0.09	−0.27	0.04	−0.48	0.25	0.10	0.23	−0.05	0.26	0.81	0.08	0.79	0.07	0.59	0.07	0.36	0.08

Download table as:  ASCIITypeset images: 1 2

Table 4. MW Chemical Abundances

ID	$\left[\tfrac{\mathrm{Fe}}{{\rm{H}}}\right]$	err	$\left[\tfrac{\mathrm{Fe}\,{\rm\small{II}}}{{\rm{H}}}\right]$	err	$\left[\tfrac{\mathrm{Na}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Al}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{\rm{O}}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Mg}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Si}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ca}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ti}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Sc}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{\rm{V}}}{\mathrm{Fe}}\right]$	err
HD 749	−0.40	0.07	−0.55	0.12	−0.09	0.12	0.23	0.09	0.250	0.08	0.20	0.08	0.08	0.09	0.06	0.06	0.07	0.09	0.11	0.09	0.10	0.13
HD 18293 (nuHyi)	0.18	0.06	0.12	0.25	−0.14	0.16	0.17	0.12	0.230	0.10	⋯	⋯	0.04	0.07	−0.14	0.14	−0.20	0.14	0.10	0.04	−0.19	0.24
HD 107328	−0.34	0.04	−0.46	0.13	−0.07	0.12	0.17	0.09	0.570	0.08	⋯	⋯	0.23	0.08	0.09	0.09	0.20	0.12	0.03	0.07	0.15	0.16
HD 148897 (* s Her)	−1.08	0.08	−1.23	0.13	−0.09	0.03	0.06	0.07	0.580	0.07	0.32	0.05	0.23	0.11	0.28	0.06	0.19	0.11	0.04	0.11	0.00	0.10
HD 190056	−0.51	0.04	−0.65	0.16	−0.10	0.11	0.38	0.10	0.660	0.08	⋯	⋯	0.22	0.08	0.18	0.10	0.24	0.14	0.24	0.05	0.17	0.17
HD 220009	−0.55	0.04	−0.68	0.15	−0.11	0.10	0.34	0.09	0.590	0.07	⋯	⋯	0.18	0.08	0.10	0.10	0.22	0.13	0.25	0.06	0.11	0.17
GES J18242374−3302060	−0.02	0.06	−0.15	0.10	−0.17	0.09	0.03	0.07	0.230	0.06	−0.00	0.03	−0.00	0.08	0.06	0.06	−0.05	0.07	0.03	0.09	0.04	0.10
GES J18225376−3406369	−0.12	0.06	−0.27	0.11	−0.08	0.07	0.20	0.07	0.370	0.07	0.22	0.05	0.04	0.08	0.08	0.08	0.13	0.08	0.03	0.08	0.14	0.12
GES J17560070−4139098	−0.27	0.08	−0.39	0.09	−0.07	0.07	0.14	0.08	0.410	0.07	0.15	0.03	0.19	0.08	0.04	0.04	0.12	0.05	0.18	0.10	0.10	0.08
GES J18222552−3413578	−0.03	0.05	−0.12	0.16	−0.19	0.12	0.12	0.09	0.140	0.08	0.16	0.07	0.02	0.08	0.08	0.08	−0.05	0.11	0.11	0.07	0.05	0.14
GES J02561410−0029286	−0.71	0.07	−0.84	0.10	−0.15	0.07	0.41	0.07	0.410	0.07	0.29	0.04	0.26	0.08	0.04	0.04	0.24	0.06	0.15	0.09	0.06	0.09
GES J13201402−0457203	−0.49	0.06	−0.64	0.11	−0.07	0.06	0.35	0.06	0.560	0.06	0.44	0.25	0.15	0.08	0.05	0.05	0.30	0.08	0.24	0.08	0.26	0.12
GES J01203074−0056038	−0.25	0.04	−0.38	0.16	−0.09	0.15	0.32	0.11	0.520	0.10	⋯	⋯	0.25	0.08	0.12	0.12	0.19	0.13	0.38	0.05	0.09	0.16
GES J14194521−0506063	−0.33	0.05	−0.46	0.13	0.10	0.14	0.38	0.10	⋯	⋯	0.35	0.04	0.25	0.09	0.09	0.09	0.20	0.10	0.21	0.07	0.16	0.14
ID	$\left[\tfrac{\mathrm{Cr}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Mn}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Co}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ni}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{Zn}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{{\rm{Y}}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Zr}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Ba}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{La}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Nd}}{\mathrm{Fe}}\right]$	err	$\left[\tfrac{\mathrm{Eu}}{\mathrm{Fe}}\right]$	err
HD 749	0.02	0.04	−0.04	0.08	0.16	0.06	0.01	0.03	0.09	0.13	0.99	0.16	0.98	0.16	1.12	0.08	1.18	0.07	0.74	0.07	0.55	0.10
HD 18293 (nuHyi)	−0.18	0.08	0.09	0.07	0.19	0.09	0.02	0.03	−0.21	0.11	0.03	0.20	−0.14	0.19	0.27	0.07	0.33	0.07	0.20	0.06	0.30	0.09
HD 107328	−0.14	0.05	−0.20	0.09	0.30	0.07	−0.01	0.04	−0.11	0.10	−0.23	0.19	−0.00	0.18	−0.33	0.08	−0.15	0.05	−0.05	0.05	0.44	0.08
HD 148897 (* s Her)	−0.12	0.10	−0.39	0.06	0.05	0.06	−0.09	0.04	−0.04	0.15	−0.10	0.18	0.26	0.17	0.24	0.10	0.16	0.11	0.08	0.07	0.42	0.16
HD 190056	−0.03	0.09	−0.16	0.08	0.25	0.06	0.00	0.04	0.17	0.13	−0.09	0.21	0.17	0.20	0.16	0.08	0.14	0.07	0.09	0.04	0.46	0.10
HD 220009	−0.11	0.09	−0.26	0.08	0.19	0.07	−0.02	0.03	0.15	0.10	−0.06	0.20	0.22	0.20	0.28	0.05	0.11	0.05	0.12	0.05	0.48	0.07
GES J18242374−3302060	−0.08	0.03	−0.09	0.07	0.07	0.08	−0.06	0.03	−0.20	0.11	0.05	0.14	0.09	0.13	0.15	0.07	0.27	0.06	0.17	0.07	0.26	0.08
GES J18225376−3406369	−0.10	0.05	−0.11	0.07	0.16	0.09	−0.01	0.03	0.05	0.11	−0.12	0.15	0.03	0.14	0.20	0.07	0.08	0.07	−0.11	0.07	0.38	0.09
GES J17560070−4139098	−0.19	0.04	−0.28	0.06	0.18	0.08	−0.00	0.03	0.04	0.12	⋯	⋯	0.03	0.11	−0.03	0.09	−0.10	0.07	−0.05	0.09	0.31	0.10
GES J18222552−3413578	−0.09	0.06	−0.02	0.08	0.11	0.09	−0.01	0.04	−0.10	0.08	−0.12	0.18	−0.03	0.16	0.09	0.04	0.09	0.05	0.08	0.06	0.26	0.08
GES J02561410−0029286	−0.11	0.04	−0.41	0.07	0.06	0.07	−0.05	0.03	0.02	0.11	0.25	0.14	0.31	0.12	0.18	0.08	0.24	0.07	0.01	0.08	0.44	0.10
GES J13201402−0457203	0.00	0.06	−0.28	0.06	0.09	0.07	0.01	0.03	0.19	0.11	−0.06	0.13	0.30	0.12	0.16	0.06	0.06	0.06	0.06	0.08	0.36	0.09
GES J01203074−0056038	−0.14	0.08	−0.11	0.11	0.29	0.07	0.06	0.04	0.20	0.11	0.02	0.22	0.19	0.20	0.09	0.07	0.26	0.06	0.27	0.06	0.68	0.08
GES J14194521−0506063	−0.04	0.07	−0.08	0.09	0.24	0.10	0.04	0.04	0.18	0.10	1.00	0.18	1.12	0.17	1.11	0.03	1.12	0.05	0.74	0.06	0.49	0.09

Download table as:  ASCIITypeset image

In this section we also compare our results with the abundances available in literature, i.e., Pompéia et al. (2008), Lapenna et al. (2012), Van der Swaelmen et al. (2013), and Nidever et al. (2020) for the LMC and Monaco et al. (2005), Sbordone et al. (2007), Carretta et al. (2010), and Mucciarelli et al. (2017a) for Sgr.

5.1. Light Elements: Na and Al

5.2.  α-Elements

5.3. Iron-peak Elements

5.4. Slow Neutron-capture Elements

5.5. Rapid Neutron-capture Elements

High-resolution UVES-FLAMES spectra of 30 LMC and 14 Sgr giant stars have been analyzed, together with a reference sample of 14 MW giant stars selected in the same metallicity range of the LMC/Sgr stars. The three samples have been analyzed with the same procedure in order to erase the main systematics of the analysis (such as solar reference abundances, atomic data, and temperature scales, among others). The homogeneous analysis of different samples of stars is a necessary step to highlight differences and similarities in the chemical compositions of these three galaxies.

The metal-rich populations in the LMC and Sgr show strong similarities in almost all the measured species, pointing out a similar chemical evolution. The main differences are related to the heavy s-process elements Ba and La, with the stars of Sgr more enriched in both the abundance ratios with respect to LMC, suggesting a different contribution by AGB stars. Overall, their similar chemical compositions suggest similar chemical enrichment histories, coherently with a scenario where the progenitor of Sgr was a galaxy with a mass and a star formation rate similar to those of the LMC, as already suggested by different authors (see, e.g., de Boer et al. 2014; Gibbons et al. 2017; Mucciarelli et al. 2017a).

The comparison between LMC/Sgr and MW samples reveals that the former galaxies have different chemical abundances with respect to the MW stars for almost all the species. This finding agrees with previous works about metal-rich stars in the LMC (Pompéia et al. 2008; Lapenna et al. 2012; Van der Swaelmen et al. 2013) and Sgr (Monaco et al. 2005; Sbordone et al. 2007; Mucciarelli et al. 2017a), but we stress that the present work is the first that allows us to directly compare the abundances of all the main groups of elements in these galaxies. The abundance ratios for elements produced by massive stars exploding as either core-collapse SNe or HNe are systematically lower in the LMC/Sgr with respect to the MW, pointing out that in these galaxies the contribution by massive stars to the chemical enrichment is less important. This can be explained in light of their low star formation rates, leading to a lower number of massive stars (poorly populating the IMF at the highest masses; see, e.g., Yan et al. 2017; Jeřábková et al. 2018) and penalizing the elements produced by very massive stars.

Finally, we recall that, among the measured elements, the most evident differences between LMC/Sgr and MW stars are measured for [V/Fe] and [Zn/Fe], where LMC/Sgr stars have abundance ratios lower than the MW stars of similar metallicity by as much as 0.5–0.7 dex. We suggest that these abundance ratios can be used to identify possible extragalactic interlopers among the Galactic disk stars with [Fe/H] > −1.0 dex, i.e., stars accreted from LMC and Sgr or from galaxies that have experienced similar chemical enrichment histories. In other words, we suggest that [V/Fe] and [Zn/Fe] can be tools for a robust chemical tagging as powerful as the classical hydrostatic [α/Fe] ratios.

We are grateful to the anonymous referee for his/her useful suggestions in improving the paper. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement.

This research is funded by the project "Light-on-Dark," granted by the Italian MIUR through contract PRIN-2017K7REXT.

A. Minelli would like to thank C. Fanelli for the useful discussions and support.

D.R. benefited from discussions held at the International Space Science Institute (ISSI, Bern, CH) and the International Space Science Institute Beijing (ISSI-BJ, Beijing, CN) thanks to the funding of the team "Chemical abundances in the ISM: the litmus test of stellar IMF variations in galaxies across cosmic time."