11institutetext:  Dipartimento di Fisica e Astronomia, Universitá degli Studi
di Firenze, Via G. Sansone 1, I-50019 Sesto Fiorentino, Italy.
22institutetext: Physics Institute, Laboratoire d’astrophysique, École
Polytechnique Fédérale de Lausanne (EPFL), Observatoire, 1290 Versoix,
Switzerland. 33institutetext: European Southern Observatory, Karl-
Schwarzschild-str. 2, 85748 Garching bei München, Germany. 44institutetext:
GEPI, Observatoire de Paris, Université PSL, CNRS, 5 Place Jules Janssen,
92190 Meudon, France. 55institutetext: INAF/Osservatorio Astrofisico di
Arcetri, Largo E. Fermi 5, I-50125 Firenze, Italy. 66institutetext:
Dipartimento di Fisica e Astronomia, Università degli Studi di Bologna, Via
Gobetti 93/2, I-40129 Bologna, Italy. 77institutetext: Institute of Astronomy
of the Russian Academy of Sciences, Pyatnitskaya st. 48, 119017, Moscow,
Russia. 88institutetext: Department of Physics and Astronomy, University of
Victoria, PO Box 3055, STN CSC, Victoria, BC V8W 3P6, Canada. 99institutetext:
Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire
Lagrange, Nice, France. 1010institutetext: Departamento de Ciencias Físicas,
Facultad de Ciencias Exactas, Universidad Andrés Bello, Fernández Concha 700,
Las Condes, Santiago, Chile. 1111institutetext: Vatican Observatory, V00120
Vatican City State, Italy. 1212institutetext: Departamento de Fisica,
Universidade Federal de Santa Catarina, Trinidade 88040-900, Florianopolis,
Brazil.

# Extremely metal-poor stars in the Fornax and Carina dwarf spheroidal
galaxies††thanks: Based on UVES and X–Shooter observations collected at the
ESO, programme ID 0100.D–0820 and 094.D–0853.

R. Lucchesi, 1122 P. Jablonka 2244 Á. Skúladóttir 1155 C. Lardo 66 L.
Mashonkina 77 F. Primas 33 K. Venn 88 V. Hill 99 D. Minniti 101011111212

(Received xx xxxx 2023; accepted xx xxxx 2023)

We present our analysis of VLT/UVES and X-shooter observations of six very
metal-poor stars, including four stars at $\rm[Fe/H]\approx-3$ in the Fornax
and Carina dwarf spheroidal galaxies (dSph). Until now, this metallicity range
in these two galaxies was either hardly or not yet investigated. The chemical
abundances of 25 elements are presented, based on 1D/LTE model atmospheres. We
discuss the different elemental groups, and find that $\alpha$\- and iron-peak
elements in these two systems are generally in good agreement with the Milky
Way halo at the same metallicity. Our analysis reveals that none of the six
stars we studied exhibit carbon enhancement, which is noteworthy given the
prevalence of carbon-enhanced metal-poor (CEMP-no; no Ba enhancement) stars in
the Galaxy at similarly low metallicities. Our compilation of literature data
shows that the fraction of CEMP-no stars in dSphs is significantly lower than
in the Milky Way, and than in ultra faint dwarf galaxies. Furthermore, we
report the discovery of the lowest metallicity, [Fe/H] = $-2.92$, r-process
rich (r-I) star in a dSph galaxy. This star, fnx_06_019, has
$\rm[Eu/Fe]=+0.8$, and also shows enhancement of La, Nd, and Dy,
$\rm[X/Fe]>+0.5$. Our new data in Carina and Fornax help to populate the
extremely low metallicity range in dSph galaxies, and add onto the evidence of
a low fraction of CEMP-no stars in these systems.

###### Key Words.:

stars: abundances – Local Group – galaxies: dwarf – galaxies: formation

##  1 Introduction

We aim at understanding the characteristics of the first stars formed in the
universe, from their imprints on low-mass stars in dwarf spheroidal galaxies
(dSphs). The stellar abundance trends and dispersion of the most metal-poor
stars reveal the nature of the now disappeared first stellar generation (e.g.,
mass, numbers), and the level of homogeneity of the primitive interstellar
medium (ISM), e.g., size/mass of star-forming regions, as well as the nature
and energy of the first supernovae (e.g. Koutsouridou et al., 2023). The
proximity of the Local Group dSphs allows to derive chemical abundances in
individual stars at comparable quality as in the Milky Way (MW). The
confrontation of galaxies with very different evolutionary paths brings
crucial information on the universality of the star-formation processes and
chemical enrichment.

Carina, Sextans, Sculptor, and Fornax are four Local Group dSphs which have so
far triggered strong observational efforts from the galactic archaeology
community. They provided the first evidence for distinct star formation
histories and chemical evolution from those of the Milky Way at $\rm[Fe/H]>-2$
(e.g. Tolstoy et al., 2009). These four dwarf galaxies form a sequence of mass
from the lowest to the highest mass limits of the classical dSphs. They
followed very different evolution: while the majority of stars in Sextans and
Sculptor formed during the first 4 Gyr (de Boer et al., 2012, 2014; Bettinelli
et al., 2018, 2019), Carina is famous for its distinct star-forming episodes,
which are separated by long periods of quiescence (de Boer et al., 2014). With
a significantly larger stellar mass, Fornax has an extended star formation
history, and a population dominated by intermediate age stars (de Boer et al.,
2012). Furthermore, in Fornax there are also six known globular clusters (GCs;
Hodge, 1961; Pace et al., 2021). The diversity of these four dSphs allows us
to probe the relation between the very early stages of star formation and the
subsequent evolutionary paths.

While we now broadly understand their later stages of evolution, their
earliest times are still poorly understood. So far, Sculptor and Sextans are
the classical dSphs with the largest number of metal-poor stars observed at
sufficient spectral quality to derive accurate chemical abundances. To date
the most studied dwarf galaxy at low [Fe/H] is Sculptor, with 13 chemically
analyzed metal-poor stars at [Fe/H] $\leq$ $-2.5$. (Tafelmeyer et al., 2010;
Frebel et al., 2010; Starkenburg et al., 2013; Jablonka et al., 2015; Simon et
al., 2015; Skúladóttir et al., 2021; Skúladóttir et al., 2023b). Only four EMP
stars out of 14 known with $\rm[Fe/H]<-2.5$ have been studied in Sextans
(Shetrone et al., 2001; Aoki et al., 2009; Starkenburg et al., 2013; Lucchesi
et al., 2020; Theler et al., 2020). Fornax has only one known EMP star that
has been chemically characterized, with total of 2 stars at [Fe/H] $<-2.5$
(Tafelmeyer et al., 2010; Lemasle et al., 2014), and Carina has 9 stars with
[Fe/H] $<-2.5$ have which been chemically analysed (Koch et al., 2008; Venn et
al., 2012; Susmitha et al., 2017; Norris et al., 2017; Hansen et al., 2023).

Figure 1: CMD ($I$, $V-I$) of the RGB of Fornax (top) and Carina (bottom). The
$V,I$ magnitudes are from ESO 2.2m WFI (Battaglia et al., 2006; Starkenburg et
al., 2010). Gray dots are probable Fornax and Carina members based on their
radial velocities (Starkenburg et al., 2010). Colored points are stars with
$\rm[Fe/H]\leq-2.5$ and more than five chemical abundances measured. Blue and
green large circles show respectively the Fornax and Carina stars analyzed
here. Other works: small blue square from Tafelmeyer et al. (2010); small
green squares from Venn et al. (2012); and small green star symbol from
Susmitha et al. (2017). Figure 2: Symbols are same as in Fig 1; and green
triangles are from Koch et al. (2008). Top panel: Spatial distribution of
Fornax stars, the large shaded blue circles correspond to the VLT/FLAMES
observations of Letarte et al. (2010) in the centre, and off-center from
Lemasle et al. (2014). Bottom panel: Spatial distribution of Carina stars. The
large shaded green circle corresponds to the VLT/FLAMES observations of
Lemasle et al. (2012). The ellipses indicates the tidal radius of Fornax and
Carina respectively. Table 1: Observation journal. The $\lambda$ range refers
to the spectral ranges used in the analysis. The SNRs are measured around the
centre of each wavelength range.

ID | $\alpha(J2000)$ | $\delta(J2000)$ | Setting |  $\lambda$ range |  $<$S/N$>$ | Vrad,helio $\pm\leavevmode\nobreak\ \sigma$
---|---|---|---|---|---|---
|  $[$h:mn:s$]$ |  $[^{\circ}$ :’:”$]$ |  | Å | [/pix] | [km s-1]
|  |  | UVES |  |  |
fnx_06_019 | 02:37:00.91 |  $-$34:10:43.10 | Dic1-CCD#2 | 3800$-$4515 | 12 | 53.78 $\pm$ 0.16
|  |  | Dic1-CCD#3(Blue) | 4790$-$5760 | 30 | 54.43 $\pm$ 0.12
|  |  | Dic1-CCD#3(Red) | 5840$-$6805 | 45 | 53.98 $\pm$ 0.16
fnx0579x$-$1 | 02:40:47.79 |  $-$34:26:46.50 | Dic1-CCD#2 | 3800$-$4520 | 12 | 49.43 $\pm$ 0.19
|  |  | Dic1-CCD#3(Blue) | 4790$-$5760 | 30 | 49.62 $\pm$ 0.15
|  |  | Dic1-CCD#3(Red) | 5840$-$6805 | 43 | 49.17 $\pm$ 0.18
|  |  | X-Shooter |  |  |
car1_t174 | 06:41:58.72 |  $-$51:06:40.30 | UBV | 3040$-$5550 | 38 | 205.37 $\pm$ 1.40
|  |  | VIS | 5550$-$6800 | 24 | 209.26 $\pm$ 0.78
car1_t194 | 06:41:42.87 |  $-$51:05:30.10 | UBV | 3040$-$5550 | 33 | 202.50 $\pm$ 1.06
|  |  | VIS | 5550$-$6800 | 30 | 207.11 $\pm$ 1.24
car1_t200 | 06:41:49.67 |  $-$51:01:31.30 | UBV | 3040$-$5550 | 34 | 214.69 $\pm$ 1.46
|  |  | VIS | 5550$-$6800 | 25 | 208.40 $\pm$ 1.72
LG04c_0008 | 06:40:49.14 |  $-$51:00:33.00 | UBV | 3040$-$5550 | 37 | 219.13 $\pm$ 1.30
|  |  | VIS | 5550$-$6800 | 40 | 221.05 $\pm$ 1.36

Table 2: Optical and near-IR photometry. $V$, $I$ from ESO 2.2m WFI. $J$, $H$,
$K_{s}$ from ESO VISTA (Battaglia et al., 2006; Starkenburg et al., 2010).

ID | $V$ | $I$ | $J$ | $H$ | $K_{s}$
---|---|---|---|---|---
fnx_06_019 | 18.336 | 17.062 | 16.005 | 15.455 | 15.310
fnx0579x-1 | 18.220 | 16.910 | 16.090 | 15.532 | 15.393
car1_t174 | 19.170 | 18.030 | 17.112 | 16.612 | 16.531
car1_t194 | 19.300 | 18.150 | 17.203 | 16.689 | 16.584
car1_t200 | 19.380 | 18.340 | 17.463 | 16.938 | 16.780
LG04c_0008 | 18.500 | 17.230 | 16.282 | 15.798 | 15.666

In the recent years it has become apparent that different dwarf galaxies show
different abundance trends at low $\rm[Fe/H]<-2.5$. Around
$\rm[Fe/H]\approx-3$, most dSph galaxies, e.g. Fornax, Sextans, and Sculptor
(Tafelmeyer et al., 2010; Theler et al., 2020; Lucchesi et al., 2020;
Skúladóttir et al., 2023b), present a plateau of enhanced
[$\alpha$/Fe]$\sim$+0.4 with a low scatter, similar to the Milky Way and the
small ultra-faint dwarf galaxies (UFDs). However, there are some deviations
from this, e.g. in Sculptor, where individual unusual low-$\alpha$ stars have
been detected at $\rm[Fe/H]\approx-2.4$ (e.g. Jablonka et al., 2015), and the
[$\alpha$/Fe] plateau seems to break down towards the lowest
$\rm[Fe/H]\approx-4$ (e.g. Skúladóttir et al., 2023b). In addition, dSphs and
UFDs show significant differences in their Sr and Ba abundances. Typically the
[Sr/Fe] and [Ba/Fe] in dSphs increase towards higher [Fe/H], e.g. in Sextans
where $\rm[Sr/Fe]\approx 0$ at $\rm[Fe/H]\gtrsim-3$, and $\rm[Ba/Fe]\approx 0$
at $\rm[Fe/H]\gtrsim-2.6$ (Lucchesi et al., 2020). On the contrary, [Sr/Fe]
and [Ba/Fe] typically stay sub-solar at all [Fe/H] in UFDs (Ji et al., 2019).
The dSph galaxies show an increasing trend in [Sr/Ba] towards the lowest
$\rm[Fe/H]\approx-4$. This is not seen in UFDs, and the Sextans and Ursa Minor
dSphs seem to be at the lower mass limit of where this trend is visible
(Mashonkina et al., 2017b; Reichert et al., 2020; Lucchesi et al., 2020). It
is likely that this relates to the earliest production sites of Sr and Ba,
however, these are still being debated.

The nucleosynthetic sites of the neutron-capture elements are still largely
debated in the literature, in particular in regards to the rapid $r$-process
which occurs under high neutron flux (e.g. Schatz et al., 2022). Investigating
stars in galaxies covering a wide mass range, provides very crucial
constraints, and supports a double origin of $r$-process elements (Skúladóttir
& Salvadori, 2020), by a rare type of massive stars (e.g., Winteler et al.,
2012), as well as neutron star mergers (e.g., Wanajo et al., 2014). Both in
the Milky Way and dwarf galaxies, individual stars have been found to exhibit
enhancement of r-process products. These stars are defined as (Beers &
Christlieb, 2005): i) r-I stars when $\rm+0.3\leq[Eu/Fe]<+1.0$,
$\rm[Ba/Eu]<0$; ii) r-II stars when [Eu/Fe]$>$+1; [Ba/Eu]$<$0\. From the
survey carried out by Barklem et al. (2005), the expected frequencies of r-II
and r-I stars in the Milky Way halo are $\sim$3% and $\sim$15%, respectively.
In Fornax, 3 r-II stars have been identified at high $\rm[Fe/H]>-1.3$
(Reichert et al., 2021), and several r-I stars have been reported at
$\rm[Fe/H]>-1.5$ in Letarte et al. (2010). In the Ursa Minor dSph, r-II stars
have also been identified at $\rm[Fe/H]>-2.5$ (Shetrone et al., 2001; Aoki et
al., 2007b). In addition, some UFDs have been found to host very r-rich stars
(Ji et al., 2016; Hansen et al., 2017). These metal-poor r-rich stars are
extremely important, since they likely show the imprints of a singular
r-event. Understanding the distribution of such stars in different systems,
therefore allows us to trace back the origin of the r-process enrichment.

This work contributes to the study of the chemical patterns of the most metal-
deficient stars in dwarf galaxies, this time focusing on Fornax and Carina.

##  2 Observations and data reduction

###  2.1 Target selection, observations, and data reduction

The EMP candidates of this work are red giant branch (RGB) stars in the Fornax
and Carina dSph galaxies (Fig. 1 and 2). Their selection was based on an
estimation of their metallicity via the Calcium II triplet (CaT),
[Fe/H]${}_{{\rm CaT}}<$ –2.5. Starkenburg et al. (2010) delivered a CaT
calibration down to $\rm[Fe/H]=-4$, which was applied to the samples of
Battaglia et al. (2006) for Fornax and Koch et al. (2006) for Carina. The
observational journal of the programme stars is in Table 1.

The two EMP candidates in Fornax, fnx_06_019 and fnx0579x$-$1, were
sufficiently bright to enable follow-up at high resolution with the UVES
spectrograph (Dekker et al., 2000) mounted at the ESO VLT (programme ID
0100.D-0820(A)). We used dichroic 1 with the CCD#2 centered at 3900 Å and the
CCD#3 centered at 5800 Å. Setting the slit width at 1.2″ led to a nominal
resolution of R$\sim$34,000. The full wavelength coverage is $\sim$3200–6800 Å
(see Table 1 for details), and the effective usable spectral information
starts from $\sim$3800 Å due to the lower SNR toward the blue part of the
spectrum. Each star has been observed for a total of five hours, split into
six individual sub-exposures.

The four EMP candidates in Carina, LG04c_0008, Car1_t200, Car1_t174, and
Car1_t194 were observed (programme ID 094.D–0853(B)) with X-Shooter (Vernet et
al., 2011). The UVB slit was open to 0.8$\times$11 arcsec2 while the VIS slit
was open to 0.9$\times$11 arcsec2, which led to a nominal resolution of
R$\sim$6,200 and R$\sim$7,400 respectively. The total exposure time, in STARE
mode, was 2.5 hours for LG04c_0008 and 3 hours for the other stars divided in
3 and 4 OBs of $\sim$3000 s, respectively. The usable wavelength range spans
3040–6800 Å.

In all cases, the reduced data, including bias subtraction, flat fielding,
wavelength calibration, spectral extraction, and order merging, were taken
from the ESO Science Archive Facility.

Table 1 provides the coordinates of our targets, the signal-to-noise ratios
(SN), and the radial velocities as measured in each wavelength interval. Table
2 lists the optical and near-infrared magnitudes of our sample. Fig. 1 shows
the Colour Magnitude Diagram (CMD) of the targets, and Fig. 2 indicates the
spatial location of our targets relative to the position of other
spectroscopic studies in Carina and Fornax.

###  2.2 Radial velocity measurements and normalization

The stellar heliocentric radial velocities (RVs) were measured with the
IRAF111Image Reduction and Analysis Facility; Astronomical Source Code Library
ascl:9911.002 task rvidlines on each individual exposure. The final RV is the
average of these individual values weighted by their uncertainties. This
approach allows us to detect possible binary stars, at least those whose RV
variations can be detected within about one year. We did not find any evidence
for binarity. After they were corrected for RV shifts, the individual
exposures were combined into a single spectrum using the IRAF task scombine
with a 2 to 3 sigma clipping. As a final step, each spectrum was visually
examined, and the few remaining cosmic rays were removed with the splot
routine.

The mean RV of each Fornax star (Table 1) coincides with the RV of Fornax,
54.1 $\pm$ 0.5 $kms^{-1}$, within the velocity dispersion
$\sigma=13.7\leavevmode\nobreak\ \pm\leavevmode\nobreak\
0.4\leavevmode\nobreak\ kms^{-1}$, measured by Battaglia et al. (2006), and
55.46 $\pm$ 0.63 $kms^{-1}$, within the velocity dispersion
$\sigma=11.62\leavevmode\nobreak\ \pm\leavevmode\nobreak\
0.45\leavevmode\nobreak\ kms^{-1}$, measured by Hendricks et al. (2014b).
Similarly, the RVs of the Carina stars fall within the mean of the galaxy,
224.4 $\pm$ 5.95 $kms^{-1}$, measured by Lemasle et al. (2012); and 223.9
$kms^{-1}$ with $\sigma$=7.5 $kms^{-1}$ measured by Koch et al. (2006). This
confirms that our stars are galaxy members. Spectra were normalized using
DAOSPEC (Stetson & Pancino, 2008) for each of the wavelength ranges presented
in Table 1. We used a 20 to 40 degree polynomial fit.

##  3 Stellar model determination and chemical analysis

###  3.1 Line list and model atmospheres

Our line list combines those of Jablonka et al. (2015), Tafelmeyer et al.
(2010), and Van der Swaelmen et al. (2013). Information on the spectral lines
was taken from the VALD database (Piskunov et al., 1995; Ryabchikova et al.,
1997; Kupka et al., 1999, 2000). The corresponding central wavelengths and
oscillator strengths are given in Table 7.

We adopted the new MARCS 1D atmosphere models and selected the Standard
composition class, that is, we included the classical $\alpha$-enhancement of
+0.4 dex at low metallicity. They were downloaded from the MARCS web site
(Gustafsson et al., 2008), and interpolated using Thomas Masseron’s
$interpol\\_modeles$ code, which is available on the same web
site222http://marcs.astro.uu.se. Inside a cube of eight reference models, this
code performs a linear interpolation on three given parameters: Teff, $\log$
g, and [Fe/H].

###  3.2 Photometric temperature and gravity

The atmospheric parameters were initially determined using photometric
information as reported in Table 2. The first approximated determination of
the stellar effective temperature, Teff, was based on the V$-$I, V$-$J, V$-$H,
and V$-$K color indices measured by Battaglia et al. (2006), and J and Ks
photometry was taken from the VISTA commissioning data, which were also
calibrated onto the 2MASS photometric system. We assumed $Av=3.24\cdot
E_{B-V}$ (Cardelli et al., 1989) and $E_{B-V}$ = 0.03 for Fornax (Letarte et
al., 2010) and $E_{B-V}$ = 0.061 for Carina (de Boer et al., 2014) for the
reddening correction, respectively. The adopted photometric effective
temperatures, $T_{\mathrm{eff}}$, are listed in Table 3. They correspond to
the simple average of the four color temperatures derived from $V-I$, $V-J$,
$V-H$, and $V-K$ with the calibration of Ramírez & Meléndez (2005).

Table 3: CaT metallicity estimates, photometric and final spectroscopic
parameters.

| Photometric Parameters |  |  | Final Parameters
---|---|---|---|---
| Teff [K] |  |  | Teff |  $\log$(g) | vt | [Fe/H]
ID | $V-I$ | $V-J$ | $V-H$ | $V-K_{s}$ | mean $\pm$ $\sigma$ |  $\log$(g) | [Fe/H]CaT | [K] | [cgs] | [km s-1] |
fnx_06_019 | 4379 | 4257 | 4248 | 4362 | 4311 $\pm$ 68 | 0.70 | $-2.54$ | 4280 | 0.68 | 1.80 |  $-$2.92
fnx0579x-1 | 4338 | 4422 | 4386 | 4427 | 4393 $\pm$ 41 | 0.71 | $-2.55$ | 4255 | 0.62 | 1.70 |  $-$2.73
car1_t174 | 4711 | 4678 | 4592 | 4646 | 4657 $\pm$ 51 | 1.42 | $-3.41$ | 4650 | 1.42 | 1.90 |  $-$3.01
car1_t194 | 4619 | 4533 | 4519 | 4544 | 4554 $\pm$ 45 | 1.42 | $-2.68$ | 4550 | 1.43 | 1.71 |  $-$2.58
car1_t200 | 4862 | 4813 | 4690 | 4663 | 4757 $\pm$ 96 | 1.56 | $-3.26$ | 4750 | 1.56 | 1.69 |  $-$2.95
LG04c_0008 | 4518 | 4504 | 4466 | 4507 | 4499 $\pm$ 23 | 1.07 | $-3.29$ | 4520 | 1.08 | 1.78 |  $-$3.05

Because only very few Fe ii lines can be detected in our X-Shooter spectra,
the determination of surface gravities from the ionisation balance of Fe I vs.
Fe II was not possible. Non-local thermodynamic equilibrium (NLTE) effects
also play a role at extremely low metallicity and impact the abundances of Fe
I, with $\Delta$(Fe II–Fe I) up to +0.20 dex at [Fe/H] = $-3$ (Mashonkina et
al., 2017a), thus surface gravities were determined from their relation with
$T_{\mathrm{eff}}$:

$\log g_{\star}=\log
g_{\odot}+\log\frac{M_{\star}}{M_{\odot}}+4\times\log\frac{T_{{\mathrm{eff}}\star}}{T_{{\mathrm{eff}}\odot}}+0.4\times\left(M_{{\rm
bol}\star}-M_{{\rm bol}\odot}\right)$ (1)

assuming $\log g_{\odot}$ = 4.44, $T_{{\mathrm{eff}}\odot}$ = 5790 K, and
Mbol⊙ = 4.75 for the Sun. We adopted a stellar mass of 0.8 M⊙ and calculated
the bolometric corrections using the Alonso et al. (1999) calibration, with a
distance of d=138 kpc (Battaglia et al., 2006) for Fornax and d=106 kpc (de
Boer et al., 2014) for Carina.

###  3.3 Final stellar parameters and abundance determination

We determined the stellar chemical abundances via the measurement of the
equivalent widths (EWs) or spectral synthesis of atomic transition lines, when
necessary, for example in the case of blended lines. Lines present in the
spectra and our line list are detected and their EWs measured with DAOSPEC
(Stetson & Pancino, 2008). This code performs a Gaussian fit of each
individual line and measures its corresponding EW. Although DAOSPEC fits
saturated Gaussians to strong lines, it cannot fit the wider Lorentz-like
wings of the profile of very strong lines, in particular beyond 120 mÅ at very
high resolution (Kirby & Cohen, 2012). For some of the strongest lines in our
spectra, we therefore derived the abundances by spectral synthesis (see
below).

The measured EWs are provided in Table 7. Values in bracket indicate that the
corresponding abundances were derived by spectral synthesis. The abundance
derivation from EWs and the spectral synthesis calculation were performed with
the Turbospectrum code (Alvarez & Plez, 1998; Plez, 2012), which assumes local
thermodynamic equilibrium (LTE), but treats continuum scattering in the source
function. We used a plane-parallel transfer for the line computation; this is
consistent with our previous work on EMP stars (Tafelmeyer et al., 2010;
Jablonka et al., 2015; Lucchesi et al., 2020).

In order to derive the final Teff and the microturbulence velocities
($v_{\mathrm{t}}$), we checked or required no trend between the abundances
derived from Fe i and excitation potential ($\chi_{exc}$) or the
predicted333According to Magain (1984), the use of observed EWs produce an
increase of $v_{\mathrm{t}}$ by 0.1$-$0.2 $kms^{-1}$, which would be reflected
in a decrease of the measured [Fe/H] values by a few hundredths of a dex in a
systematic way. A variation like this does not change the results in a
significant way. EWs. In order to minimize the NLTE effect on the measured
abundances we excluded from the analysis Fe i lines with $\chi_{exc}$ ¡ 1.4
eV. Furthermore very strong lines (EW ¿ 120mÅ) with strong wings that cannot
be well fitted are also excluded.

Starting from the initial photometric parameters of Table 3, we adjusted
$T_{\mathrm{eff}}$ and $v_{\mathrm{t}}$ by minimizing the slopes of the
diagnostic plots, within its 2$\sigma$ uncertainty. We did not force
ionization equilibrium between Fe I and Fe II, taking into account that there
will likely be NLTE effects at these low metallicities (Amarsi et al., 2016;
Mashonkina et al., 2017a; Ezzeddine et al., 2017). For each iteration the
corresponding values of $\log g$ were computed from its relation with
$T_{\mathrm{eff}}$ (Eq. 1), assuming the updated values of $T_{\mathrm{eff}}$,
and adjusting the model metallicity to the mean iron abundance derived in the
previous iteration. The final values of Teff are less than 30 K away from the
initial photometric estimates, at the exception of fnx0579x$-$1 which is 138 K
cooler than the mean photometric temperature.

We derived the chemical abundances of the strong lines with measured EW ¿ 100
mÅ by spectral synthesis. These abundances were obtained using our own code
(as in Lucchesi et al. 2020, 2022), which performs a $\chi^{2}$-minimization
between the observed spectral features and a grid of synthetic spectra
calculated on the fly with Turbospectrum. A line of a chemical element $X$ is
synthesized in a wavelength range of $\sim$50 Å. It is optimized by varying
its abundance in steps of 0.1 dex, from [$X$/Fe] = $-2.0$ dex to [$X$/Fe] =
$+2.0$ dex. In the same way, the resolution of the synthetic spectra is
optimized when needed. Starting from the nominal instrumental resolution,
synthetic spectra can be convolved with a wide range of Gaussian widths for
each abundance step. A second optimization, with abundance steps of 0.01 dex,
is then performed in a smaller range around the minimum $\chi^{2}$ in order to
refine the results. Similarly, the elements with a significant hyperfine
structure (HFS; e.g. Sc, Mn, Co, and Ba) have been determined by running
Turbospectrum in its spectral synthesis mode in order to properly take into
account blends and the HFS components in the abundance derivation, as in North
et al. (2012), Prochaska & McWilliam (2000) for Sc and Mn, and from the Kurucz
web site444http://kurucz.harvard.edu/linelists.html for Co and Ba.

The final abundances are listed in Table 4. The solar abundances are taken
from Asplund et al. (2009).

Table 4: Derived LTE abundances for the Fornax stars observed with UVES, and
the Carina stars observed with XSHOOTER along with their associated errors
(see § 3).

| Fe I | Fe II | C** | O I | Na I | Mg I | Al I | Si I | Ca I | Sc II | Ti I | Ti II | Cr I | Mn I | Co I | Ni I | Cu I | Zn I | Sr II | Y II | Zr II | Ba II | La II | Pr II | Nd II | Eu II | Dy II |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
log$\epsilon$(X)⊙ | 7.50 | 7.50 | 8.43 | 8.69 | 6.24 | 7.60 | 6.45 | 7.51 | 6.34 | 3.15 | 4.95 | 4.95 | 5.64 | 5.43 | 4.99 | 6.22 | 4.19 | 4.56 | 2.87 | 2.21 | 2.58 | 2.18 | 1.10 | 0.72 | 1.42 | 0.52 | 1.10  |
fnx_06_019 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
No. lines* | 67 | 2 | 1 | 1 | 2 | 3 | 1 | 1 | 6 | 6 | 9 | 7 | 4 | 3 | 1 | 3 | 1 | 1 | 1 | 5 | 1 | 4 | 4 | 1 | 3 | 2 | 3 |
log$\epsilon$(X) | $4.58$ | $4.67$ | $5.05$ | $6.67$ | $3.54$ | $5.23$ | $3.56$ | $5.16$ | $3.82$ | $0.40$ | $1.97$ | $2.45$ | $2.39$ | $2.09$ | $2.12$ | $3.34$ | ¡$0.41$ | $1.93$ | $-0.67$ | $-0.86$ | $-0.12$ | $-0.43$ | $-1.28$ | $-1.14$ | $-0.89$ | $-1.60$ | $-0.74$ |
[X/H] | $-2.92$ | $-2.83$ | $-3.38$ | $-2.02$ | $-2.70$ | $-2.37$ | $-2.89$ | $-2.35$ | $-2.52$ | $-2.75$ | $-2.98$ | $-2.50$ | $-3.25$ | $-3.34$ | $-2.87$ | $-2.88$ | ¡$-3.78$ | $-2.63$ | $-3.54$ | $-3.07$ | $-2.70$ | $-2.61$ | $-2.38$ | $-1.86$ | $-2.31$ | $-2.12$ | $-1.84$ |
[X/Fe] | $-0.00$ | $+0.09$ | $-0.46$ | $+0.90$ | $+0.22$ | $+0.55$ | $+0.03$ | $+0.57$ | $+0.40$ | $+0.17$ | $-0.06$ | $+0.42$ | $-0.33$ | $-0.42$ | $+0.05$ | $+0.04$ | ¡$-0.86$ | $+0.29$ | $-0.62$ | $-0.15$ | $+0.22$ | $+0.31$ | $+0.54$ | $+1.06$ | $+0.61$ | $+0.79$ | $+1.08$ |
Error | $0.10$ | $0.10$ | $0.12$ | $0.12$ | $0.10$ | $0.11$ | $0.12$ | $0.12$ | $0.10$ | $0.10$ | $0.09$ | $0.11$ | $0.09$ | $0.10$ | $0.16$ | $0.08$ | $0.12$ | $0.12$ | $0.12$ | $0.10$ | $0.12$ | $0.10$ | $0.10$ | $0.16$ | $0.10$ | $0.10$ | $0.10$ |
fnx0579x–1 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
No. lines* | 76 | 4 | 1 | 1 | 2 | 4 | $-$ | 1 | 11 | 5 | 10 | 8 | 5 | 3 | 1 | 4 | 1 | $-$ | 1 | 2 | $-$ | 4 | $-$ | $-$ | $-$ | $-$ | $-$ |
log$\epsilon$(X) | $4.77$ | $4.97$ | $5.46$ | $6.99$ | $3.50$ | $5.24$ | $-$ | $4.76$ | $3.91$ | $0.64$ | $2.01$ | $2.53$ | $2.62$ | $2.24$ | $2.07$ | $3.39$ | $0.82$ | $-$ | $-0.52$ | $-1.03$ | $-$ | $-1.21$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/H] | $-2.73$ | $-2.53$ | $-2.97$ | $-1.70$ | $-2.74$ | $-2.36$ | $-$ | $-2.75$ | $-2.43$ | $-2.51$ | $-2.94$ | $-2.42$ | $-3.02$ | $-3.19$ | $-2.92$ | $-2.83$ | $-3.37$ | $-$ | $-3.39$ | $-3.24$ | $-$ | $-3.39$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/Fe] | $+0.00$ | $+0.20$ | $-0.24$ | $+1.03$ | $-0.00$ | $+0.37$ | $-$ | $-0.02$ | $+0.30$ | $+0.22$ | $-0.21$ | $+0.31$ | $-0.29$ | $-0.46$ | $-0.19$ | $-0.10$ | $-0.64$ | $-$ | $-0.66$ | $-0.52$ | $-$ | $-0.66$ | $-$ | $-$ | $-$ | $-$ | $-$ |
Error | $0.10$ | $0.13$ | $0.12$ | $0.12$ | $0.10$ | $0.10$ | $-$ | $0.12$ | $0.10$ | $0.10$ | $0.13$ | $0.13$ | $0.10$ | $0.10$ | $0.12$ | $0.10$ | $0.12$ | $-$ | $0.12$ | $0.15$ | $-$ | $0.10$ | $-$ | $-$ | $-$ | $-$ | $-$ |
car1_t174 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
No. lines* | 10 | 2 | 1 | $-$ | 1 | 2 | $-$ | $-$ | 1 | $-$ | $-$ | 1 | 1 | 1 | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | 2 | $-$ | $-$ | $-$ | $-$ | $-$ |
log$\epsilon$(X) | $4.51$ | $4.64$ | $4.59$ | $-$ | $3.80$ | $4.98$ | $-$ | $-$ | $3.64$ | $-$ | $-$ | $2.08$ | $2.07$ | $1.55$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-1.99$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/H] | $-2.99$ | $-2.86$ | $-3.84$ | $-$ | $-2.44$ | $-2.63$ | $-$ | $-$ | $-2.70$ | $-$ | $-$ | $-2.87$ | $-3.57$ | $-3.88$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-4.17$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/Fe] | $-0.00$ | $+0.14$ | $-0.85$ | $-$ | $+0.55$ | $+0.37$ | $-$ | $-$ | $+0.29$ | $-$ | $-$ | $+0.12$ | $-0.58$ | $-0.89$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-1.18$ | $-$ | $-$ | $-$ | $-$ | $-$ |
Error | $0.13$ | $0.13$ | $0.17$ | $-$ | $0.17$ | $0.13$ | $-$ | $-$ | $0.17$ | $-$ | $-$ | $0.17$ | $0.17$ | $0.17$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-$ | $0.26$ | $-$ | $-$ | $-$ | $-$ | $-$ |
car1_t194 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
No. lines* | 24 | 2 | 1 | $-$ | 2 | 2 | $-$ | $-$ | 2 | $-$ | 3 | 3 | 1 | $-$ | $-$ | 1 | $-$ | $-$ | 1 | $-$ | $-$ | 2 | $-$ | $-$ | $-$ | $-$ | $-$ |
log$\epsilon$(X) | $4.92$ | $5.10$ | $4.90$ | $-$ | $4.12$ | $5.26$ | $-$ | $-$ | $4.10$ | $-$ | $2.63$ | $2.62$ | $2.85$ | $-$ | $-$ | $3.61$ | $-$ | $-$ | $0.33$ | $-$ | $-$ | $0.03$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/H] | $-2.58$ | $-2.40$ | $-3.53$ | $-$ | $-2.12$ | $-2.34$ | $-$ | $-$ | $-2.24$ | $-$ | $-2.32$ | $-2.33$ | $-2.79$ | $-$ | $-$ | $-2.61$ | $-$ | $-$ | $-2.54$ | $-$ | $-$ | $-2.15$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/Fe] | $-0.00$ | $+0.18$ | $-0.95$ | $-$ | $+0.47$ | $+0.24$ | $-$ | $-$ | $+0.34$ | $-$ | $+0.26$ | $+0.25$ | $-0.21$ | $-$ | $-$ | $-0.03$ | $-$ | $-$ | $+0.04$ | $-$ | $-$ | $+0.43$ | $-$ | $-$ | $-$ | $-$ | $-$ |
Error | $0.10$ | $0.16$ | $0.16$ | $-$ | $0.11$ | $0.11$ | $-$ | $-$ | $0.27$ | $-$ | $0.10$ | $0.18$ | $0.16$ | $-$ | $-$ | $0.16$ | $-$ | $-$ | $0.16$ | $-$ | $-$ | $0.11$ | $-$ | $-$ | $-$ | $-$ | $-$ |
car1_t200 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
No. lines* | 12 | $-$ | 1 | $-$ | 2 | 2 | $-$ | $-$ | $-$ | $-$ | $-$ | 2 | 1 | 1 | $-$ | $-$ | $-$ | $-$ | 1 | $-$ | $-$ | 2 | $-$ | $-$ | $-$ | $-$ | $-$ |
log$\epsilon$(X) | $4.60$ | $-$ | $5.06$ | $-$ | $4.43$ | $5.08$ | $-$ | $-$ | $-$ | $-$ | $-$ | $2.49$ | $2.41$ | $2.16$ | $-$ | $-$ | $-$ | $-$ | $-0.53$ | $-$ | $-$ | $-0.60$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/H] | $-2.90$ | $-$ | $-3.37$ | $-$ | $-1.80$ | $-2.52$ | $-$ | $-$ | $-$ | $-$ | $-$ | $-2.46$ | $-3.23$ | $-3.27$ | $-$ | $-$ | $-$ | $-$ | $-3.40$ | $-$ | $-$ | $-2.78$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/Fe] | $+0.00$ | $-$ | $-0.47$ | $-$ | $+1.10$ | $+0.38$ | $-$ | $-$ | $-$ | $-$ | $-$ | $+0.44$ | $-0.33$ | $-0.37$ | $-$ | $-$ | $-$ | $-$ | $-0.50$ | $-$ | $-$ | $+0.12$ | $-$ | $-$ | $-$ | $-$ | $-$ |
Error | $0.21$ | $-$ | $0.21$ | $-$ | $0.21$ | $0.21$ | $-$ | $-$ | $-$ | $-$ | $-$ | $0.49$ | $0.21$ | $0.21$ | $-$ | $-$ | $-$ | $-$ | $0.21$ | $-$ | $-$ | $0.27$ | $-$ | $-$ | $-$ | $-$ | $-$ |
LG04c_0008 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
No. lines* | 35 | 6 | 1 | $-$ | 2 | 2 | $-$ | $-$ | 1 | $-$ | $-$ | 2 | 1 | 1 | 2 | 1 | $-$ | $-$ | 1 | $-$ | $-$ | 2 | $-$ | $-$ | $-$ | $-$ | $-$ |
log$\epsilon$(X) | $4.47$ | $4.53$ | $4.22$ | $-$ | $3.89$ | $4.91$ | $-$ | $-$ | $3.55$ | $-$ | $-$ | $2.25$ | $1.83$ | $1.90$ | $1.78$ | $3.17$ | $-$ | $-$ | $-1.06$ | $-$ | $-$ | $-2.02$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/H] | $-3.03$ | $-2.97$ | $-4.21$ | $-$ | $-2.35$ | $-2.69$ | $-$ | $-$ | $-2.79$ | $-$ | $-$ | $-2.70$ | $-3.81$ | $-3.53$ | $-3.21$ | $-3.05$ | $-$ | $-$ | $-3.93$ | $-$ | $-$ | $-4.20$ | $-$ | $-$ | $-$ | $-$ | $-$ |
[X/Fe] | $-0.00$ | $+0.06$ | $-1.18$ | $-$ | $+0.68$ | $+0.34$ | $-$ | $-$ | $+0.24$ | $-$ | $-$ | $+0.33$ | $-0.78$ | $-0.50$ | $-0.18$ | $-0.02$ | $-$ | $-$ | $-0.90$ | $-$ | $-$ | $-1.17$ | $-$ | $-$ | $-$ | $-$ | $-$ |
Error | $0.17$ | $0.21$ | $0.17$ | $-$ | $0.17$ | $0.17$ | $-$ | $-$ | $0.17$ | $-$ | $-$ | $0.23$ | $0.17$ | $0.17$ | $0.17$ | $0.17$ | $-$ | $-$ | $0.17$ | $-$ | $-$ | $0.22$ | $-$ | $-$ | $-$ | $-$ | $-$ |

555* Number of lines kept after a careful selection of the best fitted or
synthesized lines. ** Measured from the CH molecular G-band.

###  3.4 Error budget

The uncertainties on the abundances were derived considering the uncertainties
on the atmospheric parameters and on the EWs, in a similar procedure to our
other works (e.g. Tafelmeyer et al., 2010; Jablonka et al., 2015; Hill et al.,
2019; Lucchesi et al., 2020).

  1. 1.

Uncertainties due to the atmospheric parameters. To estimate the sensitivity
of the derived abundances to the adopted atmospheric parameters, we repeated
the abundance analysis and varied only one stellar atmospheric parameter at a
time by its corresponding uncertainty, keeping the others fixed and repeating
the analysis. The estimated internal errors are $\pm$100 K in Teff, $\pm$0.15
dex in $\log$ (g), and $\pm$0.15 km s-1 in $v_{\mathrm{t}}$ for the UVES
sample, and $\pm$150 K in Teff, $\pm$0.15 dex in $\log$ (g) for the X-Shooter
sample. Because the S/N and atmospheric parameters of our sample stars are
very close to each other, we estimated the typical errors considering a single
reference star. Table 5 list the effects of these changes on the derived
abundances for fnx_06_019 in the UVES sample, and Table 6 list the effects of
these changes on the derived abundances for carLG04c_0008 in the X-Shooter
sample.

  2. 2.

Uncertainties due to EWs or spectral fitting. The uncertainties on the
individual EW measurements $\delta_{EWi}$ are provided by DAOSPEC (see Table
7) and computed according to the following formula (Stetson & Pancino, 2008) :

$\delta_{EWi}=\sqrt{\sum_{p}\left(\delta I_{p}\right)^{2}\left(\frac{\partial
EW}{\partial I_{p}}\right)^{2}+\sum_{p}\left(\delta
I_{C_{p}}\right)^{2}\left(\frac{\partial EW}{\partial I_{C_{p}}}\right)^{2}}$
(2)

where $I_{p}$ and $\delta I_{p}$ are the intensity of the observed line
profile at pixel $p$ and its uncertainty, and $I_{C_{p}}$ and $\delta
I_{C_{p}}$ are the intensity and uncertainty of the corresponding continuum.
The uncertainties on the intensities are estimated from the scatter of the
residuals that remain after subtraction of the fitted line (or lines, in the
case of blends). The corresponding uncertainties $\sigma_{EWi}$ on individual
line abundances are propagated by Turbospectrum. This is a lower limit to the
real EW error because systematic errors like the continuum placement are not
accounted for.

In order to account for additional sources of error, we quadratically added a
5% error to the EW uncertainty, so that no EW has an error smaller than 5%.
For the abundances derived by spectral synthesis (e.g., strong lines,
hyperfine structure, or carbon from the G band), the uncertainties were
visually estimated by gradually changing the parameters of the synthesis until
the deviation from the observed line became noticeable.

The abundance uncertainty for an element X due to the individual EW
uncertainties ($\sigma_{EWi}$ propagated from $\delta_{EWi}$) are computed as
:

$\sigma_{EW}(X)=\sqrt{\dfrac{N_{X}}{\sum_{i}1/\sigma_{EWi}^{2}}}$ (3)

where $N_{X}$ represents the number of lines measured for element X.

The dispersion $\sigma_{X}$ around the mean abundance of an element X measured
from several lines is computed as :

$\sigma_{X}=\sqrt{\dfrac{\sum_{i}(\epsilon_{i}-\overline{\epsilon})^{2}}{N_{X}-1}}$
(4)

where $\epsilon$ stands for the logarithmic abundance.

The final error on the elemental abundances is defined as $\sigma_{fin}$ =
max($\sigma_{EW}$(X), $\sigma_{X}/\sqrt{N_{X}}$, $\sigma_{Fe}/\sqrt{N_{X}}$).
As a consequence, no element X can have an estimated uncertainty $\sigma_{X}$
¡ $\sigma_{Fe}$; this is particularly important for species for which the
abundances are derived on very few lines.

Table 5: Changes in the mean abundances $\Delta$[X/H] caused by a $\pm 100$ K
change in $T_{\mathrm{eff}}$, a $\pm$0.15 dex change in $\log$ (g) and a
$\pm$0.15 km s-1 change in $v_{\mathrm{t}}$ for the UVES star fnx_06_019.

|  $\delta$log$\epsilon$(X)
---|---
El. |  $+\Delta$Teff |  $-\Delta$Teff |  $+\Delta\log$g |  $-\Delta\log$g |  $+\Delta$vt |  $-\Delta$vt
| fnx_06_019 ( 4280 0.68 1.8 -2.92 )
Fe I | $+0.14$ | $-0.15$ | $+0.00$ | $+0.00$ | $-0.03$ | $+0.03$
Fe II | $-0.02$ | $+0.04$ | $+0.05$ | $-0.05$ | $+0.02$ | $+0.02$
C I | $+0.13$ | $-0.08$ | $+0.00$ | $+0.01$ | $+0.00$ | $+0.00$
O I | $+0.06$ | $-0.03$ | $+0.06$ | $-0.05$ | $+0.01$ | $+0.01$
Mg I | $+0.09$ | $-0.10$ | $-0.02$ | $+0.02$ | $+0.04$ | $+0.04$
Ca I | $+0.11$ | $-0.13$ | $-0.02$ | $+0.01$ | $-0.03$ | $+0.02$
Sc II | $+0.03$ | $-0.01$ | $+0.05$ | $-0.05$ | $+0.03$ | $+0.03$
Ti I | $+0.27$ | $-0.26$ | $+0.02$ | $-0.03$ | $+0.03$ | $+0.03$
Ti II | $+0.02$ | $+0.00$ | $+0.05$ | $-0.04$ | $+0.05$ | $+0.05$
Cr I | $+0.20$ | $-0.20$ | $+0.00$ | $+0.00$ | $-0.02$ | $+0.02$
Co I | $+0.22$ | $-0.18$ | $+0.01$ | $-0.02$ | $-0.13$ | $+0.15$
Ni I | $+0.18$ | $-0.16$ | $+0.01$ | $+0.00$ | $+0.03$ | $+0.03$
Sr II | $+0.00$ | $+0.00$ | $+0.00$ | $+0.00$ | $+0.00$ | $+0.00$
Y II | $+0.05$ | $-0.02$ | $+0.05$ | $-0.05$ | $+0.02$ | $+0.02$
Ba II | $+0.06$ | $-0.04$ | $+0.06$ | $-0.05$ | $-0.05$ | $+0.07$

Table 6: Changes in the mean abundances $\Delta$[X/H] caused by a $\pm 150$ K
change in $T_{\mathrm{eff}}$ with consistent changes in photometric $\log$ (g)
and $v_{\mathrm{t}}$, and by a change of $\pm$0.15 dex in $\log$ (g) only, for
the X-Shooter star carLG04c_0008.

|  $\delta$log$\epsilon$(X)
---|---
El. |  $+\Delta$Teff($\log$g,vt) |  $-\Delta$Teff($\log$g,vt) |  $+\Delta\log$g |  $-\Delta\log$g
| carLG04c_0008 ( 4518 1.08 -3.05 1.78 )
Fe I | $+0.14$ | $-0.23$ | $-0.01$ | $+0.01$
Fe II | $+0.03$ | $-0.01$ | $+0.06$ | $-0.05$
C I | $+0.22$ | $-0.23$ | $-0.01$ | $+0.01$
Na I | $+0.31$ | $-0.36$ | $-0.01$ | $+0.00$
Mg I | $+0.30$ | $-0.33$ | $-0.03$ | $+0.03$
Ca I | $+0.11$ | $-0.14$ | $-0.01$ | $+0.00$
Ti II | $+0.11$ | $-0.10$ | $+0.06$ | $-0.07$
Cr I | $+0.26$ | $-0.27$ | $+0.02$ | $-0.01$
Co I | $+0.25$ | $-0.25$ | $+0.02$ | $-0.01$
Ni I | $+0.21$ | $-0.25$ | $+0.01$ | $-0.01$
Sr II | $+0.22$ | $-0.06$ | $+0.14$ | $-0.16$
Ba II | $+0.16$ | $-0.13$ | $+0.06$ | $-0.05$

Figure 3: X-Shooter spectra of the four Carina stars (blue) in the region of
the CH absorption, from the most metal-poor on top ([Fe/H] = $-3.03$) to the
most metal-rich at the bottom ([Fe/H] = $-2.58$). For comparison is the
spectrum of the Sculptor star Scl074_02 (black, on top) with similar
atmospheric parameters ([Fe/H] = $-3.0$) from Starkenburg et al. (2013).

Figure 4: X-Shooter spectra of the four Carina stars (blue) in the region of
the Na I doublet, from the most metal-poor on top ([Fe/H] = $-3.03$) to the
most metal-rich at the bottom ([Fe/H] = $-2.58$), and the spectrum of the
Sculptor star Scl074_02 (black, on top) with similar atmospheric parameters
([Fe/H] = $-3.0$) from Starkenburg et al. (2013).

Figure 5: Examples of the Ca I lines used in the UVES spectrum (black) for the
Fornax star fnx_06_019. Blue shows the EW fitting from DAOSPEC. Atomic data
for each line is listed on the panels, along with the derived abundances,
which agree very well between different lines.

###  3.5 Specific comments on the abundance determination

####  3.5.1 Carbon

Carbon abundances were determined by spectral synthesis of the region of the
CH molecular G-band. The carbon abundances of the UVES Fornax sample were
determined in the deeper and unblended 4222 – 4225 Å region, while carbon was
determined in a larger range of the CH molecular band, between 4270 Å and 4330
Å for the X-Shooter sample in Carina. We assumed [O/Fe] = [Mg/Fe], but since
the carbon abundance is low in our sample stars, the exact [O/Fe] assumed has
very little effect on our results. The CH molecular band is shown in Fig. 4
for the X-Shooter spectra of our four Carina stars.

####  3.5.2 Lithium

Unfortunately the Li resonance doublet at 6707 Å was not measurable in any of
our stars at our available quality of the UVES or X-Shooter spectra. This is
expected, since Li on the surface of RGB stars is typically depleted due to
dredge-up and mixing (e.g. Gratton et al., 2000; Lind et al., 2009). None of
our target stars are therefore lithium-enhanced giants, which have been found
in small fractions in most types of environments, including dwarf galaxies
(e.g. Kirby et al., 2012; Hill et al., 2019).

####  3.5.3 Sodium and Aluminium

The sodium was measured from the two 5889.951 Å and 5895.924 Å resonance lines
through spectral synthesis.

The X-Shooter spectra of the four Carina target stars are presented in the
region of the Na lines and the CH absorption in Fig. 4 and Fig. 4
respectively. They are compared to a star from Starkenburg et al. (2013) in
the Sculptor dSph galaxy, Scl074_02, with very similar atmospheric parameters
(Teff=4595 K $\log$ g=1.21 [Fe/H]=$-$3.0 $v_{\mathrm{t}}$=2.1 km s-1), but
significantly lower Na. The carbon abundance is very similar in all stars
shown in Fig. 4, with low [C/Fe] $\leq-0.5$. However, the difference can be
clearly seen in the sodium region (Fig. 4), where the sodium lines appear
stronger in Carina than in the Sculptor star. We note that interstellar Na
lines are observed at different radial velocities and are unlikely
contaminating the measured lines.

Two Al I lines are detected in the UVES spectra, but they are in a noisy part
of the spectrum and fall very close to the strong Ca II H & K absorption
doublet. Furthermore, the continuum level is hard to determine in this region,
and the derived abundances strongly depend on it. Because of these
difficulties, Al was only derived for one star, fnx_06_019 , based on one line
at 3961.52 Å.

####  3.5.4 $\alpha$-elements

  * •

$\mathit{Magnesium}$. The UVES Mg abundances are based on three lines. Two of
them are rather strong (5172.684 and 5183.604 Å), with EW ¿ 100 mÅ and have
non-Gaussian line profiles. The abundances of these lines are not consistent
with the weaker 5528.405 Å line. For this reason, we derived the Mg abundance
through spectral synthesis, after which all lines had consistent abundances.
Three additional Mg i lines (4167.271, 4351.906, and 5711.088 Å) are detected
in our spectra, but were discarded because they are too noisy, strongly
blended and too weak, respectively. The Mg abundances from the X-Shooter
sample are obtained through spectral synthesis in two 20 Å windows, one
centered on the 5172.684 Å line, taking into account the blends at the
X-Shooter resolution, and one centered on the 5183.604 Å line.

  * •

$\mathit{Silicon}$. One Si I line is detected in our UVES spectra, at 4102.936
Å, but in a noisy part of the spectrum and it falls closely to the strong
H$\delta$ absorption line. However, we were able to derive a Si abundance in
both Fornax stars, based on this one line.

  * •

$\mathit{Calcium}$. Three Ca I lines were used in the X-Shooter spectra for
the Carina stars. Calcium was not measurable in the star car1_t200. In the
Fornax sample, in the red part of the UVES spectra ( ¿5500 Å ) six and eleven
clean Ca I lines were used, for fnx0579x-1 and fnx_06_019, respectively.
Examples of the Ca I lines for fnx_06_019 are shown in Fig. 5.

  * •

$\mathit{Titanium}$. The Ti i abundances are based on 10$-$11 lines, all
giving consistent abundance values from their EW. The Ti ii abundances are
based on 8$-$14 lines. They are slightly more scattered as many of them are
rather strong. The mean abundances of Ti i and Ti ii are different by
$\Delta$(Ti ii$-$Ti i) = +0.50. This is explained by the fact that Ti ii is
less sensitive to NLTE effects than its neutral state. Thus, following
Jablonka et al. (2015), for the purpose of our discussion we adopted the Ti ii
abundances as the most representative of the Titanium content in our stars.

####  3.5.5 Iron-peak elements

  * •

$\mathit{Chromium}$. Cr abundances are derived from 4 to 5 Cr I lines in the
red part of the UVES spectra, all of them give consistent results from their
EW. Five extra lines are detected in our spectra (4254.352, 4274.812, 4289.73,
5206.023 and 5208.409 Å) but they were rejected for being too strong (¿110 mÅ)
or too noisy. In the X-Shooter spectra only the strongest $\lambda$5206.023
and 5208.409 Å lines were accessible, Cr abundances were obtained from a
single spectral synthesis in a 20 Å wavelength range covering the two lines
and taking into account the blends at this resolution.

  * •

$\mathit{Manganese}$. Mn abundances rely on the three Mn I 4030.75 Å 4033.06 Å
and 4034.48 Å lines. These were synthesized taking into account their HFS
components and give consistent abundance results. The Mn lines 4041.35 Å and
4823.52 Å are also present in our spectra but they are weak ($\sim$30 mÅ) and
too much affected by the noise and were thus discarded. In the case of
X-Shooter spectra, a single spectral synthesis has been done in a 20 Å window
centered on the Mn triplet.

####  3.5.6 Neutron-capture elements

  * •

$\mathit{Strontium}$. Three Sr II lines are present in our spectra (4077.709,
4161.792 and 4215.519 Å). While the 4215.519 Å line was the most reliable in
the UVES spectra, the 4077.709 Å line was less affected by blends and better
suited for the X-Shooter spectra.

  * •

$\mathit{Barium}$. Ba abundances were measured from 2 to 4 lines (4554.029,
4934.076, 5853.668, 6141.713 and 6496.897 Å) in the UVES and X-Shooter spectra
by spectral synthesis taking into account blends and HFS.

Additional neutron-capture elements were measurable in the spectrum of the
$r$-process rich star fnx_06_019 in Fornax. Fig. 6 compares two UVES spectra
in the region of lanthanum and europium lines, showing a clear neutron-capture
enhancement in fnx_06_019 (see also Fig. 15).

  * •

$\mathit{Lanthanum}$. The La abundance was determined from the
$\lambda$4920.98 Å line which is the reddest available La II line and the
least affected by noise. The detection was checked by computing synthetic
spectra for the 4077.34, 4086.71, and 4123.23 Å lines using the abundance
derived from the 4920.98 Å line (Fig. 15). All lines were in good agreement
with the adopted abundance.

  * •

$\mathit{Neodymium}$. The Nd abundance was determined from the two clean and
unblended Nd II lines at 4825.48 and 5319.81 Å, and further confirmed to be
consistent with the 4109.45 and 4061.08 Å lines.

  * •

$\mathit{Dysprosium}$. The abundance was measured from the Dy II 4103.31 Å
line by spectral synthesis. The 3944.68 Å line is too affected by noise and
continuum level uncertainty, while the 4449.7 Å line is too strongly blended
to be reliable.

Figure 6: Two UVES spectra in the region of the lanthanum (top) and europium
(bottom) lines. In red is the r-process rich star fnx_06_019, and in blue the
r-process normal star fnx0579x–1.

##  4 Results

The measured LTE chemical abundances for our four Carina, and two Fornax stars
are listed in Table 4 and shown in Figs. 7–13. The different element groups
are discussed in the following Sections.

###  4.1 Literature comparison samples

In Figures 7–13, abundances from the Milky Way are shown with gray dots and
are compiled from Placco et al. (2014) for carbon, from Bensby et al. (2014);
Yong et al. (2013) for Na, Mg, Ca, Ti, with the addition of Frebel et al.
(2010) for Na. Milky Way iron-peak elements (Sc, Cr, Mn, Co, Ni, Zn) are from
Bensby et al. (2014); Yong et al. (2013); Frebel et al. (2010), while
abundances of the neutron-capture elements strontium and barium are taken from
Roederer (2013). Milky Way europium abundances are from Frebel et al. (2010);
Venn et al. (2004).

Abundances measured in Carina are taken from Koch et al. (2008), Venn et al.
(2012), and Norris et al. (2017). Norris et al. (2017) compiled 63 RGB stars,
from which 14 stars were totally new observations, while 18 stars were re-
observations and 31 stars were re-analysis of stars initially studied by
Lemasle et al. (2012); Shetrone et al. (2003) and Venn et al. (2012). For the
purpose of homogeneity we show the Norris et al. (2017) results and refer to
this paper for a detailed description of the individual samples. The only
exception is made for the Venn et al. (2012) sample. Since their work includes
more chemical elements than Norris et al. (2017), we keep the original results
of the nine Carina members from Venn et al. (2012). Fornax comparison samples
are taken from Letarte et al. (2006, 2010); Lemasle et al. (2014); Tafelmeyer
et al. (2010).

###  4.2 Carbon

Figure 7 presents the carbon abundances measured in Fornax and Carina at
[Fe/H] ¡ $-$2.5, compared to literature data. The four Carina stars analyzed
in this paper all present very low carbon levels, similar to the upper limits
derived in the Carina sample of Venn et al. (2012). The Carina [C/Fe]
distribution is located at the lower edge of the Milky Way abundances, making
Carina noticeably C-poor (see Fig. 4). However, we note that two CEMP-no stars
have been identified in Carina, first in Susmitha et al. (2017), and more
recently in Hansen et al. (2023).

In Fornax, both our stars and the one star previously studied by Tafelmeyer et
al. (2010) have similar carbon-normal abundances. On average the Fornax stars
are somewhat higher in C compared to Carina, especially when corrections for
evolutionary status are taken into account.

We note that none of our six new stars are enhanced in carbon, while in the
Milky Way the typical fraction of CEMP-no stars is $\approx 40\%$ at
$\rm[Fe/H]<-3$ (Placco et al., 2014). This adds to previous results, showing
that dSph galaxies are poor in CEMP-no stars relative to the Milky Way and the
UFDs (Starkenburg et al., 2013; Skúladóttir et al., 2015, 2021; Skúladóttir et
al., 2023a; Jablonka et al., 2015; Simon et al., 2015; Kirby et al., 2015;
Hansen et al., 2018; Lucchesi et al., 2020), for a more detailed discussion on
this see Section 5.

Figure 7: [C/Fe] as a function of $\log$(L/L⊙) for Fornax (blue) and Carina
(green). Circles are this work. Green upper limits are from Venn et al.
(2012), and the green star symbol is a CEMP-no star from Susmitha et al.
(2017). The blue square is the Fornax member from Tafelmeyer et al. (2010).
Gray dots are MW halo stars (Placco et al., 2014). The dotted line traces the
criterion of Aoki et al. (2007a) to define C-enhanced stars, which takes into
account the depletion of carbon along the RGB. Only stars with
$\rm[Fe/H]<-2.5$ are included. Figure 8: LTE Sodium-to-iron ratios as a
function of [Fe/H] are shown for stars in the Fornax and Carina dSph, as well
as the MW. Fornax members are in blue: large circles are this work, small
circles are from Lemasle et al. (2014), small triangles are from Letarte et
al. (2010), small star symbols are members of Fornax globular clusters 1, 2
and 3 from Letarte et al. (2006). The square at [Fe/H] = –3.66 is an EMP star
from Tafelmeyer et al. (2010). Carina members are in green: large circles are
this work, small triangles are from Koch et al. (2008), small circles are from
Norris et al. (2017), small squares are from Venn et al. (2012), the star
symbol is a CEMP-no from Susmitha et al. (2017). Gray dots are MW stars
(Bensby et al., 2014; Yong et al., 2013; Frebel et al., 2010).

###  4.3 Light element: sodium

The LTE abundances of sodium are presented in Fig. 8. The Milky Way has a very
large scatter in [Na/Fe] at low [Fe/H] ¡ $-2$, and our new data points fall
within this range. While Fornax shows a near solar $\rm[Na/Fe]\approx 0$, all
four stars in Carina have high $\rm[Na/Fe]\gtrsim+0.5$. Since direct
comparison between the Carina (X-Shooter) and Fornax (UVES) spectra is not
meaningful, in Fig. 4 we plot the Na lines of the Carina stars together with
an X-Shooter spectrum of a Na-poor star in Sculptor. This comparison clearly
shows the Carina stars to be Na rich.

NLTE effects can play an important role on the derived sodium abundances. The
resonance lines, 5889.951 Å and 5895.924 Å, are especially sensitive. Very
limited NLTE abundances are available in the literature. The apparent large
dispersion at [Fe/H] ¡ $-2$ could probably be significantly reduced if NLTE
corrections were applied. We used the INSPECT database666http://www.inspect-
stars.com/ to compute corrections for our stars to investigate if the [Na/Fe]
difference between Fornax and Carina would remain (see Table 9). The
correction depends both on the measured LTE sodium abundances as well as the
metallicity and the stellar atmospheric parameters. The corrections for Carina
were $\langle\Delta$[Na/Fe]${}_{\text{NLTE}}\rangle=-0.33$ and for Fornax
$\langle\Delta$[Na/Fe]${}_{\text{NLTE}}\rangle=-0.16$. However, the Carina
NLTE abundances are still higher, with
$\langle$[Na/Fe]${}_{\text{NLTE}}\rangle=+0.37\pm 0.17$, and for Fornax
$\langle$[Na/Fe]${}_{\text{NLTE}}\rangle=-0.06\pm 0.14$.

The interpretation of this Na-enhancement is not straight forward. Norris et
al. (2013) found that CEMP-no stars were likely to be enhanced in Na, however,
the Carina stars are depleted in carbon, see the previous Section, and Fig. 7.
The origin of this Na enhancement, compared to other dSph galaxies, remains
therefore unclear. We note however that there are two stars from Venn et al.
(2012) with lower Na, so it seems that there a significant scatter of Na in
Carina, similar to the Milky Way.

Figure 9: Abundance ratios for the $\alpha$-elements Mg, Ca, and Ti (from top
to bottom) as a function of [Fe/H]. Symbols are the same as in Fig. 8.

###  4.4  $\alpha$-elements

The chemical abundances of the $\alpha$-elements Mg, and Ca, together with Ti,
are shown in Fig. 9. All three elements show a very similar trend of enhanced
$\rm[\alpha/Fe]\approx+0.4$ at $\rm[Fe/H]<-2.5$, in all our literature samples
as well as in Hendricks et al. (2014a) who focuses on determining the position
of the $\alpha$-knee in Fornax. Our results are in perfect agreement with the
Milky Way, and other dwarf galaxies, both the dSphs (e.g. Tafelmeyer et al.,
2010; Lucchesi et al., 2020; Theler et al., 2020) and UFDs (e.g. Simon, 2019).

The Carina dSph has a complex star formation history (e.g. Tolstoy et al.,
2009; de Boer et al., 2014), and the scatter of [Mg/Fe] at intermediate
metallicities, $\rm-2.5<[Fe/H]<-1$, is quite large, $\sigma=0.30$ dex.
However, the scatter seems to be reduced at $\rm[Fe/H]\leq-2.5$, where all
stars are consistent with the same [Mg/Fe] value, $\sigma=0.08$ dex. It is
therefore possible, that these low metallicities probe only the first star
formation burst in Carina.

Figure 10: From left to right, top to bottom: [Sc/Fe], [Cr/Fe], [Mn/Fe],
[Co/Fe], [Ni/Fe], and [Zn/Fe] for metal-poor stars in Fornax, Carina, and MW.
The symbols are the same as in Fig. 8. The stars studied in this paper are the
large circles. MW data are from Bensby et al. (2014); Yong et al. (2013);
Frebel et al. (2010).

###  4.5 Iron-peak elements

Figure 10 presents Sc, Cr, Mn, Co, Ni, and Zn trends with Fe in Carina and
Fornax, compared with the Milky Way halo and disc populations. The element Sc
could only be determined in our Fornax sample, which had high-resolution UVES
spectra. The production of Sc is dominated by core-collapse SNe (ccSN; Woosley
et al. 2002; Battistini & Bensby 2015) and therefore, as expected, [Sc/Fe] is
at the same level as the $\alpha$-elements seen in Fig. 9.

For both Fornax and Carina, Cr and Mn closely follow the Milky Way trends at
$\rm[Fe/H]<-2.5$ as derived from 1D LTE methods. NLTE calculations for the
neutral species of these elements show an over-ionization, leading to weakened
lines and positive NLTE abundance corrections (Bergemann et al., 2019).
Therefore the increasing trends of [Cr/Fe] and [Mn/Fe] with [Fe/H] might be
artificial. In the case of Co, our measurements are lower than the average
trend in the Milky Way. Similarly, the Co abundances in the Sculptor dSph are
low at $\rm[Fe/H]<-2.5$ (Skúladóttir et al., 2023b).

Nickel can be produced in ccSN, as well as in thermonuclear supernovae Type Ia
(SNIa; e.g., Jerkstrand, 2018). Before SNIa start to dominate, $\rm[Fe/H]<-2$,
our sample definitely set the level at solar value, $\rm[Ni/Fe]\approx 0$, for
both Carina and Fornax, implying that the global production of nickel follows
that of iron in core-collapse supernovae. This is in excellent agreement with
the Sculptor dSph and UFDs (Skúladóttir et al., 2023b). However, subsolar
[Ni/Fe] has been noted in the Fornax population at $\rm[Fe/H]>-1.2$ (Letarte
et al., 2010; Lemasle et al., 2014), and in Carina at $\rm[Fe/H]>-1.5$ (Norris
et al., 2017). This clearly corresponds to a stage of the galaxy chemical
evolution when the ejecta of SNIa dominate the composition of the interstellar
medium. Similar results are found in other dSph galaxies (Hill et al., 2019;
Kirby et al., 2019; Theler et al., 2020), as well as accreted dwarf galaxies
(e.g. Nissen & Schuster, 2010).

There is a known increase of [Zn/Fe] towards low [Fe/H] (e.g. Cayrel et al.,
2004), see Fig. 10 (bottom right). The NLTE corrections of Zn (Takeda et al.,
2005) are small in the metal-poor regime and do not fully explain this trend,
and it remains poorly understood. We were only able to measure Zn for the star
fnx_06_019 which falls on the Milky Way halo trend at $\rm[Zn/Fe]=+0.29$,
comparable to the level of the [$\alpha$/Fe] plateau. This was also observed
in two Sextans EMP stars (Lucchesi et al., 2020), two stars in Ursa Minor
(Cohen & Huang, 2010), and in Sculptor (Skúladóttir et al., 2017; Skúladóttir
et al., 2023b), highlighting the role of ccSN in the production of zinc in the
early stage of galaxy evolution.

Figure 11: Neutron-capture elements: Barium-to-iron ratio at the top and
Strontium-to-iron ratio at the bottom, as a function of [Fe/H] in Fornax
(blue) and Carina (green), compared to MW stars in gray from Roederer (2013).
The symbols are the same as in Fig. 8, large circles represent the new sample
analyzed here. Figure 12: Barium-to-strontium ratio as a function of [Ba/H].
References are the same as in Fig. 11. The empirical r–process limit is shown
with dashed line (Mashonkina et al., 2017b). Figure 13: Barium-to-europium
ratio as a function of [Fe/H]. The symbols are the same as in Fig. 11. MW
stars are from Frebel et al. (2010); Venn et al. (2004). The limits of pure
s-process and r-process are shown with dashed lines (Mashonkina et al.,
2017b).

###  4.6 Neutron-capture elements

Figure 11 shows our measurements of [Sr/Fe] and [Ba/Fe] with [Fe/H]. The Ba
and Sr abundances of our sample stars are consistent with the large spread in
the Milky Way. The abundance ratio of [Sr/Ba] with [Ba/H] is presented in Fig.
12. The [Sr/Ba] ratios of the Fornax stars, are compatible with those of the
Milky Way. However, these ratios in the Carina dSph are somewhat lower.
Mashonkina et al. (2017b) identified two populations in [Sr/Ba], one with
similar trend as the Milky Way (and Fornax), increasing towards low [Ba/H],
and the other of near constant [Sr/Ba], similar to the empirical r-process
ratio. The Carina abundances do seem to fall in between those two populations.

Only in the r-I star, fnx_06_019, were we able to measure [Eu/Fe]. Its [Ba/Eu]
= $-0.5$ value sits just above the pure r-process ratio, as is shown in Fig.
13. This star, therefore likely also shows some minor s-process contribution,
which is also evident from its rather high $\rm[Sr/Ba]=+0.5$, see Fig. 12. Not
only is this star rich in Eu, but it is also enhanced in La, Nd, and Dy, as
evident from the very strong lines shown in Fig. 15, and listed Table 4.
However, we note that the light neutron-capture elements Sr, Y, and Zr, are
not enhanced, with $\rm[Sr/Fe]=-0.62$, $\rm[Y/Fe]=-0.15$, and
$\rm[Zr/Fe]=+0.22$. The elements, Y, Sr, and Zr have a similar origin, and
their ratios are observed to be approximately constant in the Milky Way halo
(François et al., 2007).

This is the first r-I star identified in a dSph galaxy at such low [Fe/H]. The
r-I and r-II stars discovered in dSph galaxies so far seem to cover the more
metal-rich end of the metallicity distribution compared to halo r-I stars
(e.g. Shetrone et al., 2001; Aoki et al., 2007a; Cohen & Huang, 2009; Reichert
et al., 2020).

##  5 Discussion & Conclusions

Here we follow-up some of the first EMP candidates in the Fornax and Carina
dSphs to populate the yet uncovered metallicity range
$\rm-3.1\leq[Fe/H]\leq-2.5$. It is now clear that regardless of the subsequent
evolution of the local classical dwarf galaxies, which harbor very different
star formation histories, the first generations of stars formed in very
similar way in these systems. Almost all chemical elements follow the same
trend with (low) metallicity, and match the known relations for our Galaxy.

However, there are clear differences in the [C/Fe] abundances of dSph
galaxies, compared to UFDs and the Milky Way. In Fig. 14 we compare the
cumulative fraction of CEMP-no stars in dSph galaxies to that of the Milky
Way, in a similar way as Ji et al. (2020) did for UFDs. We used all the
available literature data, corrected for carbon depletion due stellar
evolution (Placco et al., 2014)777https://vplacco.pythonanywhere.com/, that
had no or minimal selection effect in regards to C-abundance. In particular,
we were unable to include Hansen et al. (2023), as they specifically targeted
CEMP stars, thus not providing information about the CEMP-no fraction. No
CEMP-s stars were included, however we did include the $\rm[Fe/H]=-3.38$ star
in Canes Venatici I, without Ba measurement, which Yoon et al. (2020) claimed
to be a CEMP-no star, using the stars position in the [Fe/H]-A(C) diagram. We
note that [C/Fe] in this star is $\gtrsim 1$ dex higher than all other dSph
stars found in the literature. From Fig. 14 it is evident that the CEMP-no
fraction in dSphs is significantly lower than in the Milky Way, reaching
fractions of $\approx 6\%$ at $\rm[Fe/H]<-2$, based on 15 CEMP-no stars, out
of 251 in total. At the lowest metallicities, $\rm[Fe/H]\leq-3.4$, none of the
7 known stars in dSph galaxies are C-enhanced, while the CEMP-no fraction in
the Milky Way at these metallicities is $>50\%$. This also implies a
discrepancy in the CEMP-fraction of dSphs and UFDs, since the latter are in
agreement with the Milky Way (e.g. Ji et al., 2020). Our findings therefore
confirm what has previously been stated with more limited data by e.g.
Starkenburg et al. (2013); Skúladóttir et al. (2015); Skúladóttir et al.
(2023b); Lucchesi et al. (2020).

Figure 14: Cumulative fraction of CEMP-no stars ([C/Fe]$\geq+0.7$) observed in
dSphs (orange solid line) with its associated 1$\sigma$ 84.13% confidence
level (Gehrels, 1986) (orange shaded area). Fraction in the MW halo (blue
solid line) is from Placco et al. (2014), while the fraction computed by Ji et
al. (2019) in UFDs is represented by the green solid line with its associated
uncertainty (green shaded area). Carbon abundances in dSphs are corrected for
internal mixing (Placco et al., 2014) and compiled from this work; Lucchesi et
al. (2020); Jablonka et al. (2015); Tafelmeyer et al. (2010); Skúladóttir et
al. (2015); Kirby et al. (2015); Venn et al. (2012); Starkenburg et al.
(2013); Susmitha et al. (2017); Hansen et al. (2018); Yoon et al. (2020);
Kirby & Cohen (2012); Skúladóttir et al. (2023b).

We see differences in the Na abundances of Fornax and Carina, where all the
four stars in the Carina dSph, are high in
$\rm[Na/Fe]_{\text{LTE}}\gtrsim+0.5$, see Fig. 8. This is puzzling, since high
Na abundances are typically found in CEMP-no stars (e.g. Norris et al., 2013),
and are predicted by their theoretical yields (e.g. Heger & Woosley, 2002),
but the Carina stars all have low $\rm[C/Fe]<0$. Furthermore, this is
typically not seen in other very metal-poor stars in dSph galaxies (Tafelmeyer
et al., 2010; Jablonka et al., 2015; Skúladóttir et al., 2023b).

Like in the Milky Way, at low $\rm[Fe/H]\lesssim-2.5$, we find a large scatter
of the neutron-capture elements in both the Carina and the Fornax dSph
galaxies. We report the discovery of a Eu-rich, r-I star in Fornax:
$\rm[Eu/Fe]=+0.8$, and $\rm[Eu/Ba]=+0.5$. This star, fnx_06_019, also shows an
outstanding enrichment in La, Nd and Dy ([X/Fe]¿+0.5). This is the first such
case for a C-normal star at such low metallicity ($\rm[Fe/H]=-2.92$) in a
classical dSph galaxy. This points to a prolific r-process event, early in the
history of the Fornax dSph galaxy, where r-process enhancements were
previously only seen at higher [Fe/H] ¿ –2 (Letarte et al., 2010; Lemasle et
al., 2014; Reichert et al., 2020, 2021).

The present analysis contributes to the limited understanding of the earliest
chemical enrichment in dSph galaxies. To further investigate the range of
abundance patterns observed in different systems, it is clear that more
observations are needed. Fortunately, the situation would improve drastically
with upcoming spectroscopic surveys, such as WEAVE (Jin et al., 2023) and
4MOST (de Jong et al., 2019), in particular the dedicated dwarf galaxy survey
4DWARFS (Skúladóttir et al., 2023a). With large and homogeneous data sets we
will be able to identify rare EMP stars, and better constrain the CEMP-no
fraction in different galaxies. Furthermore, we will get detailed spatial
information, which will allow us to trace individual events, causing r-process
enrichment. Our work serves to highlight that it is fundamental to study
metal-poor stars in galaxies of different sizes and star formation histories
to get a complete picture of the galaxy formation and first chemical
enrichment.

###### Acknowledgements.

We thank E. Tolstoy for useful comments and suggestions on the manuscript.
R.L. and Á.S have received funding from the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No. 804240). D.M. gratefully acknowledges support from the
ANID BASAL projects ACE210002 and FB210003, from Fondecyt Project No. 1220724,
and from CNPq Project 350104/2022-0.

## References

  * Alonso et al. (1999) Alonso, A., Arribas, S., & Martínez-Roger, C. 1999, A&AS, 140, 261
  * Alvarez & Plez (1998) Alvarez, R. & Plez, B. 1998, A&A, 330, 1109
  * Amarsi et al. (2016) Amarsi, A. M., Lind, K., Asplund, M., Barklem, P. S., & Collet, R. 2016, MNRAS, 463, 1518
  * Aoki et al. (2009) Aoki, W., Arimoto, N., Sadakane, K., et al. 2009, A&A, 502, 569
  * Aoki et al. (2007a) Aoki, W., Beers, T. C., Christlieb, N., et al. 2007a, ApJ, 655, 492
  * Aoki et al. (2007b) Aoki, W., Honda, S., Sadakane, K., & Arimoto, N. 2007b, PASJ, 59, L15
  * Asplund et al. (2009) Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, ARA&A, 47, 481
  * Barklem et al. (2005) Barklem, P. S., Christlieb, N., Beers, T. C., et al. 2005, A&A, 439, 129
  * Battaglia et al. (2006) Battaglia, G., Tolstoy, E., Helmi, A., et al. 2006, A&A, 459, 423
  * Battistini & Bensby (2015) Battistini, C. & Bensby, T. 2015, A&A, 577, A9
  * Beers & Christlieb (2005) Beers, T. C. & Christlieb, N. 2005, ARA&A, 43, 531
  * Bensby et al. (2014) Bensby, T., Feltzing, S., & Oey, M. S. 2014, A&A, 562, A71
  * Bergemann et al. (2019) Bergemann, M., Gallagher, A. J., Eitner, P., et al. 2019, A&A, 631, A80
  * Bettinelli et al. (2018) Bettinelli, M., Hidalgo, S. L., Cassisi, S., Aparicio, A., & Piotto, G. 2018, MNRAS, 476, 71
  * Bettinelli et al. (2019) Bettinelli, M., Hidalgo, S. L., Cassisi, S., et al. 2019, MNRAS, 487, 5862
  * Cardelli et al. (1989) Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245
  * Cayrel et al. (2004) Cayrel, R., Depagne, E., Spite, M., et al. 2004, A&A, 416, 1117
  * Cohen & Huang (2009) Cohen, J. G. & Huang, W. 2009, ApJ, 701, 1053
  * Cohen & Huang (2010) Cohen, J. G. & Huang, W. 2010, ApJ, 719, 931
  * de Boer et al. (2012) de Boer, T. J. L., Tolstoy, E., Hill, V., et al. 2012, A&A, 544, A73
  * de Boer et al. (2014) de Boer, T. J. L., Tolstoy, E., Lemasle, B., et al. 2014, A&A, 572, A10
  * de Jong et al. (2019) de Jong, R. S., Agertz, O., Berbel, A. A., et al. 2019, The Messenger, 175, 3
  * Dekker et al. (2000) Dekker, H., D’Odorico, S., Kaufer, A., Delabre, B., & Kotzlowski, H. 2000, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 4008, Proc. SPIE, ed. M. Iye & A. F. Moorwood, 534–545
  * Ezzeddine et al. (2017) Ezzeddine, R., Frebel, A., & Plez, B. 2017, ApJ, 847, 142
  * François et al. (2007) François, P., Depagne, E., Hill, V., et al. 2007, A&A, 476, 935
  * Frebel et al. (2010) Frebel, A., Kirby, E. N., & Simon, J. D. 2010, Nature, 464, 72
  * Gehrels (1986) Gehrels, N. 1986, ApJ, 303, 336
  * Gratton et al. (2000) Gratton, R. G., Sneden, C., Carretta, E., & Bragaglia, A. 2000, A&A, 354, 169
  * Gustafsson et al. (2008) Gustafsson, B., Edvardsson, B., Eriksson, K., et al. 2008, A&A, 486, 951
  * Hansen et al. (2018) Hansen, C. J., El-Souri, M., Monaco, L., et al. 2018, ApJ, 855, 83
  * Hansen et al. (2023) Hansen, T. T., Simon, J. D., Li, T. S., et al. 2023, arXiv e-prints, arXiv:2305.02316
  * Hansen et al. (2017) Hansen, T. T., Simon, J. D., Marshall, J. L., et al. 2017, The Astrophysical Journal, 838, 44
  * Heger & Woosley (2002) Heger, A. & Woosley, S. E. 2002, ApJ, 567, 532
  * Hendricks et al. (2014a) Hendricks, B., Koch, A., Lanfranchi, G. A., et al. 2014a, ApJ, 785, 102
  * Hendricks et al. (2014b) Hendricks, B., Koch, A., Walker, M., et al. 2014b, A&A, 572, A82
  * Hill et al. (2019) Hill, V., Skúladóttir, Á., Tolstoy, E., et al. 2019, A&A, 626, A15
  * Hodge (1961) Hodge, P. W. 1961, AJ, 66, 83
  * Jablonka et al. (2015) Jablonka, P., North, P., Mashonkina, L., et al. 2015, A&A, 583, A67
  * Jerkstrand (2018) Jerkstrand, A. 2018, in American Institute of Physics Conference Series, Vol. 1947, 14th International Symposium on Origin of Matter and Evolution of Galaxies (OMEG 2017), 020013
  * Ji et al. (2016) Ji, A. P., Frebel, A., Simon, J. D., & Chiti, A. 2016, ApJ, 830, 93
  * Ji et al. (2020) Ji, A. P., Li, T. S., Simon, J. D., et al. 2020, ApJ, 889, 27
  * Ji et al. (2019) Ji, A. P., Simon, J. D., Frebel, A., Venn, K. A., & Hansen, T. T. 2019, ApJ, 870, 83
  * Jin et al. (2023) Jin, S., Trager, S. C., Dalton, G. B., et al. 2023, MNRAS[arXiv:2212.03981]
  * Kirby & Cohen (2012) Kirby, E. N. & Cohen, J. G. 2012, AJ, 144, 168
  * Kirby et al. (2012) Kirby, E. N., Fu, X., Guhathakurta, P., & Deng, L. 2012, ApJ, 752, L16
  * Kirby et al. (2015) Kirby, E. N., Guo, M., Zhang, A. J., et al. 2015, ApJ, 801, 125
  * Kirby et al. (2019) Kirby, E. N., Xie, J. L., Guo, R., et al. 2019, ApJ, 881, 45
  * Koch et al. (2008) Koch, A., Grebel, E. K., Gilmore, G. F., et al. 2008, AJ, 135, 1580
  * Koch et al. (2006) Koch, A., Grebel, E. K., Wyse, R. F. G., et al. 2006, AJ, 131, 895
  * Koutsouridou et al. (2023) Koutsouridou, I., Salvadori, S., Skúladóttir, Á., et al. 2023, MNRAS, 525, 190
  * Kupka et al. (1999) Kupka, F., Piskunov, N., Ryabchikova, T. A., Stempels, H. C., & Weiss, W. W. 1999, A&AS, 138, 119
  * Kupka et al. (2000) Kupka, F. G., Ryabchikova, T. A., Piskunov, N. E., Stempels, H. C., & Weiss, W. W. 2000, Baltic Astronomy, 9, 590
  * Lemasle et al. (2014) Lemasle, B., de Boer, T. J. L., Hill, V., et al. 2014, A&A, 572, A88
  * Lemasle et al. (2012) Lemasle, B., Hill, V., Tolstoy, E., et al. 2012, A&A, 538, A100
  * Letarte et al. (2006) Letarte, B., Hill, V., Jablonka, P., et al. 2006, A&A, 453, 547
  * Letarte et al. (2010) Letarte, B., Hill, V., Tolstoy, E., et al. 2010, A&A, 523, A17
  * Lind et al. (2009) Lind, K., Primas, F., Charbonnel, C., Grundahl, F., & Asplund, M. 2009, A&A, 503, 545
  * Lucchesi et al. (2022) Lucchesi, R., Lardo, C., Jablonka, P., et al. 2022, MNRAS, 511, 1004
  * Lucchesi et al. (2020) Lucchesi, R., Lardo, C., Primas, F., et al. 2020, A&A, 644, A75
  * Magain (1984) Magain, P. 1984, A&A, 134, 189
  * Mashonkina et al. (2017a) Mashonkina, L., Jablonka, P., Pakhomov, Y., Sitnova, T., & North, P. 2017a, A&A, 604, A129
  * Mashonkina et al. (2017b) Mashonkina, L., Jablonka, P., Sitnova, T., Pakhomov, Y., & North, P. 2017b, A&A, 608, A89
  * Nissen & Schuster (2010) Nissen, P. E. & Schuster, W. J. 2010, A&A, 511, L10
  * Norris et al. (2013) Norris, J. E., Yong, D., Bessell, M. S., et al. 2013, ApJ, 762, 28
  * Norris et al. (2017) Norris, J. E., Yong, D., Venn, K. A., et al. 2017, ApJS, 230, 28
  * North et al. (2012) North, P., Cescutti, G., Jablonka, P., et al. 2012, A&A, 541, A45
  * Pace et al. (2021) Pace, A. B., Walker, M. G., Koposov, S. E., et al. 2021, arXiv.org [2105.00064v1]
  * Piskunov et al. (1995) Piskunov, N. E., Kupka, F., Ryabchikova, T. A., Weiss, W. W., & Jeffery, C. S. 1995, A&AS, 112, 525
  * Placco et al. (2014) Placco, V. M., Frebel, A., Beers, T. C., & Stancliffe, R. J. 2014, ApJ, 797, 21
  * Plez (2012) Plez, B. 2012, Turbospectrum: Code for spectral synthesis, Astrophysics Source Code Library
  * Prochaska & McWilliam (2000) Prochaska, J. X. & McWilliam, A. 2000, ApJ, 537, L57
  * Ramírez & Meléndez (2005) Ramírez, I. & Meléndez, J. 2005, ApJ, 626, 465
  * Reichert et al. (2021) Reichert, M., Hansen, C. J., & Arcones, A. 2021, ApJ, 912, 157
  * Reichert et al. (2020) Reichert, M., Hansen, C. J., Hanke, M., et al. 2020, A&A, 641, A127
  * Roederer (2013) Roederer, I. U. 2013, AJ, 145, 26
  * Ryabchikova et al. (1997) Ryabchikova, T. A., Piskunov, N. E., Kupka, F., & Weiss, W. W. 1997, Baltic Astronomy, 6, 244
  * Schatz et al. (2022) Schatz, H., Becerril Reyes, A. D., Best, A., et al. 2022, Journal of Physics G Nuclear Physics, 49, 110502
  * Shetrone et al. (2003) Shetrone, M., Venn, K. A., Tolstoy, E., et al. 2003, AJ, 125, 684
  * Shetrone et al. (2001) Shetrone, M. D., Côté, P., & Sargent, W. L. W. 2001, ApJ, 548, 592
  * Simon (2019) Simon, J. D. 2019, ARA&A, 57, 375
  * Simon et al. (2015) Simon, J. D., Jacobson, H. R., Frebel, A., et al. 2015, ApJ, 802, 93
  * Skúladóttir et al. (2023a) Skúladóttir, Á., Puls, A. A., Amarsi, A. M., et al. 2023a, The Messenger, 190, 19
  * Skúladóttir & Salvadori (2020) Skúladóttir, Á. & Salvadori, S. 2020, A&A, 634, L2
  * Skúladóttir et al. (2021) Skúladóttir, Á., Salvadori, S., Amarsi, A. M., et al. 2021, ApJ, 915, L30
  * Skúladóttir et al. (2017) Skúladóttir, Á., Tolstoy, E., Salvadori, S., Hill, V., & Pettini, M. 2017, A&A, 606, A71
  * Skúladóttir et al. (2015) Skúladóttir, Á., Tolstoy, E., Salvadori, S., et al. 2015, A&A, 574, A129
  * Skúladóttir et al. (2023b) Skúladóttir, Á., Vanni, I., Salvadori, S., & Lucchesi, R. 2023b, arXiv e-prints, arXiv:2305.02829
  * Starkenburg et al. (2013) Starkenburg, E., Hill, V., Tolstoy, E., et al. 2013, A&A, 549, A88
  * Starkenburg et al. (2010) Starkenburg, E., Hill, V., Tolstoy, E., et al. 2010, A&A, 513, A34
  * Stetson & Pancino (2008) Stetson, P. B. & Pancino, E. 2008, PASP, 120, 1332
  * Susmitha et al. (2017) Susmitha, A., Koch, A., & Sivarani, T. 2017, A&A, 606, A112
  * Tafelmeyer et al. (2010) Tafelmeyer, M., Jablonka, P., Hill, V., et al. 2010, A&A, 524, A58
  * Takeda et al. (2005) Takeda, Y., Hashimoto, O., Taguchi, H., et al. 2005, PASJ, 57, 751
  * Theler et al. (2020) Theler, R., Jablonka, P., Lucchesi, R., et al. 2020, A&A, 642, A176
  * Tolstoy et al. (2009) Tolstoy, E., Hill, V., & Tosi, M. 2009, ARA&A, 47, 371
  * Van der Swaelmen et al. (2013) Van der Swaelmen, M., Hill, V., Primas, F., & Cole, A. A. 2013, A&A, 560, A44
  * Venn et al. (2004) Venn, K. A., Irwin, M., Shetrone, M. D., et al. 2004, AJ, 128, 1177
  * Venn et al. (2012) Venn, K. A., Shetrone, M. D., Irwin, M. J., et al. 2012, ApJ, 751, 102
  * Vernet et al. (2011) Vernet, J., Dekker, H., D’Odorico, S., et al. 2011, A&A, 536, A105
  * Wanajo et al. (2014) Wanajo, S., Sekiguchi, Y., Nishimura, N., et al. 2014, ApJ, 789, L39
  * Winteler et al. (2012) Winteler, C., Käppeli, R., Perego, A., et al. 2012, ApJ, 750, L22
  * Woosley et al. (2002) Woosley, S. E., Heger, A., & Weaver, T. A. 2002, Reviews of Modern Physics, 74, 1015
  * Yong et al. (2013) Yong, D., Norris, J. E., Bessell, M. S., et al. 2013, ApJ, 762, 26
  * Yoon et al. (2020) Yoon, J., Whitten, D. D., Beers, T. C., et al. 2020, ApJ, 894, 7

##  Appendix A Additional tables

Table 7: Lines measured in the Fornax UVES spectra. Line parameters, observed
EWs, and elemental abundances are provided. EWs in brackets are given as an
estimation of the strength of the line only. They should not be used to derive
chemical abundances since most of them are blended, have large uncertainties,
or derive from a Gaussian profile; the quoted abundances are derived through
spectral synthesis for these lines.

El. | $\lambda$ | $\chi_{ex}$ | log($gf$) | EW [mÅ] | log$\epsilon$(X) | EW [mÅ] | log$\epsilon$(X)
---|---|---|---|---|---|---|---
| [Å] | [eV] |  | fnx_06_019 | fnx0579x–1
Al  I | 3961.52 | 0.01 | $-0.323$ | (162.4) | $3.56$ | – | –
Ba II | 4934.076 | 0.0 | $-0.150$ | (192.8) | $-0.39$ | ( 93.2) | $-1.35$
Ba II | 5853.668 | 0.6 | $-1.000$ | ( 70.4) | $-0.65$ | ( 35.9) | $-1.17$
Ba II | 6141.713 | 0.7 | $-0.076$ | (126.8) | $-0.45$ | ( 83.9) | $-1.23$
Ba II | 6496.897 | 0.6 | $-0.377$ | (136.7) | $-0.22$ | ( 81.5) | $-1.10$
C  I | 4325.0 | $--$ | $--$ | – | $5.05$ | – | $5.46$
Ca  I | 5581.965 | 2.52 | $-0.555$ | – | – | 25.2 $\pm$ 3.6 | $3.86$
Ca  I | 5588.749 | 2.53 | $0.358$ | – | – | 67.7 $\pm$ 6.1 | $3.73$
Ca  I | 5590.114 | 2.52 | $-0.571$ | – | – | 31.9 $\pm$ 3.8 | $4.02$
Ca  I | 5601.277 | 2.53 | $-0.523$ | – | – | 27.8 $\pm$ 4.3 | $3.89$
Ca  I | 5857.451 | 2.93 | $0.240$ | 33.6 $\pm$ 4.2 | $3.80$ | 41.0 $\pm$ 5.0 | $3.90$
Ca  I | 6102.723 | 1.88 | $-0.793$ | 55.4 $\pm$ 5.6 | $3.78$ | 71.1 $\pm$ 6.3 | $3.97$
Ca  I | 6122.217 | 1.89 | $-0.316$ | 88.3 $\pm$ 7.4 | $3.81$ | 98.8 $\pm$ 9.1 | $3.93$
Ca  I | 6162.173 | 1.9 | $-0.090$ | 105.6 $\pm$ 7.5 | $3.87$ | – | –
Ca  I | 6169.042 | 2.52 | $-0.797$ | – | – | 20.6 $\pm$ 3.9 | $3.95$
Ca  I | 6169.563 | 2.53 | $-0.478$ | 27.4 $\pm$ 3.6 | $3.84$ | 31.4 $\pm$ 3.4 | $3.87$
Ca  I | 6439.075 | 2.53 | $0.390$ | 79.3 $\pm$ 8.4 | $3.82$ | 88.5 $\pm$ 7.6 | $3.93$
Ca  I | 6717.681 | 2.71 | $-0.524$ | – | – | 21.6 $\pm$ 4.4 | $3.91$
Co  I | 4121.318 | 0.92 | $-0.320$ | 105.6 $\pm$ 6.3 | $2.12$ | (130.5) | $2.07$
Cr  I | 5296.691 | 0.98 | $-1.360$ | 36.9 $\pm$ 4.7 | $2.51$ | 48.9 $\pm$ 5.6 | $2.62$
Cr  I | 5298.271 | 0.98 | $-1.140$ | – | – | 63.6 $\pm$ 6.3 | $2.63$
Cr  I | 5345.796 | 1.0 | $-0.896$ | 56.2 $\pm$ 6.0 | $2.39$ | 72.5 $\pm$ 5.4 | $2.55$
Cr  I | 5348.314 | 1.0 | $-1.210$ | 34.4 $\pm$ 4.8 | $2.34$ | 59.6 $\pm$ 4.5 | $2.66$
Cr  I | 5409.784 | 1.03 | $-0.670$ | 64.2 $\pm$ 5.7 | $2.31$ | 90.3 $\pm$ 8.4 | $2.64$
Cu  I | 5105.537 | 1.39 | $-1.542$ | – | $<0.41$ | ( 20.7) | $0.82$
Dy II | 3944.68 | 0.0 | $0.000$ | – | $-0.74$ | – | –
Dy II | 4103.31 | 0.0 | $0.000$ | – | $-0.74$ | – | –
Dy II | 4449.7 | 0.0 | $0.000$ | – | $-0.74$ | – | –
Eu II | 4129.708 | 0.0 | $0.220$ | ( 84.6) | $-1.56$ | – | –
Eu II | 4205.042 | 0.0 | $0.210$ | (143.7) | $-1.65$ | – | –
Fe  I | 4859.741 | 2.88 | $-0.764$ | 73.9 $\pm$ 6.3 | $4.50$ | 79.6 $\pm$ 7.8 | $4.58$
Fe  I | 4871.318 | 2.87 | $-0.363$ | 100.4 $\pm$ 9.8 | $4.60$ | – | –
Fe  I | 4872.138 | 2.88 | $-0.567$ | 87.0 $\pm$ 8.3 | $4.56$ | 106.4 $\pm$ 9.9 | $4.93$
Fe  I | 4890.755 | 2.88 | $-0.394$ | 101.7 $\pm$ 8.3 | $4.66$ | 104.8 $\pm$ 9.7 | $4.71$
Fe  I | 4891.492 | 2.85 | $-0.112$ | 104.7 $\pm$ 11.2 | $4.41$ | – | –
Fe  I | 4903.31 | 2.88 | $-0.926$ | 78.8 $\pm$ 8.4 | $4.75$ | 85.1 $\pm$ 8.8 | $4.85$
Fe  I | 4924.77 | 2.28 | $-2.241$ | 53.1 $\pm$ 6.1 | $4.77$ | 67.3 $\pm$ 8.2 | $4.97$
Fe  I | 4938.814 | 2.88 | $-1.077$ | 58.4 $\pm$ 7.7 | $4.51$ | 73.9 $\pm$ 8.5 | $4.76$
Fe  I | 4966.088 | 3.33 | $-0.871$ | 45.0 $\pm$ 5.5 | $4.68$ | 58.5 $\pm$ 8.2 | $4.89$
Fe  I | 5001.863 | 3.88 | $0.010$ | 41.9 $\pm$ 4.7 | $4.47$ | 49.7 $\pm$ 5.2 | $4.58$
Fe  I | 5006.119 | 2.83 | $-0.638$ | 90.2 $\pm$ 10.5 | $4.59$ | – | –
Fe  I | 5014.942 | 3.94 | $-0.303$ | 38.9 $\pm$ 4.5 | $4.80$ | 35.8 $\pm$ 7.0 | $4.71$
Fe  I | 5044.211 | 2.85 | $-2.038$ | – | – | 32.1 $\pm$ 5.9 | $4.90$
Fe  I | 5049.82 | 2.28 | $-1.355$ | 93.8 $\pm$ 9.4 | $4.59$ | 101.9 $\pm$ 11.0 | $4.72$
Fe  I | 5068.766 | 2.94 | $-1.042$ | 46.3 $\pm$ 4.7 | $4.33$ | 73.7 $\pm$ 7.9 | $4.78$
Fe  I | 5074.748 | 4.22 | $-0.200$ | – | – | 24.7 $\pm$ 3.5 | $4.72$
Fe  I | 5079.223 | 2.2 | $-2.067$ | 73.5 $\pm$ 6.5 | $4.81$ | 86.1 $\pm$ 7.8 | $5.00$
Fe  I | 5131.468 | 2.22 | $-2.515$ | 37.2 $\pm$ 4.7 | $4.67$ | 50.7 $\pm$ 5.0 | $4.84$
Fe  I | 5141.739 | 2.42 | $-1.964$ | 38.3 $\pm$ 4.8 | $4.41$ | 48.1 $\pm$ 4.7 | $4.52$
Fe  I | 5145.094 | 2.2 | $-2.876$ | – | – | 20.7 $\pm$ 3.9 | $4.57$
Fe  I | 5162.272 | 4.18 | $0.020$ | 30.4 $\pm$ 4.0 | $4.60$ | 40.9 $\pm$ 4.5 | $4.78$
Fe  I | 5191.455 | 3.04 | $-0.551$ | 78.1 $\pm$ 8.0 | $4.52$ | 89.6 $\pm$ 8.5 | $4.71$
Fe  I | 5192.344 | 3.0 | $-0.421$ | 86.1 $\pm$ 7.9 | $4.48$ | 102.5 $\pm$ 9.0 | $4.77$
Fe  I | 5198.711 | 2.22 | $-2.135$ | 57.4 $\pm$ 6.1 | $4.62$ | 70.3 $\pm$ 5.8 | $4.78$
Fe  I | 5202.336 | 2.18 | $-1.838$ | 83.4 $\pm$ 6.7 | $4.70$ | – | –
Fe  I | 5215.18 | 3.27 | $-0.871$ | 44.0 $\pm$ 4.1 | $4.54$ | – | –
Fe  I | 5216.274 | 1.61 | $-2.150$ | 99.9 $\pm$ 11.6 | $4.50$ | – | –
Fe  I | 5217.389 | 3.21 | $-1.070$ | 33.4 $\pm$ 4.8 | $4.47$ | 56.4 $\pm$ 5.4 | $4.84$
Fe  I | 5242.491 | 3.63 | $-0.967$ | – | – | 27.8 $\pm$ 6.1 | $4.77$
Fe  I | 5266.555 | 3.0 | $-0.386$ | – | – | 101.9 $\pm$ 10.5 | $4.70$
Fe  I | 5281.79 | 3.04 | $-0.834$ | 50.8 $\pm$ 8.7 | $4.31$ | 69.0 $\pm$ 7.0 | $4.58$
Fe  I | 5283.621 | 3.24 | $-0.432$ | 69.2 $\pm$ 8.0 | $4.50$ | 87.4 $\pm$ 9.4 | $4.81$
Fe  I | 5302.3 | 3.28 | $-0.720$ | 45.9 $\pm$ 5.4 | $4.44$ | 60.3 $\pm$ 7.3 | $4.65$
Fe  I | 5307.361 | 1.61 | $-2.987$ | 65.1 $\pm$ 5.9 | $4.72$ | 77.3 $\pm$ 6.1 | $4.86$
Fe  I | 5322.041 | 2.28 | $-2.803$ | 20.3 $\pm$ 3.9 | $4.65$ | 26.1 $\pm$ 4.4 | $4.72$
Fe  I | 5324.179 | 3.21 | $-0.103$ | 87.6 $\pm$ 7.2 | $4.46$ | 97.5 $\pm$ 9.5 | $4.62$
Fe  I | 5332.899 | 1.56 | $-2.777$ | 78.8 $\pm$ 8.9 | $4.66$ | 92.5 $\pm$ 7.4 | $4.84$
Fe  I | 5339.929 | 3.27 | $-0.647$ | 53.0 $\pm$ 5.9 | $4.46$ | 70.4 $\pm$ 7.8 | $4.73$
Fe  I | 5364.871 | 4.45 | $0.228$ | – | – | 32.1 $\pm$ 3.3 | $4.73$

El. | $\lambda$ | $\chi_{ex}$ | log($gf$) | EW [mÅ] | log$\epsilon$(X) | EW [mÅ] | log$\epsilon$(X)
---|---|---|---|---|---|---|---
| [Å] | [eV] |  | fnx_06_019 | fnx0579x–1
Fe  I | 5365.399 | 3.57 | $-1.020$ | – | – | 21.9 $\pm$ 4.5 | $4.59$
Fe  I | 5367.466 | 4.41 | $0.443$ | – | – | 41.8 $\pm$ 6.1 | $4.67$
Fe  I | 5369.961 | 4.37 | $0.536$ | 37.6 $\pm$ 5.0 | $4.46$ | 43.9 $\pm$ 4.3 | $4.55$
Fe  I | 5383.369 | 4.31 | $0.645$ | 41.3 $\pm$ 4.0 | $4.35$ | 58.3 $\pm$ 7.8 | $4.63$
Fe  I | 5393.167 | 3.24 | $-0.715$ | 51.1 $\pm$ 5.3 | $4.46$ | 67.1 $\pm$ 5.8 | $4.69$
Fe  I | 5410.91 | 4.47 | $0.398$ | 27.2 $\pm$ 4.2 | $4.52$ | 33.8 $\pm$ 3.9 | $4.63$
Fe  I | 5415.199 | 4.39 | $0.642$ | 45.1 $\pm$ 5.3 | $4.51$ | 54.2 $\pm$ 5.6 | $4.65$
Fe  I | 5424.068 | 4.32 | $0.520$ | 45.1 $\pm$ 5.1 | $4.55$ | 56.0 $\pm$ 6.7 | $4.72$
Fe  I | 5445.042 | 4.39 | $-0.020$ | 20.0 $\pm$ 2.7 | $4.64$ | 30.3 $\pm$ 3.2 | $4.86$
Fe  I | 5569.618 | 3.42 | $-0.486$ | 52.9 $\pm$ 4.8 | $4.47$ | – | –
Fe  I | 5572.842 | 3.4 | $-0.275$ | 68.0 $\pm$ 7.0 | $4.49$ | 80.7 $\pm$ 7.6 | $4.68$
Fe  I | 5586.755 | 3.37 | $-0.120$ | 80.4 $\pm$ 6.9 | $4.51$ | 96.9 $\pm$ 9.5 | $4.78$
Fe  I | 5615.644 | 3.33 | $0.050$ | 101.2 $\pm$ 8.8 | $4.65$ | 106.0 $\pm$ 8.9 | $4.72$
Fe  I | 5701.544 | 2.56 | $-2.216$ | 29.0 $\pm$ 3.9 | $4.61$ | 49.3 $\pm$ 4.7 | $4.91$
Fe  I | 6065.482 | 2.61 | $-1.530$ | 67.9 $\pm$ 5.9 | $4.60$ | 84.5 $\pm$ 7.6 | $4.81$
Fe  I | 6136.615 | 2.45 | $-1.400$ | 89.7 $\pm$ 7.9 | $4.58$ | – | –
Fe  I | 6137.691 | 2.59 | $-1.403$ | 72.3 $\pm$ 7.0 | $4.50$ | 95.5 $\pm$ 8.6 | $4.82$
Fe  I | 6151.617 | 2.18 | $-3.299$ | – | – | 20.7 $\pm$ 3.5 | $4.87$
Fe  I | 6173.334 | 2.22 | $-2.880$ | 21.8 $\pm$ 2.1 | $4.62$ | 32.1 $\pm$ 4.0 | $4.76$
Fe  I | 6191.558 | 2.43 | $-1.417$ | 84.1 $\pm$ 6.8 | $4.47$ | 98.8 $\pm$ 9.0 | $4.66$
Fe  I | 6200.312 | 2.61 | $-2.437$ | – | – | 26.7 $\pm$ 3.7 | $4.74$
Fe  I | 6213.429 | 2.22 | $-2.482$ | 43.5 $\pm$ 5.2 | $4.62$ | 56.0 $\pm$ 5.6 | $4.75$
Fe  I | 6219.28 | 2.2 | $-2.433$ | 52.0 $\pm$ 4.9 | $4.67$ | 70.2 $\pm$ 6.5 | $4.88$
Fe  I | 6230.722 | 2.56 | $-1.281$ | 98.2 $\pm$ 7.6 | $4.73$ | – | –
Fe  I | 6240.646 | 2.22 | $-3.233$ | – | – | 25.3 $\pm$ 3.9 | $4.97$
Fe  I | 6246.318 | 3.6 | $-0.733$ | 31.3 $\pm$ 3.7 | $4.53$ | 46.2 $\pm$ 5.3 | $4.75$
Fe  I | 6252.555 | 2.4 | $-1.687$ | 77.1 $\pm$ 6.2 | $4.58$ | 91.0 $\pm$ 9.3 | $4.75$
Fe  I | 6265.132 | 2.18 | $-2.550$ | 43.1 $\pm$ 4.7 | $4.62$ | 62.3 $\pm$ 5.5 | $4.84$
Fe  I | 6297.792 | 2.22 | $-2.740$ | – | – | 49.4 $\pm$ 8.6 | $4.90$
Fe  I | 6301.5 | 3.65 | $-0.718$ | – | – | 59.5 $\pm$ 7.4 | $5.01$
Fe  I | 6302.494 | 3.69 | $-0.973$ | – | – | 22.1 $\pm$ 2.2 | $4.63$
Fe  I | 6322.685 | 2.59 | $-2.426$ | 26.7 $\pm$ 3.3 | $4.76$ | 37.8 $\pm$ 4.9 | $4.90$
Fe  I | 6335.33 | 2.2 | $-2.177$ | 66.0 $\pm$ 6.7 | $4.61$ | 83.0 $\pm$ 7.0 | $4.80$
Fe  I | 6344.148 | 2.43 | $-2.923$ | – | – | 23.0 $\pm$ 3.2 | $4.89$
Fe  I | 6355.028 | 2.85 | $-2.350$ | – | – | 22.1 $\pm$ 3.7 | $4.86$
Fe  I | 6393.601 | 2.43 | $-1.432$ | 84.5 $\pm$ 6.2 | $4.46$ | 100.0 $\pm$ 9.5 | $4.65$
Fe  I | 6400.0 | 3.6 | $-0.290$ | 53.7 $\pm$ 10.8 | $4.46$ | 73.6 $\pm$ 13.8 | $4.73$
Fe  I | 6408.018 | 3.69 | $-1.018$ | – | – | 28.1 $\pm$ 3.7 | $4.80$
Fe  I | 6411.648 | 3.65 | $-0.595$ | 32.7 $\pm$ 3.6 | $4.47$ | 48.8 $\pm$ 6.1 | $4.71$
Fe  I | 6421.35 | 2.28 | $-2.027$ | 75.6 $\pm$ 6.8 | $4.70$ | 95.9 $\pm$ 7.5 | $4.96$
Fe  I | 6430.845 | 2.18 | $-2.006$ | 90.5 $\pm$ 6.7 | $4.75$ | 104.1 $\pm$ 7.7 | $4.90$
Fe  I | 6592.913 | 2.73 | $-1.473$ | 62.2 $\pm$ 5.2 | $4.56$ | 79.9 $\pm$ 7.0 | $4.77$
Fe  I | 6593.87 | 2.43 | $-2.422$ | 33.1 $\pm$ 3.7 | $4.64$ | 45.3 $\pm$ 4.2 | $4.78$
Fe  I | 6609.11 | 2.56 | $-2.692$ | – | – | 23.4 $\pm$ 2.4 | $4.82$
Fe  I | 6677.985 | 2.69 | $-1.418$ | 80.3 $\pm$ 6.5 | $4.71$ | 104.0 $\pm$ 9.9 | $5.03$
Fe  I | 6750.151 | 2.42 | $-2.621$ | 28.6 $\pm$ 3.7 | $4.73$ | 44.4 $\pm$ 5.1 | $4.94$
Fe II | 5197.567 | 3.23 | $-2.100$ | 45.5 $\pm$ 4.9 | $4.68$ | 53.5 $\pm$ 7.8 | $4.88$
Fe II | 5234.623 | 3.22 | $-2.230$ | – | – | 54.6 $\pm$ 7.8 | $5.02$
Fe II | 5284.103 | 2.89 | $-2.990$ | 23.3 $\pm$ 4.0 | $4.66$ | 31.0 $\pm$ 5.6 | $4.86$
Fe II | 6516.077 | 2.89 | $-3.320$ | – | – | 28.5 $\pm$ 4.4 | $5.06$
La II | 4920.98 | 0.13 | $-0.580$ | ( 37.6) | $-1.28$ | – | –
La II | 3995.75 | 0.0 | $0.000$ | – | $-1.28$ | – | –
La II | 4077.34 | 0.0 | $0.000$ | – | $-1.28$ | – | –
La II | 4123.23 | 0.0 | $0.000$ | – | $-1.28$ | – | –
Mg  I | 5172.684 | 2.71 | $-0.450$ | (235.1) | $5.17$ | (134.2) | $5.17$
Mg  I | 5183.604 | 2.72 | $-0.239$ | (180.3) | $5.27$ | (163.9) | $5.20$
Mg  I | 5528.405 | 4.35 | $-0.498$ | 90.4 $\pm$ 9.3 | $5.26$ | ( 55.9) | $5.25$
Mn  I | 4030.75 | 0.0 | $-0.494$ | (162.2) | $2.06$ | – | –
Mn  I | 4033.06 | 0.0 | $-0.644$ | (171.8) | $2.10$ | (191.7) | $2.27$
Mn  I | 4034.48 | 0.0 | $-0.842$ | (125.0) | $2.10$ | (103.0) | $2.27$
Mn  I | 4823.52 | 2.32 | $0.121$ | – | – | 45.3 $\pm$ 5.9 | $2.17$
Na  I | 5889.951 | 0.0 | $0.108$ | (208.8) | $3.52$ | (207.0) | $3.48$
Na  I | 5895.924 | 0.0 | $-0.194$ | (186.0) | $3.57$ | (186.3) | $3.53$
Nd II | 4825.48 | 0.18 | $-0.420$ | ( 41.4) | $-0.89$ | – | –
Nd II | 5319.81 | 0.55 | $-0.140$ | ( 28.4) | $-0.89$ | – | –
Nd II | 4061.08 | 0.0 | $0.000$ | – | $-0.89$ | – | –
Ni  I | 5081.11 | 3.85 | $0.300$ | – | – | 20.9 $\pm$ 4.2 | $3.39$
Ni  I | 5476.904 | 1.83 | $-0.780$ | 101.0 $\pm$ 7.6 | $3.20$ | 107.0 $\pm$ 10.1 | $3.29$
Ni  I | 6643.63 | 1.68 | $-2.220$ | 40.2 $\pm$ 5.0 | $3.29$ | 48.7 $\pm$ 5.7 | $3.36$
Ni  I | 6767.772 | 1.83 | $-2.140$ | 39.8 $\pm$ 3.8 | $3.40$ | 44.2 $\pm$ 4.4 | $3.41$
O  I | 6300.304 | 0.0 | $-9.750$ | ( 31.0) | $6.67$ | ( 31.0) | $6.99$
Pr II | 4222.934 | 0.05 | $0.271$ | 60.6 $\pm$ 7.3 | $-1.14$ | – | –
Sc II | 4246.822 | 0.31 | $0.242$ | – | – | (167.7) | $0.73$
Sc II | 4400.389 | 0.61 | $-0.536$ | ( 94.5) | $0.46$ | – | –
Sc II | 4415.557 | 0.6 | $-0.668$ | ( 88.4) | $0.35$ | (104.4) | $0.90$
Sc II | 5031.021 | 1.36 | $-0.400$ | ( 49.6) | $0.30$ | ( 51.4) | $0.35$
Sc II | 5526.79 | 1.77 | $0.024$ | ( 49.4) | $0.39$ | ( 58.6) | $0.57$
Sc II | 5657.896 | 1.51 | $-0.603$ | ( 42.9) | $0.51$ | ( 51.7) | $0.67$
Sc II | 6604.601 | 1.36 | $-1.309$ | ( 17.4) | $0.40$ | – | –
Si  I | 4102.936 | 1.91 | $-3.140$ | (122.7) | $5.16$ | ( 78.8) | $4.76$
Sm II | 4424.34 | 0.49 | $0.140$ | 42.5 $\pm$ 6.8 | $-1.12$ | – | –

Table 8: continued.

El. | $\lambda$ | $\chi_{ex}$ | log($gf$) | EW [mÅ] | log$\epsilon$(X) | EW [mÅ] | log$\epsilon$(X)
---|---|---|---|---|---|---|---
| [Å] | [eV] |  | fnx_06_019 | fnx0579x–1
Sr II | 4215.519 | 0.0 | $-0.145$ | (170.7) | $-0.67$ | (126.4) | $-0.52$
Ti  I | 4840.874 | 0.9 | $-0.430$ | – | – | 30.4 $\pm$ 4.7 | $2.09$
Ti  I | 4981.73 | 0.85 | $0.570$ | 85.8 $\pm$ 8.2 | $2.01$ | 93.8 $\pm$ 9.1 | $2.06$
Ti  I | 4991.066 | 0.84 | $0.450$ | 82.1 $\pm$ 9.6 | $2.05$ | 80.0 $\pm$ 10.1 | $1.92$
Ti  I | 4999.503 | 0.83 | $0.320$ | 68.9 $\pm$ 7.6 | $1.95$ | 72.0 $\pm$ 7.9 | $1.90$
Ti  I | 5016.161 | 0.85 | $-0.480$ | 25.3 $\pm$ 3.9 | $2.04$ | – | –
Ti  I | 5039.958 | 0.02 | $-1.080$ | 54.5 $\pm$ 4.8 | $1.94$ | 64.6 $\pm$ 7.0 | $1.95$
Ti  I | 5064.653 | 0.05 | $-0.940$ | 61.5 $\pm$ 6.5 | $1.94$ | 79.9 $\pm$ 8.2 | $2.07$
Ti  I | 5173.743 | 0.0 | $-1.060$ | 64.8 $\pm$ 5.9 | $2.01$ | 69.9 $\pm$ 8.1 | $1.94$
Ti  I | 5192.969 | 0.02 | $-0.950$ | 71.3 $\pm$ 6.3 | $2.02$ | 79.0 $\pm$ 10.0 | $1.99$
Ti  I | 5210.384 | 0.05 | $-0.820$ | 67.8 $\pm$ 6.5 | $1.88$ | 72.7 $\pm$ 11.4 | $1.81$
Ti II | 4798.531 | 1.08 | $-2.660$ | 43.6 $\pm$ 7.3 | $2.49$ | – | –
Ti II | 5129.156 | 1.89 | $-1.340$ | 53.4 $\pm$ 6.3 | $2.39$ | 64.4 $\pm$ 7.2 | $2.63$
Ti II | 5154.068 | 1.57 | $-1.750$ | 61.5 $\pm$ 7.0 | $2.50$ | 62.2 $\pm$ 6.3 | $2.55$
Ti II | 5185.902 | 1.89 | $-1.410$ | 49.2 $\pm$ 4.4 | $2.38$ | 54.7 $\pm$ 6.1 | $2.51$
Ti II | 5188.687 | 1.58 | $-1.050$ | – | – | 109.4 $\pm$ 12.8 | $2.81$
Ti II | 5226.539 | 1.57 | $-1.260$ | 94.0 $\pm$ 7.9 | $2.61$ | 93.6 $\pm$ 8.2 | $2.66$
Ti II | 5336.786 | 1.58 | $-1.600$ | – | – | 63.7 $\pm$ 10.6 | $2.42$
Ti II | 5381.021 | 1.57 | $-1.970$ | 53.2 $\pm$ 6.2 | $2.55$ | 45.1 $\pm$ 6.5 | $2.43$
Ti II | 5418.768 | 1.58 | $-2.130$ | 34.5 $\pm$ 5.2 | $2.40$ | 39.8 $\pm$ 4.5 | $2.52$
Y II | 4883.682 | 1.08 | $0.070$ | ( 36.5) | $-0.92$ | ( 23.1) | $-1.18$
Y II | 4900.119 | 1.03 | $-0.090$ | ( 38.0) | $-0.78$ | – | –
Y II | 5087.419 | 1.08 | $-0.170$ | ( 26.2) | $-0.92$ | ( 27.0) | $-0.89$
Y II | 5200.41 | 0.99 | $-0.570$ | ( 18.0) | $-0.86$ | – | –
Y II | 5205.722 | 1.03 | $-0.340$ | ( 31.0) | $-0.80$ | – | –
Zn  I | 4810.528 | 4.08 | $-0.137$ | ( 24.4) | $1.93$ | – | $<1.91$
Zr II | 4161.2 | 0.71 | $-0.590$ | ( 42.9) | $-0.12$ | – | –

Table 9: Computed NLTE corrections for Na.

ID | fnx_06_019 | fnx0579x-1 | car1_t174 | car1_t194 | car1_t200 | LG04c_0008
---|---|---|---|---|---|---
| 5889.951 Å
log$\epsilon$(Na)LTE | 3.52 | 3.48 | 3.80 | 4.16 | 4.52 | 3.78
log$\epsilon$(Na)NLTE | 3.37 | 3.36 | 3.42 | 3.96 | 4.25 | 3.43
$\Delta$(NLTE-LTE) | $-0.15$ | $-0.12$ | $-0.38$ | $-0.20$ | $-0.27$ | $-0.35$
$[Na/Fe]_{NLTE}$ | $+0.04$ | $-0.16$ | $+0.18$ | $+0.26$ | $+0.95$ | $+0.23$
| 5895.924 Å
log$\epsilon$(Na)LTE | 3.57 | 3.53 | $--$ | 4.09 | 4.35 | 4.00
log$\epsilon$(Na)NLTE | 3.38 | 3.37 | $--$ | 3.79 | 3.95 | 3.61
$\Delta$(NLTE-LTE) | $-0.19$ | $-0.16$ | $--$ | $-0.30$ | $-0.40$ | $-0.39$
$[Na/Fe]_{NLTE}$ | $+0.05$ | $-0.15$ | $--$ | $+0.09$ | $+0.65$ | $+0.41$

Table 10: Lines measured in the Carina XSHOOTER spectra. Line parameters,
observed EWs, and elemental abundances are provided. EWs in brackets are given
as indication only; the quoted abundances are derived through spectral
synthesis for these lines.

El. | $\lambda$ | $\chi_{ex}$ | log($gf$) | EW [mÅ] | log$\epsilon$(X) | EW [mÅ] | log$\epsilon$(X) | EW [mÅ] | log$\epsilon$(X) | EW [mÅ] | log$\epsilon$(X)
---|---|---|---|---|---|---|---|---|---|---|---
| [Å] | [eV] |  | car1_t174 | car1_t194 | car1_t200 | LG04c_0008
Ba II | 4554.029 | 0.0 | $0.170$ | ( 79.2) | $-1.73$ | (165.8) | $0.14$ | (139.2) | $-0.32$ | ( 84.7) | $-1.80$
Ba II | 4934.076 | 0.0 | $-0.150$ | ( 38.4) | $-2.25$ | (164.7) | $-0.08$ | (115.0) | $-0.87$ | ( 51.9) | $-2.23$
C  I | 4300.0 | – | – | – | $4.59$ | – | $4.90$ | – | $5.06$ | – | $4.22$
Ca  I | 4226.728 | 0.0 | $0.244$ | 239.1 $\pm$ 13.6 | $3.64$ | – | – | – | – | – | –
Ca  I | 6122.217 | 1.89 | $-0.316$ | – | – | 78.9 $\pm$ 15.2 | $3.96$ | – | – | – | –
Ca  I | 6439.075 | 2.53 | $0.390$ | – | – | 92.4 $\pm$ 16.5 | $4.30$ | – | – | 48.1 $\pm$ 8.5 | $3.55$
Co  I | 4118.773 | 1.05 | $-0.490$ | – | – | – | – | – | – | (102.1) | $1.81$
Co  I | 4121.318 | 0.92 | $-0.320$ | – | – | – | – | – | – | (107.7) | $1.75$
Cr  I | 5206 | 0.94 | $0.020$ | – | $2.07$ | – | $2.85$ | – | $2.41$ | – | $1.83$
Fe  I | 4202.029 | 1.49 | $-0.708$ | – | – | – | – | 120.2 $\pm$ 11.6 | $4.70$ | – | –
Fe  I | 4337.045 | 1.56 | $-1.695$ | – | – | – | – | – | – | 96.8 $\pm$ 7.5 | $4.74$
Fe  I | 4352.735 | 2.22 | $-1.287$ | – | – | – | – | – | – | 66.7 $\pm$ 11.5 | $4.49$
Fe  I | 4430.614 | 2.22 | $-1.659$ | – | – | – | – | – | – | 47.0 $\pm$ 13.3 | $4.44$
Fe  I | 4442.339 | 2.2 | $-1.255$ | – | – | – | – | – | – | 84.2 $\pm$ 13.1 | $4.76$
Fe  I | 4459.117 | 2.18 | $-1.279$ | – | – | – | – | – | – | 76.8 $\pm$ 15.2 | $4.59$
Fe  I | 4602.941 | 1.49 | $-2.209$ | – | – | – | – | – | – | 72.2 $\pm$ 9.7 | $4.52$
Fe  I | 4733.591 | 1.49 | $-2.988$ | – | – | – | – | – | – | 40.0 $\pm$ 7.7 | $4.67$
Fe  I | 4871.318 | 2.87 | $-0.363$ | – | – | – | – | 75.0 $\pm$ 13.2 | $4.69$ | 78.6 $\pm$ 11.9 | $4.50$
Fe  I | 4872.138 | 2.88 | $-0.567$ | – | – | – | – | – | – | 55.3 $\pm$ 11.8 | $4.28$
Fe  I | 4890.755 | 2.88 | $-0.394$ | – | – | 93.2 $\pm$ 7.1 | $4.83$ | 69.3 $\pm$ 9.6 | $4.61$ | – | –
Fe  I | 4891.492 | 2.85 | $-0.112$ | – | – | 110.0 $\pm$ 7.4 | $4.85$ | 75.7 $\pm$ 8.9 | $4.43$ | 94.4 $\pm$ 18.8 | $4.56$
Fe  I | 4903.31 | 2.88 | $-0.926$ | – | – | 68.3 $\pm$ 7.4 | $4.87$ | – | – | 51.2 $\pm$ 8.2 | $4.56$
Fe  I | 4918.994 | 2.87 | $-0.342$ | – | – | 114.4 $\pm$ 3.6 | $5.17$ | 70.4 $\pm$ 11.0 | $4.57$ | – | –
Fe  I | 4920.502 | 2.83 | $0.068$ | – | – | – | – | – | – | 98.1 $\pm$ 10.9 | $4.43$
Fe  I | 4938.814 | 2.88 | $-1.077$ | – | – | – | – | 39.0 $\pm$ 6.2 | $4.71$ | – | –
Fe  I | 5006.119 | 2.83 | $-0.638$ | – | – | – | – | 51.0 $\pm$ 12.6 | $4.44$ | 71.3 $\pm$ 14.8 | $4.57$
Fe  I | 5049.82 | 2.28 | $-1.355$ | 55.2 $\pm$ 5.9 | $4.41$ | 96.9 $\pm$ 7.6 | $5.10$ | – | – | 62.7 $\pm$ 17.9 | $4.42$
Fe  I | 5110.413 | 0.0 | $-3.760$ | – | – | – | – | 81.4 $\pm$ 11.1 | $4.73$ | – | –
Fe  I | 5171.596 | 1.49 | $-1.793$ | – | – | – | – | – | – | 98.6 $\pm$ 12.8 | $4.53$
Fe  I | 5191.455 | 3.04 | $-0.551$ | 62.5 $\pm$ 8.6 | $4.64$ | – | – | – | – | – | –
Fe  I | 5192.344 | 3.0 | $-0.421$ | 65.2 $\pm$ 13.9 | $4.51$ | – | – | – | – | 61.3 $\pm$ 9.9 | $4.35$
Fe  I | 5194.941 | 1.56 | $-2.090$ | 71.3 $\pm$ 11.8 | $4.52$ | – | – | 75.4 $\pm$ 13.4 | $4.83$ | 70.1 $\pm$ 15.1 | $4.35$
Fe  I | 5202.336 | 2.18 | $-1.838$ | – | – | 89.2 $\pm$ 5.0 | $5.26$ | – | – | 54.3 $\pm$ 9.9 | $4.60$
Fe  I | 5216.274 | 1.61 | $-2.150$ | – | – | 80.9 $\pm$ 5.4 | $4.68$ | – | – | 55.6 $\pm$ 8.2 | $4.21$
Fe  I | 5217.389 | 3.21 | $-1.070$ | – | – | 40.2 $\pm$ 7.2 | $4.88$ | – | – | – | –
Fe  I | 5232.94 | 2.94 | $-0.058$ | – | – | 103.2 $\pm$ 6.1 | $4.70$ | – | – | – | –
Fe  I | 5266.555 | 3.0 | $-0.386$ | – | – | 86.3 $\pm$ 4.2 | $4.76$ | 56.0 $\pm$ 10.3 | $4.45$ | – | –
Fe  I | 5281.79 | 3.04 | $-0.834$ | – | – | 68.8 $\pm$ 6.7 | $4.93$ | – | – | 37.3 $\pm$ 8.1 | $4.37$
Fe  I | 5283.621 | 3.24 | $-0.432$ | – | – | 71.4 $\pm$ 4.6 | $4.83$ | – | – | 44.2 $\pm$ 9.2 | $4.35$
Fe  I | 5302.3 | 3.28 | $-0.720$ | – | – | 49.6 $\pm$ 4.2 | $4.78$ | – | – | – | –
Fe  I | 5324.179 | 3.21 | $-0.103$ | 53.5 $\pm$ 9.6 | $4.24$ | – | – | 59.3 $\pm$ 11.8 | $4.48$ | 61.8 $\pm$ 5.9 | $4.29$
Fe  I | 5332.899 | 1.56 | $-2.777$ | – | – | 67.5 $\pm$ 4.8 | $4.97$ | – | – | 35.6 $\pm$ 7.0 | $4.41$
Fe  I | 5339.929 | 3.27 | $-0.647$ | – | – | 54.6 $\pm$ 3.9 | $4.77$ | – | – | – | –
Fe  I | 5369.961 | 4.37 | $0.536$ | – | – | 43.9 $\pm$ 5.2 | $4.76$ | – | – | – | –
Fe  I | 5371.489 | 0.96 | $-1.645$ | 126.3 $\pm$ 4.7 | $4.41$ | – | – | 114.8 $\pm$ 10.5 | $4.54$ | – | –
Fe  I | 5383.369 | 4.31 | $0.645$ | – | – | 68.4 $\pm$ 6.9 | $5.02$ | – | – | – | –
Fe  I | 5393.167 | 3.24 | $-0.715$ | – | – | 48.4 $\pm$ 6.7 | $4.69$ | – | – | – | –
Fe  I | 5410.91 | 4.47 | $0.398$ | – | – | 50.6 $\pm$ 4.1 | $5.14$ | – | – | – | –
Fe  I | 5415.199 | 4.39 | $0.642$ | – | – | 65.6 $\pm$ 9.3 | $5.06$ | – | – | – | –
Fe  I | 5424.068 | 4.32 | $0.520$ | – | – | 59.2 $\pm$ 4.4 | $4.99$ | – | – | 38.0 $\pm$ 6.5 | $4.61$
Fe  I | 5434.523 | 1.01 | $-2.122$ | 112.7 $\pm$ 7.0 | $4.66$ | – | – | – | – | – | –
Fe  I | 6065.482 | 2.61 | $-1.530$ | – | – | 69.0 $\pm$ 12.6 | $5.01$ | – | – | 34.3 $\pm$ 10.1 | $4.41$
Fe  I | 6136.615 | 2.45 | $-1.400$ | 42.7 $\pm$ 7.9 | $4.37$ | – | – | – | – | 69.5 $\pm$ 6.4 | $4.68$
Fe  I | 6137.691 | 2.59 | $-1.403$ | – | – | – | – | – | – | 57.1 $\pm$ 8.4 | $4.64$
Fe  I | 6191.558 | 2.43 | $-1.417$ | 72.0 $\pm$ 6.8 | $4.83$ | – | – | – | – | 62.7 $\pm$ 12.3 | $4.55$
Fe  I | 6230.722 | 2.56 | $-1.281$ | 51.7 $\pm$ 6.8 | $4.52$ | – | – | – | – | 58.2 $\pm$ 10.4 | $4.50$
Fe  I | 6252.555 | 2.4 | $-1.687$ | – | – | 76.9 $\pm$ 15.0 | $5.02$ | – | – | 42.8 $\pm$ 10.2 | $4.45$
Fe  I | 6393.601 | 2.43 | $-1.432$ | – | – | – | – | – | – | 50.1 $\pm$ 11.5 | $4.34$
Fe  I | 6400.0 | 3.6 | $-0.290$ | – | – | – | – | – | – | 31.5 $\pm$ 3.9 | $4.34$
Fe  I | 6421.35 | 2.28 | $-2.027$ | – | – | 63.7 $\pm$ 10.7 | $4.96$ | – | – | – | –
Fe  I | 6430.845 | 2.18 | $-2.006$ | – | – | – | – | – | – | 48.0 $\pm$ 12.7 | $4.55$
Fe  I | 6494.98 | 2.4 | $-1.273$ | – | – | – | – | – | – | 62.3 $\pm$ 11.2 | $4.33$
Fe  I | 6677.985 | 2.69 | $-1.418$ | – | – | – | – | – | – | 41.5 $\pm$ 8.0 | $4.49$
Fe II | 4522.627 | 2.84 | $-2.030$ | – | – | – | – | – | – | 45.2 $\pm$ 12.2 | $4.26$
Fe II | 4583.829 | 2.81 | $-1.860$ | – | – | – | – | – | – | 78.6 $\pm$ 13.3 | $4.72$
Fe II | 4923.921 | 2.89 | $-1.320$ | ( 88.1) | $4.53$ | 109.4 $\pm$ 6.7 | $5.06$ | – | – | 97.7 $\pm$ 6.9 | $4.62$
Fe II | 5018.436 | 2.89 | $-1.220$ | (104.9) | $4.76$ | – | – | – | – | 108.2 $\pm$ 13.6 | $4.72$
Fe II | 5197.567 | 3.23 | $-2.100$ | – | – | – | – | – | – | 56.6 $\pm$ 17.0 | $4.96$
Fe II | 5234.623 | 3.22 | $-2.230$ | – | – | 52.6 $\pm$ 10.1 | $5.17$ | – | – | – | –
Fe II | 5275.997 | 3.2 | $-1.940$ | – | – | – | – | – | – | 32.2 $\pm$ 8.1 | $4.30$
Mg  I | 5172.684 | 2.71 | $-0.450$ | (162.6) | $4.88$ | (209.5) | $5.36$ | (132.0) | $4.92$ | (151.8) | $4.80$
Mg  I | 5183.604 | 2.72 | $-0.239$ | (173.6) | $5.07$ | (158.6) | $5.16$ | (181.3) | $5.25$ | (174.3) | $5.02$
Mn  I | 4030 | 0.0 | $-0.494$ | – | $1.55$ | – | – | – | $2.16$ | – | $1.90$
Na  I | 5889.951 | 0.0 | $0.108$ | (132.4) | $3.80$ | (226.7) | $4.16$ | (224.7) | $4.52$ | (193.5) | $3.78$
Na  I | 5895.924 | 0.0 | $-0.194$ | – | – | (174.9) | $4.09$ | (169.7) | $4.35$ | (183.4) | $4.00$
Ni  I | 5476.904 | 1.83 | $-0.780$ | – | – | 96.9 $\pm$ 7.5 | $3.61$ | – | – | 74.8 $\pm$ 7.4 | $3.17$
Sr II | 4077.709 | 0.0 | $0.167$ | – | – | (240.9) | $0.33$ | (124.7) | $-0.53$ | (143.1) | $-1.06$
Ti  I | 4681.909 | 0.05 | $-1.030$ | – | – | ( 60.1) | $2.68$ | – | – | – | –
Ti  I | 4999.503 | 0.83 | $0.320$ | – | – | ( 74.1) | $2.64$ | – | – | – | –
Ti  I | 5064.653 | 0.05 | $-0.940$ | – | – | ( 75.5) | $2.57$ | – | – | – | –
Ti II | 4468.493 | 1.13 | $-0.630$ | – | – | 143.9 $\pm$ 14.2 | $3.05$ | 110.1 $\pm$ 22.7 | $2.52$ | 122.8 $\pm$ 11.3 | $2.45$
Ti II | 4563.757 | 1.22 | $-0.690$ | 96.3 $\pm$ 8.0 | $2.08$ | 119.1 $\pm$ 13.3 | $2.71$ | 102.3 $\pm$ 19.7 | $2.46$ | 100.0 $\pm$ 9.4 | $2.08$
Ti II | 5336.786 | 1.58 | $-1.600$ | – | – | 54.0 $\pm$ 3.3 | $2.59$ | – | – | – | –

##  Appendix B Measured lines of r-process elements

Figure 15: Individual lines of heavy (Z¿56) neutron-capture elements measured
in the r-process rich star, fnx_06_019. From top to bottom: La II, Nd II, Eu
II, and Dy II. The best fit synthetic spectra used for the abundance
determination are shown in green, while synthetic spectra in blue are computed
only to check agreement with other detected lines of lesser quality. In orange
the synthetic spectra are computed without the element of interest, allowing
the identification of blends.