11institutetext: Instituto de Ciencias Astronómicas, de la Tierra y del
Espacio (ICATE-CONICET), C.C 467, 5400, San Juan, Argentina. 11email:
<EMAIL_ADDRESS>22institutetext: Universidad Nacional de San Juan
(UNSJ), Facultad de Ciencias Exactas, Físicas y Naturales (FCEFN), San Juan,
Argentina. 33institutetext: Observatorio Astronómico de Córdoba (OAC), Laprida
854, X5000BGR, Córdoba, Argentina. 44institutetext: Instituto de Investigación
Multidisciplinar en Ciencia y Tecnología, Universidad de La Serena, Raúl
Bitrán 1305, La Serena, Chile 55institutetext: Departamento de Física y
Astronomía, Universidad de La Serena, Av. Cisternas 1200 N, La Serena, Chile.
66institutetext: Consejo Nacional de Investigaciones Científicas y Técnicas
(CONICET), Argentina

# Chemical analysis of early-type stars with planets

C. Saffe 112266 P. Miquelarena 112266 J. Alacoria 1166 M. Flores 112266 M.
Jaque Arancibia 4455 D. Calvo 22 G. Martín Girardi 22 M. Grosso 112266 A.
Collado 112266

(Received xxx, xxx ; accepted xxxx, xxxx)

###### Abstract

Aims. To explore the chemical pattern of early-type stars with planets,
searching for a possible signature of planet formation. In particular, we
study a likely relation between the $\lambda$ Boötis chemical pattern and the
presence of giant planets.

Methods. We performed a detailed abundance determination in a sample of early-
type stars with and without planets via spectral synthesis. Fundamental
parameters were initially estimated using Strömgren photometry or literature
values and then refined by requiring excitation and ionization balances of Fe
lines. We derived chemical abundances for 23 different species by fitting
observed spectra with an iterative process. Synthetic spectra were calculated
using the program SYNTHE together with local thermodynamic equilibrium (LTE)
ATLAS12 model atmospheres. We used specific opacities calculated for each
star, depending on the individual composition and microturbulence velocity
vmicro through the opacity sampling (OS) method. The complete chemical pattern
of the stars were then compared to those of $\lambda$ Boötis stars and other
chemically peculiar stars.

Results.  We compared the chemical pattern of the stars in our sample (13
stars with planets and 24 stars without detected planets) with those of
$\lambda$ Boötis and other chemically peculiar stars. We have found four
$\lambda$ Boötis stars in our sample, two of which present planets and
circumstellar disks (HR 8799 and HD 169142) and one without planets detected
(HD 110058). We have also identified the first $\lambda$ Boötis star orbited
by a brown dwarf ($\zeta$ Del). This interesting pair $\lambda$ Boötis star +
brown dwarf could help to test stellar formation scenarios. We found no unique
chemical pattern for the group of early-type stars bearing giant planets.
However, our results support, in principle, a suggested scenario in which
giant planets orbiting pre-main-sequence stars possibly block the dust of the
disk and result in a $\lambda$ Boötis-like pattern. On the other hand, we do
not find a $\lambda$ Boötis pattern in different hot-Jupiter planet host
stars, which do not support the idea of possible accretion from the winds of
hot-Jupiters, recently proposed in the literature. Then, other mechanisms
should account for the presence of the $\lambda$ Boötis pattern between main-
sequence stars. Finally, we suggest that the formation of planets around
$\lambda$ Boötis stars such as HR 8799 and HD 169142 is also possible through
the core accretion process and not only gravitational instability.

###### Key Words.:

Stars: early-type – Stars: abundances – Stars: planetary systems – Stars:
individual: $\beta$ Pictoris, Fomalhaut, HR 8799, HD 95086, HD 169142,
HAT-P-49, KELT-9, KELT-17, KELT-20, $\lambda$ Boötis, MASCARA-1, Vega,
WASP-33, WASP-167, WASP-189

##  1 Introduction

The $\lambda$ Boötis stars are a group of chemically peculiar objects on the
upper main-sequence, showing underabundances ($\sim$1-2 dex) of iron-peak
elements and near-solar abundances of C , N , O and S (e.g. Kamp et al., 2001;
Heiter, 2002; Andrievsky et al., 2002). The class was discovered by Morgan et
al. (1943) and named following the bright prototype $\lambda$ Boötis, which is
one extreme member of the class. This group of refractory-poor objects
comprises about 2$\%$ of early B through early F stars (Gray & Corbally, 1998;
Paunzen, 2001). However, among the pre-main-sequence Herbig Ae/Be stars, the
progenitors of A-type stars, the $\lambda$ Boötis-like fraction is about 33%
(Folsom et al., 2012). The origin of the peculiarity still remains a puzzle,
as we can read in the recent discussion of Murphy & Paunzen (2017). Unlike
common chemical peculiarities seen in Am and Ap stars, $\lambda$ Boötis stars
are not constrained to slow rotation (Abt & Morrell, 1995; Murphy et al.,
2015). Cowley et al. (1982) first suggested that $\lambda$ Boötis could
possibly originate from the interstellar medium (ISM) with non-solar
composition, or from the separation of grains and gas. Then, Venn & Lambert
(1990) proposed that $\lambda$ Boötis stars likely occur when circumstellar
gas is separated from grains and then accreted to the stars, due to the
similarity of its abundance pattern with the ISM. Other proposed mechanisms
include the interaction of a star with a diffuse interstellar cloud (Kamp &
Paunzen, 2002; Martinez-Galarza et al., 2009), where the underabundances are
produced by different amounts of accreted material. Turcotte & Charbonneau
(1993) estimate that once the accretion stops, the photospheric mixing and
meridional circulation would erase this peculiar signature on a $\sim$1 Myr
timescale. By studying the distribution of $\lambda$ Boötis stars on the HR
diagram, Murphy & Paunzen (2017) conclude that multiple mechanisms could
result in a $\lambda$ Boötis spectra, depending on the age and environment of
the star.

In addition to the mentioned scenarios, a number of works propose a possible
relation between the $\lambda$ Boötis phenomena and the presence of planets.
For instance, Gray & Corbally (2002) suggest that planetary bodies could
perturb the orbits of comets and volatile-rich objects, likely sending them
toward the star and possibly originating this pattern. Marois et al. (2008)
detected three planets and a debris disk by direct imaging orbiting around the
bright A5-type star HR 8799. This object was one of the first early-type stars
with planets detected, also showing $\lambda$ Boötis-like abundances (Gray &
Kaye, 1999; Sadakane, 2006). Then, Kama et al. (2015) studied the chemical
abundances and disk properties for a sample of pre-main-sequence Herbig Ae/Be
stars. They propose that the depletion of heavy elements observed in $\sim$33%
of these stars (Folsom et al., 2012), originates when Jupiter-like planets
(with mass between 0.1 and 10 MJup) block the accretion of part of the metal-
rich dust of the primordial disk, while gas-phase C and O continues to flow
toward the central star. The authors also suggest that main-sequence stars,
with a $\lambda$ Boötis fraction of $\sim$2%, do not host massive
protoplanetary disks and then their peculiarity should disappear on a $\sim$1
Myr timescale. For the case of main-sequence stars, Jura (2015) proposed that
this peculiar abundance pattern could also be directly originated from the
winds of hot-Jupiters, taking the planet as a possible source of gas
relatively near to the star. However, he caution that other channels could
likely result in the $\lambda$ Boötis pattern (see e.g. Murphy & Paunzen,
2017). Recently, Kunimoto et al. (2018) simulated numerically the pre-main-
sequence evolution of stars including the effects of planet formation, and
concluded that stars with Teff $>$ 7000 K may show a metallic deficit
compatible with the refractory-poor $\lambda$ Boötis stars. Therefore, the
possible link between planet-bearing stars and the $\lambda$ Boötis chemical
pattern motivated the present study.

To date, important trends are known for the case of late-type stars with
planets, such as the giant planet-metallicity correlation (Santos et al.,
2004, 2005; Fischer & Valenti, 2005; Johnson et al., 2010a; Sousa et al.,
2011). However, early-type stars with planets are poorly studied compared to
late-type stars. This is partly because hot stars rotate rapidly and have few
spectral lines, making radial velocity searches of planets more difficult.
Transit and microlensing surveys are also more sensitive to planets orbiting
low-mass stars (although for different reasons, see e.g. Wright & Gaudi,
2013). In the past few years, a slowly growing number of planets orbiting
early-type stars were found, detected mainly by transits (e.g. from the KELT
Collaboration, Pepper et al., 2007) and also from direct imaging (such as the
GPIES survey, Nielsen et al., 2019). This give us the opportunity to start a
homogeneous study of this interesting group of stars, by performing (to our
knowledge, for the first time) a detailed chemical analysis, allowing a
comparison with the $\lambda$ Boötis pattern. Our sample includes some
remarkable objects (such as HR 8799, $\beta$ Pictoris, Fomalhaut, KELT-9),
some important prototype/standard stars for comparison ($\lambda$ Boötis,
Vega), and a number of stars for which no abundance study was previously
performed in the literature (HR 4502 A, BU Psc, HD 105850, HD 110058, HD
129926, HD 153053, HD 156751, HD 188228, HD 23281, HD 50445, HD 56537 and V435
Car).

This work is organized as follows. In Section 2 we describe the observations
and data reduction, while in Section 3 we present the stellar parameters and
chemical abundance analysis. In Section 4 we show the results and discussion,
and finally in Section 5 we highlight our main conclusions.

##  2 Stellar samples and observations

We compiled a list of early-type stars with planets taken from the Extrasolar
Planets Encyclopaedia111http://exoplanet.eu/. These stars comprise mainly
A-type and few F-type stars, and are listed in the Table 2. Some stars listed
in the mentioned catalog present companions with masses above $\sim$13 MJup,
the minimum mass to burn Deuterium (e.g. Grossman & Graboske, 1973; Saumon et
al., 1996). These stars are likely orbited by brown dwarfs (BDs) rather than
planets, and some of them are also included in this work for comparison. We
also included a group of early-type stars without planets nor brown dwarfs
detected, taken from the GPIES imaging survey (Nielsen et al., 2019), which is
mainly focused on young and nearby stars. We note that the stars included in
this work were taken from different surveys using for instance transits and
imaging, for which the comparisons should be then performed with caution. We
also take the opportunity and include in our sample the stars Vega and
$\lambda$ Boötis, as standard or prototype stars for comparison.

Overall, the sample of stars analyzed in this work consists of 37 objects,
including 13 stars with planets (detected by transits or direct imaging), 3
stars likely orbited by brown dwarfs and 21 objects without planets nor brown
dwarfs detected. The effective temperatures cover 6730 K $<$ Teff $<$ 10262 K
and superficial gravities between 3.60 $<$ $\log g$ $<$ 4.37. The complete
list of stars analyzed in this work is presented in Table 2, showing the name
of the star, spectral type (taken from the
SIMBAD222http://simbad.u-strasbg.fr/simbad/ database), companion detection
method (transits, imaging or RV), companion mass, type of companion (planet or
brown dwarf), infrared IR excess, source of the spectra, signal-to-noise ratio
(S/N) measured at $\sim$5000 Å, and finally the reference for the companion
data and/or IR excess. The column labeled IR Excess was added to give
information about the possible presence of circumstellar dust orbiting around
the stars.

We downloaded archive spectra for the case of HARPS, HARPS-N, HIRES, SOPHIE
and ELODIE spectrographs. General characteristics of these instruments are
showed in the Table 1, including the resolving power, CCD detector, pixel
size, telescope and approximate wavelength range. The reduction was performed
by using the Data Reduction Software (DRS) pipeline for the case of HARPS and
HARPS-N
spectra333https://www.eso.org/sci/facilities/lasilla/instruments/harps/doc.html,
using the reduction package MAKEE 3 with HIRES
spectra444http://www.astro.caltech.edu/ tb/makee/, the DRS pipeline with
SOPHIE spectra555http://www.obs-hp.fr/guide/sophie/sophie-eng.shtml#drs and
the TACOS program with ELODIE spectra666http://www.obs-
hp.fr/www/guide/elodie/manuser2.html. The continuum normalization and other
operations (such as Doppler correction and combining spectra) were performed
using Image Reduction and Analysis Facility (IRAF)777IRAF is distributed by
the National Optical Astronomical Observatories, which is operated by the
Association of Universities for Research in Astronomy, Inc., under a
cooperative agreement with the National Science Foundation..

Table 1: General characteristics of the spectrographs used in this work. Instrument | R | CCD | Pixel | Telescope | Approx.
---|---|---|---|---|---
|  | Detector | size |  | Wave. Range
HARPS | 115000 | 4k x 4k |  15 $\mu$m | La Silla 3.6m | 3800 - 6800
HARPS-N | 115000 | 4k x 4k |  15 $\mu$m | TNG 3.6m | 3800 - 6800
HIRES | 67000 | 2k x 4k |  15 $\mu$m | Keck 10m | 3750 - 9000
SOPHIE | 75000 | 4k x 2k |  15 $\mu$m | OHP 1.93m | 3900 - 6800
ELODIE | 42000 | 1k x 1k |  24 $\mu$m | OHP 1.93m | 3850 - 6800
REOSC | 13000 | 1k x 1k |  24 $\mu$m | CASLEO 2.1m | 3800 - 6000

We also completed the sample with observations obtained at Complejo
Astrónomico El Leoncito (CASLEO) during the observing runs 2018A, 2018B and
2019A. We used the _Jorge Sahade_ 2.15 m telescope equipped with a REOSC high-
resolution echelle spectrograph888On loan from the Institute d’Astrophysique
de Liege, Belgium and a TEK 1024x1024 CCD detector. The REOSC spectrograph
uses gratings as cross dispersers, selecting in this case a grating with 400
lines mm-1. We take a number of stellar spectra for each target, followed by a
ThAr lamp in order to derive an appropriate pixel versus wavelength solution.
The REOSC spectra were reduced using IRAF by performing the usual operations
including, for example, bias subtraction, flat fielding, spectral order
extraction and wavelength calibration. The final spectra covered the visual
range $\lambda\lambda$3800-6000, and the average S/N ratio of the spectra was
around $\sim$350.

Table 2: Sample of stars studied in this work.

Star name | Spectral | Companion | Companion | Companion | IR | Spectra | S/N | Companion &
---|---|---|---|---|---|---|---|---
| Type | Detection |  Mass [MJup] | Type | Excess |  | @5000 Å | IR Excess Refs.
|  | Method |  |  |  |  |  |
Exoplanet host stars |  |  |  |  |  |
$\beta$ Pic | A6V | Imaging | 9.9, 8.9 | Planet | Yes | HARPS | 1500 | R1, R14, R20, R21
Fomalhaut | A4V | Imaging |  $<$ 1 | Planet | Yes | REOSC | 490 | R2, R20, R21
KELT-9 | B9.5 – A0 | Transit | 2.88 | Planet | No | HARPS-N | 550 | R3, R23
HD 95086 | A8III | Imaging | 2.6 | Planet | Yes | HARPS | 310 | R4, R14, R24, R25
HD 169142 | F1VekA3mA3 HAeBe | Imaging |  $<$ 1, $<$ 10 | Planet | Yes | HARPS | 210 | R5, R26
HR 8799 | F0+VkA5mA5 | Imaging | 8.3, 8.3, 9.2 | Planet | Yes | ELODIE | 370 | R6, R14, R27, R28
KELT-17 | A2 | Transit | 1.31 | Planet | No | REOSC | 210 | R7
KELT-20 | A0 | Transit | 3.5 | Planet | No | HARPS-N | 450 | R8
MASCARA-1 | A8 | Transit | 3.7 | Planet | … | HARPS-N | 560 | R9
WASP-33 | kA5hA8mF4 | Transit |  $<$ 4.1 | Planet | … | HIRES | 250 | R10
HAT-P-49 | A8 | Transit | 1.73 | Planet | … | SOPHIE | 135 | R15
WASP-167 | F1V | Transit |  $<$ 8 | Planet | … | HARPS | 205 | R16
WASP-189 | A4/5IV/V | Transit | 1.99 | Planet | … | HARPS | 1105 | R17
Stars with a brown dwarf (BD) companion |  |  |  |  |  |
$\beta$ Cir | A3Va | Imaging | 58.7 | BD | Yes | HARPS | 250 | R11, R22
59 Dra | A7 HAeBe | RV | 25 | BD | … | ELODIE | 350 | R12
$\zeta$ Del | A3Va | … | 50 | BD | … | ELODIE | 290 | R18
Stars with no-companion detected |  |  |  |  |  |
HD 133803 | F2IVm-2 | … | … | … | … | HARPS | 300 | R14
HR 4502 A | A0V | … | … | … | … | HARPS | 130 | R14
BU Psc | A9V/IV | … | … | … | … | HARPS | 110 | R14
HD 29391 | F0 IV | … | … | … | … | HARPS | 410 | R14
HD 105850 | A1V | … | … | … | … | HARPS | 650 | R14
HD 110058 | A0V | … | … | … | Yes | HARPS | 450 | R14, R29
HD 115820 | A7/8V | … | … | … | … | HARPS | 250 | R14
HD 120326 | F0V | … | … | … | … | HARPS | 200 | R14
HD 129926 | F0VSr+G1V | … | … | … | … | HARPS | 600 | R14
HD 146624 | A1 Va | … | … | … | … | HARPS | 620 | R14
HD 153053 | A5IV/V | … | … | … | Yes | HARPS | 600 | R14, R22
HD 156751 | A7II/III | … | … | … | … | HARPS | 410 | R14
HD 159492 | A5IV/V | … | … | … | Yes | HARPS | 720 | R14, R22
HD 188228 | A0Va | … | … | … | Yes | HARPS | 840 | R14, R21
HD 23281 | A5III/IV | … | … | … | … | HARPS | 470 | R14
HD 50445 | A3V | … | … | … | … | HARPS | 680 | R14
HD 56537 | A4IV | … | … | … | Yes | HARPS | 620 | R14, R20
HD 88955 | A2Va | … | … | … | Yes | HARPS | 590 | R14, R20
V435 Car | A5V | … | … | … | Yes | HARPS | 200 | R14
$\lambda$ Boötis | A0Va lBoo | … | … | … | Yes | ELODIE | 525 | R20, R21
Vega | A0Va | … | … | … | Yes | SOPHIE | 1230 | R19, R20, R21

Companions data: R1 (Lagrange et al., 2019), R2 (Kalas et al., 2013), R3
(Borsa et al., 2019), R4 (De Rosa et al., 2016), R5 (Fedele et al., 2017), R6
(Wang et al., 2018), R7 (Zhou et al., 2016), R8 (Lund et al., 2017), R9
(Talens et al., 2017), R10 (Collier Cameron et al., 2010), R11 (Smith et al.,
2015), R12 (Galland et al., 2006), R13 (Aller et al., 2013), R14 (Nielsen et
al., 2019), R15 (Bieryla et al., 2014), R16 (Temple et al., 2017), R17 (Lendl
et al., 2020), R18 (De Rosa et al., 2014), R19 (Matrà et al., 2020), R20
(Rieke et al., 2005), R21 (Su et al., 2006), R22 (Morales et al., 2011), R23
(Gaudi et al., 2017), R24 (Moór et al., 2013), R25 (Su et al., 2017), R26
(Reggiani et al., 2014), R27 (Su et al., 2009), R28 (Matthews et al., 2014),
R29 (Esposito et al., 2020)

We present in the Fig. 1 a theoretical HR diagram ($\log$ Teff versus $\log$
L/L☉) for the stars in our sample. The luminosity L was evaluated from the
visual magnitude corrected by interstellar reddening according to the
extinction maps of Schlegel et al.
(1998),999https://irsa.ipac.caltech.edu/applications/DUST/ following the
procedure of Bilir et al. (2008). We used Gaia DR2 parallaxes (Gaia
Collaboration, 2018) and bolometric corrections interpolated in the tables of
Flower et al. (1996). Stars with planets, without planets and with a BD
companion are showed with filled circles, empty circles and crosses,
respectively. We also show PARSEC evolutionary tracks (Bressan et al., 2012)
for stars with different masses. Blue and magenta lines correspond to main-
sequence and evolved phases.

Figure 1: Effective temperature versus luminosity for stars with planets,
without planets and with a BD companion (filled circles, empty circles and
crosses). Evolutionary tracks for stars of different masses are showed in
blue/magenta for main-sequence/evolved stars. The numbers are expressed in
solar masses.

##  3 Stellar parameters and abundance analysis

###  3.1 Effective temperature and gravity

Effective temperature Teff and superficial gravity $\log g$ were first
estimated by using the Strömgren uvby$\beta$ mean photometry of Hauck &
Mermilliod (1998) for most stars in our sample or by taking previously
published results. We used the program TempLogG (Kaiser, 2006) together with
the calibration of Napiwotzki et al. (1993) and derredenned colors according
to Domingo & Figueras (1999), in order to derive the fundamental parameters.
Then, these values were refined (when neccesary and/or possible) by enforcing
excitation and ionization balances of the iron lines. The same strategy was
previously applied in the literature (e.g. Acke & Waelkens, 2004; Saffe &
Levato, 2014). The values derived in this way are listed in the Table 3, with
an average dispersion of $\sim$175 K and $\sim$0.15 dex for Teff and $\log g$.
In the Fig. 2 we compare Teff values with those collected from literature
(Erspamer & North, 2003; Lepine et al., 2003; Paunzen et al., 2006; Masana et
al., 2008; Zorec & Royer, 2012; De Rosa et al., 2016; Zhou et al., 2016;
Kahraman Alicavus et al., 2016; Gray et al., 2017; Lund et al., 2017; Talens
et al., 2017; Borsa et al., 2019), showing a general agreement. Average
dispersion bars are showed in the upper left corner of the panel.

Figure 2: Effective temperature Teff derived in this work versus literature
data. Average dispersion bars are showed in the upper left corner of the
panel.

###  3.2 Rotational velocities $v\sin i$

Projected rotational velocities $v\sin i$ were first estimated by fitting the
observed profile of the line Mg II 4481.23 Å and then refined by fitting most
Fe I and Fe II lines in the spectra. Synthetic spectra were calculated using
the program SYNTHE (Kurucz & Avrett, 1981) together with ATLAS9 (Kurucz, 1993)
model atmospheres, and then convolved with a rotational profile (using the
Kurucz’s command rotate) and with an instrumental profile for each
spectrograph (using the command broaden). Rotational velocities were varied
for each line, adopting as final value the average of different lines. The
resulting $v\sin i$ values are showed in the 4th column of Table 3, covering
between 14.8 and 153.5 km s-1 for the stars in our sample. The average
dispersion in $v\sin i$ resulted $\sim$2.2 km s-1. In the Fig. 3 we compare
$v\sin i$ values derived in this work with those from literature, showing a
general agreement. Average dispersion bars are showed in the upper left corner
of the panel.

Figure 3: Projected rotational velocity $v\sin i$ derived in this work versus
literature data. Average dispersion bars are showed in the upper left corner
of the panel.

###  3.3 Microturbulence velocity

Microturbulence velocity vmicro is commonly used as a free parameter in
abundance analysis. Several studies have found that microturbulence appears to
vary systematically with Teff for early-type stars (Chaffee, 1970; Nissen,
1981; Coupry & Burkhart, 1992; Gray et al., 2001; Takeda et al., 2008; Gebran
et al., 2014). They showed that vmicro increases with increasing Teff, peaking
around mid-A type ($\sim$8500 K), before falling away to almost $\sim$0 km s-1
for B-type stars. In this work, we adopted the formula derived by Gebran et
al. (2014) in order to estimate vmicro as a function of Teff, which is valid
for $\sim$6000 K $<$ Teff $<$ $\sim$10000 K. Gebran et al. (2014) showed that
the formula has an uncertainty of $\sim$25 $\%$, which we adopted as the error
in the vmicro values. The effect of this relatively large uncertainty (and
uncertainties of other fundamental parameters) on the abundance values is
estimated in the next sections.

Table 3: Fundamental parameters derived for the stars in this work. Star | Teff [K] |  $\log g$ [dex] | vmicro [km s-1] |  $v\sin i$ [km s-1]
---|---|---|---|---
$\beta$ Pic | 8084 $\pm$ 130 | 4.22 $\pm$ 0.13 | 3.31 $\pm$ 0.83 | 113.0 $\pm$ 1.3
Fomalhaut | 8745 $\pm$ 195 | 4.17 $\pm$ 0.10 | 2.95 $\pm$ 0.74 | 82.0 $\pm$ 3.2
KELT-9 | 9329 $\pm$ 118 | 4.00 $\pm$ 0.14 | 2.27 $\pm$ 0.57 | 113.5 $\pm$ 4.6
HD 95086 | 7593 $\pm$ 122 | 4.02 $\pm$ 0.14 | 3.09 $\pm$ 0.77 | 30.0 $\pm$ 1.4
HD 169142 | 7296 $\pm$ 365 | 4.20 $\pm$ 0.25 | 2.75 $\pm$ 0.69 | 55.0 $\pm$ 0.8
HR 8799 | 7301 $\pm$ 190 | 4.12 $\pm$ 0.23 | 2.76 $\pm$ 0.69 | 50.5 $\pm$ 1.0
KELT-17 | 7471 $\pm$ 210 | 4.20 $\pm$ 0.14 | 2.50 $\pm$ 0.63 | 43.0 $\pm$ 0.6
KELT-20 | 8652 $\pm$ 160 | 4.11 $\pm$ 0.20 | 3.03 $\pm$ 0.76 | 111.0 $\pm$ 3.1
MASCARA-1 | 7687 $\pm$ 238 | 4.09 $\pm$ 0.14 | 3.17 $\pm$ 0.79 | 99.0 $\pm$ 3.9
WASP-33 | 7373 $\pm$ 164 | 4.14 $\pm$ 0.20 | 2.86 $\pm$ 0.71 | 82.5 $\pm$ 2.0
HD 133803 | 6998 $\pm$ 193 | 4.08 $\pm$ 0.23 | 2.29 $\pm$ 0.57 | 89.5 $\pm$ 1.3
$\beta$ Cir | 8552 $\pm$ 297 | 3.94 $\pm$ 0.18 | 3.12 $\pm$ 0.78 | 61.0 $\pm$ 0.8
59 Dra | 7053 $\pm$ 194 | 4.18 $\pm$ 0.21 | 2.38 $\pm$ 0.60 | 53.0 $\pm$ 1.1
HR 4502 A | 9569 $\pm$ 253 | 4.00 $\pm$ 0.16 | 1.96 $\pm$ 0.49 | 18.5 $\pm$ 0.7
BU Psc | 7185 $\pm$ 160 | 4.22 $\pm$ 0.14 | 2.59 $\pm$ 0.65 | 53.0 $\pm$ 2.6
HD 29391 | 7259 $\pm$ 167 | 4.12 $\pm$ 0.20 | 2.70 $\pm$ 0.68 | 70.0 $\pm$ 1.7
HD 105850 | 9052 $\pm$ 167 | 4.08 $\pm$ 0.08 | 2.61 $\pm$ 0.65 | 125.0 $\pm$ 1.5
HD 110058 | 7839 $\pm$ 202 | 4.00 $\pm$ 0.14 | 3.26 $\pm$ 0.81 | 153.5 $\pm$ 2.9
HD 115820 | 7610 $\pm$ 135 | 4.30 $\pm$ 0.15 | 3.11 $\pm$ 0.78 | 92.2 $\pm$ 1.8
HD 120326 | 6925 $\pm$ 143 | 4.37 $\pm$ 0.11 | 2.17 $\pm$ 0.54 | 66.5 $\pm$ 1.5
HD 129926 | 7101 $\pm$ 167 | 4.18 $\pm$ 0.20 | 2.46 $\pm$ 0.62 | 113.0 $\pm$ 2.1
HD 146624 | 9489 $\pm$ 184 | 4.13 $\pm$ 0.07 | 2.06 $\pm$ 0.52 | 34.0 $\pm$ 0.5
HD 153053 | 7916 $\pm$ 129 | 4.03 $\pm$ 0.14 | 3.29 $\pm$ 0.82 | 103.0 $\pm$ 1.6
HD 156751 | 7432 $\pm$ 175 | 3.92 $\pm$ 0.21 | 2.93 $\pm$ 0.73 | 100.0 $\pm$ 4.3
HD 159492 | 8076 $\pm$ 128 | 4.24 $\pm$ 0.13 | 3.31 $\pm$ 0.83 | 52.3 $\pm$ 1.2
HD 188228 | 10262 $\pm$ 172 | 4.29 $\pm$ 0.06 | 1.17 $\pm$ 0.29 | 83.0 $\pm$ 3.5
HD 23281 | 7761 $\pm$ 135 | 4.18 $\pm$ 0.15 | 3.22 $\pm$ 0.80 | 77.7 $\pm$ 2.4
HD 50445 | 7922 $\pm$ 117 | 4.03 $\pm$ 0.14 | 3.29 $\pm$ 0.82 | 96.0 $\pm$ 1.9
HD 56537 | 8231 $\pm$ 122 | 3.70 $\pm$ 0.12 | 3.29 $\pm$ 0.82 | 146.0 $\pm$ 4.3
HD 88955 | 8733 $\pm$ 154 | 3.76 $\pm$ 0.10 | 2.96 $\pm$ 0.74 | 99.0 $\pm$ 3.0
V435 Car | 7510 $\pm$ 165 | 4.21 $\pm$ 0.14 | 3.01 $\pm$ 0.75 | 106.4 $\pm$ 1.9
HAT-P-49 | 6730 $\pm$ 234 | 4.02 $\pm$ 0.14 | 1.82 $\pm$ 0.46 | 14.8 $\pm$ 0.2
$\lambda$ Boötis | 8512 $\pm$ 144 | 3.95 $\pm$ 0.06 | 3.15 $\pm$ 0.79 | 115.0 $\pm$ 3.1
Vega | 9505 $\pm$ 188 | 3.95 $\pm$ 0.19 | 2.04 $\pm$ 0.51 | 20.5 $\pm$ 0.7
WASP-167 | 6770 $\pm$ 210 | 4.05 $\pm$ 0.14 | 1.90 $\pm$ 0.47 | 52.0 $\pm$ 2.0
WASP-189 | 7946 $\pm$ 136 | 3.85 $\pm$ 0.12 | 3.30 $\pm$ 0.82 | 95.2 $\pm$ 3.3
$\zeta$ Del | 8236 $\pm$ 124 | 3.60 $\pm$ 0.12 | 3.29 $\pm$ 0.82 | 108.0 $\pm$ 3.6

###  3.4 Abundance analyses

We applied an iterative procedure to determine the chemical abundances for the
stars in our sample. We started by computing an ATLAS12 (Kurucz, 1993) model
atmosphere for the adopted Teff, $\log g$ and vmicro values. For this initial
model, we used solar metallicity values taken from Asplund et al. (2009). The
abundances were determined by fitting a synthetic spectra to the different
lines using the program SYNTHE (Kurucz, 1993). With the new abundance values,
we derived a new model atmosphere and started the process again. If
neccessary, Teff and $\log g$ were refined to achieve the balance of Fe I and
Fe II lines. In each step, opacities were calculated for an arbitrary
composition and vmicro using the opacity sampling (OS) method, similar to
previous works (Saffe et al., 2018, 2019, 2020). In this case, two runs of
ATLAS12 are used (see e.g. Castelli, 2005; Saffe et al., 2018): the first for
a preselection of important lines and the second for the final calculation of
the model structure. In this way, abundances are consistently derived using
specific opacities rather than solar-scaled values. An estimation of the
differences obtained when using these two approaches for the case of solar-
type stars, can be seen in Saffe et al. (2018).

We compared observed and synthetic spectra using a $\chi^{2}$ function,
calculated as the quadratic sum of the differences between both spectra. The
abundances were varied in steps of 0.01 dex until reach a minimum in
$\chi^{2}$, similar to Saffe & Levato (2014). The fits were also verified by
eye inspection, using intervals spanning 10 Å around the lines of interest.
Abundances derived in this way are presented in the Table 4 of the Appendix,
showing the average and dispersion for the stars in our sample. The values are
showed using the square bracket notation, which denotes abundances relative to
the Sun, that is [N/H]=log(N/H)Star $-$ log(N/H)Sun, where log(N/H)Star and
log(N/H)Sun are abundance values for the star and for the Sun, the later taken
from Asplund et al. (2009).

Chemical abundances were derived for 23 different species, including C I, C
II, O I, Mg I, Mg II, Al I, Al II, Si II, Ca I, Ca II, Sc II, Ti II, Cr II, Mn
I, Mn II, Fe I, Fe II, Ni II, Zn I, Sr II, Y II, Zr II and Ba II. The atomic
line list and laboratory data used in this work are basically those described
in Castelli & Hubrig (2004), updated with specialized references as described
in Sect. 7 of González et al. (2014). In Figs. 4 to 6 we present an example of
observed, synthetic and difference spectra (black, blue dotted and red lines)
for the stars in our sample. The stars are sorted in the plot by increasing
$v\sin i$. There is a good agreement between modeling and observations for the
lines of different chemical species.

###  3.5 Uncertainty of abundance values

In general, the uncertainty in the abundance values have different sources.
First, we estimated the measurement error e1 from the line-to-line dispersion
as $\sigma/\sqrt{n}$ , where $\sigma$ is the standard deviation of the line-
by-line abundances and n is the number of lines. For elements with only one
line, we adopted for $\sigma$ the standard deviation of the iron lines. Then,
we determined the contribution to the abundance error due to the uncertainty
in stellar parameters. We modified Teff and $\log g$ by their uncertainties
and recalculated the abundances, obtaining the corresponding differences e2
and e3. We also wanted to estimate the contribution to the error due to the
uncertainty in vmicro, which is not always included in the error calculation.
Similarly, we modified vmicro by its uncertainty and obtained the difference
e4 by recalculating the abundances. Finally, the total error was estimated as
the quadratic sum of e1, e2, e3 and e4. These values are presented in the
Table 4 of the Appendix, in order to determine their contribution to the total
error.

###  3.6 NLTE effects

The basic difference between LTE and NLTE is the behavior of atomic level
populations. LTE allows a relatively simple calculation using a Saha-Boltzman
distribution, while in NLTE the level populations are affected by the
radiation field and should be determined by kinetic equilibrium (see e.g.
Kubát, 2014). Departures from LTE are more pronounced in stars with high
temperature and with low gravity and metallicity. For instance, the reduction
of surface gravity results in a decreased efficiency of collisions with
electrons and hydrogen atoms, reducing the thermalizing effect, which leads to
stronger NLTE effects (e.g. Gratton et al., 1999). Subsequently, some
particular species and transitions should be taken with caution.

Rentzsch-Holm (1996) estimated NLTE departures for C I lines in early-type
stars (up to $\sim$0.2 dex for lines with equivalent widths W${}_{eq}\sim$100
mÅ, and lower departures with decreasing Weq). Weak and intense C II lines
could also show pronounced NLTE effects (Przybilla et al., 2011), except for C
II 5145 Å and other members of the multiplet. For O I, NLTE effects are
expected, especially in the near-IR triplet O I 7771 Å and the other lines of
the same multiplet (e.g. Sitnova et al., 2013; Przybilla et al., 2011). For
the case of Mg, Przybilla et al. (2001) found that the intense line Mg II 4481
systematically yields notably higher abundances due to NLTE effects (between
0.2 - 0.8 dex for early-type stars). More recently, Alexeeva et al. (2018)
studied the formation of Mg lines under LTE and NLTE. For stars with 7000 K
$<$ Teff $<$ 17500 K, they recommend to use the Mg II lines 3848.21 Å, 4427.99
Å, 4384.64 Å and 4390.57 Å even at the LTE assumption. However, these lines
are not always available in our spectra. For stars with 7000 K $<$ Teff $<$
8000 K, they showed that the line 4702.99 and the Mg I b triplet could be
safely used in LTE. For each star, they also estimate that the average
difference between Mg I and Mg II diminish from $\sim$0.23 dex in LTE to
$\sim$0.09 dex in NLTE. This could explain, at least in part, the higher
abundances of Mg II compared to Mg I observed in some stars. However, the
authors also caution that the difference Mg II $-$ Mg I even in NLTE could
amount up to $\sim$0.24 dex for metal-poor stars, for a reason that require
future investigation. For the case of Ti II, Sitnova et al. (2016) showed some
small NLTE departures (for instance, up to $\sim$0.03 dex for the line
5336.79) and originating possible discrepancies between Ti I and Ti II.

Figure 4: Observed, synthetic and difference spectra (black, blue dotted and
red lines) for the stars in our sample, sorted by $v\sin i$. Figure 5:
Observed, synthetic and difference spectra (black, blue dotted and red lines)
for the stars in our sample, sorted by $v\sin i$. Figure 6: Observed,
synthetic and difference spectra (black, blue dotted and red lines) for the
stars in our sample, sorted by $v\sin i$.

###  3.7 Comparison with literature

We present in the Fig. 7 a comparison of metallicity values derived in this
work and from literature. We collected these values from different sources
(Andrievsky et al., 2002; Erspamer & North, 2003; Gray et al., 2006; Sadakane,
2006; Collier Cameron et al., 2010; Yoon et al., 2010; Prugniel et al., 2011;
Folsom et al., 2012; Moór et al., 2013; Bieryla et al., 2014; Zhou et al.,
2016; Gaudi et al., 2017; Luck, 2017; Lund et al., 2017; Talens et al., 2017;
Temple et al., 2017; Anderson et al., 2018; Bochanski et al., 2018; Arentsen
et al., 2019; Cheng et al., 2019). The Fig. 7 shows a good agreement with
literature data in general for most stars. The point in the lower corner of
the plot corresponds to the star $\lambda$ Boötis.

The largest differences in metallicity corresponds to the stars KELT-17 and HD
88955, with [Fe/H] differences of 0.48 and 0.56 dex, respectively. Both stars
are identified in the Fig. 7. Given the relatively large differences, we
briefly explore the possible source of discrepancies. Zhou et al. (2016)
discovered a giant planet around KELT-17 and adopted a final [Fe/H] value of
-0.018$\pm$0.073 dex by iterating through a global analysis of the transit,
constrained by a transit-derived stellar density and stellar isochrone models.
The authors also note that, when using only spectroscopic data (a single
interval centered around the Mg b lines), the resulting metallicity could vary
between -0.10$\pm$0.08 dex and +0.25$\pm$0.08 dex (by fixing the $\log g$
value). In this way, the global solution adopted by Zhou et al. (2016) depends
on several parameters and models, not specifically designed to derive
abundances. On the other hand, Saffe et al. (2020) showed that the chemical
pattern of KELT-17 closely resembles those of Am stars (for many species and
not only iron), using a process different than those used by Zhou et al.
(2016).

The other star with a notable difference in metallicity is HD 88955. Erspamer
& North (2003) derived for this object [Fe/H] $=$ 0.06 dex using an automatic
procedure with an ELODIE (R$\sim$42000) spectra. They used a spectral
synthesis program (modified by the authors) in order to accept ATLAS9 model
atmospheres instead of ATLAS5 models as in their original version. On the
other hand, for this star we obtained [Fe/H] $=$ -0.50$\pm$0.14 dex using a
HARPS (R$\sim$115000) spectra together with ATLAS12 models. The difference is
possibly due to the adopted stellar parameters (difference of 220 K in Teff
and 0.37 dex in $\log g$) and laboratory data for the lines. Unfortunately,
Erspamer & North (2003) do not report a [Fe/H] error for this star, which
difficults a later comparison.

Figure 7: Metallicity values derived in this work ([Fe/H]) versus literature
data. Average dispersion bars are showed in the upper left corner of the
panel. The stars HD 88955 and KELT-17 are identified in the plot (see text for
more details).

##  4 Discussion

In the present section, we discuss different aspects related to the metallic
content of the early-type stars with planets. We start by searching $\lambda$
Boötis stars in our sample and studying the possible relation between hot-
Jupiter planets and $\lambda$ Boötis stars. Then, we search for other possible
chemically peculiar stars in our sample. Finally, we discuss the possible
implications of our results within the context of the planet formation models.

###  4.1 $\lambda$ Boötis stars in our sample

We compared the abundances of our sample stars with the average pattern of
$\lambda$ Boötis stars. As explained in the Introduction, $\lambda$ Boötis
stars are early-type objects showing underabundances ($\sim$1-2 dex) of iron-
peak elements and near-solar abundances of C , N , O and S (e.g. Kamp et al.,
2001; Heiter, 2002; Gray et al., 2017). A representative chemical pattern was
derived by using the average of 12 $\lambda$ Boötis stars taken from Heiter
(2002). As result of this comparison, we have identified four (or five) stars
with the $\lambda$ Boötis pattern: HD 110058, HD 169142, HR 8799 and $\zeta$
Del (the star $\lambda$ Boötis itself would be the 5th object). We present in
the Fig. 8 the abundances of these four stars, compared to the average pattern
of $\lambda$ Boötis stars. The vertical bars in the average $\lambda$ Boötis
pattern correspond to the standard deviation of the different stars, as
derived by Heiter (2002). The figure shows two panels for each star,
corresponding to elements with atomic number z$<$32 and z$>$32\. In general,
these stars present near-solar values of C and O, together with subsolar
values of the other metals. An individual description for each star can be
read in the Appendix B. HD 169142 was also previously identified as a
$\lambda$ Boötis object (Folsom et al., 2012; Gray et al., 2017), as well as
HR 8799 (Gray & Kaye, 1999; Sadakane, 2006) and $\lambda$ Boötis (Venn &
Lambert, 1990; Paunzen et al., 1999; Cheng et al., 2019).

Most of the $\lambda$ Boötis stars identified here present evidence of
circumstellar material. HR 8799 and HD 169142 are orbited by dusty disks and
planets detected by direct imaging (Marois et al., 2008; Fedele et al., 2017).
Up to now, there is no planet detected around HD 110058, although presents an
IR excess indicative of a dusty disk (Nielsen et al., 2019; Esposito et al.,
2020). It is also interesting to note that $\zeta$ Del is orbited by a brown
dwarf detected by direct imaging (De Rosa et al., 2014), with a projected
separation of 13.51$\pm$0.08 arcsec, or 912$\pm$15 AU at the distance of
$\zeta$ Del. There is also evidence of IR excess around $\zeta$ Del likely
related to the presence of dust (Nielsen et al., 2019; Esposito et al., 2020).
To our knowledge, $\zeta$ Del is the first $\lambda$ Boötis star orbited by a
brown dwarf, which could be used as a laboratory to test stellar formation
scenarios. Interestingly, our sample includes other two stars orbited by brown
dwarfs (59 Dra and $\beta$ Cir), although not showing $\lambda$ Boötis
characteristics.

We also present in the Fig. 9 the abundances of HD 156751, which shows a less
clear $\lambda$ Boötis signature (their $\sim$solar values of Sr, Y and Ba are
not typical of $\lambda$ Boötis stars). The same Fig. 9 presents the star
$\lambda$ Boötis itself, which shows rather extreme characteristics for its
class (a very low metallic content). Up to now, there is no planet detected
around HD 156751 nor $\lambda$ Boötis (Nielsen et al., 2019), while there is
IR excess detected around $\lambda$ Boötis indicative of a dusty disk (Rieke
et al., 2005; Su et al., 2006).

In our sample of early-type stars, there is no obvious relation between the
presence of planets (13 stars) and the $\lambda$ Boötis pattern (4 objects, or
5 if we include the star $\lambda$ Boötis). Kama et al. (2015) proposed that
the $\lambda$ Boötis observed in $\sim$33% of pre-main-sequence Herbig AeBe
stars (Folsom et al., 2012), originates when Jupiter-like planets (with mass
between 0.1 and 10 MJup) block the accretion of dust from the primordial disk.
Our sample includes the star HD 169142, which have been classified as a young
pre-main-sequence object and also as a $\lambda$ Boötis star (Folsom et al.,
2012). This object is included in our sample and shows the mentioned chemical
peculiarity (see Fig. 8). Although not strictly a pre-main-sequence object, HR
8799 is also a young star (age of 42$\pm$5 Myr, Nielsen et al., 2019) which
shows the $\lambda$ Boötis signature (see Fig. 8). Then, the $\lambda$ Boötis
signature that we observe in these two stars, support in principle the
scenario proposed by Kama et al. (2015).

It is worthwhile to mention that $\beta$ Pictoris and HD 95086 are also young
stars (ages $<\sim$50 Myr) hosting giant planets (Lagrange et al., 2019; De
Rosa et al., 2016), but not showing a clear $\lambda$ Boötis signature.
$\beta$ Pictoris is sligthly metal-poor (including C), while Ca and Ba show
solar values. Its $\lambda$ Boötis classification was initially suggested
based on its evolutionary status and the presence of a circumstellar disk
(King & Patten, 1992). However, this peculiar classification was then ruled
out by different authors, using an optical spectral (Holweger et al., 1997)
and also from the ratio of UV lines (Cheng et al., 2016). In this work, we do
not identify the star $\beta$ Pictoris with a $\lambda$ Boötis pattern. The
other young star (HD 95086) presents mostly solar or very slightly subsolar
abundances, different than average $\lambda$ Boötis stars. However, the fact
that these young stars ($\beta$ Pictoris and HD 95086) do not display the
$\lambda$ Boötis peculiarity, do not rule out the scenario proposed by Kama et
al. (2015). $\beta$ Pictoris and HD 95086 are young stars although not
strictly accreting pre-main-sequence objects. Kama et al. (2015) propose that
for main-sequence stars without a massive protoplanetary disk (that is, after
the accretion of volatile-rich gas), the peculiarity should disappear on a
short timescale ($\sim$1 Myr), as estimated by Turcotte & Charbonneau (1993).
Following the scenario of Kama et al. (2015), it is possible that these young
stars showed the $\lambda$ Boötis peculiarity in the past, which was then
erased few Myrs ago.

Figure 8: Abundances of four early-type stars (black), compared to the average
pattern of $\lambda$ Boötis stars (blue). We show two panels for each star,
corresponding to elements with z$<$32 and z$>$32.

Figure 9: Abundances of the stars HD 156751 and $\lambda$ Boötis (black),
compared to the average pattern of $\lambda$ Boötis stars (blue). We show two
panels for each star, corresponding to elements with z$<$32 and z$>$32.

###  4.2 $\lambda$ Boötis stars and hot-Jupiter planets

Hot-Jupiter planets present short orbital periods ($<$ 10 d) and large
planetary masses ($>$ 0.1 MJup), that is, they are gas giants orbiting very
close to their stars (e.g. Wang et al., 2015). Recently, Jura (2015) proposed
that $\lambda$ Boötis stars could be originated by accreting volatile-rich gas
from the winds of hot-Jupiter planets, rather than from the interaction with a
molecular cloud. In our sample, there are some stars orbited by hot-Jupiter
planets, all detected by the transits technique: WASP-33, WASP-167, WASP-189,
KELT-9, KELT-17, KELT-20, MASCARA-1 and HAT-P-49. We present in the Figures 11
and 12 of the Appendix, the abundances of these hot-Jupiter hosts, compared to
the average pattern of $\lambda$ Boötis stars. We do not recognize a clear
$\lambda$ Boötis pattern in these objects. Most of them show approximately
solar abundances; the possible exceptions are WASP-167 showing a metal-rich
spectra, and KELT-17 which is an Am star (Saffe et al., 2020). KELT-20
presents subsolar metallic abundances, being likely closer to the $\lambda$
Boötis pattern. However, this star still presents differences with this class
([C/H]=-0.42$\pm$0.11 is subsolar, while Si and Ba present suprasolar values),
which rule out its $\lambda$ Boötis nature.

In principle, the abundances derived for these stars do not support the
accretion scenario from the winds of hot-Jupiters. This is possibly due to a
number of reasons, as explained by Jura (2015). For example, the hot-Jupiter
composition is assumed to be nearly solar; the elements in the flow should be
efficiently separated (this depends on the viscosity of the gas); the amount
of planetary gas expelled (and then accreted onto the star) should be enough
to produce the effect; and finally, the flow from the planet should not be
magnetically funneled (this perhaps avoid elemental separations). If these
conditions are not met, the $\lambda$ Boötis pattern will likely not appear
(Jura, 2015). The author caution that other channels could also result in a
$\lambda$ Boötis pattern. In particular, Murphy & Paunzen (2017) conclude that
multiple mechanisms could possibly produce a $\lambda$ Boötis spectra,
depending on the age and environment of the star.

###  4.3 Other chemically peculiar stars in our sample

We also compared the abundances of the early-type stars with those of
chemically peculiar Am, ApSi and HgMn stars. In this case, the origin of their
peculiar abundances is commonly attributed to diffussion processes (e.g.
Michaud, 1970; Michaud et al., 1976, 1983; Vauclair et al., 1978; Richer et
al., 2000), taking place in the stable atmospheres of slowly rotating A-type
stars. In principle, there is no direct relation between these peculiar
patterns and the presence of planets. After inspecting the chemical patterns
of our early-type stars, we only found one clear Am object: the exoplanet host
star KELT-17 (Saffe et al., 2020). In general, Am stars present overabundances
of most heavy elements in their spectra, particularly Fe and Ni , together
with underabundances of Ca II and Sc II (see e.g. the work of Catanzaro et
al., 2019, and references therein). We compared the abundances of KELT-17 with
an average pattern of 62 Am stars recently determined by Catanzaro et al.
(2019) and found a good agreement, as we can see in the Fig. 10. KELT-17 is
the first exoplanet host whose chemical pattern was identified as an Am star
(Saffe et al., 2020), being an early result of this study. Although not
included in the present sample, other planet bearing stars with a possible Am
pattern include KELT-19 (Siverd et al., 2017) and KELT-26 A (Rodríguez
Martínez et al., 2019).

Figure 10: Abundances of the exoplanet host star KELT-17 (black), compared to
the average pattern of Am stars (magenta). The two panels correspond to
elements with z$<$32 and z$>$32.

In general, by inspecting the abundances of the planet host stars in our
sample, we found a number of stars showing mostly solar values (Fomalhaut,
KELT-9, MASCARA-1, WASP-33, HAT-P-49 and WASP-189). Other objects show a
$\lambda$ Boötis signature (such as the young stars HD 169142 and HR 8799),
while other planet hosts show a subsolar or slightly subsolar metallic content
($\beta$ Pictoris, HD 95086 and KELT-20). In addition, we also found a
chemically peculiar Am star (KELT-17) and a metal-rich star (WASP-167). Then,
no single chemical pattern could account for the complete group of planet
bearing stars.

###  4.4 Early-type stars and models of planet formation

In this section we briefly review planet formation models and the possible
relation to our observations. The two main models of planet formation are the
Core Accretion (CA) and the Gravitational Instability (GI). In the CA model,
the accretion of dust particles and planetesimals could result in a solid core
of few M⊕, forming low-mass planets and cores of giant planets. If the core
reach a critical mass of $\sim$5-10 M⊕ before the dissipation of gas disk,
then they could undergo a runaway accretion of gas and form giant planets
(e.g. Safronov & Zvjagina, 1969; Pollack et al., 1996; Ida & Lin, 2004;
Alibert et al., 2005, 2011; Mordasini et al., 2012). In the GI model, a
massive and cold protoplanetary disk fragments into clumps which then cool and
contract to form giant planets (e.g. Kuiper, 1951; Boss, 1998, 2002, 2017). In
the last years, CA models become the dominant planet formation theory for
solar-mass stars, matching observed features such as the abundance of Neptune
and Jupiter-mass planets (e.g. Udry et al., 2007) and the planet-metallicity
correlation (Ida & Lin, 2004; Mordasini et al., 2012). On the other hand,
initial GI models cannot provide an explanation of the planet-metallicity
correlation101010But note that recent GI works seem to find the correlation
with the inclusion of peeble accretion (Nayakshin, 2015). Both CA and GI
models have received considerable improvements in the last years (such as
planet migration, peeble accretion, etc.) and are still under developement
(see e.g. the reviews of Lissauer & Stevenson, 2007; Durisen et al., 2007;
Helled et al., 2014; Raymond & Morbidelli, 2020).

It has been claimed that, for solar-type stars, CA models could face some
difficulties (in principle) explaining the presence of giant planets around
metal-poor stars, or massive planets at long radial distances (see e.g. Helled
et al., 2014). In particular, HR 8799 is a metal-poor A5 star included in our
sample, hosting three giant planets orbiting beyond 10 AU (Marois et al.,
2008). Then, some authors proposed that the planets orbiting HR 8799 are
likely formed by GI, given that GI models can take place at large radii and in
low metal environments (Marois et al., 2008; Dodson-Robinson et al., 2009;
Meru & Bate, 2010). Other works cast some doubts about the planet formation
around HR 8799, showing that CA models are also possible (Currie et al., 2011)
or even a combination of GI and CA (Marois et al., 2010). For the case of
$\beta$ Pictoris and HD 169142, also having giant planets at long distances,
CA models seem to be favored (GRAVITY Collaboration, 2020; Nowak et al., 2020;
Pérez et al., 2019). However, an important word of caution about these works
is in order. Some of the stars mentioned (HR 8799 and HD 169142) display
(superficial) metal-poor abundances, showing in fact a $\lambda$ Boötis
pattern (see for example Fig. 8). As previously mentioned, the most accepted
idea about the origin of this peculiar signature, suppose a solar-like
composition for the original molecular cloud where the stars born, and then
some kind of selective accretion to obtain a $\lambda$ Boötis pattern. In this
way, it would be not entirely appropriate to assume a metal-poor natal
environment for stars like HR 8799, as assumed by some works to support a GI
planet formation (e.g. Meru & Bate, 2010). This fact was early noted by
Paunzen et al. (2014), in their comparison of $\lambda$ Boötis stars and
Population II type stars. Numerical simulations of planet formation around
$\lambda$ Boötis stars should assume a solar-like composition (rather than a
metal-poor natal environment), and this could have important consequences for
the subsequent results.

We prefer to be more cautious about the origin of planets orbiting around HR
8799 and similar stars, and explore subsequent predictions of CA models, even
including a low metallicity natal environment. Alibert et al. (2011) studied
the formation of planets under the CA assumption, specially for the case of
stars with different masses (0.5, 1.0 and 2.0 M☉). They found that the
metallicity effect of planet formation is weakly dependent on stellar mass,
that is, stars hosting giant planets resulted, on average, more metal rich
than stars without planets. However, they showed that the metallicity effect
depends also on the mass of the disk. If the disk mass scales with the stellar
mass, the effect of metallicity decreases as the mass of the primary
increases. Then, the minimum metallicity required to form a massive planet is
correspondingly lower for massive stars than lower mass stars. Mordasini et
al. (2012) also suggest a ”compensation effect”, where giant planet cores
could form even at low metallicities and large distances but compensated by
high disk masses. They caution, however, that low metallicities cannot be
compensated by high gas masses ad infinitum, at least if higher mass disks
have an ice line farther out due to stronger viscous dissipation. In other
words, it seems possible for stars having massive gas disks to form giant
planets though CA, without the necessity of higher metallicities.

##  5 Conclusions

In the present work, we performed a detailed abundance determination for a
number of early-type stars with and without planets, by fitting high-
resolution stellar spectra with a synthetic spectra. We compared the complete
chemical pattern of the sample with those of $\lambda$ Boötis as well as with
other chemically peculiar stars. Then, the main results of this study are as
follows:

-We have found four $\lambda$ Boötis stars in our sample, two of which present planets (HR 8799 and HD 169142), one without planets (HD 110058), and the first $\lambda$ Boötis star orbited by a brown dwarf ($\zeta$ Del). This last interesting pair composed by a $\lambda$ Boötis star + brown dwarf, could help to test stellar formation scenarios.

-We find no unique chemical pattern for (early-type) planet-bearing stars. Within this group, we found $\lambda$ Boötis stars (HD 8799 and HD 169142), a chemically peculiar Am star (KELT-17), a number of stars showing mostly solar abundaces, and one metal-rich object (WASP-167).

-The $\lambda$ Boötis signature that we observe in the Herbig AeBe star HD 169142 and in the young star HR 8799, support in principle the scenario proposed by Kama et al. (2015). They suggest that the presence of giant planets in very young stars possibly block the dust from protostellar disks and allow the accretion of volatile-rich gas, resulting in a $\lambda$ Boötis pattern.

-The abundances derived in this work for different hot-Jupiter exoplanet host stars do not support, in principle, the accretion from hot-Jupiters winds proposed to explain the origin of $\lambda$ Boötis stars. We suggest that other mechanisms should account for the presence of main-sequence $\lambda$ Boötis stars.

-It was previously suggested that gravitational instability could account for the formation of planets around low metallicity stars like HR 8799. However, we caution that it seems also possible for stars having massive gas disks to form giant planets though core accretion.

The interesting initial findings that we found here encourage us to continue
investigating early-type stars and the possible relation between planets and
$\lambda$ Boötis stars. We suggest to increase the number of stars studied in
order to improve the statistical significance of the results.

###### Acknowledgements.

We thank the referee Dr. Ernst Paunzen for constructive comments that improved
the paper. CS acknowledge the project grants CICITCA E1134 and PICT 2017-2294.
The authors wish to recognize and acknowledge the very significant cultural
role and reverence that the summit of Mauna Kea has always had within the
indigenous Hawaiian community. We are most fortunate to have the opportunity
to conduct observations from this mountain. The authors also thank Dr. Robert
Kurucz for making their codes available to us.

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##  Appendix A Detailed chemical abundances

We present in this section individual abundances for each star, showing
average$\pm$total error and the uncertainties e1, …, e4 for the chemical
species (see Table 4).

Table 4: Abundances derived in this work. For each specie, we present average$\pm$total error and the uncertainties e1, …, e4. Specie | [N/H] |  e1 |  e2 |  e3 |  e4 | [N/H] |  e1 |  e2 |  e3 |  e4 | [N/H] |  e1 |  e2 |  e3 |  e4
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
| HD 135379 |  $\beta$ Pictoris | HD 216956
C I |  -0.49 $\pm$ 0.17 | 0.04 | 0.16 | 0.02 | 0.02 |  -0.20 $\pm$ 0.11 | 0.09 | 0.02 | 0.04 | 0.02 |  -0.43 $\pm$ 0.19 | 0.17 | 0.09 | 0.01 | 0.02
Mg I |  -0.16 $\pm$ 0.38 | 0.13 | 0.25 | 0.06 | 0.25 |  -0.22 $\pm$ 0.20 | 0.07 | 0.05 | 0.03 | 0.18 |  0.02 $\pm$ 0.28 | 0.14 | 0.15 | 0.05 | 0.18
Mg II |  -0.19 $\pm$ 0.10 | 0.08 | 0.03 | 0.04 | 0.04 |  -0.01 $\pm$ 0.19 | 0.13 | 0.06 | 0.01 | 0.12 |  0.06 $\pm$ 0.15 | 0.14 | 0.02 | 0.01 | 0.05
Al I |  -0.63 $\pm$ 0.28 | 0.05 | 0.21 | 0.01 | 0.17 |  -0.84 $\pm$ 0.21 | 0.11 | 0.02 | 0.01 | 0.18 |  -0.32 $\pm$ 0.28 | 0.14 | 0.18 | 0.01 | 0.17
Si II |  -0.24 $\pm$ 0.14 | 0.06 | 0.10 | 0.06 | 0.05 |  -0.14 $\pm$ 0.24 | 0.19 | 0.08 | 0.04 | 0.11 |  -0.20 $\pm$ 0.14 | 0.09 | 0.07 | 0.03 | 0.07
Ca I |  -0.02 $\pm$ 0.48 | 0.08 | 0.35 | 0.06 | 0.32 |  0.11 $\pm$ 0.38 | 0.13 | 0.13 | 0.01 | 0.33 |  |  |  |  |
Ca II |  -0.14 $\pm$ 0.24 | 0.08 | 0.23 | 0.02 | 0.01 |  0.10 $\pm$ 0.14 | 0.13 | 0.03 | 0.02 | 0.01 |  -0.10 $\pm$ 0.18 | 0.14 | 0.12 | 0.02 | 0.01
Sc II |  0.07 $\pm$ 0.35 | 0.06 | 0.24 | 0.04 | 0.24 |  -0.14 $\pm$ 0.25 | 0.07 | 0.07 | 0.08 | 0.22 |  -0.06 $\pm$ 0.32 | 0.10 | 0.19 | 0.04 | 0.23
Ti II |  -0.16 $\pm$ 0.15 | 0.02 | 0.13 | 0.04 | 0.06 |  -0.08 $\pm$ 0.19 | 0.03 | 0.03 | 0.05 | 0.18 |  0.13 $\pm$ 0.17 | 0.03 | 0.10 | 0.02 | 0.13
Cr II |  -0.23 $\pm$ 0.11 | 0.02 | 0.08 | 0.04 | 0.05 |  -0.18 $\pm$ 0.10 | 0.05 | 0.02 | 0.04 | 0.08 |  0.23 $\pm$ 0.08 | 0.05 | 0.05 | 0.02 | 0.04
Mn I |  -0.39 $\pm$ 0.29 | 0.10 | 0.27 | 0.04 | 0.01 |  -0.23 $\pm$ 0.13 | 0.08 | 0.08 | 0.02 | 0.06 |  -0.27 $\pm$ 0.29 | 0.08 | 0.28 | 0.02 | 0.03
Fe I |  -0.25 $\pm$ 0.26 | 0.01 | 0.25 | 0.03 | 0.07 |  -0.28 $\pm$ 0.14 | 0.02 | 0.06 | 0.02 | 0.12 |  0.12 $\pm$ 0.19 | 0.02 | 0.15 | 0.02 | 0.11
Fe II |  -0.19 $\pm$ 0.16 | 0.02 | 0.12 | 0.04 | 0.10 |  -0.26 $\pm$ 0.14 | 0.04 | 0.03 | 0.04 | 0.12 |  0.11 $\pm$ 0.15 | 0.04 | 0.07 | 0.02 | 0.13
Ni II |  -0.11 $\pm$ 0.22 | 0.05 | 0.19 | 0.02 | 0.10 |  |  |  |  |  |  0.46 $\pm$ 0.16 | 0.09 | 0.13 | 0.02 | 0.04
Sr II |  0.28 $\pm$ 0.48 | 0.07 | 0.32 | 0.03 | 0.35 |  -0.47 $\pm$ 0.36 | 0.09 | 0.11 | 0.07 | 0.32 |  0.53 $\pm$ 0.34 | 0.08 | 0.17 | 0.03 | 0.28
Y II |  0.30 $\pm$ 0.20 | 0.05 | 0.19 | 0.04 | 0.03 |  -0.01 $\pm$ 0.09 | 0.08 | 0.02 | 0.04 | 0.01 |  0.59 $\pm$ 0.16 | 0.07 | 0.14 | 0.03 | 0.03
Zr II |  0.37 $\pm$ 0.14 | 0.05 | 0.12 | 0.06 | 0.02 |  0.50 $\pm$ 0.11 | 0.09 | 0.01 | 0.02 | 0.04 |  0.57 $\pm$ 0.18 | 0.14 | 0.12 | 0.01 | 0.03
Ba II |  0.30 $\pm$ 0.26 | 0.04 | 0.25 | 0.01 | 0.07 |  -0.04 $\pm$ 0.17 | 0.11 | 0.07 | 0.02 | 0.11 |  1.22 $\pm$ 0.34 | 0.15 | 0.15 | 0.01 | 0.27
| HD 180777 | HD 195689 | HD 95086
C I |  -0.21 $\pm$ 0.10 | 0.06 | 0.03 | 0.05 | 0.05 |  -0.13 $\pm$ 0.09 | 0.05 | 0.07 | 0.03 | 0.01 |  -0.12 $\pm$ 0.07 | 0.06 | 0.03 | 0.03 | 0.02
O I |  |  |  |  |  |  -0.08 $\pm$ 0.13 | 0.13 | 0.02 | 0.01 | 0.01 |  |  |  |  |
Mg I |  -0.21 $\pm$ 0.20 | 0.06 | 0.13 | 0.11 | 0.08 |  0.04 $\pm$ 0.18 | 0.08 | 0.09 | 0.07 | 0.12 |  0.10 $\pm$ 0.23 | 0.06 | 0.07 | 0.04 | 0.21
Mg II |  0.01 $\pm$ 0.20 | 0.10 | 0.11 | 0.03 | 0.13 |  0.12 $\pm$ 0.11 | 0.10 | 0.01 | 0.02 | 0.05 |  0.24 $\pm$ 0.18 | 0.11 | 0.05 | 0.02 | 0.13
Al I |  |  |  |  |  |  -0.61 $\pm$ 0.12 | 0.06 | 0.09 | 0.04 | 0.05 |  -0.45 $\pm$ 0.27 | 0.08 | 0.07 | 0.01 | 0.25
Si II |  0.20 $\pm$ 0.18 | 0.10 | 0.12 | 0.08 | 0.01 |  0.08 $\pm$ 0.07 | 0.05 | 0.02 | 0.03 | 0.04 |  -0.05 $\pm$ 0.12 | 0.07 | 0.08 | 0.05 | 0.04
Ca I |  -0.21 $\pm$ 0.32 | 0.10 | 0.22 | 0.09 | 0.19 |  -0.09 $\pm$ 0.38 | 0.08 | 0.26 | 0.10 | 0.24 |  0.08 $\pm$ 0.30 | 0.11 | 0.17 | 0.04 | 0.22
Ca II |  |  |  |  |  |  0.04 $\pm$ 0.13 | 0.08 | 0.09 | 0.04 | 0.01 |  -0.18 $\pm$ 0.12 | 0.11 | 0.05 | 0.01 | 0.01
Sc II |  0.03 $\pm$ 0.37 | 0.09 | 0.09 | 0.09 | 0.34 |  -0.14 $\pm$ 0.17 | 0.08 | 0.07 | 0.01 | 0.13 |  -0.12 $\pm$ 0.26 | 0.06 | 0.11 | 0.07 | 0.22
Ti II |  -0.08 $\pm$ 0.17 | 0.03 | 0.06 | 0.06 | 0.14 |  0.10 $\pm$ 0.16 | 0.02 | 0.06 | 0.03 | 0.15 |  -0.07 $\pm$ 0.10 | 0.02 | 0.04 | 0.04 | 0.08
Cr II |  -0.12 $\pm$ 0.12 | 0.03 | 0.07 | 0.06 | 0.07 |  0.00 $\pm$ 0.07 | 0.03 | 0.03 | 0.02 | 0.06 |  -0.05 $\pm$ 0.09 | 0.03 | 0.04 | 0.04 | 0.07
Mn I |  -0.29 $\pm$ 0.14 | 0.06 | 0.11 | 0.02 | 0.07 |  |  |  |  |  |  -0.18 $\pm$ 0.10 | 0.05 | 0.06 | 0.01 | 0.07
Fe I |  -0.19 $\pm$ 0.22 | 0.02 | 0.13 | 0.03 | 0.18 |  -0.09 $\pm$ 0.11 | 0.02 | 0.09 | 0.04 | 0.04 |  -0.08 $\pm$ 0.18 | 0.01 | 0.09 | 0.01 | 0.15
Fe II |  -0.16 $\pm$ 0.14 | 0.02 | 0.07 | 0.02 | 0.12 |  -0.08 $\pm$ 0.14 | 0.02 | 0.03 | 0.03 | 0.13 |  -0.05 $\pm$ 0.16 | 0.02 | 0.04 | 0.03 | 0.15
Ni II |  |  |  |  |  |  -0.01 $\pm$ 0.10 | 0.08 | 0.03 | 0.01 | 0.06 |  |  |  |  |
Sr II |  0.19 $\pm$ 0.27 | 0.07 | 0.16 | 0.01 | 0.22 |  -0.54 $\pm$ 0.21 | 0.08 | 0.14 | 0.01 | 0.14 |  0.35 $\pm$ 0.33 | 0.08 | 0.14 | 0.03 | 0.29
Y II |  0.01 $\pm$ 0.14 | 0.09 | 0.06 | 0.08 | 0.07 |  |  |  |  |  |  -0.07 $\pm$ 0.09 | 0.05 | 0.03 | 0.04 | 0.05
Zr II |  0.00 $\pm$ 0.14 | 0.07 | 0.04 | 0.07 | 0.09 |  |  |  |  |  |  -0.20 $\pm$ 0.12 | 0.06 | 0.08 | 0.04 | 0.05
Ba II |  0.25 $\pm$ 0.29 | 0.10 | 0.11 | 0.03 | 0.26 |  |  |  |  |  |  0.25 $\pm$ 0.27 | 0.16 | 0.07 | 0.03 | 0.20
| HD 169142 | HD 218396 | KELT-17
C I |  0.13 $\pm$ 0.09 | 0.06 | 0.02 | 0.06 | 0.01 |  -0.11 $\pm$ 0.07 | 0.04 | 0.01 | 0.05 | 0.01 |  -4.09 $\pm$ 0.17 | 0.16 | 0.02 | 0.01 | 0.02
Mg I |  -0.51 $\pm$ 0.29 | 0.08 | 0.22 | 0.09 | 0.15 |  -0.66 $\pm$ 0.24 | 0.10 | 0.13 | 0.07 | 0.17 |  -0.26 $\pm$ 0.22 | 0.09 | 0.11 | 0.04 | 0.16
Mg II |  -0.31 $\pm$ 0.25 | 0.12 | 0.17 | 0.06 | 0.12 |  -0.48 $\pm$ 0.18 | 0.08 | 0.09 | 0.05 | 0.12 |  -0.02 $\pm$ 0.24 | 0.16 | 0.10 | 0.01 | 0.14
Al I |  -1.27 $\pm$ 0.34 | 0.08 | 0.28 | 0.05 | 0.16 |  |  |  |  |  |  -0.56 $\pm$ 0.32 | 0.16 | 0.18 | 0.03 | 0.20
Si II |  -0.52 $\pm$ 0.21 | 0.06 | 0.19 | 0.08 | 0.05 |  -0.50 $\pm$ 0.21 | 0.06 | 0.19 | 0.07 | 0.04 |  0.05 $\pm$ 0.32 | 0.31 | 0.09 | 0.01 | 0.02
Ca I |  |  |  |  |  |  -0.80 $\pm$ 0.36 | 0.08 | 0.24 | 0.05 | 0.25 |  |  |  |  |
Ca II |  -0.83 $\pm$ 0.23 | 0.12 | 0.20 | 0.01 | 0.01 |  |  |  |  |  |  -0.98 $\pm$ 0.18 | 0.16 | 0.08 | 0.01 | 0.02
Sc II |  -0.67 $\pm$ 0.22 | 0.06 | 0.16 | 0.10 | 0.11 |  -0.79 $\pm$ 0.16 | 0.04 | 0.09 | 0.09 | 0.11 |  -0.88 $\pm$ 0.21 | 0.12 | 0.04 | 0.07 | 0.15
Ti II |  -0.53 $\pm$ 0.18 | 0.03 | 0.12 | 0.08 | 0.11 |  -0.67 $\pm$ 0.12 | 0.02 | 0.06 | 0.07 | 0.08 |  0.18 $\pm$ 0.20 | 0.05 | 0.06 | 0.05 | 0.18
Cr II |  -0.58 $\pm$ 0.10 | 0.03 | 0.06 | 0.07 | 0.04 |  -0.66 $\pm$ 0.09 | 0.02 | 0.04 | 0.06 | 0.04 |  0.63 $\pm$ 0.12 | 0.05 | 0.05 | 0.03 | 0.09
Mn I |  -0.53 $\pm$ 0.21 | 0.05 | 0.20 | 0.02 | 0.05 |  -0.68 $\pm$ 0.12 | 0.03 | 0.11 | 0.03 | 0.02 |  0.29 $\pm$ 0.13 | 0.08 | 0.06 | 0.01 | 0.09
Fe I |  -0.64 $\pm$ 0.25 | 0.02 | 0.22 | 0.02 | 0.11 |  -0.77 $\pm$ 0.16 | 0.01 | 0.12 | 0.02 | 0.10 |  0.47 $\pm$ 0.22 | 0.03 | 0.11 | 0.02 | 0.19
Fe II |  -0.67 $\pm$ 0.19 | 0.05 | 0.04 | 0.07 | 0.16 |  -0.70 $\pm$ 0.15 | 0.02 | 0.04 | 0.06 | 0.13 |  0.51 $\pm$ 0.17 | 0.03 | 0.07 | 0.02 | 0.15
Sr II |  -0.24 $\pm$ 0.39 | 0.08 | 0.28 | 0.03 | 0.26 |  -0.45 $\pm$ 0.30 | 0.06 | 0.14 | 0.05 | 0.25 |  0.92 $\pm$ 0.32 | 0.16 | 0.16 | 0.02 | 0.22
Y II |  -0.47 $\pm$ 0.16 | 0.06 | 0.13 | 0.08 | 0.01 |  -0.52 $\pm$ 0.13 | 0.08 | 0.08 | 0.08 | 0.01 |  1.27 $\pm$ 0.34 | 0.10 | 0.09 | 0.08 | 0.30
Zr II |  -0.34 $\pm$ 0.28 | 0.18 | 0.20 | 0.08 | 0.02 |  -0.23 $\pm$ 0.16 | 0.13 | 0.06 | 0.06 | 0.02 |  0.08 $\pm$ 0.24 | 0.16 | 0.05 | 0.07 | 0.15
Ba II |  -0.30 $\pm$ 0.28 | 0.11 | 0.21 | 0.04 | 0.15 |  -0.38 $\pm$ 0.23 | 0.10 | 0.12 | 0.03 | 0.17 |  1.47 $\pm$ 0.33 | 0.16 | 0.11 | 0.04 | 0.26
| HD 185603 | MASCARA-1 | WASP-33
C I |  -0.42 $\pm$ 0.10 | 0.07 | 0.06 | 0.01 | 0.02 |  -0.32 $\pm$ 0.08 | 0.07 | 0.02 | 0.02 | 0.04 |  -0.24 $\pm$ 0.16 | 0.15 | 0.04 | 0.03 | 0.02
O I |  |  |  |  |  |  |  |  |  |  |  0.58 $\pm$ 0.23 | 0.11 | 0.03 | 0.01 | 0.20
Mg I |  -0.52 $\pm$ 0.21 | 0.08 | 0.12 | 0.07 | 0.14 |  -0.33 $\pm$ 0.24 | 0.06 | 0.08 | 0.03 | 0.22 |  -0.11 $\pm$ 0.21 | 0.09 | 0.11 | 0.09 | 0.12
Mg II |  -0.33 $\pm$ 0.11 | 0.07 | 0.04 | 0.02 | 0.06 |  -0.12 $\pm$ 0.21 | 0.09 | 0.14 | 0.02 | 0.13 |  0.06 $\pm$ 0.21 | 0.15 | 0.04 | 0.02 | 0.13
Al I |  -1.11 $\pm$ 0.16 | 0.07 | 0.13 | 0.01 | 0.05 |  -0.34 $\pm$ 0.25 | 0.09 | 0.06 | 0.01 | 0.23 |  -0.64 $\pm$ 0.25 | 0.11 | 0.15 | 0.03 | 0.16
Si II |  -0.07 $\pm$ 0.13 | 0.08 | 0.05 | 0.08 | 0.04 |  0.07 $\pm$ 0.17 | 0.09 | 0.14 | 0.05 | 0.02 |  0.11 $\pm$ 0.20 | 0.15 | 0.10 | 0.07 | 0.01
Ca I |  -0.59 $\pm$ 0.39 | 0.07 | 0.28 | 0.07 | 0.25 |  0.01 $\pm$ 0.37 | 0.09 | 0.20 | 0.04 | 0.29 |  -0.01 $\pm$ 0.39 | 0.15 | 0.23 | 0.07 | 0.26
Ca II |  -0.45 $\pm$ 0.14 | 0.07 | 0.12 | 0.02 | 0.01 |  0.13 $\pm$ 0.10 | 0.09 | 0.04 | 0.01 | 0.01 |  -0.20 $\pm$ 0.17 | 0.15 | 0.08 | 0.01 | 0.01
Sc II |  -0.71 $\pm$ 0.24 | 0.07 | 0.20 | 0.10 | 0.06 |  0.00 $\pm$ 0.28 | 0.05 | 0.09 | 0.06 | 0.25 |  0.02 $\pm$ 0.36 | 0.08 | 0.12 | 0.10 | 0.32
Ti II |  -0.25 $\pm$ 0.18 | 0.02 | 0.09 | 0.05 | 0.15 |  -0.04 $\pm$ 0.13 | 0.02 | 0.02 | 0.04 | 0.12 |  0.08 $\pm$ 0.16 | 0.04 | 0.04 | 0.06 | 0.13
Cr II |  -0.21 $\pm$ 0.10 | 0.02 | 0.03 | 0.04 | 0.08 |  -0.09 $\pm$ 0.12 | 0.05 | 0.06 | 0.04 | 0.08 |  0.13 $\pm$ 0.11 | 0.06 | 0.06 | 0.03 | 0.08
Mn I |  -0.26 $\pm$ 0.29 | 0.17 | 0.23 | 0.08 | 0.01 |  -0.07 $\pm$ 0.11 | 0.09 | 0.06 | 0.02 | 0.03 |  0.05 $\pm$ 0.11 | 0.08 | 0.06 | 0.02 | 0.05
Fe I |  -0.35 $\pm$ 0.15 | 0.02 | 0.13 | 0.03 | 0.06 |  -0.11 $\pm$ 0.15 | 0.02 | 0.06 | 0.01 | 0.14 |  0.11 $\pm$ 0.23 | 0.04 | 0.12 | 0.02 | 0.20
Fe II |  -0.30 $\pm$ 0.15 | 0.02 | 0.06 | 0.04 | 0.13 |  -0.10 $\pm$ 0.13 | 0.02 | 0.02 | 0.03 | 0.13 |  0.13 $\pm$ 0.16 | 0.04 | 0.04 | 0.02 | 0.15
Ni II |  -0.15 $\pm$ 0.15 | 0.07 | 0.08 | 0.01 | 0.10 |  |  |  |  |  |  |  |  |  |
Sr II |  -0.81 $\pm$ 0.32 | 0.07 | 0.20 | 0.04 | 0.24 |  0.49 $\pm$ 0.33 | 0.14 | 0.15 | 0.02 | 0.26 |  0.45 $\pm$ 0.36 | 0.11 | 0.16 | 0.02 | 0.31
Y II |  |  |  |  |  |  0.54 $\pm$ 0.11 | 0.06 | 0.02 | 0.06 | 0.08 |  0.33 $\pm$ 0.15 | 0.13 | 0.03 | 0.05 | 0.05
Zr II |  |  |  |  |  |  0.30 $\pm$ 0.15 | 0.06 | 0.11 | 0.06 | 0.05 |  -0.20 $\pm$ 0.18 | 0.15 | 0.08 | 0.03 | 0.05
Ba II |  0.43 $\pm$ 0.20 | 0.08 | 0.15 | 0.01 | 0.11 |  0.58 $\pm$ 0.29 | 0.10 | 0.09 | 0.02 | 0.26 |  0.94 $\pm$ 0.26 | 0.10 | 0.08 | 0.03 | 0.22
Table 1: Continued. Abundances derived in this work. For each specie, we present average$\pm$total error and the uncertainties e1, …, e4. Specie | [N/H] |  e1 |  e2 |  e3 |  e4 | [N/H] |  e1 |  e2 |  e3 |  e4 | [N/H] |  e1 |  e2 |  e3 |  e4
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
| HR 4502 A | BU Psc | HD 29391
C I |  -0.15 $\pm$ 0.14 | 0.04 | 0.13 | 0.03 | 0.01 |  -0.20 $\pm$ 0.07 | 0.05 | 0.01 | 0.03 | 0.02 |  -0.22 $\pm$ 0.09 | 0.07 | 0.03 | 0.04 | 0.04
O I |  -0.25 $\pm$ 0.07 | 0.07 | 0.01 | 0.02 | 0.01 |  |  |  |  |  |  |  |  |  |
Mg I |  0.18 $\pm$ 0.28 | 0.15 | 0.20 | 0.07 | 0.11 |  -0.29 $\pm$ 0.14 | 0.06 | 0.06 | 0.07 | 0.09 |  -0.13 $\pm$ 0.20 | 0.08 | 0.12 | 0.09 | 0.10
Mg II |  0.04 $\pm$ 0.12 | 0.11 | 0.02 | 0.04 | 0.01 |  -0.08 $\pm$ 0.17 | 0.11 | 0.04 | 0.02 | 0.13 |  0.04 $\pm$ 0.20 | 0.13 | 0.06 | 0.02 | 0.13
Al I |  -0.35 $\pm$ 0.21 | 0.06 | 0.19 | 0.02 | 0.06 |  -0.90 $\pm$ 0.18 | 0.07 | 0.05 | 0.02 | 0.15 |  -0.72 $\pm$ 0.21 | 0.09 | 0.11 | 0.03 | 0.15
Al II |  -0.21 $\pm$ 0.12 | 0.09 | 0.07 | 0.05 | 0.01 |  |  |  |  |  |  |  |  |  |
Si II |  -0.15 $\pm$ 0.07 | 0.04 | 0.03 | 0.04 | 0.04 |  -0.05 $\pm$ 0.12 | 0.09 | 0.06 | 0.05 | 0.01 |  -0.04 $\pm$ 0.27 | 0.24 | 0.10 | 0.07 | 0.01
Ca I |  0.22 $\pm$ 0.38 | 0.09 | 0.29 | 0.08 | 0.22 |  -0.20 $\pm$ 0.28 | 0.11 | 0.10 | 0.06 | 0.23 |  -0.09 $\pm$ 0.37 | 0.13 | 0.23 | 0.08 | 0.24
Ca II |  0.00 $\pm$ 0.23 | 0.09 | 0.21 | 0.06 | 0.01 |  -0.34 $\pm$ 0.11 | 0.07 | 0.06 | 0.01 | 0.05 |  -0.09 $\pm$ 0.18 | 0.13 | 0.11 | 0.03 | 0.01
Sc II |  -0.11 $\pm$ 0.16 | 0.04 | 0.15 | 0.02 | 0.03 |  0.01 $\pm$ 0.32 | 0.08 | 0.04 | 0.06 | 0.31 |  0.05 $\pm$ 0.34 | 0.07 | 0.10 | 0.10 | 0.30
Ti II |  0.01 $\pm$ 0.12 | 0.01 | 0.12 | 0.02 | 0.04 |  -0.10 $\pm$ 0.14 | 0.03 | 0.02 | 0.04 | 0.13 |  -0.02 $\pm$ 0.15 | 0.03 | 0.08 | 0.06 | 0.12
Cr II |  -0.07 $\pm$ 0.08 | 0.02 | 0.07 | 0.03 | 0.02 |  -0.20 $\pm$ 0.07 | 0.03 | 0.02 | 0.04 | 0.04 |  -0.08 $\pm$ 0.10 | 0.04 | 0.04 | 0.05 | 0.07
Mn I |  -0.22 $\pm$ 0.25 | 0.05 | 0.24 | 0.02 | 0.01 |  -0.34 $\pm$ 0.07 | 0.04 | 0.04 | 0.01 | 0.05 |  -0.24 $\pm$ 0.11 | 0.05 | 0.09 | 0.01 | 0.04
Fe I |  -0.04 $\pm$ 0.18 | 0.01 | 0.18 | 0.04 | 0.02 |  -0.31 $\pm$ 0.18 | 0.01 | 0.06 | 0.01 | 0.17 |  |  |  |  |
Fe II |  -0.11 $\pm$ 0.10 | 0.02 | 0.07 | 0.03 | 0.07 |  -0.25 $\pm$ 0.11 | 0.03 | 0.04 | 0.02 | 0.10 |  -0.06 $\pm$ 0.10 | 0.03 | 0.06 | 0.03 | 0.07
Ni II |  -0.22 $\pm$ 0.08 | 0.06 | 0.05 | 0.02 | 0.01 |  |  |  |  |  |  |  |  |  |
Sr II |  -0.08 $\pm$ 0.33 | 0.06 | 0.25 | 0.01 | 0.22 |  0.23 $\pm$ 0.28 | 0.07 | 0.05 | 0.01 | 0.27 |  0.13 $\pm$ 0.34 | 0.09 | 0.16 | 0.03 | 0.28
Y II |  0.01 $\pm$ 0.19 | 0.06 | 0.18 | 0.01 | 0.01 |  -0.04 $\pm$ 0.11 | 0.09 | 0.03 | 0.05 | 0.05 |  0.03 $\pm$ 0.13 | 0.07 | 0.06 | 0.07 | 0.05
Zr II |  0.22 $\pm$ 0.13 | 0.03 | 0.13 | 0.03 | 0.01 |  0.15 $\pm$ 0.21 | 0.20 | 0.02 | 0.04 | 0.06 |  -0.16 $\pm$ 0.17 | 0.13 | 0.08 | 0.04 | 0.05
Ba II |  0.29 $\pm$ 0.26 | 0.12 | 0.23 | 0.04 | 0.01 |  0.19 $\pm$ 0.28 | 0.11 | 0.04 | 0.02 | 0.25 |  0.20 $\pm$ 0.25 | 0.06 | 0.09 | 0.03 | 0.22
| HD 105850 | HD 110058 | HD 115820
C I |  -0.41 $\pm$ 0.13 | 0.08 | 0.10 | 0.01 | 0.02 |  -0.14 $\pm$ 0.06 | 0.04 | 0.02 | 0.03 | 0.02 |  -0.13 $\pm$ 0.08 | 0.07 | 0.03 | 0.03 | 0.02
Mg I |  -0.27 $\pm$ 0.19 | 0.10 | 0.11 | 0.03 | 0.12 |  -1.26 $\pm$ 0.16 | 0.09 | 0.06 | 0.02 | 0.12 |  -0.04 $\pm$ 0.18 | 0.08 | 0.08 | 0.06 | 0.12
Mg II |  -0.07 $\pm$ 0.14 | 0.12 | 0.04 | 0.01 | 0.07 |  -1.01 $\pm$ 0.21 | 0.09 | 0.14 | 0.05 | 0.11 |  0.20 $\pm$ 0.19 | 0.14 | 0.05 | 0.01 | 0.11
Al I |  -0.80 $\pm$ 0.13 | 0.06 | 0.10 | 0.01 | 0.07 |  -2.14 $\pm$ 0.15 | 0.09 | 0.12 | 0.01 | 0.01 |  -0.46 $\pm$ 0.22 | 0.10 | 0.08 | 0.03 | 0.18
Si II |  -0.45 $\pm$ 0.12 | 0.08 | 0.04 | 0.03 | 0.07 |  |  |  |  |  |  0.21 $\pm$ 0.21 | 0.10 | 0.07 | 0.04 | 0.17
Ca I |  -0.07 $\pm$ 0.39 | 0.09 | 0.26 | 0.05 | 0.27 |  -1.32 $\pm$ 0.36 | 0.09 | 0.20 | 0.01 | 0.29 |  0.08 $\pm$ 0.33 | 0.14 | 0.18 | 0.06 | 0.23
Ca II |  -0.15 $\pm$ 0.14 | 0.09 | 0.11 | 0.01 | 0.01 |  -1.17 $\pm$ 0.11 | 0.09 | 0.06 | 0.01 | 0.01 |  -0.07 $\pm$ 0.15 | 0.14 | 0.05 | 0.01 | 0.01
Sc II |  -0.21 $\pm$ 0.17 | 0.07 | 0.15 | 0.01 | 0.06 |  -1.45 $\pm$ 0.11 | 0.09 | 0.02 | 0.04 | 0.03 |  0.12 $\pm$ 0.31 | 0.10 | 0.11 | 0.06 | 0.26
Ti II |  -0.09 $\pm$ 0.18 | 0.03 | 0.09 | 0.02 | 0.15 |  -1.32 $\pm$ 0.12 | 0.04 | 0.06 | 0.05 | 0.09 |  0.20 $\pm$ 0.17 | 0.04 | 0.03 | 0.05 | 0.15
Cr II |  -0.27 $\pm$ 0.07 | 0.03 | 0.04 | 0.02 | 0.04 |  -1.03 $\pm$ 0.11 | 0.10 | 0.05 | 0.01 | 0.02 |  0.05 $\pm$ 0.13 | 0.04 | 0.04 | 0.03 | 0.12
Mn I |  |  |  |  |  |  |  |  |  |  |  -0.07 $\pm$ 0.11 | 0.05 | 0.06 | 0.02 | 0.07
Fe I |  -0.29 $\pm$ 0.14 | 0.02 | 0.12 | 0.02 | 0.06 |  -1.35 $\pm$ 0.13 | 0.03 | 0.08 | 0.01 | 0.09 |  -0.06 $\pm$ 0.18 | 0.02 | 0.09 | 0.02 | 0.15
Fe II |  -0.24 $\pm$ 0.13 | 0.02 | 0.05 | 0.02 | 0.12 |  -1.28 $\pm$ 0.08 | 0.03 | 0.02 | 0.04 | 0.06 |  -0.02 $\pm$ 0.09 | 0.04 | 0.05 | 0.02 | 0.06
Ni II |  -0.22 $\pm$ 0.18 | 0.09 | 0.06 | 0.01 | 0.14 |  |  |  |  |  |  |  |  |  |
Sr II |  -0.59 $\pm$ 0.29 | 0.08 | 0.19 | 0.01 | 0.21 |  -2.01 $\pm$ 0.19 | 0.13 | 0.11 | 0.04 | 0.08 |  0.09 $\pm$ 0.33 | 0.15 | 0.15 | 0.04 | 0.25
Y II |  |  |  |  |  |  |  |  |  |  |  0.17 $\pm$ 0.11 | 0.09 | 0.03 | 0.05 | 0.02
Zr II |  -0.06 $\pm$ 0.10 | 0.09 | 0.03 | 0.01 | 0.04 |  |  |  |  |  |  -0.13 $\pm$ 0.17 | 0.14 | 0.09 | 0.02 | 0.01
Ba II |  -0.01 $\pm$ 0.25 | 0.20 | 0.15 | 0.02 | 0.04 |  -1.13 $\pm$ 0.21 | 0.16 | 0.13 | 0.03 | 0.04 |  0.49 $\pm$ 0.25 | 0.07 | 0.08 | 0.02 | 0.23
| HD 120326 | HD 129926 | HD 133803
C I |  -0.17 $\pm$ 0.09 | 0.08 | 0.01 | 0.03 | 0.02 |  -0.09 $\pm$ 0.19 | 0.16 | 0.02 | 0.08 | 0.07 |  -0.07 $\pm$ 0.10 | 0.08 | 0.01 | 0.05 | 0.03
Mg I |  -0.23 $\pm$ 0.15 | 0.08 | 0.11 | 0.06 | 0.05 |  0.09 $\pm$ 0.20 | 0.10 | 0.12 | 0.10 | 0.06 |  -0.03 $\pm$ 0.21 | 0.10 | 0.14 | 0.12 | 0.05
Mg II |  -0.02 $\pm$ 0.20 | 0.14 | 0.07 | 0.02 | 0.13 |  0.38 $\pm$ 0.23 | 0.18 | 0.03 | 0.02 | 0.13 |  0.29 $\pm$ 0.22 | 0.17 | 0.07 | 0.04 | 0.12
Al I |  -0.51 $\pm$ 0.14 | 0.10 | 0.09 | 0.04 | 0.04 |  -0.23 $\pm$ 0.20 | 0.13 | 0.09 | 0.07 | 0.11 |  -0.23 $\pm$ 0.22 | 0.12 | 0.14 | 0.10 | 0.07
Si II |  0.32 $\pm$ 0.13 | 0.10 | 0.07 | 0.03 | 0.01 |  0.53 $\pm$ 0.19 | 0.13 | 0.08 | 0.07 | 0.09 |  0.27 $\pm$ 0.25 | 0.15 | 0.10 | 0.06 | 0.17
Ca I |  0.01 $\pm$ 0.25 | 0.14 | 0.17 | 0.05 | 0.11 |  0.41 $\pm$ 0.31 | 0.18 | 0.18 | 0.09 | 0.16 |  0.03 $\pm$ 0.36 | 0.17 | 0.24 | 0.10 | 0.19
Ca II |  0.20 $\pm$ 0.17 | 0.14 | 0.09 | 0.06 | 0.02 |  0.52 $\pm$ 0.25 | 0.18 | 0.11 | 0.14 | 0.02 |  0.32 $\pm$ 0.32 | 0.17 | 0.12 | 0.24 | 0.01
Sc II |  0.06 $\pm$ 0.28 | 0.17 | 0.07 | 0.04 | 0.21 |  0.95 $\pm$ 0.33 | 0.09 | 0.14 | 0.07 | 0.28 |  0.22 $\pm$ 0.31 | 0.10 | 0.15 | 0.11 | 0.23
Ti II |  -0.05 $\pm$ 0.14 | 0.03 | 0.05 | 0.02 | 0.13 |  0.99 $\pm$ 0.21 | 0.04 | 0.05 | 0.04 | 0.20 |  0.10 $\pm$ 0.15 | 0.04 | 0.05 | 0.08 | 0.11
Cr II |  -0.11 $\pm$ 0.08 | 0.05 | 0.04 | 0.02 | 0.03 |  0.58 $\pm$ 0.18 | 0.14 | 0.04 | 0.04 | 0.09 |  0.19 $\pm$ 0.11 | 0.06 | 0.07 | 0.05 | 0.05
Mn I |  -0.33 $\pm$ 0.14 | 0.05 | 0.09 | 0.01 | 0.10 |  |  |  |  |  |  0.00 $\pm$ 0.14 | 0.07 | 0.05 | 0.05 | 0.10
Fe I |  -0.17 $\pm$ 0.20 | 0.02 | 0.11 | 0.02 | 0.17 |  0.39 $\pm$ 0.29 | 0.06 | 0.12 | 0.06 | 0.25 |  0.03 $\pm$ 0.24 | 0.03 | 0.14 | 0.04 | 0.19
Fe II |  -0.11 $\pm$ 0.10 | 0.04 | 0.06 | 0.01 | 0.07 |  0.38 $\pm$ 0.12 | 0.11 | 0.03 | 0.01 | 0.04 |  0.02 $\pm$ 0.15 | 0.06 | 0.08 | 0.02 | 0.11
Sr II |  0.12 $\pm$ 0.22 | 0.10 | 0.12 | 0.01 | 0.15 |  0.62 $\pm$ 0.27 | 0.13 | 0.15 | 0.04 | 0.18 |  0.16 $\pm$ 0.33 | 0.12 | 0.19 | 0.02 | 0.24
Y II |  0.07 $\pm$ 0.14 | 0.09 | 0.05 | 0.04 | 0.08 |  1.10$\pm$ 0.25 | 0.18 | 0.03 | 0.04 | 0.16 |  0.10 $\pm$ 0.21 | 0.13 | 0.09 | 0.12 | 0.05
Zr II |  -0.02 $\pm$ 0.20 | 0.17 | 0.07 | 0.04 | 0.07 |  |  |  |  |  |  -0.27 $\pm$ 0.21 | 0.17 | 0.09 | 0.01 | 0.08
Ba II |  0.16 $\pm$ 0.23 | 0.07 | 0.07 | 0.01 | 0.21 |  1.27 $\pm$ 0.28 | 0.21 | 0.08 | 0.01 | 0.17 |  0.52 $\pm$ 0.27 | 0.13 | 0.09 | 0.03 | 0.23
| HD 146624 | HD 153053 | HD 156751
C I |  -0.42 $\pm$ 0.11 | 0.05 | 0.10 | 0.01 | 0.01 |  -0.18 $\pm$ 0.06 | 0.05 | 0.01 | 0.02 | 0.02 |  -0.13 $\pm$ 0.08 | 0.07 | 0.02 | 0.04 | 0.01
O I |  -0.39 $\pm$ 0.13 | 0.12 | 0.02 | 0.01 | 0.02 |  |  |  |  |  |  |  |  |  |
Mg I |  -0.10 $\pm$ 0.20 | 0.07 | 0.14 | 0.03 | 0.12 |  -0.30 $\pm$ 0.23 | 0.09 | 0.04 | 0.03 | 0.20 |  -0.26 $\pm$ 0.22 | 0.09 | 0.10 | 0.08 | 0.15
Mg II |  -0.01 $\pm$ 0.08 | 0.08 | 0.01 | 0.02 | 0.01 |  -0.11 $\pm$ 0.17 | 0.11 | 0.06 | 0.05 | 0.11 |  -0.01 $\pm$ 0.20 | 0.14 | 0.07 | 0.04 | 0.12
Al I |  -0.48 $\pm$ 0.18 | 0.07 | 0.16 | 0.01 | 0.06 |  -0.69 $\pm$ 0.24 | 0.14 | 0.05 | 0.02 | 0.20 |  -0.65 $\pm$ 0.27 | 0.10 | 0.07 | 0.04 | 0.24
Si II |  -0.05 $\pm$ 0.08 | 0.05 | 0.03 | 0.02 | 0.05 |  -0.35 $\pm$ 0.18 | 0.11 | 0.05 | 0.04 | 0.13 |  -0.43 $\pm$ 0.22 | 0.09 | 0.09 | 0.08 | 0.17
Ca I |  -0.23 $\pm$ 0.27 | 0.10 | 0.20 | 0.03 | 0.15 |  -0.04 $\pm$ 0.33 | 0.11 | 0.13 | 0.01 | 0.28 |  -0.03 $\pm$ 0.36 | 0.14 | 0.23 | 0.05 | 0.24
Ca II |  -0.23 $\pm$ 0.16 | 0.10 | 0.13 | 0.02 | 0.01 |  -0.02 $\pm$ 0.11 | 0.11 | 0.02 | 0.03 | 0.01 |  -0.35 $\pm$ 0.16 | 0.14 | 0.08 | 0.02 | 0.01
Sc II |  -0.34 $\pm$ 0.12 | 0.06 | 0.10 | 0.02 | 0.02 |  -0.22 $\pm$ 0.28 | 0.06 | 0.06 | 0.08 | 0.26 |  -0.34 $\pm$ 0.30 | 0.11 | 0.14 | 0.10 | 0.22
Ti II |  0.01 $\pm$ 0.09 | 0.02 | 0.08 | 0.01 | 0.04 |  -0.17 $\pm$ 0.10 | 0.02 | 0.02 | 0.05 | 0.09 |  -0.15 $\pm$ 0.15 | 0.04 | 0.05 | 0.07 | 0.12
Cr II |  0.15 $\pm$ 0.07 | 0.02 | 0.05 | 0.01 | 0.04 |  -0.28 $\pm$ 0.08 | 0.04 | 0.02 | 0.03 | 0.07 |  -0.53 $\pm$ 0.10 | 0.05 | 0.05 | 0.04 | 0.05
Mn I |  -0.07 $\pm$ 0.18 | 0.08 | 0.16 | 0.01 | 0.01 |  -0.21 $\pm$ 0.10 | 0.05 | 0.07 | 0.03 | 0.05 |  -0.82 $\pm$ 0.12 | 0.07 | 0.07 | 0.04 | 0.05
Fe I |  -0.01 $\pm$ 0.14 | 0.01 | 0.13 | 0.02 | 0.03 |  -0.29 $\pm$ 0.14 | 0.02 | 0.06 | 0.01 | 0.13 |  -0.47 $\pm$ 0.17 | 0.03 | 0.11 | 0.02 | 0.13
Fe II |  0.01 $\pm$ 0.11 | 0.02 | 0.06 | 0.02 | 0.09 |  -0.22 $\pm$ 0.15 | 0.02 | 0.03 | 0.04 | 0.14 |  -0.45 $\pm$ 0.09 | 0.04 | 0.04 | 0.04 | 0.07
Ni II |  0.16 $\pm$ 0.08 | 0.07 | 0.04 | 0.01 | 0.01 |  |  |  |  |  |  |  |  |  |
Sr II |  -0.11 $\pm$ 0.30 | 0.07 | 0.18 | 0.01 | 0.23 |  0.25 $\pm$ 0.32 | 0.07 | 0.10 | 0.05 | 0.29 |  0.08 $\pm$ 0.31 | 0.10 | 0.18 | 0.02 | 0.23
Y II |  0.00 $\pm$ 0.18 | 0.06 | 0.17 | 0.01 | 0.01 |  0.34 $\pm$ 0.10 | 0.06 | 0.03 | 0.06 | 0.05 |  -0.09 $\pm$ 0.12 | 0.07 | 0.05 | 0.08 | 0.03
Zr II |  0.21 $\pm$ 0.16 | 0.12 | 0.11 | 0.01 | 0.01 |  0.50 $\pm$ 0.13 | 0.11 | 0.02 | 0.04 | 0.04 |  -0.25 $\pm$ 0.18 | 0.14 | 0.11 | 0.04 | 0.01
Ba II |  1.01 $\pm$ 0.19 | 0.06 | 0.17 | 0.02 | 0.07 |  0.35 $\pm$ 0.22 | 0.12 | 0.05 | 0.03 | 0.18 |  0.34 $\pm$ 0.33 | 0.10 | 0.11 | 0.02 | 0.30
Table 1: Continued. Abundances derived in this work. For each specie, we present average$\pm$total error and the uncertainties e1, …, e4. Specie | [N/H] |  e1 |  e2 |  e3 |  e4 | [N/H] |  e1 |  e2 |  e3 |  e4 | [N/H] |  e1 |  e2 |  e3 |  e4
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
| HD 159492 | HD 188228 | HD 23281
C I |  -0.24 $\pm$ 0.06 | 0.05 | 0.03 | 0.02 | 0.02 |  -0.55 $\pm$ 0.16 | 0.13 | 0.08 | 0.02 | 0.02 |  -0.30 $\pm$ 0.07 | 0.06 | 0.03 | 0.02 | 0.02
Mg I |  -0.06 $\pm$ 0.23 | 0.08 | 0.03 | 0.03 | 0.21 |  0.02 $\pm$ 0.13 | 0.07 | 0.10 | 0.03 | 0.02 |  -0.13 $\pm$ 0.20 | 0.08 | 0.06 | 0.02 | 0.17
Mg II |  0.16 $\pm$ 0.16 | 0.09 | 0.08 | 0.03 | 0.10 |  0.02 $\pm$ 0.10 | 0.10 | 0.03 | 0.01 | 0.01 |  0.10 $\pm$ 0.17 | 0.09 | 0.07 | 0.05 | 0.11
Al I |  -0.61 $\pm$ 0.25 | 0.08 | 0.05 | 0.01 | 0.24 |  -0.36 $\pm$ 0.18 | 0.08 | 0.16 | 0.01 | 0.01 |  -0.46 $\pm$ 0.24 | 0.07 | 0.10 | 0.01 | 0.21
Si II |  -0.06 $\pm$ 0.14 | 0.11 | 0.06 | 0.04 | 0.04 |  -0.13 $\pm$ 0.09 | 0.08 | 0.02 | 0.02 | 0.03 |  -0.07 $\pm$ 0.17 | 0.14 | 0.06 | 0.05 | 0.05
Ca I |  0.07 $\pm$ 0.31 | 0.09 | 0.10 | 0.01 | 0.28 |  -0.19 $\pm$ 0.26 | 0.08 | 0.24 | 0.04 | 0.02 |  -0.34 $\pm$ 0.33 | 0.09 | 0.19 | 0.04 | 0.25
Ca II |  0.23 $\pm$ 0.10 | 0.09 | 0.02 | 0.03 | 0.01 |  -0.22 $\pm$ 0.12 | 0.08 | 0.08 | 0.03 | 0.01 |  -0.26 $\pm$ 0.10 | 0.09 | 0.03 | 0.03 | 0.01
Sc II |  0.09 $\pm$ 0.24 | 0.05 | 0.03 | 0.07 | 0.23 |  -0.56 $\pm$ 0.11 | 0.08 | 0.08 | 0.01 | 0.01 |  -0.41 $\pm$ 0.26 | 0.05 | 0.07 | 0.12 | 0.21
Ti II |  0.07 $\pm$ 0.13 | 0.03 | 0.03 | 0.04 | 0.12 |  -0.03 $\pm$ 0.11 | 0.02 | 0.08 | 0.01 | 0.07 |  0.00 $\pm$ 0.14 | 0.02 | 0.04 | 0.06 | 0.12
Cr II |  -0.06 $\pm$ 0.08 | 0.03 | 0.01 | 0.04 | 0.07 |  0.12 $\pm$ 0.06 | 0.03 | 0.04 | 0.01 | 0.04 |  0.20 $\pm$ 0.07 | 0.03 | 0.03 | 0.04 | 0.04
Mn I |  -0.11 $\pm$ 0.09 | 0.06 | 0.06 | 0.01 | 0.02 |  |  |  |  |  |  -0.10 $\pm$ 0.11 | 0.05 | 0.05 | 0.01 | 0.09
Fe I |  -0.04 $\pm$ 0.16 | 0.01 | 0.06 | 0.01 | 0.15 |  0.03 $\pm$ 0.11 | 0.02 | 0.10 | 0.02 | 0.02 |  0.08 $\pm$ 0.18 | 0.02 | 0.07 | 0.01 | 0.16
Fe II |  -0.02 $\pm$ 0.11 | 0.02 | 0.02 | 0.03 | 0.10 |  0.02 $\pm$ 0.08 | 0.02 | 0.04 | 0.02 | 0.06 |  0.11 $\pm$ 0.10 | 0.03 | 0.04 | 0.04 | 0.08
Ni II |  |  |  |  |  |  0.09 $\pm$ 0.09 | 0.08 | 0.04 | 0.01 | 0.01 |  |  |  |  |
Sr II |  0.23 $\pm$ 0.31 | 0.06 | 0.06 | 0.04 | 0.29 |  -0.32 $\pm$ 0.16 | 0.06 | 0.14 | 0.01 | 0.06 |  0.48 $\pm$ 0.28 | 0.07 | 0.12 | 0.02 | 0.24
Y II |  0.32 $\pm$ 0.09 | 0.06 | 0.04 | 0.04 | 0.04 |  |  |  |  |  |  0.48 $\pm$ 0.10 | 0.06 | 0.04 | 0.02 | 0.08
Zr II |  0.33 $\pm$ 0.08 | 0.07 | 0.01 | 0.03 | 0.03 |  |  |  |  |  |  0.14 $\pm$ 0.18 | 0.07 | 0.08 | 0.03 | 0.15
Ba II |  0.39 $\pm$ 0.21 | 0.10 | 0.07 | 0.02 | 0.18 |  0.99 $\pm$ 0.18 | 0.11 | 0.14 | 0.02 | 0.01 |  0.92 $\pm$ 0.22 | 0.06 | 0.07 | 0.02 | 0.20
| HD 50445 | HD 56537 | HD 88955
C I |  -0.22 $\pm$ 0.05 | 0.04 | 0.01 | 0.02 | 0.02 |  -0.42 $\pm$ 0.13 | 0.11 | 0.07 | 0.02 | 0.01 |  -0.61 $\pm$ 0.11 | 0.07 | 0.09 | 0.02 | 0.02
Mg I |  -0.25 $\pm$ 0.24 | 0.09 | 0.04 | 0.02 | 0.21 |  -0.39 $\pm$ 0.21 | 0.07 | 0.07 | 0.03 | 0.18 |  -0.37 $\pm$ 0.21 | 0.09 | 0.11 | 0.04 | 0.14
Mg II |  -0.09 $\pm$ 0.16 | 0.11 | 0.05 | 0.03 | 0.11 |  -0.09 $\pm$ 0.13 | 0.11 | 0.03 | 0.01 | 0.07 |  -0.09 $\pm$ 0.14 | 0.12 | 0.02 | 0.01 | 0.07
Al I |  -0.69 $\pm$ 0.26 | 0.10 | 0.07 | 0.01 | 0.23 |  -1.23 $\pm$ 0.14 | 0.08 | 0.06 | 0.01 | 0.11 |  -0.97 $\pm$ 0.16 | 0.07 | 0.11 | 0.03 | 0.09
Si II |  -0.34 $\pm$ 0.15 | 0.08 | 0.06 | 0.05 | 0.09 |  -0.28 $\pm$ 0.16 | 0.09 | 0.08 | 0.04 | 0.10 |  -0.34 $\pm$ 0.11 | 0.09 | 0.03 | 0.04 | 0.05
Ca I |  -0.23 $\pm$ 0.28 | 0.08 | 0.11 | 0.02 | 0.24 |  |  |  |  |  |  -0.39 $\pm$ 0.42 | 0.09 | 0.32 | 0.05 | 0.24
Ca II |  -0.25 $\pm$ 0.09 | 0.08 | 0.02 | 0.03 | 0.01 |  -0.11 $\pm$ 0.12 | 0.11 | 0.06 | 0.02 | 0.01 |  -0.28 $\pm$ 0.15 | 0.09 | 0.11 | 0.01 | 0.01
Sc II |  -0.53 $\pm$ 0.21 | 0.04 | 0.05 | 0.08 | 0.19 |  -0.27 $\pm$ 0.21 | 0.05 | 0.11 | 0.06 | 0.17 |  -0.39 $\pm$ 0.19 | 0.05 | 0.14 | 0.03 | 0.12
Ti II |  -0.41 $\pm$ 0.19 | 0.03 | 0.02 | 0.05 | 0.19 |  -0.16 $\pm$ 0.19 | 0.03 | 0.05 | 0.04 | 0.18 |  -0.19 $\pm$ 0.19 | 0.02 | 0.08 | 0.02 | 0.17
Cr II |  -0.33 $\pm$ 0.10 | 0.03 | 0.02 | 0.04 | 0.09 |  -0.37 $\pm$ 0.11 | 0.05 | 0.04 | 0.03 | 0.08 |  -0.40 $\pm$ 0.08 | 0.04 | 0.04 | 0.02 | 0.06
Mn I |  -0.26 $\pm$ 0.12 | 0.10 | 0.06 | 0.01 | 0.04 |  -0.28 $\pm$ 0.16 | 0.07 | 0.14 | 0.03 | 0.02 |  |  |  |  |
Fe I |  -0.31 $\pm$ 0.13 | 0.01 | 0.05 | 0.01 | 0.12 |  -0.51 $\pm$ 0.13 | 0.02 | 0.10 | 0.01 | 0.08 |  -0.50 $\pm$ 0.14 | 0.02 | 0.13 | 0.02 | 0.04
Fe II |  -0.28 $\pm$ 0.16 | 0.02 | 0.01 | 0.05 | 0.16 |  -0.43 $\pm$ 0.16 | 0.03 | 0.03 | 0.03 | 0.15 |  -0.45 $\pm$ 0.13 | 0.02 | 0.06 | 0.02 | 0.12
Ni II |  |  |  |  |  |  |  |  |  |  |  -0.31 $\pm$ 0.14 | 0.09 | 0.07 | 0.01 | 0.08
Sr II |  0.03 $\pm$ 0.26 | 0.07 | 0.09 | 0.06 | 0.23 |  -0.72 $\pm$ 0.30 | 0.07 | 0.16 | 0.04 | 0.24 |  -0.58 $\pm$ 0.31 | 0.07 | 0.18 | 0.01 | 0.24
Y II |  0.14 $\pm$ 0.10 | 0.07 | 0.03 | 0.05 | 0.03 |  -0.07 $\pm$ 0.10 | 0.07 | 0.06 | 0.04 | 0.02 |  -0.08 $\pm$ 0.12 | 0.07 | 0.10 | 0.02 | 0.01
Zr II |  0.04 $\pm$ 0.11 | 0.08 | 0.05 | 0.05 | 0.01 |  -0.21 $\pm$ 0.12 | 0.11 | 0.03 | 0.03 | 0.05 |  0.03 $\pm$ 0.12 | 0.09 | 0.07 | 0.02 | 0.01
Ba II |  0.25 $\pm$ 0.19 | 0.06 | 0.05 | 0.02 | 0.17 |  -0.22 $\pm$ 0.19 | 0.15 | 0.11 | 0.01 | 0.05 |  -0.10 $\pm$ 0.18 | 0.12 | 0.14 | 0.01 | 0.02
| V435 Car | HAT-P-49 |  $\lambda$ Boötis
C I |  -0.07 $\pm$ 0.08 | 0.07 | 0.02 | 0.01 | 0.02 |  0.04 $\pm$ 0.06 | 0.04 | 0.02 | 0.04 | 0.01 |  -0.37 $\pm$ 0.08 | 0.06 | 0.05 | 0.01 | 0.01
O I |  |  |  |  |  |  |  |  |  |  |  -0.32 $\pm$ 0.13 | 0.13 | 0.01 | 0.02 | 0.01
Mg I |  -0.09 $\pm$ 0.20 | 0.08 | 0.09 | 0.11 | 0.11 |  -0.09 $\pm$ 0.12 | 0.07 | 0.06 | 0.07 | 0.03 |  -2.26 $\pm$ 0.13 | 0.09 | 0.09 | 0.01 | 0.04
Mg II |  0.32 $\pm$ 0.20 | 0.14 | 0.08 | 0.08 | 0.09 |  0.25 $\pm$ 0.19 | 0.10 | 0.08 | 0.01 | 0.14 |  -2.07 $\pm$ 0.13 | 0.13 | 0.02 | 0.01 | 0.02
Al I |  -0.60 $\pm$ 0.22 | 0.10 | 0.06 | 0.06 | 0.18 |  -0.53 $\pm$ 0.15 | 0.10 | 0.08 | 0.03 | 0.07 |  |  |  |  |
Si II |  0.07 $\pm$ 0.32 | 0.25 | 0.06 | 0.02 | 0.19 |  |  |  |  |  |  |  |  |  |
Ca I |  -0.06 $\pm$ 0.38 | 0.14 | 0.21 | 0.14 | 0.24 |  -0.08 $\pm$ 0.15 | 0.10 | 0.08 | 0.07 | 0.05 |  -2.31 $\pm$ 0.20 | 0.13 | 0.15 | 0.01 | 0.02
Ca II |  -0.08 $\pm$ 0.15 | 0.14 | 0.06 | 0.01 | 0.01 |  |  |  |  |  |  |  |  |  |
Sc II |  -0.06 $\pm$ 0.30 | 0.07 | 0.12 | 0.04 | 0.26 |  0.24 $\pm$ 0.32 | 0.27 | 0.02 | 0.04 | 0.18 |  |  |  |  |
Ti II |  0.12 $\pm$ 0.15 | 0.04 | 0.04 | 0.03 | 0.14 |  0.11 $\pm$ 0.12 | 0.02 | 0.02 | 0.04 | 0.11 |  |  |  |  |
Cr II |  0.08 $\pm$ 0.12 | 0.06 | 0.03 | 0.01 | 0.10 |  0.07 $\pm$ 0.07 | 0.02 | 0.01 | 0.04 | 0.05 |  |  |  |  |
Mn I |  -0.22 $\pm$ 0.22 | 0.08 | 0.10 | 0.03 | 0.17 |  -0.10 $\pm$ 0.08 | 0.02 | 0.04 | 0.01 | 0.06 |  |  |  |  |
Fe I |  -0.15 $\pm$ 0.18 | 0.03 | 0.09 | 0.05 | 0.15 |  -0.05 $\pm$ 0.16 | 0.01 | 0.06 | 0.02 | 0.15 |  -2.07 $\pm$ 0.13 | 0.06 | 0.12 | 0.01 | 0.02
Fe II |  -0.11 $\pm$ 0.09 | 0.04 | 0.05 | 0.02 | 0.06 |  0.00 $\pm$ 0.10 | 0.02 | 0.04 | 0.02 | 0.09 |  -2.04 $\pm$ 0.10 | 0.08 | 0.05 | 0.02 | 0.02
Ni II |  |  |  |  |  |  0.15 $\pm$ 0.13 | 0.07 | 0.06 | 0.04 | 0.08 |  |  |  |  |
Zn I |  |  |  |  |  |  -0.32 $\pm$ 0.10 | 0.07 | 0.04 | 0.01 | 0.07 |  |  |  |  |
Sr II |  -0.39 $\pm$ 0.33 | 0.11 | 0.20 | 0.02 | 0.24 |  0.31 $\pm$ 0.11 | 0.07 | 0.06 | 0.01 | 0.07 |  -2.52 $\pm$ 0.18 | 0.14 | 0.12 | 0.01 | 0.01
Y II |  0.07 $\pm$ 0.09 | 0.08 | 0.03 | 0.03 | 0.01 |  0.06 $\pm$ 0.11 | 0.05 | 0.02 | 0.05 | 0.08 |  |  |  |  |
Zr II |  -0.26 $\pm$ 0.18 | 0.14 | 0.10 | 0.04 | 0.01 |  0.13 $\pm$ 0.08 | 0.04 | 0.02 | 0.04 | 0.04 |  |  |  |  |
Ba II |  0.21 $\pm$ 0.28 | 0.10 | 0.09 | 0.03 | 0.24 |  0.53 $\pm$ 0.24 | 0.09 | 0.04 | 0.01 | 0.22 |  |  |  |  |
| Vega | WASP-167 | WASP-189
C I |  -0.33 $\pm$ 0.11 | 0.03 | 0.10 | 0.04 | 0.01 |  0.09 $\pm$ 0.12 | 0.09 | 0.02 | 0.04 | 0.07 |  -0.40 $\pm$ 0.11 | 0.09 | 0.04 | 0.01 | 0.04
O I |  -0.36 $\pm$ 0.10 | 0.09 | 0.01 | 0.04 | 0.01 |  |  |  |  |  |  |  |  |  |
Mg I |  -0.57 $\pm$ 0.21 | 0.07 | 0.16 | 0.06 | 0.11 |  -0.02 $\pm$ 0.13 | 0.09 | 0.06 | 0.07 | 0.03 |  0.06 $\pm$ 0.24 | 0.10 | 0.06 | 0.04 | 0.21
Mg II |  -0.53 $\pm$ 0.07 | 0.05 | 0.02 | 0.04 | 0.03 |  0.37 $\pm$ 0.20 | 0.16 | 0.06 | 0.01 | 0.11 |  0.19 $\pm$ 0.24 | 0.21 | 0.04 | 0.02 | 0.11
Al I |  -1.13 $\pm$ 0.17 | 0.04 | 0.16 | 0.04 | 0.02 |  -0.43 $\pm$ 0.18 | 0.16 | 0.06 | 0.03 | 0.04 |  -0.19 $\pm$ 0.34 | 0.29 | 0.10 | 0.01 | 0.15
Si II |  -0.61 $\pm$ 0.10 | 0.04 | 0.03 | 0.09 | 0.02 |  |  |  |  |  |  0.08 $\pm$ 0.22 | 0.20 | 0.02 | 0.04 | 0.08
Ca I |  -0.87 $\pm$ 0.25 | 0.06 | 0.22 | 0.09 | 0.04 |  0.08 $\pm$ 0.21 | 0.16 | 0.08 | 0.07 | 0.09 |  0.04 $\pm$ 0.33 | 0.15 | 0.17 | 0.01 | 0.24
Ca II |  -0.76 $\pm$ 0.19 | 0.06 | 0.16 | 0.08 | 0.03 |  0.32 $\pm$ 0.18 | 0.16 | 0.04 | 0.08 | 0.01 |  -0.14 $\pm$ 0.15 | 0.15 | 0.03 | 0.01 | 0.01
Sc II |  -0.98 $\pm$ 0.14 | 0.06 | 0.12 | 0.02 | 0.03 |  0.17 $\pm$ 0.22 | 0.16 | 0.02 | 0.06 | 0.13 |  0.05 $\pm$ 0.28 | 0.16 | 0.05 | 0.05 | 0.22
Ti II |  -0.65 $\pm$ 0.10 | 0.01 | 0.09 | 0.03 | 0.02 |  0.31 $\pm$ 0.16 | 0.04 | 0.04 | 0.02 | 0.15 |  0.06 $\pm$ 0.12 | 0.03 | 0.02 | 0.04 | 0.11
Cr II |  -0.57 $\pm$ 0.07 | 0.02 | 0.05 | 0.03 | 0.01 |  0.27 $\pm$ 0.09 | 0.04 | 0.02 | 0.04 | 0.06 |  0.12 $\pm$ 0.09 | 0.05 | 0.03 | 0.03 | 0.06
Mn I |  -0.78 $\pm$ 0.20 | 0.04 | 0.20 | 0.03 | 0.01 |  0.23 $\pm$ 0.13 | 0.07 | 0.04 | 0.02 | 0.10 |  0.11 $\pm$ 0.11 | 0.07 | 0.04 | 0.01 | 0.08
Fe I |  -0.73 $\pm$ 0.15 | 0.01 | 0.15 | 0.05 | 0.01 |  0.08 $\pm$ 0.15 | 0.03 | 0.06 | 0.03 | 0.13 |  -0.01 $\pm$ 0.15 | 0.03 | 0.07 | 0.01 | 0.13
Fe II |  -0.72 $\pm$ 0.08 | 0.01 | 0.06 | 0.04 | 0.03 |  0.03 $\pm$ 0.15 | 0.07 | 0.04 | 0.01 | 0.13 |  0.05 $\pm$ 0.13 | 0.04 | 0.06 | 0.02 | 0.11
Ni II |  -0.73 $\pm$ 0.06 | 0.04 | 0.03 | 0.04 | 0.01 |  |  |  |  |  |  0.59 $\pm$ 0.24 | 0.10 | 0.04 | 0.03 | 0.22
Zn I |  |  |  |  |  |  -0.17 $\pm$ 0.14 | 0.11 | 0.03 | 0.02 | 0.07 |  |  |  |  |
Sr II |  -1.15 $\pm$ 0.20 | 0.06 | 0.18 | 0.03 | 0.04 |  0.44 $\pm$ 0.20 | 0.16 | 0.08 | 0.01 | 0.09 |  0.58 $\pm$ 0.26 | 0.09 | 0.09 | 0.04 | 0.22
Y II |  |  |  |  |  |  0.22 $\pm$ 0.22 | 0.13 | 0.04 | 0.05 | 0.16 |  0.92 $\pm$ 0.17 | 0.09 | 0.04 | 0.05 | 0.14
Zr II |  -0.59 $\pm$ 0.14 | 0.08 | 0.11 | 0.03 | 0.01 |  0.31 $\pm$ 0.21 | 0.16 | 0.02 | 0.01 | 0.13 |  0.61 $\pm$ 0.17 | 0.10 | 0.05 | 0.02 | 0.13
Ba II |  -0.48 $\pm$ 0.22 | 0.14 | 0.16 | 0.05 | 0.02 |  0.58 $\pm$ 0.20 | 0.13 | 0.04 | 0.01 | 0.14 |  0.89 $\pm$ 0.23 | 0.11 | 0.06 | 0.02 | 0.19
Table 1: Continued. Abundances derived in this work. For each specie, we present average$\pm$total error and the uncertainties e1, …, e4. Specie | [N/H] |  e1 |  e2 |  e3 |  e4 |  |  |
---|---|---|---|---|---|---|---|---
|  $\zeta$ Del |  |
C I |  -0.06 $\pm$ 0.07 | 0.06 | 0.04 | 0.01 | 0.01 |  |  |
O I |  0.08 $\pm$ 0.13 | 0.13 | 0.03 | 0.02 | 0.01 |  |  |
Mg I |  -0.50 $\pm$ 0.23 | 0.06 | 0.07 | 0.04 | 0.21 |  |  |
Mg II |  -0.38 $\pm$ 0.15 | 0.09 | 0.04 | 0.01 | 0.11 |  |  |
Si II |  -0.30 $\pm$ 0.18 | 0.14 | 0.07 | 0.07 | 0.07 |  |  |
Ca I |  -1.10 $\pm$ 0.34 | 0.11 | 0.23 | 0.02 | 0.22 |  |  |
Sc II |  -0.77 $\pm$ 0.22 | 0.11 | 0.09 | 0.02 | 0.16 |  |  |
Ti II |  -0.48 $\pm$ 0.15 | 0.03 | 0.05 | 0.03 | 0.14 |  |  |
Cr II |  -0.53 $\pm$ 0.07 | 0.04 | 0.03 | 0.02 | 0.05 |  |  |
Fe I |  -0.68 $\pm$ 0.12 | 0.02 | 0.10 | 0.02 | 0.07 |  |  |
Fe II |  -0.59 $\pm$ 0.13 | 0.03 | 0.04 | 0.03 | 0.12 |  |  |
Sr II |  -1.13 $\pm$ 0.31 | 0.16 | 0.13 | 0.03 | 0.23 |  |  |
Ba II |  -0.53 $\pm$ 0.18 | 0.14 | 0.11 | 0.01 | 0.01 |  |  |

##  Appendix B Comments about individual stars

In this section we briefly comment the chemical features that we observe on
individual stars.

59 Dra: This object presents mostly solar values.

$\beta$ Cir: This star presents some slightly subsolar abundances (such as
[Fe/H]=-0.25$\pm$0.26 dex) but also suprasolar values of s-process elements
(Sr, Y, Zr and Ba by $\sim$+0.3 dex). In particular, C is clearly subsolar
(-0.49$\pm$0.17 dex). We do not identify a $\lambda$ Boötis pattern.

$\beta$ Pic: This star presents some sligthly subsolar values of some species
(for example [Fe/H]=-0.28$\pm$0.14 dex) but also solar values of Mg, Ca, Sc,
Ti, Y and Ba. C resulted slightly subsolar (-0.20$\sim$0.11 dex). Then, we do
not detect clear $\lambda$ Boötis signature. Its $\lambda$ Boötis
classification was initially suggested based on its evolutionary status and
the presence of a circumstellar disk (King & Patten, 1992). However, its
$\lambda$ Boötis nature was then ruled out by using optical spectra (Holweger
et al., 1997) and also using the ratio of UV lines (Cheng et al., 2016).

BU Psc: This star resulted sligthly subsolar in some elements (Al, Cr, Fe)
although solar in other species (Si, Sc, Ti, Y, Ba).

Fomalhaut: This star shows mostly solar values (such as [Fe/H]=0.12$\pm$0.19
dex), and slightly enriched in Ni and s-process elements (Sr, Y, Zr and Ba).
We do not observe $\lambda$ Boötis-like characteristics.

HD 29391: Most metals in this star show solar abundances.

HD 105850: This object shows some slightly depleted elements (Cr, Fe) and some
solar species (Ca, Sc, Ti, Zr, Ba). We do not identify a $\lambda$ Boötis
pattern.

HD 110058: We observe a clear $\lambda$ Boötis pattern. Most metals show very
low abundances (between 1-2 dex), while C is almost solar
([C/H]=-0.14$\pm$0.06 dex), in agreement with most $\lambda$ Boötis stars.

HD 115820: Most elements in this object show solar abundances.

HD 120326: Mostly solar values. Some elements are very slightly subsolar (Mn,
Fe) while other show solar values (Ca, Sc, Ti, Cr).

HD 129926: Corbally (1984) classified this star as a close binary (F0 V + G1
V), with V magnitudes of 5.10 and 7.12 and a separation of $\sim$8.2 arcsec.
He reported strong Sr and Fe II for the primary, and strong lines for the
secondary. The HARPS data present a metal-rich spectra, showing similarities
but also differences to Am and ApSi stars. For instance, Cr, Fe, and Sr show
lower values than ApSi stars, while Ca and Sc show higher values than Am
stars.

HD 133803: This star shows solar (or slightly suprasolar) abundances in most
elements.

HD 146624: This star presents solar abundances (for example Mg, Si, Ti, Fe). C
and O both shows subsolar values.

HD 153053: Some species present slightly subsolar values (such as
[Fe/H]=-0.29$\pm$0.14 dex), while s-process elements show slightly suprasolar
abundances (Sr, Y, Zr and Ba by $\sim$+0.3 dex).

HD 156751: This star would classify as mild-$\lambda$ Boötis, if we only
inspect those elements with atomic number z$<$28, showing subsolar values of
metals (for example [Fe/H]=-0.47$\pm$0.17 dex) and near-solar C
(-0.13$\pm$0.08 dex). However, we also measured solar values for some
s-process elements (Sr, Y and Ba), being somewhat higher than average
$\lambda$ Boötis stars.

HD 159492: This object presents mostly solar abundances (such as Mg, Si, Sc,
Ti, Cr, Fe).

HD 169142: This star presents a clear $\lambda$ Boötis pattern. Subsolar
abundances of most metals (between 0.50-0.75 dex) together with a solar
abundance of C ([C/H]=0.13$\pm$0.09 dex). This star was previously identified
as a $\lambda$ Boötis object (Folsom et al., 2012; Gray et al., 2017),
although for some authors their $\lambda$ Boötis pattern is less clear (Murphy
et al., 2015). Interestingly, Gray et al. (2017) suggest a likely spectral
variation for this star, proposing a follow up to see if its $\lambda$ Boötis
nature could also vary.

HD 188228: Mostly solar values (Mg, Si, Ti, Cr, Fe), with subsolar C and
suprasolar Ba.

HD 23281: Mostly solar values (Mg, Si, Ti, Fe), with slightly subsolar C and
suprasolar values of s-process elements (Sr, Y, Zr and Ba).

HD 50445: This star presents some subsolar abundances ([Fe/H]=-0.31$\pm$0.13
dex). However, it also shows solar values of Mg, Sr, Y, Zr and Ba unlike most
$\lambda$ Boötis stars.

HD 56537: This object shows some subsolar values (for example
[Fe/H]=-0.51$\pm$0.13 dex). However, C also shows a low value
([C/H]=-0.42$\pm$0.13 dex)), while Ca, Ti, Y and Ba show almost solar values,
different of most $\lambda$ Boötis stars.

HD 88955: This star presents some subsolar abundances (such as
[Fe/H]=-0.50$\pm$0.14 dex) but also a low value for C (-0.61$\pm$0.11 dex).
However some s-process species show solar values (Y, Zr, Ba). Then, is
different of most $\lambda$ Boötis stars.

HD 95086: This object presents solar values of most metals.

HR 4502 A: This star presents mostly solar abundances.

HR 8799: This star presents a $\lambda$ Boötis pattern. Subsolar metallic
abundances (between 0.50-0.75 dex) together with a near-solar C
([C/H]=-0.11$\pm$0.07 dex). Its $\lambda$ Boötis nature was also previously
reported in the literature (Gray & Kaye, 1999; Sadakane, 2006).

KELT-17: This object shows a chemically peculiar Am pattern. KELT-17 presents
subsolar values of Ca and Sc, while other metals show overabundances (Ti, Cr,
Mn, Fe, Sr, Y, Ba). The Am nature of this star was recently reported by Saffe
et al. (2020).

KELT-20: This star presents mostly subsolar values (for example
[Fe/H]=-0.35$\pm$0.15 dex). However, it also shows a low C abundance
([C/H]=-0.42$\pm$0.10 dex), also solar or suprasolar values of Si, Ni and Ba,
different of average $\lambda$ Boötis stars.

KELT-9: This star presents solar abundances for most metals, with slightly
subsolar values for Al and Sr.

MASCARA-1: This object shows mostly solar values in general, with suprasolar
abundances of Sr, Y, Zr and Ba.

V435 Car: This star presents solar values of most elements.

WASP-33: This star shows mostly solar abundances, together with a suprasolar O
abundance. We caution however that, for this star, the O abundance was derived
using the O I near-IR triplet at $\sim$7771 Å, which suffer of NLTE effects
(e.g. Sitnova et al., 2013; Przybilla et al., 2011). In this star, some
s-process elements (Sr, Y and Ba) also show suprasolar values.

HAT-P-49: This object presents mostly solar values, with slightly suprasolar
abundances of Sc, Sr and Ba.

$\lambda$ Boötis: This object is more metal-poor than the average pattern of
$\lambda$ Boötis stars. In addition, this star shows C and O slightly subsolar
rather than solar, in agreement with previous works (Venn & Lambert, 1990;
Paunzen et al., 1999; Cheng et al., 2019). Then, we would consider this object
as a rather extreme case of the $\lambda$ Boötis class.

Vega: This star presents subsolar abundances of most metals and slightly
subsolar values of O (-0.36$\pm$0.10 dex): these features are, in principle,
similar to other $\lambda$ Boötis stars. However, C presents a lower abundance
([C/H]=-0.33$\pm$0.11 dex) than most $\lambda$ Boötis stars. A $\lambda$
Boötis nature for this star was previously suggested (Yoon et al., 2010),
however this class was then ruled out by Cheng et al. (2016), in agreement
with the present work.

WASP-167: This star presents a slightly metal-rich abundance pattern. However,
it is different of Am stars (showing higher Ca, Sc and lower Cr, Sr, Y, Zr,
Ba), different of ApSi stars (showing lower Ti, Cr, Mn, Fe) and different of
HgMn stars (lower Mn and no Hg observed).

WASP-189: This object is listed in the Renson & Manfroid (2009)’s catalog of
chemically peculiar stars with a ”doubtful” A4m classification. Its suspected
Am class was then ruled out (Anderson et al., 2018). This star presents Ca and
Sc almost solar (different of Am stars), mostly solar abundances and some
suprasolar s-process elements (Sr, Y, Zr and Ba), as we can see in the Fig.
11.

$\zeta$ Del: This star shows a clear $\lambda$ Boötis pattern: subsolar
metallic abundances (for example [Fe/H]=-0.68$\pm$0.12 dex), together with
solar values of both [C/H] and [O/H] (-0.06$\pm$0.07 and 0.08$\pm$0.13 dex).

##  Appendix C Abundance pattern of hot-Jupiter stars

We present in this section a number of Figures, comparing the abundances of
early-type stars which host hot-Jupiter planets, with the chemical pattern of
$\lambda$ Boötis stars.

Figure 11: Abundances of hot-Jupiter host stars (WASP-33, WASP-167, WASP-189
and KELT-9, in black) compared to an average $\lambda$ Boötis pattern (blue).
We show two panels for each star, corresponding to elements with z$<$32 and
z$>$32\. See text for more details.

Figure 12: Abundances of hot-Jupiter host stars (KELT-17, KELT-20, MASCARA-1
and HAT-P-49, in black) compared to an average $\lambda$ Boötis pattern
(blue). We show two panels for each star, corresponding to elements with
z$<$32 and z$>$32\. See text for more details.