# The detailed chemical abundance patterns of accreted halo stars from the
optical to infrared

Andreia Carrillo1,2,3, Keith Hawkins1, Paula Jofré4, Danielle de Brito Silva4,
Payel Das5, and Madeline Lucey1
1Department of Astronomy, University of Texas at Austin, 2515 Speedway, Stop
C1400, Austin, TX 78712-1205, USA
2Institute for Computational Cosmology, Department of Physics, Durham
University, Durham DH1 3LE, UK
3Large Synoptic Survey Telescope Corporation Data Science Fellow
4Núcleo de Astronomía, Facultad de Ingeniería y Ciencias, Universidad Diego
Portales, Ejercito 441, Santiago, Chile
5Department of Physics, University of Surrey, Guildford GU2 7XH, UK
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

Understanding the assembly of our Galaxy requires us to also characterize the
systems that helped build it. In this work, we accomplish this by exploring
the chemistry of accreted halo stars from the Gaia-Enceladus/Gaia-Sausage
(GES) selected in the infrared from the Apache Point Observatory Galactic
Evolution Experiment (APOGEE) Data Release 16. We use high resolution optical
spectra for 62 GES stars to measure abundances in 20 elements spanning the
$\alpha$, Fe-peak, light, odd-Z, and notably, the neutron-capture groups of
elements to understand their trends in the context of and in contrast to the
Milky Way and other stellar populations. Using these derived abundances we
find that the optical and the infrared abundances agree to within 0.15 dex
except for O, Co, Na, Cu, and Ce. These stars have enhanced neutron-capture
abundance trends compared to the Milky Way, and their [Eu/Mg] and neutron-
capture abundance ratios (e.g., [Y/Eu], [Ba/Eu], [Zr/Ba], [La/Ba], and
[Nd/Ba]) point to r-process enhancement and a delay in s-process enrichment.
Their [$\alpha$/Fe] trend is lower than the Milky Way trend for [Fe/H]$>$-1.5
dex, similar to previous studies of GES stars and consistent with the picture
that these stars formed in a system with a lower rate of star formation. This
is further supported by their depleted abundances in Ni, Na, and Cu
abundances, again, similar to previous studies of low-$\alpha$ stars with
accreted origins.

###### keywords:

stars: abundances – Galaxy: halo – Galaxy: abundances – Galaxy: formation

††pubyear: 2019††pagerange: The detailed chemical abundance patterns of
accreted halo stars from the optical to infrared–B

##  1 Introduction

The hierarchical model posits two phases to the formation of larger galactic
systems: a first phase dominated by mergers between similar-sized galaxies,
and a second phase dominated by accretion of smaller systems. We are
especially able to study such interactions in the Milky Way where we can
resolve the individual stars. There are streams of stars in the halo, remnants
of smaller systems, i.e. galaxies or globular clusters, being tidally
disrupted by our Galaxy’s potential (e.g., Ibata et al. 1994; Lynden-Bell &
Lynden-Bell 1995; Belokurov et al. 2006; Bonaca et al. 2012; Shipp et al.
2018). However, this is only evidence for recent interactions with the Milky
Way—there is little spatially-distinct evidence for past merger events, as
these accreted stars would have been phase-mixed in the Galaxy over time.
These ex-situ stars no longer cluster spatially but they may be identifiable
through their kinematics and chemical tagging (Freeman & Bland-Hawthorn,
2002). Through doing this, we are able to recover one of Milky Way’s most
significant merger event (Helmi et al., 2018).

To study the systems that the Milky Way has accreted through its lifetime, we
search for old, metal-poor stars in the halo. Low-metallicity, kinematically
hot, halo stars in the Solar neighborhood have been shown to have two
chemically-distinct stellar populations – one with high [$\alpha$/Fe]111The
bracket notation denotes differential analysis with the Sun i.e. [X/H] =
log($N_{X}$/$N_{H}$)⋆ \- log($N_{X}$/$N_{H}$)⊙ = log$A_{X,\star}$ \-
log$A_{X,\odot}$ where log$N_{H}$ is 12.00. Alternatively, abundance is
reported with respect to the Solar Fe abundance, i.e. [X/Fe] = [X/H] - [Fe/H].
Additionally, [$\alpha$/Fe] is the average abundance of $\alpha$ elements
(e.g. O, Mg, Ca, Si) with respect to Solar values.  abundance and one with low
[$\alpha$/Fe] abundance (Nissen & Schuster, 1997; Fulbright, 2002; Nissen &
Schuster, 2010). The kinematics, orbital parameters, and ages of these stars
show that they may have formed through very different scenarios (Schuster et
al., 2012). The low-$\alpha$ stars (at metallicities, [Fe/H] $\geq$-1.5 dex)
are postulated to have come from a dwarf galaxy with a lower star formation
rate and different chemical evolution than the Milky Way progenitor. On the
other hand, the high-$\alpha$ stars at the same [Fe/H] are thought to be pre-
existing in-situ disk material, dispersed to halo kinematics in the infancy of
our Galaxy, because of a significant merger event (Zolotov et al., 2009, 2010;
Purcell et al., 2010).

Investigation on the origin of these low-$\alpha$ stars has been further
advanced with the advent of the European Space Agency satellite Gaia (Gaia
Collaboration et al., 2016a) whose second data release (DR2, Gaia
Collaboration et al. 2018) revolutionized the 3D map of our Galaxy. Having
observed 1.7 billion stars, the survey provides astrometric, photometric, and
for a subset, radial velocity (RV) information. This has especially opened the
doors to reconstructing accretion events in the Milky Way as they would leave
considerable substructure in phase-space (Johnston et al., 1996). Helmi et al.
(2018) used Gaia DR2 to kinematically select accreted stars that once belonged
to the system that the authors dubbed Gaia-Enceladus. Gaia-Enceladus stars
cover almost the full sky but systematically show slight retrograde motion,
which is seen as evidence that they once belonged to a singular system
separate from the Milky Way. Belokurov et al. (2018) found the same population
of stars using the Sloan Digital Sky Survey (SDSS)-Gaia catalogue (Ahn et al.,
2012; Gaia Collaboration et al., 2016b) that contains proper motions (from
Gaia DR1) and [Fe/H]. They found more radial orbits for stars in the inner
halo and a change in the halo velocity ellipsoid, $\beta$, as a function of
[Fe/H] and height from the disc plane. These results are best supported by a
formation scenario where the Milky Way accreted a system with
$M_{vir}>10^{10}M_{\odot}$ during the epoch of disc formation, 8 to 11 Gyr
ago, later called Gaia-Sausage. In this work, we refer to this system as the
Gaia-Enceladus-Sausage (GES) galaxy.

Detailed chemical abundance studies using large spectroscopic surveys, like
the high-resolution infrared (IR) survey Apache Point Observatory (APO)
Galactic Evolution Experiment (APOGEE, Eisenstein et al. 2011), have further
enlightened the origin of these accreted stars and for a much larger sample.
Hawkins et al. (2015) used APOGEE DR12 (Holtzman et al., 2015) to show that
the accreted inner halo stars are distinct in the [$\alpha$/Fe], [Mn/Fe], and
[Al/Fe] vs [Fe/H] planes to name a few, hinting at a slower chemical evolution
and star formation history. Combinations of these chemical abundances are
therefore promising in disentangling the stars that formed inside and outside
of the Milky Way. Hayes et al. (2018), in a similar vein, used the $\alpha$
element Mg to separate low-metallicity stars in APOGEE DR 13 (Albareti et al.,
2017) into a low-Mg and high-Mg population. They find that the two groups are
also distinct from each other in other chemical abundance planes and that the
low-Mg population has halo-like kinematics and are most likely accreted.
Combining the power of chemistry from APOGEE DR14 and kinematics from Gaia
DR2, Mackereth et al. (2019) found that the canonical halo stars defined in
the [Mg/Fe] vs [Fe/H] plane can be divided into a low eccentricity, low-e, and
high eccentricity, high-e, group. They find that the high-e stars show lower
Mg, Al, and Ni abundances compared to the low-e group, reaffirming the
distinguishing elements suggested from Hawkins et al. (2015). To explain the
existence of these high-e stars, Mackereth et al. (2019) supplemented their
study with comparisons to the EAGLE simulation and found that the high e (i.e.
0.85) can be explained by a merger that happened at z$\lesssim$1.5 with
stellar mass between $\rm 10^{8.5}<M_{\star}<10^{9}$ $M_{\odot}$.

Using the combination of elements presented by Hawkins et al. (2015) to purely
chemically select stars accreted onto the Milky Way, Das et al. (2020) further
showed that the combination of APOGEE (DR14) and Gaia DR2 is a powerful tool
in disentangling ex-situ vs in-situ stars, and characterizing their kinematics
and ages. The authors find a “blob" of 856 likely accreted stars in the
[Mg/Mn] vs [Al/Fe] plane and with a Bayesian isochrone pipeline, derived ages
for these blob stars that range between 8 and 13 Gyr. With a single progenitor
scenario and from dynamical arguments, these blob stars likely belonged to a
system with a total mass of $\rm\sim 10^{11}M_{\odot}$, where the star
formation proceeded for 5 Gyr until it was cannibalized by the Milky Way 8 Gyr
ago.

Combining the power of large Milky Way surveys has enabled the community to
further characterize the GES system but to fully understand this progenitor’s
chemistry and its scatter in abundances, we need access to many more elements.
APOGEE DR16 (Jönsson et al., 2020) provides abundances for $>$20 elements,
including Cerium (Ce) and Neodymium (Nd), both neutron-capture elements.
Neutron-capture elements are thought to play a bigger role in the chemical
evolution of lower mass systems. Simulations show that slow (s)-process
neutron capture element abundance can can be used to distinguish the origin of
the halo, especially at lower metallicities (Spitoni et al., 2016). Nissen &
Schuster (2011) and Fishlock et al. (2017) specifically derived predominant
s-process element abundances for low-$\alpha$ stars in the inner halo and
concluded that low-metallicity, low-mass asymptotic giant branch (AGB) stars
dispersed metals in the progenitor with a time-delay. More recent studies
(e.g. Matsuno et al. 2020, Matsuno et al. 2021,Aguado et al. 2021) also find
r-process enhancement in GES stars. Most of the studies aforementioned have
samples of 10-30 low-$\alpha$ stars, but as been shown with more recent
studies using large surveys (e.g. Belokurov et al. 2018; Helmi et al. 2018;
Hayes et al. 2018; Mackereth et al. 2019; Bird et al. 2019; Lancaster et al.
2019), it is possible to select accreted halo stars en masse. However, most
neutron-capture elements like Barium (Ba), Lanthanum (La), Neodymium (Nd),
Yttrium (Y), Zirconium (Zr), and (the predominantly r-process element)
Europium (Eu), are harder to measure, if not impossible, in the IR compared to
the optical. Some neutron-capture elements are available in other optical
spectroscopic surveys (e.g. GALAH, Buder et al. 2018) and have indeed been
used in the more recent GES literature (Matsuno et al., 2021; Aguado et al.,
2021). However, a sample selected from giants in IR data (such as APOGEE)
probes stars at larger distances.

Therefore, in this work, we present a complementary study of the GES system:
motivated by Das et al. (2020), we take advantage of the power of chemical
tagging and select a sample of accreted stars based solely on their chemistry
in the IR and derive their detailed chemical abundances in the $\alpha$, Fe-
peak, light, odd-Z, and neutron capture elements in the optical. We aim to
showcase the elemental abundance trends of the GES system particularly in the
neutron-capture elements, to understand its enrichment and chemistry in the
context of the satellite population of the Milky Way. We also seek to compare
the detailed chemical abundances between the optical and IR, and quantify
their systematic differences for the same set of stars at such low
metallicities. This paper is outlined as followed: Section 2 describes our
target selection of accreted halo stars that form a blob in the [Mg/Mn] vs
[Al/Fe] plane and outline our observations. We refer to our sample as blob
stars. Section 3 outlines how we derived the stellar parameters and the
abundances. Section 4 compares the stellar parameters and abundances between
what we derived vs their APOGEE values. Section 5 discusses the [X/Fe] vs
[Fe/H] for our sample of stars in contrast with different stellar populations.
Section 6 considers the implications of our sample’s abundance trends on its
progenitor’s chemical evolution and its context within the rest of the Milky
Way satellite population. Lastly, Section 7 summarizes the main results from
this study and avenues for future work.

##  2 Data

###  2.1 Accreted Stars Selection

Figure 1: Chemically selecting stars with likely accretion origin. [Mg/Mn] vs
[Al/Fe] that shows the 2,258 accreted stars as a “blob" in this plane
(orange), in contrast with the rest of the stars from APOGEE DR16 (shown as
logarithm of the number count in gray). The colorbar indicates the number of
stars per hexbin in the APOGEE DR16 data.

We employ a pure chemical selection of accreted halo stars using APOGEE DR16
(Ahumada et al., 2019; Jönsson et al., 2020). APOGEE has moderate resolution
(R $\sim$ 22,500) H-band spectra (1.5-1.7 $\mu$m) for 473,307 stars in the
16th data release (DR16), taken both in the Northern hemisphere with the Sloan
Foundation 2.5-m Telescope at APO (APOGEE-2N) and in the Southern hemisphere
with the du Pont 2.5-m Telescope at Las Campanas Observatory (LCO).

The stellar parameters and abundances were derived through the APOGEE Stellar
Parameters and Chemical Abundances Pipeline (ASPCAP; García Pérez et al.
2016). ASPCAP determines the best-matching synthetic spectra that has known
stellar parameters to the observed spectra. A new set of synthetic grids have
been utilized for this analysis using MARCS model atmospheres (Gustafsson et
al., 2008) that cover a wide range in surface gravity (log $g$), effective
temperature ($T_{\rm eff}$), microturbulence ($\rm v_{micro}$), [Fe/H], and
abundance parameters [$\alpha$/M], [C/M], and [N/M]. APOGEE contains chemical
abundances, [X/Fe], based on the molecular lines of C, N, O, and Si, and
atomic lines of C, Na, Mg, Al, Si, P, S, K, Ca, Ti I, Ti II, V, Cr, Mn, Fe,
Co, Ni, Cu, Ge, Rb, Ce, Nd, and Yb.

Using APOGEE DR12 data, Hawkins et al. (2015) introduced a new combination of
chemical abundances i.e. [C+N/Fe], [Al/Fe], and [Mg/Mn] that could discern
stars belonging to different Galactic components, independent of their
kinematics. Mackereth et al. (2019) reaffirmed this later, and showed that not
only [Mg/Fe] but also [Al/Fe] and [Ni/Fe] separate stars that have likely ex-
situ origins as shown by their high-$e$. These elements provide more ways to
separate the in-situ and ex-situ Milky Way stars, in addition to the
canonically-used [$\alpha$/Fe]. In this study, we use APOGEE DR16 to select
targets with potential accreted origin in the [Mg/Mn] vs [Al/Fe] plane.

While APOGEE DR16 contains information for several elements, including neutron
capture elements Ce and Nd (Jönsson et al. 2020), these are typically
difficult to measure for low metallicity stars. We therefore obtain high-
resolution optical spectra for better derivation of neutron-capture element
abundances.

We followed the method from Das et al. (2020) in selecting the likely accreted
stars in the [Mg/Mn] vs [Al/Fe] plane. Selecting in chemistry is particularly
advantageous because the stellar atmospheric abundances are essentially
preserved throughout a star’s lifetime except for some light elements, such as
Li, C, and N due to dredge-up processes. This is especially promising as Das
et al. (2020) showed that using this combination of abundances, their sample
of accreted stars have older ages (see their Figure 7) and kinematics (see
their Figure 8) similar to accreted stars in the literature (e.g., Belokurov
et al. 2018). Whether selecting dynamically or chemically gives a cleaner or
different sample of accreted stars is worth exploring and has been the subject
of the work from Buder et al. (2022). Using GALAH DR3 data and the combination
of [Na/Fe] and [Mg/Mn], the authors found that their GES sample from a
chemical selection overlaps with 29% of a pure dynamically-selected sample, as
suggested by Feuillet et al. (2021). Likewise, there is a mismatch for their
dynamically-selected GES stars with 72% of the sample having [Na/Fe] abundance
above the 84th percentile of the chemical selection.

In this work, we applied Gaussian Mixture Modeling (GMM) 222https://scikit-
learn.org/stable/modules/mixture.html in the [Mg/Mn] vs [Al/Fe] plane. GMM is
a probablistic model that assumes that the data is drawn from a mixture of a
finite number of Gaussian distributions. However, determining the number of
Gaussian distributions is non-trivial, especially for data that do not have
distinctly separate distributions. To determine the optimal number of Gaussian
components, we compared GMMs with one to 20 components and find that the
optimal number is 17 using Bayesian Information Criterion (BIC). As it is a
probablistic model, each star has a probability to be part of one of the 17
components. We determined the cutoff probability to be $>$0.7 in assigning a
star to a certain Gaussian component. There are a total of 2,258 sources in
the red giant branch associated with the accreted component, where the stars
form a “blob" in the [Mg/Mn] vs [Al/Fe] plane, as shown in Figure 1. We
similarly refer to our sample as “blob stars". In contrast, Das et al. (2020)
used APOGEE DR14, had 14 components from the GMM, and found 856 stars
associated to their blob sample with 7% contamination where some stars picked
out by the GMM have Milky Way disk kinematics and [Fe/H] (see their Figure 5).
In order to account for this contamination in our sample and pick purely
accreted halo material, we selected only lower-metallicity stars with [Fe/H]
$<$-0.8 dex. We also note that one of the stars in our blob sample,
2M14534136+4304352, was part of the blob in APOGEE DR14 (Das et al., 2020),
though not in APOGEE DR16. We include it nonetheless.

Figure 2: Continuum normalized optical spectra for three blob stars. They include 2M15561756+4703281 with [Fe/H] = -1.17 dex (orange), 2M10313588+3010198 with [Fe/H] = -1.44 dex (purple), and 2M12071560+4622126 with [Fe/H] = -1.81 dex (orange).  APOGEE ID | RA (deg) | Dec (deg) | Gaia DR2 source ID | G (mag) | RV ($\rm kms^{-1}$) |  $\rm\sigma_{RV}$ ($\rm kms^{-1}$) | SNR ($\rm pixel^{-1}$)
---|---|---|---|---|---|---|---
2M09121759+4408563 | 138.07 | 44.15 | 817319945578821504 | 11.43 | -268.14 | 0.27 | 86.67
2M11115726+4551087 | 167.99 | 45.85 | 788225596597420160 | 10.76 | -51.21 | 0.17 | 72.86
2M12071560+4622126 | 181.82 | 46.37 | 1539803504272415232 | 10.88 | -179.02 | 0.20 | 84.85
2M13581572+2602122 | 209.57 | 26.04 | 1450722893255972992 | 11.18 | -85.31 | 0.31 | 62.80
2M09381836+3706176 | 144.58 | 37.10 | 799015207281513600 | 10.63 | 187.96 | 0.13 | 85.06
2M11482205-0030318 | 177.09 | -0.51 | 3794814922703318272 | 11.09 | 40.64 | 0.28 | 66.81
2M10013420+4345558 | 150.39 | 43.77 | 808093771712305664 | 11.36 | -107.64 | 0.17 | 82.65
2M13015242+2911180 | 195.47 | 29.19 | 1464266230811360256 | 11.07 | -207.34 | 0.25 | 75.82
2M14181562+4651580 | 214.57 | 46.87 | 1506860143038459520 | 11.23 | -46.52 | 0.28 | 95.55
2M15410952+3014067 | 235.29 | 30.24 | 1273071638461821952 | 10.75 | -97.31 | 0.17 | 66.98
Table 1: Properties for 10 out of 62 blob targets including the APOGEE ID, RA
and Dec of the star from APOGEE, Gaia DR2 source ID, Gaia G-band magnitude,
radial velocity and error corrected for barycentric motion derived from the
optical spectra, and SNR. Full version is provided online.

###  2.2 High Resolution Optical Spectroscopy of Accreted Stars

We selected stars with $G$ $<$ 12 mag and obtained high-resolution optical
spectra with the Tull Echelle Spectrograph (Tull et al., 1995) at the 2.7-m
Harlan J. Smith telescope at McDonald Observatory. We used the Coudè
spectrograph in the TS23 mode, utilizing slit#5, with width 1.79" and full
width half maximum (FWHM) 2.78 pixels. This achieves R $\sim$40,000 over a
wavelength range of 3400 – 9000 Å. Typical exposure times range from 1200 to
1800 seconds and the number of exposures vary from one to four, depending on
the magnitude of the target and the weather conditions, in order to reach
moderate signal-to-noise ratio (SNR) of at least 60 pixel-1 and remove cosmic
rays for the fainter targets. For every night, we observed a solar port
spectrum (to ensure that our setup does not change night to night), biases,
flats, Thorium-Argon (ThAr) comparison frames for wavelength calibration,
telluric and RV standards, and a twilight spectrum to derive Solar abundances
for use in our analysis. In addition to the science targets, we also observed
telluric and RV standards.

We performed standard reduction (i.e. bias subtraction, flat-fielding,
wavelength calibration) using IRAF333IRAF is distributed by the National
Optical Astronomy Observatories, which is operated by the Association of
Universities for Research in Astronomy, Inc., under contract to the National
Science Foundation. and pyraf for the data taken at McDonald Observatory. Each
spectra has $\sim$60 orders, with greater gaps between orders towards the
redder part of the spectrum. We masked bad pixels as well as instrumental
artifacts and subtracted scattered light. We then normalized the spectra from
each order using a fifth-degree polynomial fit to the continuum, and stitched
the orders to obtain the full spectra.

We also obtained high resolution optical spectra in the Southern hemisphere
with the Magellan Inamori Kyocera Echelle (MIKE, Bernstein et al. 2003)
spectrograph at the Magellan Telescopes at Las Campanas Observatory (LCO). We
observed with the MIKE blue setup (4100-5000 Å) and red setup (4900-9000 Å)
with R $\sim$ 28,000 and 22,000 respectively. Biases, flats, ThAr arc lamps,
RV and telluric standards, and science frames were taken, with exposure times
ranging between 400 and 900 seconds for the science targets.

The MIKE spectra were reduced using CarPy (Kelson et al., 2000; Kelson, 2003).
CarPy is written in python and generates science ready 2D spectra considering
flats and biases taken with the same setups. For a proper wavelength solution,
ThAr arcs were taken in between observations, and CarPy considers the arc that
was most recently taken from the observation. CarPy also automatically co-adds
spectra of multiple exposures of the same object. We then stitched the
extracted 2D blue and red spectra using IRAF scombine to have a final 1D
spectrum per star.

We determined and corrected for RV with iSpec (Blanco-Cuaresma et al., 2014;
Blanco-Cuaresma, 2019) using the cross-correlation of our spectra with that of
Arcturus. For stars that we observed at McDonald with multiple exposures, we
co-added their spectra to increase their SNR. In the end, we have reduced,
extracted, wavelength-corrected, RV-corrected, and co-added spectra for 62
blob stars. We list the observational properties of some stars from our sample
in Table 1 and show sample spectra in Figure 2.

##  3 Stellar Parameter and Abundance Determination

In this section, we outline our derivation of atmospheric parameters for the
blob stars: $T_{\rm eff}$ through the infrared flux method (IRFM, Blackwell et
al. 1980,Ramírez & Meléndez 2005,González Hernández & Bonifacio 2009), $\log
g$ from isochrone fitting (e.g. Yong et al. 2013; Roederer et al. 2014), and
$\rm v_{micro}$ and [Fe/H] using the Brussels Automatic Code for
Characterizing High accUracy Spectra (BACCHUS, Masseron et al. 2016) code.
Using these stellar parameters, we proceeded to obtain detailed chemical
abundances from the high-resolution optical spectra using the BACCHUS code.

We adopted Equation 10 from González Hernández & Bonifacio (2009), which
quantifies an empirical relation to derive the $T_{\rm eff}$ from [Fe/H] and
colour. For the input to the IRFM, we used the [Fe/H] from APOGEE DR16, and
the $J$ and $K_{S}$ mags from the Two Micron All-Sky Survey (2MASS, Skrutskie
et al. 2006), which were corrected for reddening using the dustmaps package
(Green, 2018) and its built in modules for 2D (Planck Collaboration et al.,
2014) or 3D corrections (Green et al., 2019), where available. We accounted
for the appropriate coefficients for giant stars using $J-K_{S}$ colour from
Table 5 in González Hernández & Bonifacio (2009). We derived the $\log g$
through isochrone fitting using the Yonsei-Yale ($Y^{2}$) isochrones (Demarque
et al., 2004) interpolator, that requires the following inputs: $V$-band and
European Southern Observatory (ESO) $K$-band magnitudes (among other filter
combinations), age, [Fe/H], [$\alpha$/Fe]. We used the [Fe/H] and
[$\alpha$/Fe] from APOGEE DR16, converted the Gaia $G$ magnitude to Johnson-
Cousins $V$ using the transformation from the Gaia Data Release Documentation
444https://gea.esac.esa.int/archive/documentation/GDR2/Data_processing/chap_cu5pho/sec_cu5pho_calibr/ssec_cu5pho_PhotTransf.html,
and converted the 2MASS $K_{S}$-band magnitude to ESO $K$
555https://www.astro.caltech.edu/~jmc/2mass/v3/transformations/ to get an
isochrone with the same properties as the star of interest. We interpolate
over the isochrone to get the associated $\log g$ using the $M_{V}$ vs $V-K$
colour-magnitude diagram (CMD). To obtain the absolute magnitude $M_{V}$ from
apparent magnitude $V$, we used the distance estimates from Bailer-Jones et
al. (2021) instead of simply inverting the Gaia parallaxes. Lastly, in
creating the isochrones, we assumed a fixed age of 10 Gyr and note that
modifying the age by 2 Gyr (i.e., 8 Gyr and 12 Gyr), changes the $\log g$ by
only 0.04 dex.

To obtain the remaining stellar atmospheric parameters (i.e., [Fe/H] and
broadening from rotation and the instrument) we used the param module in
BACCHUS. BACCHUS uses line by line analysis to derive the stellar parameters
and abundances. It utilizes the fifth version of the atomic line list from
Gaia-ESO (Heiter et al., 2021) that includes hyperfine structure (HFS) for Sc
I, V I Mn I, Co I, Cu I, Ba II, Eu II, La II, Nd II, Sm II. Additionally, the
line list also includes molecular lines for CH (Masseron et al., 2014), CN,
NH, OH, MgH, and C2 (T. Masseron, private communication), SiH (Kurucz linelist
666http://kurucz.harvard.edu/linelists/linesmol/), and TiO, ZrO, FeH, and CaH
(B. Plez, private communication). BACCHUS uses MARCS model atmosphere grid
(Gustafsson et al., 2008) and synthesizes model spectra using TURBOSPECTRUM
(Alvarez & Plez, 1998; Plez, 2012). For more details on how BACCHUS derives
stellar parameters, we refer the reader to Section 4 of Lucey et al. (2019)
and Section 3 of Hawkins et al. (2020).

We employ BACCHUS and its eqw routine to determine the equivalent widths (EW)
of Fe lines for our sample, which are later used for calculating convolution,
$\rm v_{micro}$ and [Fe/H]. The EWs are calculated by integrating synthesized
spectra over some previously determined spectral window (Masseron et al.,
2016). The convolution, which in BACCHUS is the broadening as a result of the
amalgamation of instrumental resolution, vsini, and macroturbulence, is
determined from ensuring the Fe abundance computed from a line’s core and from
its EW are similar. $\rm v_{micro}$ is computed by requiring no correlation
between Fe abundance and the reduced equivalent width (EW/wavelength). [Fe/H]
convergence is determined through $\chi^{2}$ minimization between the model
spectra and the observed spectra in the defined spectral window.

With the $T_{\rm eff}$, $\log g$, $\rm v_{micro}$, and [Fe/H] determined, we
then calculated the abundances for each element, X, using the abund routine in
BACCHUS. This creates synthetic spectra given the stellar parameters, at
different values of log$A_{X}$.

The abundance for each line of every element is determined by $\chi^{2}$
minimization between the synthesized spectra and the observed spectra in the
defined spectral window. The final adopted atmospheric abundance is derived by
computing the median [X/Fe] value for the lines of species X that BACCHUS
accepts through its automatic decision tree (see Hawkins et al. 2016 for
details). Generally, the solution for a line is flagged and/or rejected if it
is an upper limit, an extrapolation, or saturated (i.e. not in the linear part
of the curve of growth with core depth $\approx$ 0.2 in normalized flux). The
internal uncertainty is computed as the standard error of the mean. For
elements with only one line vetted as good, we assumed a 0.10 dex error.

We also used BACCHUS to derive solar atmospheric parameters and chemical
abundances from our observed twilight spectra 777$T_{\rm eff}$=5715 K, $\log
g$=4.41 dex, [Fe/H]=0 dex, and $\rm v_{micro}$=0.89 km/s, which we then
adopted for calculating the [X/Fe] for the program stars. We took this
approach to further reduce the systematic offsets introduced by our chemical
abundance determination. A key difference, however, is that we employed
ionization-excitation balance to derive solar $T_{\rm eff}$ and $\log g$, as
these could be more reliably derived from solar spectra, than from our sample
of low-metallicity, low-surface gravity stars. We note that our derived
abundance, log$(\epsilon)$, values are comparable to values in the literature
(e.g. Asplund et al. 2005; Asplund et al. 2009,Guo et al. 2017,Hawkins et al.
2020). The tabulated comparison is listed in Table 2.

Element | log(X) | $\rm\sigma_{log(X)}$ | A05 | A09
---|---|---|---|---
O | 8.72 | 0.09 | 8.66 | 8.69
Na | 6.26 | 0.04 | 6.17 | 6.24
Mg | 7.54 | 0.05 | 7.53 | 7.60
Si | 7.48 | 0.03 | 7.51 | 7.51
Ca | 6.35 | 0.02 | 6.31 | 6.34
Sc | 3.21 | 0.03 | 3.05 | 3.15
V | 3.82 | 0.02 | 4.00 | 3.93
Cr | 5.54 | 0.02 | 5.64 | 5.64
Mn | 5.26 | 0.04 | 5.39 | 5.43
Co | 4.75 | 0.04 | 4.92 | 4.99
Ni | 6.19 | 0.04 | 6.23 | 6.22
Fe | 7.45 | 0.01 | 7.45 | 7.50
Cu | 4.00 | 0.06 | 4.21 | 4.19
Zn | 4.46 | 0.07 | 4.60 | 4.56
Y | 1.96 | 0.05 | 2.21 | 2.21
Zr | 2.58 | 0.06 | 2.59 | 2.58
Ba | 2.24 | 0.07 | 2.17 | 2.18
La | 1.13 | 0.06 | 1.13 | 1.10
Ce | 1.36 | 0.05 | 1.58 | 1.58
Nd | 1.22 | 0.06 | 1.45 | 1.42
Eu | 0.23 | 0.09 | 0.52 | 0.52
Table 2: Independent, BACCHUS-derived solar abundances from twilight spectrum taken at McDonald Observatory. We use these solar abundances in calculating the [X/Fe] of the stars in this study. We also show other reference studies for solar abundances, i.e. Asplund et al. (2005), A05, and Asplund et al. (2009), A09.  [X/H] | $\pm\sigma_{T_{\rm eff}}$ | $\pm\sigma_{\mbox{$\log g$}}$ | $\pm\rm\sigma_{[Fe/H]}$ | $\pm\rm\sigma_{\rm v_{micro}}$
---|---|---|---|---
O | 0.07 | 0.07 | 0.15 | 0.07
Mg | 0.05 | 0.05 | 0.06 | 0.05
Si | 0.00 | 0.01 | 0.00 | 0.01
Ca | 0.05 | 0.05 | 0.06 | 0.04
Sc | 0.09 | 0.10 | 0.09 | 0.09
V | 0.07 | 0.05 | 0.06 | 0.05
Cr | 0.07 | 0.05 | 0.08 | 0.06
Mn | 0.05 | 0.05 | 0.05 | 0.05
Co | 0.04 | 0.04 | 0.04 | 0.04
Ni | 0.02 | 0.01 | 0.00 | 0.01
Cu | 0.05 | 0.04 | 0.04 | 0.03
Zn | 0.05 | 0.05 | 0.04 | 0.05
Y | 0.06 | 0.06 | 0.09 | 0.06
Zr | 0.02 | 0.03 | 0.04 | 0.03
Ba | 0.08 | 0.09 | 0.07 | 0.07
La | 0.09 | 0.10 | 0.11 | 0.09
Ce | 0.14 | 0.14 | 0.12 | 0.14
Nd | 0.10 | 0.09 | 0.09 | 0.09
Table 3: Parameter sensitivity test using 2M10313588+3010198. We list the
change in [X/H] for every element (1) as a function of changing each stellar
parameter by $\pm$ the mean uncertainty in $T_{\rm eff}$ (2), $\log g$ (3),
[Fe/H] (4), and $\rm v_{micro}$ (5).

###  3.1 Uncertainties

There are various sources of random and systematic uncertainties that could
lead to offsets between our derived abundances and those derived in APOGEE and
other studies.

For example, the line selection, which we list in Table 5, is a source of
internal scatter for the final abundance. Additionally, different line
selections between the optical and the IR or between various studies also
introduce systematic differences. For more details on the line selection, we
refer to Appendix A.

There are several other potential sources of systematics that should be noted.
One such source is our solar abundance scaling which can differ by as much as
0.2 dex from the solar abundances of Asplund et al. (2009) such as for Co
($\Delta$ = 0.24 dex), Y ($\Delta$ = 0.25 dex), Ce ($\Delta$ = 0.22 dex), Nd
($\Delta$ = 0.20 dex), and Eu ($\Delta$ = 0.29 dex). An additional source of
systematic uncertainty is in our treatment of HFS. Taking into account the HFS
for strong lines is especially important as this could lead to larger
equivalent widths and overestimation of the abundance. In our analysis, this
is accounted for in the creation of the model spectra from which we determine
the abundance through $\chi^{2}$ minimization.

We also performed a parameter sensitivity test for a representative target,
2M10313588+3010198. We determined the representative target based on the mean
values for the stellar parameters and their uncertainties which are $4661\pm
95$ K for $T_{\rm eff}$, $1.63\pm 0.08$ dex for $\log g$, $-1.43\pm 0.14$ dex
for [Fe/H], and $1.7\pm 0.12$ $\rm km~{}s^{-1}$ for $\rm v_{micro}$. We
perturbed the stellar parameters of 2M10313588+301019 (e.g., $T_{\rm
eff}$=4660 K, $\log g$=1.57 dex, [Fe/H]=-1.45 dex, and $\rm v_{micro}$=1.55
$\rm km~{}s^{-1}$) one by one by the average stellar parameter uncertainty,
while holding all others fixed to explore how the [X/Fe] changes. The change
in the abundance with respect to the change in stellar atmospheric parameter
is listed in Table 3. We note that Na and Eu were not measured for this star
and are therefore not included in the table. Through this test, we find that
most elements vary by $<$0.10 dex with a change in stellar parameter aside
from O which is sensitive to the [Fe/H], and Ce which is sensitive to all four
stellar atmospheric parameters.

##  4 Comparison with APOGEE for metal-poor stars

###  4.1 Stellar Parameters

Figure 3: Comparison of stellar parameters from this study and APOGEE.
$\Delta$ is defined as this study - APOGEE vs the values derived in this work.
Starting from the left-most column going to the right, the x-axis shows
$T_{\rm eff}$, $\log g$, [Fe/H], and $\rm v_{micro}$ and from the top-most row
going down, the y-axis shows the $\Delta$parameter for $T_{\rm eff}$, $\log
g$, [Fe/H], and $\rm v_{micro}$. We calculate the following offsets compared
to APOGEE: $\Delta$$T_{\rm eff}$=12.95$\pm$103.64 K, $\Delta$$\log
g$=-0.08$\pm$0.31 dex, $\Delta$[Fe/H]=-0.02$\pm$0.09 dex, and $\Delta$$\rm
v_{micro}$=0$\pm$0.35 km/s.

We now compare our derived stellar parameters with the parameters derived from
APOGEE as illustrated in Figure 3. To recall, the APOGEE stellar parameters
and abundances were derived through ASPCAP (García Pérez et al., 2016), which
determines the best-matching full synthetic spectra that has known stellar
parameters to the observed spectra. A new set of synthetic grids have been
utilized for this analysis using MARCS model atmospheres (Gustafsson et al.,
2008). We note that the reported $T_{\rm eff}$ and $\log g$ in APOGEE were
spectroscopically-derived but were also calibrated based on the photometric
$T_{\rm eff}$ from González Hernández & Bonifacio (2009) for the former and
asteroseismic $\log g$ from Pinsonneault et al. (2018) for the latter.

In Figure 3, the $\Delta$ indicate our values minus the APOGEE values. We find
a slightly higher $T_{\rm eff}$ in our analysis compared to the ASPCAP values
for the same stars, with an offset of 12.95 K and scatter of 103.64 K. There
is a slight positive trend between $\Delta$$T_{\rm eff}$ and $T_{\rm eff}$, as
similarly seen by González Hernández & Bonifacio (2009) in their comparison to
the $T_{\rm eff}$ in the literature. The same work, which we based our IRFM-
derived $T_{\rm eff}$ from, measure $\Delta$$T_{\rm eff}$= +50 $\pm$ 131 K for
their sample of giants compared to Alonso et al. (1999).

For $\log g$, our derived parameters are lower than the APOGEE values, with an
offset of 0.08 dex and scatter 0.31 dex. There is a slight increase in
$\Delta$$\log g$ with increasing $\log g$. Noticeably, there is an outlier,
2M19110434-5954152, at $\Delta$$\log g$$<$ 1 dex. This target has an observed
$M_{V}$ vs $V-K$ that is far from the theoretical isochrone made from the
star’s [$\alpha$/Fe], [Fe/H] and an age of 10 Gyr, causing the discrepancy.

We measure [Fe/H] that are lower than APOGEE values with an offset of 0.02 dex
and scatter 0.09 dex. The $\Delta$[Fe/H], shows a slight increase with $T_{\rm
eff}$, akin to the trend for $\Delta$$T_{\rm eff}$ vs $T_{\rm eff}$. This
follows as the measured [Fe/H] is derived from model spectra that has a
prescribed $T_{\rm eff}$ from our determination.

Lastly, we compare $\rm v_{micro}$ and find no offset with the APOGEE values
but find a scatter of 0.35 $\rm kms^{-1}$. There is a slight increasing trend
in $\Delta$$\rm v_{micro}$ with $T_{\rm eff}$ and $\log g$ which, similar to
[Fe/H], is because of the dependence of $\rm v_{micro}$ on these parameters,
reflecting a similar trend. There are two outlier stars with $\Delta$$\rm
v_{micro}$ $>$ 1 $\rm kms^{-1}$, 2M13581572+2602122 and 2M19120432-5951550,
which have $\rm v_{micro}$ = 0.46 $\rm kms^{-1}$ and 0.47 $\rm kms^{-1}$ from
APOGEE, respectively. We find that the $\rm v_{micro}$ derived from the
optical spectra for these stars are reliable, however, because of their flat
trends in log$(\epsilon)$ vs the reduced equivalent width.

###  4.2 Detailed Chemical Abundances from the Optical and IR

Figure 4: Violin plot summarizing the [X/Fe] abundances. We show the abundance distributions of 21 elements measured in this study (left, gold) side-by-side with the abundances from APOGEE where available (right, orange),ordered by increasing atomic number, to highlight the differences in the offsets and scatters in our sample from the optical and from the IR. We tabulate the abundance means and the scatters derived in this study in Table 4. We note that the optical and IR samples for a given element do not necessarily have the same number of stars. (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9)
---|---|---|---|---|---|---|---|---
$\rm[X/Fe]$ |  $\rm\mu_{optical}$ (dex) |  $\rm\sigma_{optical}$ (dex) | $\rm N_{optical}$ |  $\rm\mu_{IR}$ (dex) |  $\rm\sigma_{IR}$ (dex) | $\rm N_{IR}$ |  $\rm median_{[X/Fe],O-IR}$ (dex) |  $\rm\sigma_{[X/Fe],O-IR}$ (dex)
Mg | 0.33 | 0.09 | 60 | 0.24 | 0.08 | 62 | 0.09 | 0.09
O | 0.58 | 0.11 | 45 | 0.31 | 0.11 | 56 | 0.30 | 0.15
Si | 0.29 | 0.09 | 62 | 0.22 | 0.05 | 62 | 0.07 | 0.08
Ca | 0.16 | 0.08 | 62 | 0.15 | 0.17 | 62 | 0.01 | 0.18
Mn | -0.36 | 0.09 | 59 | -0.31 | 0.09 | 61 | -0.04 | 0.11
Cr | -0.12 | 0.08 | 62 | -0.09 | 0.18 | 62 | -0.03 | 0.20
Co | 0.22 | 0.11 | 57 | -0.15 | 0.27 | 60 | 0.36 | 0.25
Ni | -0.03 | 0.06 | 62 | -0.02 | 0.06 | 62 | -0.01 | 0.08
Zn | 0.06 | 0.12 | 62 | - | - | - | - | -
Na | -0.19 | 0.10 | 49 | 0.04 | 0.35 | 56 | -0.24 | 0.38
Sc | 0.07 | 0.13 | 62 | - | - | - | - | -
V | 0.07 | 0.14 | 60 | 0.19 | 0.26 | 47 | -0.11 | 0.27
Cu | -0.35 | 0.21 | 47 | 0.31 | 0.31 | 59 | -0.60 | 0.40
Ba | -0.02 | 0.21 | 58 | - | - | - | - | -
La | 0.29 | 0.28 | 59 | - | - | - | - | -
Ce | 0.31 | 0.22 | 47 | -0.04 | 0.32 | 47 | 0.35 | 0.25
Nd | 0.46 | 0.25 | 62 | - | - | - | - | -
Y | 0.08 | 0.14 | 60 | - | - | - | - | -
Zr | 0.22 | 0.17 | 56 | - | - | - | - | -
Eu | 0.69 | 0.28 | 14 | - | - | - | - | -
Table 4: Summary statistics for the [X/Fe] trends as shown by the violin plot
in Figure 4. We tabulate the mean [X/Fe], scatter in [X/Fe], and the number of
stars where the element, X, is measured for the optical data (columns 2-4) and
APOGEE (columns 5-7). We also report the median offset and the scatter in
$\rm[X/Fe]_{optical}-[X/Fe]_{IR}$ (columns 8 and 9).

In this work, we have selected accreted halo stars based solely on their
chemistry using the IR-derived abundances for [Mg/Mn] and [Al/Fe] from APOGEE
DR16. We then derived elemental abundances in follow-up optical spectra for
species spanning different families i.e. $\alpha$, Fe-peak, light and odd-Z,
and more notably neutron-capture (both $s$ and $r$).

From this analysis, we are able to compare the optical vs IR abundances for 13
elements we have in common with APOGEE DR16, namely O, Mg, Si, Ca, V, Cr, Mn,
Co, Ni, Cu, and Ce, as shown in the violin plot in Figure 4 and listed in
Table 4. Of these elements, O, Co, Na, Cu, and Ce show offsets $>$0.15 dex.
For some elements such as Co, Cu, and Ce, this is partially due to the
abundances we derived from twilight which were different by 0.20 dex from the
solar abundance reported from Asplund et al. (2009). Cr, Co, Na, V, Cu, and Ce
show optical-IR scatters $>$0.20 dex, which are mostly driven by the scatter
in the ASPCAP abundances as seen in Figure 4. Jönsson et al. (2018) similarly
compared the APOGEE DR13 and DR14 abundances with independent analyses in the
optical and measure a median offset and scatter of 0.05 dex and 0.15 dex,
respectively. On the other hand, our median offset and scatter are -0.01 dex
and 0.18 dex, respectively; we note that our sample is significantly metal-
poorer, and we include Cu (offset by -0.60$\pm$0.40 dex) and Ce (offset by
0.35$\pm$ 0.25 dex) which are not in the Jönsson et al. (2018) analysis, yet
our median offset and scatter are comparable to theirs.

Some elements are better measured in the optical while some are better
measured in the IR. For example we are able to derive the neutron-capture
element abundances for seven species, in comparison to only one (Ce) in the IR
data from APOGEE for our sample of accreted halo stars. On the other hand, we
could only, if even possible, poorly derive abundances for N and Al with our
optical spectra and therefore did not include those results, whilst APOGEE has
good measurements for them. Extensive discussions about individual elements
can be further found in the recent review of (Jofré et al., 2019, section
4.3). Al is one of the elements in APOGEE that our target selection was based
on, therefore confirming and quantifying the systematics between its optical
and IR abundances is critical. However, we were unable to determine accurate
Al abundances from the optical spectra. First, the atomic information of the
Al lines 6696.0 Å and 6698.7 Å have been flagged as possibly unreliable (Jofré
et al., 2019; Heiter et al., 2021). Second, 3D and non-LTE effects are
different for each line, in particular in metal-poor stars. Nordlander & Lind
(2017) studied these effects for the 2 lines discussed here and at least one
included in APOGEE (16763 Å), illustrating this point. Third, in most of the
cases of this particular study, they fall on the echelle order gaps. For the
11 stars in which the line was detected, the lines either fall between orders
making the normalisation in that region very uncertain or the spectra were too
noisy and abundances unreliable.

Additionally, determining Al in metal-poor stars is not straightforward
indeed. The recent work of Roederer & Lawler (2021) shows how for metal-poor
stars the two optical lines used here are rarely detected, and if detected,
yield abundances that are significantly higher than from blue or near UV
lines, making Al abundances difficult to interpret. Hence, to properly compare
IR with optical Al abundances for metal-poor stars remain subject of future
studies.

####  4.2.1 A comprehensive chemical dataset for accreted halo stars

Understanding the chemical abundances of accreted halo stars from both the
optical and the IR is therefore largely complementary and beneficial and gives
access to as many elements as possible. Because of this, in the following
analysis, we show mostly the optically-derived abundances for our sample but
for some elements we consider instead the APOGEE ASPCAP values, keeping in
mind their systematic differences as outlined in this section. Specifically,
we used the IR values for the following elements (1) O because the derived
abundance in the optical is enhanced ($\mu$ = 0.58 dex) which is contrary to
what is expected for stars with likely accreted origins (enhanced [O/Fe] were
similarly found by Jönsson et al. 2018 in their independent optical spectra
analysis of APOGEE stars) and (2) Si because its total scatter in the optical
is larger by 0.04 dex compared to the scatter in the IR, unlike the other
elements measured in the optical. This could possibly be due to our line
selection in Si that introduces an internal scatter of 0.08 dex, compared to
that in the IR (e.g., 0.05 dex).

##  5 Chemical Abundance Patterns of blob stars

Here, we discuss the detailed chemical abundances of the blob stars alongside
different stellar populations. We show the [X/Fe] vs [Fe/H] trends for these
potential accreted stars as open stars colored black if from the optical and
gray if from the IR. We group the elements into their different families:
$\alpha$ elements (Figures 5 and 6), Fe-peak (Figure 7), light and odd-Z
(Figure 8), and neutron-capture (Figure 9). Where available, we include data
for the Milky Way thin disc, thick disc, and halo (Bensby, 2014; Battistini &
Bensby, 2015, 2016; Reddy et al., 2003, 2006; Yong et al., 2013) as purple
diamonds, low-$\alpha$ accreted halo stars (Nissen & Schuster, 2010, 2011;
Fishlock et al., 2017) as gold pentagons, and LMC (Pompéia et al., 2008; Van
der Swaelmen et al., 2013) as green triangles. We also mark [X/Fe] = 0 dex and
[Fe/H] = 0 dex (i.e. solar metallicity) with grey dashed lines to guide the
eye. We note that these comparison data do not have overlap with our sample,
and therefore caution the reader that there are likely systematic offsets that
exist between our study and those in the literature as discussed in Sections
3.1 and 4.2. We also refer back to these sections regarding a discussion of
the offsets between our optical abundances and the APOGEE IR abundances in
interpreting our results.

###  5.1 $\alpha$ elements: Mg, O, Si, Ca

Figure 5: Total [$\alpha$/Fe] trend. We calculated [$\alpha$/Fe] from the
abundances of Mg, Si, and Ca for the blob targets in the optical (black stars)
and compare to the Milky Way disc (purple diamonds, Bensby 2014), low-$\alpha$
stars (teal pentagons, Nissen & Schuster 2010), and the LMC (green triangles,
Van der Swaelmen et al. 2013). The blob stars show lower [$\alpha$/Fe]
abundance compared to the Milky Way at [Fe/H] $>$-1.5 dex and similar trends
to the LMC and low-$\alpha$ stars. Figure 6: $\alpha$ elements. The [X/Fe]
abundance ratios in the $\alpha$ family of elements—Mg, O, Si, and Ca—against
[Fe/H] for the blob stars in the optical (black stars) and IR (gray stars) as
well as other comparison data. These samples are shown as follows: purple
diamonds for the Milky Way (Yong et al., 2013; Bensby, 2014), gold pentagons
for accreted stars (Nissen & Schuster, 2010), and green triangles for LMC (Van
der Swaelmen et al., 2013). We mark [X/Fe] = 0 and [Fe/H] = 0 with dashed grey
lines to guide the eye.

We show the [$\alpha$/Fe] vs [Fe/H] for our sample in Figure 5, where $\alpha$
is the averaged abundance for Mg, Ca, and Si derived from the high-resolution
optical spectra. We measure lower [$\alpha$/Fe] for the blob stars compared to
the Milky Way disk stars at the same [Fe/H], up to [Fe/H]$\sim$-1.5 dex. The
global [$\alpha$/Fe] trend show similarities with the LMC and the low-$\alpha$
stars from Nissen & Schuster (2010) where their [Fe/H] overlap. We next
discuss the individual [X/Fe] for the $\alpha$ elements. Mg: The [Mg/Fe] trend
of blob stars is similar to what Nissen & Schuster (2011) found for their
low-$\alpha$ sample, where the low-$\alpha$ population is distinct from the
high-$\alpha$ population up to [Fe/H]=-1.5 dex. The blob stars trend is
similar to that of the LMC as well, where the former appears to be an
extension of the latter’s trend to lower [Fe/H]. At -1.4 dex $<$ [Fe/H] $<$
-0.8 dex, where stars from our sample overlap with the comparison stars from
LMC, we see overlapping range in [Mg/Fe]. For the higher [Fe/H] end of our
sample (i.e. [Fe/H] $>$ -1.5 dex), the [Mg/Fe] values are systematically lower
compared to the Milky Way disc (e.g. Bensby 2014), in line with other previous
studies of the accreted halo population (e.g. Nissen & Schuster 2010; Hawkins
et al. 2015; Helmi et al. 2018; Hayes et al. 2018; Mackereth et al. 2019). O:
The [O/Fe] trend in the IR is lower than the Milky Way disc trend from Bensby
(2014), similar to what is found for our Mg results as well as for the
previous studies of low-$\alpha$ stars (Hawkins et al., 2015; Hayes et al.,
2018). This is reasonable given that both O and Mg are hydrostatic $\alpha$
elements which are created during hydrostatic burning that occurs in shells
within the cores of massive stars. Where there is overlap in [Fe/H], the blob
stars and the LMC stars from Van der Swaelmen et al. (2013) similarly overlap
in their [O/Fe] abundance, though the blob stars’ trend appears to have
different and shallower slope. Si: The [Si/Fe] trend in the IR is similar to
the low-$\alpha$ stars trend from Nissen & Schuster (2010) and to the LMC at
the same [Fe/H]. Previous studies have noted that the low-$\alpha$ and
high-$\alpha$ stars are less separated in [Si/Fe] (e.g. Hawkins et al. 2015;
Hayes et al. 2018) compared to other $\alpha$ elements in APOGEE, which we
similarly find in our sample comparing to Milky Way disc stars from Bensby
(2014). Ca: The [Ca/Fe] trend for the blob stars show the most similarity with
the LMC trend of all the $\alpha$ elements. It is lower than both the trends
for the Milky Way (disc and halo) and for the low-$\alpha$ stars from Nissen &
Schuster (2010). Like Si, Ca also does not separate the in-situ Milky Way
stars from the accreted halo stars as well as Mg and O do (Nissen & Schuster,
2010; Hayes et al., 2018), especially at the [Fe/H] regime in this study.
However, at the higher [Fe/H] end of our sample, i.e. [Fe/H] $>$ -1.0 dex, the
blob stars have lower [Ca/Fe] values compared to the thick disc stars from
Bensby (2014).

###  5.2 Fe-peak elements

Figure 7: Fe-peak elements. The [X/Fe] abundance ratios for Fe-peak elements
(Mn, Cr, Co, Ni, and Zn) against [Fe/H] for the blob stars in the optical
(black stars) as well as other comparison data shown as follows: purple
diamonds for the Milky Way (Yong et al., 2013; Bensby, 2014; Battistini &
Bensby, 2015), gold pentagons for accreted stars (Nissen & Schuster, 2011),
and green triangles for LMC (Van der Swaelmen et al., 2013). We mark [X/Fe] =
0 and [Fe/H] = 0 with dashed grey lines to guide the eye.

Fe-peak elements (Mn, Cr, Co, Ni, Zn), in contrast to $\alpha$ elements are
predominantly produced and dispersed via SNIa (Iwamoto et al., 1999). These
elements generally track the Fe abundance although other production mechanisms
like Si-burning in core-collapse supernovae (SNe) cause deviations from this
general trend (Kobayashi et al., 2006). Mn: The [Mn/Fe] we measure for the
blob stars in optical decreases with decreasing [Fe/H]. The sample of
low-$\alpha$ stars from Nissen & Schuster (2011) also agree with this [Mn/Fe]
trend at the higher [Fe/H] end. Nissen & Schuster (2011) and Hayes et al.
(2018) find that their sample of low-$\alpha$ (Mg) stars are indistinguishable
in the [Mn/Fe] vs [Fe/H] plane from in-situ Milky Way stars, which is shown as
well with our comparison to Milky Way disc and halo trends. The comparison
studies (e.g. Nissen & Schuster (2011) for the low-$\alpha$ stars and
Battistini & Bensby (2015) for the Milky Way disc stars) both take into
account HFS for Mn from Prochaska & McWilliam (2000). Cr: The [Cr/Fe] trend
has a slight decrease with lower [Fe/H] and is systematically lower from the
solar value (i.e. [Cr/Fe] = 0 dex) by 0.12 dex. This trend is slightly lower
compared to that of the Milky Way and LMC, and would be even lower by 0.10 dex
if we used the solar Cr abundance from Asplund et al. (2009) rather than the
one derived from our twilight spectra. At the higher [Fe/H] end of the sample,
the Cr abundances overlap with the low-$\alpha$ stars from Nissen & Schuster
(2011), where they find that the low- and high-$\alpha$ stellar populations
are not distinct from each other. Co: The [Co/Fe] trend for the blob stars
decreases with higher [Fe/H]. The [Co/Fe] trend for the blob stars and the LMC
seem to follow the same trend where (1) they have similar [Co/Fe] values where
their [Fe/H] overlap and (2) they have similar slopes with [Fe/H] that are
shallower than the Milky Way’s. Van der Swaelmen et al. (2013) account for Co
HFS for the LMC using data from Fuhr et al. (1988) while Battistini & Bensby
(2015) use Prochaska & McWilliam (2000) for the Milky Way disc stars and both
works, similar to our analysis, determine the abundance from the best-fit
model spectra, especially when the element is affected by HFS. Ni: The [Ni/Fe]
trend for the blob stars decreases with increasing [Fe/H]. Hayes et al. (2018)
noted that of the Fe-peak elements in their study, [Ni/Fe] separates the low-
Mg (accreted halo) and high-Mg (in-situ) populations the most. At [Fe/H]
$\geq$ -1.5 dex, the [Ni/Fe] trend for the blob stars is below the Milky Way
disc trend at a given [Fe/H], similar to previous studies (Nissen & Schuster,
2010; Hawkins et al., 2015; Hayes et al., 2018; Mackereth et al., 2019).
Interestingly, the [Ni/Fe] abundances overlap for our sample of stars and for
the LMC at the same [Fe/H]. Zn: The [Zn/Fe] trend for the blob stars is
enhanced at [Fe/H] $<$-1.5 dex and decreases with increasing [Fe/H], reaching
solar values at [Fe/H] = -1 dex. The blob stars share a similar [Zn/Fe] trend
with the low-$\alpha$ stars from Nissen & Schuster (2010), where the two
samples overlap at [Fe/H] $>$-1.5 dex. Nissen & Schuster (2010) also noted
that the [Zn/Fe] trend for their low-$\alpha$ stars, i.e. decreasing Zn with
increasing [Fe/H], is different from the trend they find for the high-$\alpha$
(in-situ) stars, i.e. constant Zn with [Fe/H]. For comparison, the Milky Way
disc stars have solar [Zn/Fe] abundance for the most part, changing to a
slightly above-solar but flat trend at [Fe/H] $<$ -1.0 dex, distinct from what
we find for our sample.

###  5.3 Light and Odd-Z elements

Figure 8: Light and odd-Z elements. The [X/Fe] abundance ratios for light and
odd-Z elements (Na, Sc, V, and Cu) against [Fe/H] for the blob stars in the
optical (black stars) as well as other comparison data shown as follows:
purple diamonds for the Milky Way (Yong et al., 2013; Bensby, 2014; Battistini
& Bensby, 2015; Reddy et al., 2003, 2006), gold pentagons for accreted stars
(Nissen & Schuster, 2010, 2011; Fishlock et al., 2017), and green triangles
for LMC (Van der Swaelmen et al., 2013). We mark [X/Fe] = 0 and [Fe/H] = 0
with dashed grey lines to guide the eye.

The production of Odd-Z elements depend on the neutron excess from
$\rm{}^{22}Ne$ and are therefore, for the most part, metallicity-dependent
except for certain elements (e.g. V) (Kobayashi et al., 2020). Na is mainly
produced in core-collapse SNe and is sensitive to the initial C in the star
forming gas (Kobayashi et al., 2006). At higher [Fe/H], AGB stars are also
expected to produce some Na (Nomoto et al., 2013). Sc is mainly produced in
massive stars during C and Ne burning and is eventually dispersed through
core-collapse SNe (Woosley et al., 2002). It is therefore seen to follow other
$\alpha$ elements in its trend with metallicity. Na: The [Na/Fe] for the blob
stars in the optical shows a flat trend with [Fe/H] with a mean abundance of
-0.19 dex and error of 0.05 dex. In comparison, the same set of stars in
APOGEE have typical uncertainties of $\sim$0.20 dex, highlighting why deriving
the abundance in the optical for certain elements, such as Na, is necessary.
Nissen & Schuster (2010) find a depleted and flat [Na/Fe] trend for their
low-$\alpha$ stars compared to their high-$\alpha$ stars as well, similar to
what we find for our blob stars compared to Milky Way stars from Bensby (2014)
at [Fe/H] $\gtrsim$ -1.2 dex. At lower [Fe/H] the Milky Way disc stars overlap
with our sample. The blob stars [Na/Fe] abundances are also very similar to
the LMC’s where there is overlap in [Fe/H]. Sc: The [Sc/Fe] trend for the blob
stars is essentially flat with [Fe/H]. In comparison, the LMC stars from Van
der Swaelmen et al. (2013) show a flat trend that turns over and decreases at
higher [Fe/H]. Fishlock et al. (2017) specifically followed up on the accreted
stars from Nissen & Schuster (2010) and derived [Sc/Fe] abundances to compare
to an earlier study (i.e. Nissen et al. 2000). Nissen et al. (2000) found that
the [Sc/Fe] of the low-$\alpha$ stars is lower compared to that of the
high-$\alpha$ stars at the same [Fe/H] for the range -1.4 $<$ [Fe/H] $<$ -0.7
dex. At the higher [Fe/H] end of our sample, the blob stars overlap with the
stars from Fishlock et al. (2017) and both are lower than the Milky Way disk
trend at the same [Fe/H]. However, at the same [Fe/H], some of our program
stars also have higher [Sc/Fe] abundances, and in general the mean [Sc/Fe] for
the blob stars is 0.07 dex. V: We find a flat [V/Fe] trend for the blob stars
with a mean [V/Fe] = 0.07 dex. Where there is overlap in metallicity i.e.
[Fe/H]$>$-1.5 dex, the [V/Fe] abundance trend for our sample also greatly
resembles the LMC trend from Van der Swaelmen et al. (2013), both distinct
from the Milky Way disc (Battistini & Bensby, 2015). Both comparison studies
also take into account HFS, namely from Martin et al. (1988) for the LMC and
from Prochaska & McWilliam (2000) for the Milky Way disc stars. Taking into
account the HFS effect is important for V. For example, as Van der Swaelmen et
al. (2013) illustrated for the LMC, they measure [V/Fe] that is higher by
$\approx$0.22 dex without the HFS corrections. Cu: We find depleted [Cu/Fe]
abundances for the blob stars with mean of -0.35 dex, where the trend is
essentially flat for [Fe/H]$>$-1.5 dex but is decreasing with decreasing
[Fe/H] below this value. Our Cu result agrees with that of Nissen & Schuster
(2011) as well as the more recent study from Matsuno et al. (2020), where both
show [Cu/Fe] abundances below 0 dex for low-$\alpha$ accreted halo stars.
Taking into account the difference between our solar Cu abundance and that of
Asplund et al. (2009) would put the blob stars’ [Cu/Fe] at an even lower
trend. Van der Swaelmen et al. (2013) similarly find [Cu/Fe] $<$ 0 dex for the
LMC. The blob stars, the low-$\alpha$ stars, and the LMC all show lower Cu
abundances than the Milky Way (Reddy et al., 2003, 2006). All comparison
studies also take into account the HFS for Cu, i.e., Prochaska & McWilliam
(2000) for the low-$\alpha$ stars, Bielski (1975) for the LMC, and Kurucz
models for the Milky Way stars from Reddy et al. (2003, 2006).

###  5.4 Neutron-capture elements

Figure 9: Neutron-capture elements. The [X/Fe] abundance ratios for neutron-
capture elements—Ba, La, Ce, Nd (heavy-s process), Y, Zr (light-s process),
and Eu (r-process)—against [Fe/H] for the the blob stars in the optical (black
stars) and the IR (gray stars) as well as other comparison data shown as
follows: purple diamonds for the Milky Way (Yong et al., 2013; Bensby, 2014;
Battistini & Bensby, 2016), gold pentagons for accreted stars (Nissen &
Schuster, 2011; Fishlock et al., 2017), and green triangles for LMC (Van der
Swaelmen et al., 2013). We mark [X/Fe] = 0 and [Fe/H] = 0 with dashed grey
lines to guide the eye.

Neutron-capture elements are heavier than Fe and made through a slow ($s$) or
rapid ($r$) capture of neutrons. The main difference is that the $s$-process
neutron capture happens slower than the $\beta$-decay while the $r$-process
captures many neutrons at timescales faster than the $\beta$-decay. The
envelopes of AGB stars are considered the main source of $s$-process (Busso et
al., 1999), but a weaker component also comes from massive stars related to
22Ne neutron production (Pignatari et al., 2010; Frischknecht et al., 2016).
On the other hand, the production site of $r$-process elements are less known,
though core-collapse SNe and neutron star mergers provide viable pathways
(e.g. Kasen et al. 2017). Ba, La, Ce, and Nd are heavy $s$-process elements
while Y, and Zr are light $s$-process elements, with heavy and light
pertaining to the atomic number (Busso et al., 2001). Eu on the other hand is
considered a pure $r$-process elements, contributing 97% of the Eu present in
the sun (Sneden et al., 2008). Ba:The blob stars have a flat [Ba/Fe] trend
with [Fe/H] centered around solar values (mean of -0.02 dex) and a scatter
that increases with lower [Fe/H] irrespective of the SNR. On the other hand,
the low-$\alpha$ stars from Nissen & Schuster (2011) have [Ba/Fe] below solar
where they find that the high and low-$\alpha$ halo stars overlap in [Ba/Fe].
The sample of accreted stars from Matsuno et al. (2021) has an elevated range
in [Ba/Fe] i.e., 0 $<$ [Ba/Fe] $<$ 1 dex compared to our sample with -0.5 $<$
[Ba/Fe] $<$ 0.6 dex at the same [Fe/H] range. Aguado et al. (2021) also
measure [Ba/Fe] for GES stars and find Ba abundances that span a large range
of above-solar values from GALAH DR3 (Buder et al., 2020), though for the
stars which they derived the abundances themselves, they measure solar
[Ba/Fe], similar to what we find. Compared to our sample, the LMC has elevated
[Ba/Fe] centered on $\sim$ 0.5 dex with [Ba/Fe] increasing with [Fe/H]. The MW
disc similarly has [Ba/Fe] centered at 0 dex. All the comparison studies
account for HFS as well, namely McWilliam (1998) for the low-$\alpha$ stars
and Rutten (1978) for the LMC. La: The blob stars have a flat [La/Fe] trend
with [Fe/H], similar to the low-$\alpha$ stars from Fishlock et al. (2017).
However, our stars are offset higher by 0.3 dex compared to their sample
centered at [La/Fe] = 0 dex, where they find no difference in the [La/Fe]
abundance of high and low-$\alpha$ stars. Matsuno et al. (2020) similarly find
elevated [La/Fe] abundances for their sample of accreted stars centered at
$\sim$0.4 dex. Matsuno et al. (2021) further studied GES stars using GALAH DR3
data and find elevated [La/Fe] abundances as well. They likewise find that La
does not separate accreted vs in-situ populations. The blob stars’ [La/Fe]
trend exhibit similarities with the LMC, as the LMC also shows a flat and
elevated [La/Fe] trend with [Fe/H] compared to the Milky Way disc. In
contrast, the Milky Way disc has lower [La/Fe] trend that decreases with
[Fe/H]. Ce: The [Ce/Fe] trend for the blob stars is flat and centered at
[Ce/Fe] = 0.31 dex. On the other hand, the low-$\alpha$ accreted halo stars
from Fishlock et al. (2017) have subsolar [Ce/Fe] that is flat with [Fe/H].The
same authors note that there is no difference in the Ce abundances of their
sample of high and low-$\alpha$ stars. Matsuno et al. (2020) also find
elevated Ce values for their low-$\alpha$ stars sample, with the [Ce/Fe] trend
centered at $\sim$0.2 dex. Nd: The blob stars show a flat [Nd/Fe] trend with
[Fe/H], similar to the low-$\alpha$ stars from Fishlock et al. (2017) but
shifted to higher values. Our sample is centered on 0.46 dex while theirs is
centered on 0.20 dex. However, the [Nd/Fe] trend for the blob stars would be
shifted lower by 0.20 dex and closer to the trend from Fishlock et al. (2017)
if we were to use solar abundance from Asplund et al. (2009). These authors
find no difference in the [Nd/Fe] of their sample of high and low-$\alpha$
stars, though the Nd for the low-$\alpha$ stars have a higher scatter. Matsuno
et al. (2020) also measure Nd for their sample of accreted stars and find
similarly flat and elevated values at [Nd/Fe] = 0.40 dex. They likewise find
no difference in the [Nd/Fe] trend with metallicity for their sample of
accreted versus in-situ stars. The Milky Way disc stars from Battistini &
Bensby (2016), on the other hand show a lower, and decreasing [Nd/Fe] trend
with higher [Fe/H]. This comparison Milky Way data had HFS accounted for from
Roederer et al. (2008). Y: The [Y/Fe] trend for the blob stars is flat with
[Fe/H] and elevated with a mean of 0.08 dex. For comparison, Nissen & Schuster
(2011), Aguado et al. (2021), and Matsuno et al. (2020) measure below solar,
below solar, and solar values for [Y/Fe], respectively, with the low-$\alpha$
stars from Nissen & Schuster (2011) also showing a flat [Y/Fe] vs [Fe/H]
trend. Adopting Y solar abundance from Asplund et al. (2009) however would
decrease the mean abundance by $\sim$0.25 dex and put our sample at the same
[Y/Fe] range as these studies. The Milky Way stars (Bensby, 2014) show a flat
[Y/Fe] trend with [Fe/H] that similarly lie $<$0 dex. The LMC, on the other
hand, has an elevated [Y/Fe] vs [Fe/H] trend compared to the blob stars. Zr:
The blob stars exhibit a flat [Zr/Fe] vs [Fe/H] trend centered at 0.22 dex.
This trend is offset higher compared to the low-$\alpha$ accreted stars sample
from Fishlock et al. (2017) which has [Zr/Fe] $\sim$ 0 dex. The LMC [Zr/Fe]
trend from Van der Swaelmen et al. (2013) is similarly flat and elevated. On
the contrary, the Milky Way disc from Battistini & Bensby (2016) shows
decreasing [Zr/Fe] with higher [Fe/H]. Eu: Though we have a sample of 62
accreted halo stars, we are only able to measure Eu for a handful of them. We
find enhancement in Eu for the blob stars that is flat and centered at
[Eu/Fe]=0.69 dex. Using Eu solar abundance from Asplund et al. (2009) would
shift the trend down by 0.3 dex. The sample of low-$\alpha$ stars from
Fishlock et al. (2017) are offset lower but still with super-solar values
centered at 0.30 dex which slightly decreases with increasing [Fe/H]. These
authors find that the low-$\alpha$ stars have higher [Eu/Fe] compared to the
high-$\alpha$ stars that have in-situ origins. Matsuno et al. (2020), Matsuno
et al. (2021), and Aguado et al. (2021) all find enhanced Eu abundances for
their respective samples of low-$\alpha$ accreted stars, pointing to the
prevalence of r-process in their progenitor. It is worth noting that r-process
sites are rare and so the r-process abundance trends in low-mass systems are
mostly due to stochastic effects (e.g., Ji et al. 2016). Matsuno et al. (2021)
additionally find that [Eu/Fe] separate in-situ versus accreted material very
well, and [Eu/Mg] even more so. Van der Swaelmen et al. (2013) measure Eu
abundances for LMC stars that decrease with increasing [Fe/H], similar to what
Fishlock et al. (2017) find for their sample, but unlike the trend that we see
for the blob stars that seem to increase with [Fe/H]. However, it is harder to
comment more definitively on the [Eu/Fe] trend because we do not have many
stars with measured Eu abundance and for those that do, they show an overall
high scatter $\sim$0.28 dex. Both the accreted stars and the LMC exhibit
higher [Eu/Fe] abundances compared to in-situ Milky Way stars from Battistini
& Bensby (2016). These comparison studies all similarly take into account HFS
i.e., from Lawler et al. (2001) for the accreted stars from Aguado et al.
(2021) and Fishlock et al. (2017), and the Milky Way stars from Battistini &
Bensby (2016).

##  6 Discussion

###  6.1 Neutron-capture element abundance ratios

Figure 10: Element ratios with Eu. [Y/Eu] and [Eu/Mg] trends with [Fe/H] for
the blob sample (black stars) as well as other comparison data shown as
follows: purple diamonds for the Milky Way (Bensby, 2014; Battistini & Bensby,
2016), gold pentagons for accreted stars (Nissen & Schuster, 2011; Fishlock et
al., 2017), and green triangles for LMC (Van der Swaelmen et al., 2013). We
mark [X/Fe] = 0 with dashed grey lines to guide the eye. Figure 11: Element
ratios with Ba. Element to element ratio with Ba as a function of [Fe/H] for
the blob sample (black stars) as well as other comparison data shown as
follows: purple diamonds for the Milky Way (Bensby, 2014; Battistini & Bensby,
2016), gold pentagons for accreted stars (Nissen & Schuster, 2011; Fishlock et
al., 2017), and green triangles for LMC (Van der Swaelmen et al., 2013). We
mark [X/Fe] = 0 and [Fe/H] = 0 with dashed grey lines to guide the eye. We
also show a pure r-process ratio with a dotted blue line taken from Bisterzo
et al. (2014). Figure 12: [La/Zr] vs [Fe/H] the blob sample (black stars) as
well as other comparison data shown as follows: purple diamonds for the Milky
Way (Bensby, 2014; Battistini & Bensby, 2016), gold pentagons for accreted
stars (Fishlock et al., 2017), and green triangles for LMC (Van der Swaelmen
et al., 2013). We mark [X/Fe] = 0 with dashed grey lines to guide the eye.

We take a deeper look into the neutron-capture abundance ratios with respect
to each other to understand better which processes dominate the chemical
evolution of our sample of accreted stars. Specifically, we highlight [Y/Eu]
and [Eu/Mg] as a function of [Fe/H] in Figure 10, abundance ratios with
respect to Ba in Figure 11, and [La/Zr] vs [Fe/H] in Figure 12. The figure
legends follow those of Figures 5, 6, 7, 8, and 9. We combined data sets with
overlapping sample selection and methods to compare our results to other
stellar populations, i.e., Bensby (2014) and Battistini & Bensby (2016) for
the Milky Way, and Nissen & Schuster (2010), Nissen & Schuster (2011), and
Fishlock et al. (2017) for low-$\alpha$ stars. We also include stars from the
LMC from Van der Swaelmen et al. (2013).

These combinations of elements have been previously explored by other studies
on accreted stars (e.g. Nissen & Schuster, 2011; Fishlock et al., 2017; Aguado
et al., 2021; Matsuno et al., 2020; Matsuno et al., 2021) and compared to
trends within dwarf galaxies (e.g. Venn et al., 2004; Tolstoy et al., 2009)
because they are an indicator of the relative contributions of s- and
r-processes in the creation of these elements. This is especially important to
discuss for dwarf galaxies because (1) r-process nucleosynthesis is very rare,
and so its stochasticity in these lower-mass systems can greatly affect
r-process enrichment, and (2) a delayed s-process enrichment suggests lower
star formation rate.

The GCE modeling from Bisterzo et al. (2014) find the following solar
s-process contributions: 72% for Y, 66% for Zr, 85% for Ba, 76% for La, 83%
for Ce, 58% for Nd, and 6% for Eu. In Figure 11, we show where the stars lie
(dotted blue line) should they have been purely made through r-process, which
is adapted from Battistini & Bensby (2016) using the GCE model from Bisterzo
et al. (2014), where they had a sample of Milky Way stars within the
metallicity range -1.4 $<$ [Fe/H] $<$ 0.4 dex. We note that our comparison is
done with solar s-process predictions though our sample has lower [Fe/H].
Nonetheless, we show the resulting pure r-process prediction from this as a
reference point as previous studies have done.

####  6.1.1 [Y/Eu] and [Eu/Mg]

The blob stars show depleted [Y/Eu] at -0.76$\pm$0.22 dex, which is lower
compared to the LMC, Milky Way and low-$\alpha$ stars. However, we note that
our sample is more metal-poor and we barely have overlapping [Fe/H] with these
other stellar populations. Since the scatter is large, it is hard to tell if
there is a trend in [Y/Eu] with [Fe/H], although as s-process should start
contributing at later times, the [Y/Eu] trend is expected to increase with
[Fe/H] as is seen for the Milky Way. Fishlock et al. (2017) and Matsuno et al.
(2020) find that at the same [Fe/H], the in-situ Milky Way stars have higher
[Y/Eu], suggesting the delayed nature of s-process production in the accreted
population. This may be similar to what we see for the blob stars with
[Fe/H]$>$-1.5 dex compared to the Milky Way stars from Bensby (2014) and
Battistini & Bensby (2016), but this could possibly be due to systematic
differences. Present day dwarf spheroidals have also been observed to have a
lower [Y/Eu] compare to the Milky Way halo (Venn et al., 2004; Tolstoy et al.,
2009). Y is a product of the weak s-process that depends on $\rm{}^{22}Ne$ for
neutrons, which in turn depends on the CNO abundance. Similar to Matsuno et
al. (2020) and Nissen & Schuster (2011), we find that the weak s-process is
inefficient in the progenitor of the blob stars because of their depleted
[Y/Eu], suggesting a lower star formation rate.

The [Eu/Mg] trend for the blob stars is elevated with a mean abundance of
0.29$\pm$0.29 dex, slightly higher than low-$\alpha$ stars from Nissen &
Schuster (2010) and Fishlock et al. (2017) and the Milky Way (Bensby, 2014;
Battistini & Bensby, 2016), but lower compared to the LMC (Van der Swaelmen et
al., 2013). Matsuno et al. (2020); Matsuno et al. (2021) similarly find
elevated [Eu/Mg] at $\sim$0.30 dex for their GES stars compared to in-situ
stars ([Eu/Mg] = 0 dex) at the same [Fe/H]. These authors posited that the
observed [Eu/Mg] for GES is either due to (1) the delayed production of Eu
through r-process with neutron star mergers or (2) underproduction of Mg
through a top-light initial mass function (IMF). Their chemical evolution
modeling supports the former scenario, in agreement with our results, which we
discuss in detail in the following section comparing element abundances to Ba.
Indeed, a more recent study by Naidu et al. (2021) proposed that the r-process
enrichment from NSM is delayed by 0.5 to 1 Gyr to explain their GES Eu
abundance.

####  6.1.2 Element abundance ratios with Barium

In this section, we compare the element abundance ratios with respect Ba. We
find an increasing [Ba/Y] with [Fe/H] for the blob stars, similar to what
Nissen & Schuster (2011) find for their sample of low-$\alpha$ stars. Our
sample has a a mean [Ba/Y] = -0.06 $\pm$ 0.14 while Fishlock et al. (2017)
report [Ba/Y] = 0.01 $\pm$ 0.06 dex for the low-$\alpha$ population. The
chemical evolution modeling from Nissen & Schuster (2011) posit that the
increasing trend in [Ba/Y] for the low-$\alpha$ stars supports a progenitor
that had a lower rate of chemical evolution, mostly enriched by SNIa with a
delayed s-process enrichment from low-metallicity low-mass AGB stars. Such
high [Ba/Y] ratio is also seen in dwarf spheroidals around the Milky Way and
is attributed to lower rate of chemical evolution (Tolstoy et al., 2009).

Following from the [Ba/Y], Fishlock et al. (2017) explored the [La/Zr] trend
for low-$\alpha$ stars as Ba and La are both heavy s-process elements produced
through the main s-process in the envelopes of AGB stars, while Y and Zr are
both light s-process elements produced through the weak s-process in massive
stars. We similarly show in Figure 12 the [La/Zr] as a function of [Fe/H] for
the blob stars. We find a mean of 0.07 dex for our sample and though there is
large scatter, the majority of the blob stars follow the same trend as the
low-$\alpha$ stars from Fishlock et al. (2017). The same authors used
predictions from Fishlock et al. (2014) to explore the [La/Zr] for AGB stars
of different masses and find that at [Fe/H] = -1.2 dex, the super-solar
[La/Zr] ratios are more consistent with enrichment by low mass (i.e., 1-3 $\rm
M_{\odot}$) AGB stars.

[Ba/Eu] is a good diagnostic in chemical evolution as Ba is mainly produced
through the s-process while Eu is considered a pure r-process elements, with
only 6% of Eu being produced in s-process at solar and low [Fe/H] (e.g., -0.3
dex) (Bisterzo et al., 2010, 2014). The [Ba/Eu] trend for the blob stars
support a pure r-process enrichment, with a mean of -0.89$\pm$0.21, in
agreement with the theoretical abundance ratio for r-process (Bisterzo et al.,
2014; Battistini & Bensby, 2016). On the other hand, the low-$\alpha$ stars
from Fishlock et al. (2017) are offset higher at -0.39$\pm$0.12 dex, though
they also have higher [Fe/H]. They also find that the in-situ stars have
higher [Ba/Eu], further supporting the r-process enhancement scenario for the
low-$\alpha$ stars compared to the Milky Way. In comparison, the LMC has a
higher [Ba/Eu] compared to the Milky Way at the same [Fe/H], alluding to the
larger contribution of s-process. This heavy s-process enhancement is
similarly seen in other present day dwarf galaxies (Letarte et al., 2010; Hill
et al., 2019) which further shows that the neutron-capture element enrichment
in the blob progenitor and present day Milky Way dwarfs are dominated by
different processes. The GES stars from Aguado et al. (2021) similarly exhibit
depleted [Ba/Eu] at -0.7 dex and find that the trend is flat for [Fe/H]$<$-1.5
dex, and increases at higher metallicity, signaling the start of s-process
enrichment. To confirm this trend seen by the authors, we require Eu abundance
measurements from higher metallicity blob stars.

The rest of the element abundance ratios with Ba in Figure 11 i.e., [Zr/Ba] at
0.19$\pm$0.21 dex, [La/Ba] at 0.24$\pm$0.16 dex, [Ce/Ba] at 0.27$\pm$0.16 dex,
and [Nd/Ba] at 0.44$\pm$0.16 dex further support that the blob stars are
r-process enhanced, which is different compared to present day dwarfs like the
LMC that have greater s-process contribution because of an extended star
formation compared to GES.

###  6.2 Comparison to previous studies of low-$\alpha$ stars

We further compare the abundance patterns of the blob stars to those of
low-$\alpha$ accreted halo stars from Nissen & Schuster (2010, 2011), Fishlock
et al. (2017), and Matsuno et al. (2020). This comparison comes with caveats
in that the data, sample of stars, and analyses are different among these
studies and ours. All three comparative studies did a line-by-line
differential analysis with a low-metallicity standard star and used solar
abundances from Asplund et al. (2005); Asplund et al. (2009) while we derived
our abundances with respect to the Sun and used solar abundances derived from
our own twilight spectra. However, even with these differences, we can still
compare the relative trends of the accreted halo stars from each study. We
note that there are absolute differences as well, but caution that this could
be due to a number of effects (e.g., line selection, continuum normalization,
NLTE, HFS treatment etc.).

Stellar populations in the halo that have different [$\alpha$/Fe] abundances
and kinematics have been observed in earlier studies (e.g. Nissen & Schuster
1997; Fulbright 2002; Gratton et al. 2003). However, whether this abundance
distribution is continuous or bimodal was not known until Nissen & Schuster
(2010, 2011) and Schuster et al. (2012) derived high precision abundances and
orbital integration for their sample of inner halo stars. We therefore focus
our comparison with Nissen & Schuster (2010) and Nissen & Schuster (2011) that
derived abundances for $\alpha$, Fe-peak, light/odd-Z, and neutron-capture
elements. They selected low metallicity dwarf stars in the solar neighborhood
that have halo kinematics (i.e. $V_{\rm total}>$ 180 $\rm km$ $s^{-1}$). In
addition to the two populations separating in [$\alpha$/Fe]-[Fe/H], they also
differ in their Ni and Na trends with the low-$\alpha$ population having lower
values compared to the high-$\alpha$ population. These trends are similar to
our result (Figure 8 and 7), indicating that our blob stars are chemically
similar to the low-$\alpha$, accreted stars from Nissen & Schuster (2010,
2011). They also found low values and high scatter for Cu in their
low-$\alpha$ population, distinct from the high-$\alpha$ trend which is offset
higher with lower scatter. We observe the same behavior as their low-$\alpha$
stars for our sample’s Cu abundances. Kobayashi et al. (2006, 2020) showed
that Cu production depends on the excess neutrons from $\rm{}^{22}Ne$ which is
produced from $\rm{}^{14}N$ during the CNO cycle; Nissen & Schuster (2011)
posit that the trend they found, similar to ours, is due to these stars
forming from gas enriched by SNIa and Cu produced by CNO-poor massive stars.
This picture is also supported by the blob stars’ lower abundances in Na and
Ni compared to the Milky Way at the same [Fe/H], as these elements are
similarly made in massive stars.

Fishlock et al. (2017) followed up on the sample from Nissen & Schuster (2010)
and derived abundances for neutron-capture elements (e.g. Zr, La, Ce, Nd, and
Eu) as well as Sc for 27 Galactic dwarf stars. They investigated the neutron-
capture element abundances of these stars to constrain the mass range of AGB
stars that contributed to the chemical enrichment of their progenitor. Among
their neutron-capture elements, they found that light-$s$ process element Zr
separates the low-$\alpha$ stars from high-$\alpha$ in-situ stars the most.
The measured Zr abundance for our sample is elevated compared to their study,
though the relative trends are similar where both show an essentially flat
trend with [Fe/H]. On the other hand, the heavy-$s$ process elements i.e. La,
Ce, and Nd do not have distinct trends between these two populations. Similar
to Nissen & Schuster (2010), their chemical evolution modeling of these
n-capture abundances point to a time-delay of low-mass AGB stars’
contribution. Though we find offsets between our derived [X/Fe] for the
neutron-capture elements and those from this study, the neutron-capture
element-to-element ratios actually agree between these two samples, as
discussed in Section 6.1 and shown in Figure 12 pointing to similar chemical
evolution scenarios.

Lastly, we compare to the recent study by Matsuno et al. (2020) that, similar
to this work, observed low-$\alpha$ accreted halo stars in the red giant
branch. Specifically, their sample consisted of 7 metal-poor stars, 7
$\alpha$-rich stars, 9 $\alpha$-poor stars, and 3 very $\alpha$-poor stars.
They measured abundances for 23 different elements, similarly spanning groups
that are of interest to our study, and in addition, derived masses for these
stars with asteroseismology. They found subsolar values for Y as well as Cu,
similar to Nissen & Schuster (2011), a result of the time delay in the light-s
process element production. In contrast, we measure slightly above solar
values for our Y abundances, but subsolar values for the Cu abundances,
similar to Matsuno et al. (2020). However, we do confirm an underproduction of
Y (Figure 10) and delay in s-process enrichment (Figure 11) as discussed in
the previous section when looking at neutron-capture abundance ratios.

Very recently, there have been works by Matsuno et al. (2021), Aguado et al.
(2021), and Naidu et al. (2021) that focus on the r-process in GES stars where
all found elevated Eu, highlighting the r-process enhancement in the GES
system. There are various sites for r-process production (e.g., electron-
capture supernovae or magnetorotationally-driven supernovae, Cescutti &
Chiappini (2014)) but the simple chemical evolution model from Matsuno et al.
(2021) best agree with a neutron star merger scenario (e.g. Rosswog et al.
2018) for their sample of GES stars. The 14 stars where we measure Eu from
similarly show Eu enhancement and the neutron-capture element abundance ratio
discussion in Section 6.1 support the dominance of the r-process in the
progenitor of the blob stars.

From this comparison, we put forth that the detailed abundance patterns for
our sample of blob stars generally agree with these previous studies of
low-$\alpha$ stars and suggest that they were accreted from a dwarf galaxy
with a lower rate of chemical evolution compared to the Milky Way. It is quite
noteworthy that the detailed chemical abundances of our sample of likely
accreted halo stars, which were selected purely through chemical tagging, have
good overall agreement with these studies of low-$\alpha$, accreted stars that
were selected differently through kinematics, or sometimes in combination with
metallicity.

###  6.3 Comparison to Milky Way dwarf galaxies

The previous section, as well as more recent studies suggest that these
low-$\alpha$ blob stars were accreted from a massive dwarf galaxy with stellar
mass in the range of $\rm 8.5<logM_{\odot}<9.0$ (Mackereth et al., 2019;
Fernández-Alvar et al., 2018) and a total mass of $\rm\sim 10^{11}M_{\odot}$
(Das et al., 2020) during the epoch of disc formation, 8-10 Gyr ago. Das et
al. (2020) find a range of ages (8 to 13 Gyr) of stars belonging to the blob,
and argue that it is hard to disentangle a single vs multiple progenitor
scenario, especially as these stars were accreted earlier in the history of
our Galaxy. However, as pointed out by the same authors, not very many massive
systems can exist around the Milky Way (see Rodríguez-Puebla et al. 2013). In
this section, we compare the detailed chemical abundances of blob stars to
those of massive Milky Way dwarf galaxies.

First we compare to the LMC, Milky Way’s most massive satellite with a
dynamical mass of $\sim\rm 10^{11}M_{\odot}$ (Erkal et al., 2020). This is a
relevant comparison as mass estimates for the GES system roughly compare to
that of LMC. From Section 5 and using LMC abundances from Van der Swaelmen et
al. (2013), we showed that the $\alpha$ (Mg, Si, Ca), Fe-peak (Cr, Ni, Co),
light/odd-Z element (Na, V, Cu), and neutron-capture (La, Y, Zr) element
trends for the blob stars bear great similarity with the trends from LMC.
However, a closer look at the neutron-capture element ratios show that the
blob stars have a larger r-process enrichment compared to the LMC. These
comparisons indicate that although the $\alpha$, Fe-peak, and light/odd-Z
production may be similar for the blob progenitor and the LMC, their heavy-
element production are distinct from each other. However, this could well may
be a [Fe/H] effect; it is interesting to speculate how the blob track would
compare to the LMC if it survived to the present day.

Next, we compare to the Milky Way dwarf galaxy Sagittarius (Ibata et al.,
1994), which is currently being disrupted by the Galaxy’s potential. From its
stars’ velocity dispersion, Law & Majewski (2010) estimated an initial bound
mass of $\rm 6.4\times 10^{8}~{}M_{\odot}$ for Sagittarius before it was
stripped off stars by the Milky Way. It is interesting to think of these
comparison satellite galaxies as follows: the LMC as an intact massive
satellite, Sagittarius as a currently disrupted massive satellite, and GES as
a fully disrupted massive satellite. McWilliam et al. (2013) similarly found
low [$\alpha$/Fe], [Na/Fe], [Al/Fe], and [Cu/Fe] for the Sagittarius dwarf
stars compared to the Milky Way halo. However, they posit that this is due
instead to a top-light IMF instead of a SNIa time-delay.

Fornax is another massive Milky Way dwarf satellite with mass $\rm 1.6\times
10^{8}~{}M_{\odot}$ (Łokas, 2009). Letarte et al. (2010) investigated the
detailed chemical abundance of Fornax stars and found, similar to this study,
$\alpha$ element abundance trends that are lower than the Milky Way’s at a
given [Fe/H]. They also measured low Ni and Na, akin to what we see for our
blob stars. It is important to make a distinction however, that the stars in
Fornax from Letarte et al. (2010) are young (2 to 6 Gyr old) compared to the
blob stars in our sample.

Tolstoy et al. (2009) and Nissen & Schuster (2011) discussed in length the
[$\alpha$/Fe] vs [Fe/H] of different Milky Way dwarf galaxies and where their
respective [Fe/H]knee and [Fe/H]max occur. The former is an indication of star
formation rate i.e. when SNIa started enriching the system’s gas while the
latter is related to how long star formation proceeded in the galaxy. Lower
mass dwarf galaxies have lower [Fe/H]knee and [Fe/H]max (e.g. Koch et al.
2008). Meanwhile, the dwarf galaxies we have compared to in this section have
higher values for either parameter, and sometimes both. Sagittarius has
[Fe/H]knee = -1.3 dex and [Fe/H]max = 0 dex (Sbordone et al., 2007; Carretta
et al., 2010), and Fornax has [Fe/H]max = -0.6 dex (Letarte et al., 2010). The
LMC has an interestingly low [Fe/H]knee at $\leq$-2.2 dex (Nidever et al.,
2020). On the other hand, Nissen & Schuster (2011) did not find a [Fe/H]knee
for their low-$\alpha$ because of a lack of metal poor stars with [Fe/H] $<$
-1.5 dex, though they found a [Fe/H]max $\approx$ -0.75 dex . In contrast, we
cover a larger sample of metal-poor stars but a sample extending to even lower
metallicities i.e. [Fe/H] $<$ -2.0 is needed in order to fully characterize
where the plateau is.

To summarize, these comparisons to Milky Way dwarfs suggest that the blob
stars were likely accreted from a massive dwarf galaxy that had a lower rate
of chemical evolution that the Milky Way.

##  7 Summary

In this work, we combine optical and IR data to understand the detailed
chemical abundance patterns of accreted halo stars. We have obtained detailed
chemical abundances for 62 accreted halo stars using high-resolution
(R$\sim$40,000) optical spectra which were chemically selected from APOGEE
DR16 using [Mg/Mn] vs [Al/Fe], a combination of chemical abundances that
separates the in-situ Milky Way stars from accreted stars that form a "blob"
in this plane. We obtained abundances for 20 elements spanning the $\alpha$,
Fe-peak, light, odd-Z, and neutron-capture groups of elements. This work
outlines the detailed chemical abundances of these accreted halo stars in both
the optical and the IR to understand these individual elements’ abundance
trends with respect to the Milky Way, its satellites, and previously-known
low-$\alpha$ stars. Investigating neutron-capture element abundances, which
are harder to access in the IR, is especially important for systems with lower
rate of chemical evolution i.e. dwarf galaxies less massive than the Milky
Way.

We find that for the most part, the optical and IR abundances agree but some
elements like O, Co, Na, Cu, and Ce have trends that highlight the differences
in deriving abundances in the optical and the IR. We confirm that the $\alpha$
element trends for the blob stars, both individual and total, are lower than
the Milky Way disk at the same metallicity for [Fe/H] > -1.5 dex. This,
together with our sample’s depleted abundances in Ni, Na, and Cu suggest that
their progenitor system had a lower star formation rate or lower rate of
chemical evolution. This is similar to what previous studies of low-$\alpha$
stars (Nissen & Schuster, 2010, 2011; Fishlock et al., 2017; Matsuno et al.,
2020) found, which is even more interesting given that we had a completely
different sample selection. We measure abundances for seven neutron-capture
elements (e.g. Ba, La, Ce, Nd, Y, Zr, Eu) and find that they are similarly
enhanced compared to the low-$\alpha$ stars sample from Matsuno et al. (2020),
Matsuno et al. (2021), and Aguado et al. (2021), and that they exhibit
relative trends that agree with Nissen & Schuster (2010, 2011) and Fishlock et
al. (2014). Additionally, we explored the neutron-capture abundance ratios and
similarly find that our blob sample is r-process enhanced and had delayed and
inefficient s-process enrichment. When coupled with the [$\alpha$/Fe] ratios,
this supports a star formation scenario slower than the Milky Way’s, that was
interrupted before significant contribution by AGB stars to the chemical
enrichment. This overall agreement with previous studies of accreted halo
stars proves that our independent selection is noteworthy. Our work has shown
that chemically selecting accreted stars in [Mg/Mn] vs [Al/Fe] is a powerful
tool that could be used for upcoming surveys that peer deeper into the halo,
especially if the kinematics are uncertain. Lastly, comparing to Milky Way
satellites (e.g.,Tolstoy et al. 2009; Letarte et al. 2010; Van der Swaelmen et
al. 2013; McWilliam et al. 2013), we find that the blob stars exhibit detailed
chemical abundances in the $\alpha$, Fe-peak, and light/odd-Z elements in line
with those of massive Milky Way dwarf galaxies, especially the LMC, but heavy-
element abundance patterns that point to contributions from different
production mechanisms.

This work presents the detailed chemical abundances for accreted halo stars
and opens up many avenues for follow-up investigation. Galactic chemical
evolution modeling would provide a better way of understanding the
contribution and timescales of processes and stars that enriched the
progenitor of these accreted stars. As discussed in Section 6.3, it would be
worthwhile to find the knee in the [$\alpha$/Fe] vs [Fe/H] plane for the blob
stars by observing a more metal-poor sample. Lastly, we observe differences in
the abundance trends for a few elements in the optical vs IR. A more detailed
investigation on these differences is recommended, especially at such lower
[Fe/H], similar to the APOGEE comparison to independent analyses from Jönsson
et al. (2018).

The synergy of using large spectroscopic survey data from APOGEE and high-
resolution follow up spectra like in this work provides a larger discovery
space for studying the origins of stars, even after being cannibalized and
fully phase-mixed with our Galaxy. The future is especially brighter with the
next generation of large spectroscopic surveys (e.g. SDSS-V’s Milky Way
Mapper, 4MOST, WEAVE) as well as thirty-meter class telescopes (e.g. GMT) for
following-up on even fainter and farther ex-situ stars. Finding ways to
complement these upcoming data sets will not only give a wider view of the
Galaxy in volume, but also on its total chemical space.

## Acknowledgements

The authors thank the referee for the suggestions that ultimately improved the
analysis and the manuscript. AC & KH have been partially supported by a
TDA/Scialog (2018-2020) grant funded by the Research Corporation and a
TDA/Scialog grant (2019-2021) funded by the Heising-Simons Foundation. AC
thanks the Large Synoptic Survey Telescope Corporation (LSSTC) Data Science
Fellowship Program, which is funded by LSSTC, NSF Cybertraining Grant 1829740,
the Brinson Foundation, and the Moore Foundation. AC & KH acknowledges support
from the National Science Foundation grant AST-1907417 and AST-2108736 and
from the Wootton Center for Astrophysical Plasma Properties funded under the
United States Department of Energy collaborative agreement DE-NA0003843. This
work was performed in part at Aspen Center for Physics, which is supported by
National Science Foundation grant PHY-1607611. PJ acknowledges partial support
from FONDECYT REGULAR 1200703 and FONDECYT Iniciación 11170174. PD
acknowledges funding from the UK Research and Innovation council (grant number
MR/S032223/1).

This paper includes data taken at The McDonald Observatory of The University
of Texas at Austin. We thank the staff at McDonald Observatory for making this
project possible. Funding for the Sloan Digital Sky Survey IV has been
provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy
Office of Science, and the Participating Institutions. SDSS acknowledges
support and resources from the Center for High-Performance Computing at the
University of Utah. The SDSS web site is www.sdss.org. SDSS is managed by the
Astrophysical Research Consortium for the Participating Institutions of the
SDSS Collaboration including the Brazilian Participation Group, the Carnegie
Institution for Science, Carnegie Mellon University, the Chilean Participation
Group, the French Participation Group, Harvard-Smithsonian Center for
Astrophysics, Instituto de Astrofasica de Canarias, The Johns Hopkins
University, Kavli Institute for the Physics and Mathematics of the Universe
(IPMU) / University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz
Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie
(MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-
Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical
Observatory of China, New Mexico State University, New York University,
University of Notre Dame, Observatório Nacional / MCTI, The Ohio State
University, Pennsylvania State University, Shanghai Astronomical Observatory,
United Kingdom Participation Group, Universidad Nacional Autónoma de México,
University of Arizona, University of colourado Boulder, University of Oxford,
University of Portsmouth, University of Utah, University of Virginia,
University of Washington, University of Wisconsin, Vanderbilt University, and
Yale University.

##  8 Data Availability

Data is available upon request from the corresponding author. The APOGE DR16
data used in this work can found at https://www.sdss.org/dr16.

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##  Appendix A Line Selection

APOGEE ID | Element | Wavelength | log(gf) | $\chi$ | log$(\epsilon)$
---|---|---|---|---|---
|  | (Å) |  | (eV) | (dex)
2M09121759+4408563 | O I | 6363.8 | -10.19 | 0.020 | 7.939
2M09121759+4408563 | Na I | 5688.2 | -0.404 | 2.104 | 4.659
2M09121759+4408563 | Na I | 6160.8 | -1.246 | 2.104 | 4.842
2M09121759+4408563 | Mg I | 5771.1 | -1.724 | 4.346 | 6.460
2M09121759+4408563 | Si I | 5665.6 | -1.940 | 4.920 | 6.226
2M09121759+4408563 | Si I | 5690.4 | -1.773 | 4.930 | 6.173
2M09121759+4408563 | Si I | 5701.1 | -1.773 | 4.930 | 6.332
2M09121759+4408563 | Si I | 5772.1 | -1.653 | 5.082 | 6.313
2M09121759+4408563 | Si I | 5948.5 | -1.130 | 5.082 | 6.342
2M09121759+4408563 | Ca I | 5260.4 | -1.179 | 2.521 | 5.171
2M09121759+4408563 | Ca I | 5261.7 | -0.579 | 2.521 | 5.081
… | … | … | … | … | …
Table 5: A sample from the line selection with the following columns: (1)
APOGEE ID, (2) Element (3) Wavelength in Å, (4) log (gf), (5) excitation
potential, $\chi$, in eV (5), and abundance, log$(\epsilon)$, in dex before
scaling to the solar abundance.

Here, we discuss the reliability of abundances along with the lines we used to
derive them from our optical spectra. A sample of the line selection is listed
in Table 5. For each element, if the majority of stars have more than one line
available for abundance determination, we highlight a target that has
representative errors in its [X/Fe] i.e., closest to the mean [X/Fe] error
values for the whole sample, and examine the range in abundances derived from
its individual lines to quantify internal errors. For consistency with the
comparison studies, we report the abundances derived with local thermodynamic
equilibrium (LTE) but note the difference when non-LTE (NLTE) effects are
considered. We discuss the NLTE effects on the abundances further in Appendix
B.

O: We use only the 6363.8 Å forbidden line for O which is present in all our
spectra. We do not include the O triplet because half of our spectra have
poorer quality in that region. The NLTE corrections for 6363.8 Å are either
zero or unreliable from Sitnova et al. (2013), in line with what Amarsi et al.
(2016) found. Heiter et al. (2021) also flag this line as possibly blended,
which could alter the measured abundance. There is a known, increasing
difference in [O/Fe] between the optical and IR at [Fe/H]$<$1 dex, and the
APOGEE [O/Fe] has been noted to not reach as high a value compared to
reference works (Jönsson et al., 2018).

Na: We use three neutral lines for Na: 4982.8 Å, 5688.2 Å, and 6160.8 Å. All
the lines have transition probabilities with undecided quality (Heiter et al.,
2021). Nonetheless, we use these lines for Na as we derive reasonably small
[Na/Fe] scatter in the optical (0.10 dex) compared to the IR (0.35 dex). All
three lines are in the target 2M14530873+1611041 that has an APOGEE [Na/Fe] =
0.17 $\pm$ 0.08 dex and [Na/Fe] = -0.11 $\pm$ 0.03 dex from the optical. Its
abundance offset in the optical and IR (-0.28 dex) is also representative of
the whole sample offset (-0.24 dex). A visual inspection of these lines show
that the 5688.2 Å line has log$(\epsilon)$ higher by 0.05 dex from the mean
value, likely due to the continuum normalization that is affected by a nearby
NdII line.

Mg: We use the lines 4571.1 Å and 5711.1 Å with and without NLTE corrections
(see Appendix B). The 4571.1 Å line is at times saturated but is caught by
BACCHUS in its automatic flagging routine and was only deemed reliable for 9
of the stars. The 5711.1 Å line on the other hand has a log$gf$ marked U by
the GES line list team, meaning the quality is undecided (Heiter et al.,
2021). We nonetheless use the [Mg/Fe] from the optical because even with the
majority of the abundances being determined from only 5711.1 Å, the [Mg/Fe]
scatter in the optical is comparable to the scatter in the IR and is only
offset by 0.09 dex.

Si: We use 5 neutral lines for Si, 5665.6 Å, 5690.4 Å, 5701.1 Å, 5772.1 Å,
5948.5 Å, and some of these lines prone to blending (e.g., 5665.6 Å, and
5772.1 Å) are likely causing the higher scatter in [Si/Fe] in the optical
compared to the IR. With NLTE corrections from Bergemann et al. (2013), the
mean [Si/Fe] decreases from 0.29 dex to 0.24 dex but the scatter increases
from 0.09 dex to 0.11 dex, meanwhile, the scatter in the IR is lower at 0.05
dex. We therefore opt to use the APOGEE [Si/Fe] for the rest of this work. We
also examine the individual line abundances for the target 2M19111765+4359072
which has [Si/Fe] = 0.27 $\pm$ 0.02 dex from APOGEE and [Si/Fe] = 0.30 $\pm$
0.06 dex from the optical, which has representative errors as the whole
sample. Only three out of the maximum five lines were available for this star
e.g., 5665.6 Å, 5701.1 Å, 5772.1 Å and as expected, the lines with the
blending flag introduce the scatter: the 5665.6 Å line has log$(\epsilon)$
lower by 0.133 dex and the 5772.1 Å line has log$(\epsilon)$ higher by 0.105
dex compared to the mean log$(\epsilon)$.

Ca: The Ca abundances were derived from 14 lines: 5260.4 Å, 5261.7 Å, 5349.5
Å, 5513 Å, 5588.7 Å, 5590.1 Å, 5857.5 Å, 6166.4 Å, 6169 Å, 6169.6 Å, 6455.6 Å,
6471.7 Å, 6493.8 Å, 6499.6 Å. We note that there are no NLTE corrections for
Ca in the spherical MARCS models. The quality of the transition probabilities
and the lines are all superb for the Ca lines being considered here aside from
5349.5 Å, 5513 Å, and 5857.5 Å which are sometimes blended. We examine
2M16153915+4712530 with [Ca/Fe] = 0.21 $\pm$ 0.04 dex from APOGEE and [Ca/Fe]
= 0.23 $\pm$ 0.03 dex from our analysis. We find that there is a slight
increasing trend for the log$(\epsilon)$ with wavelength, having a
log$(\epsilon)$ offset of -0.097 dex from the 5260 Å line and +0.155 dex from
the 6471.7 Å line compared to the mean log$(\epsilon)$.

Sc: We consider three singly-ionized Sc lines, 5667.2 Å, 5684.2 Å, and 6604.6
Å, for abundance determination, all of which have accurate transition
probabilities. On the other hand, the 5684.2 Å and 6604.6 Å lines are
sometimes blended (Heiter et al., 2021). We examine these lines in
2M09121759+4408563 with [Sc/Fe] = 0.09 $\pm$ 0.026 dex, which is
representative of the mean [Sc/Fe] abundance and error for the whole sample.
The individual log$(\epsilon)$ for 5667.2 Å, 5684.2 Å, and 6604.6 Å are 1.938
dex, 1.918 dex, and 1.835 dex, respectively, spanning a narrow, $\sim$0.10 dex
range in log$(\epsilon)$.

V: We use 5 neutral V lines, 4875.5 Å, 5627.6 Å, 5670.9 Å, 5727 Å, and 6111.6
Å to derive its abundance. All the lines have accurate transition
probabilities and only 5670.9 Å and 6111.6 Å have fully unblended lines. V has
HFS data from Childs et al. (1979); Unkel et al. (1989); El-Kashef & Ludwig
(1992); Palmeri et al. (1995); Cochrane et al. (1998); Lefèbvre et al. (2002)
that are included in the line list (Heiter et al., 2021). We examine
2M15035120+2235309 which has an APOGEE [V/Fe] = 0.28 $\pm$ 0.10 dex and [V/Fe]
= 0.11 $\pm$ 0.05 dex from this study; this is representative of the mean
optical-IR offset and mean [V/Fe] error across the whole sample. The abundance
was measured from only four lines in this star, namely 4875.5 Å, 5670.9 Å,
5727 Å, and 6111.6 Å. Of these lines, 4875.5 Å exhibits the maximum positive
offset of 0.104 dex and 5670.9 Å the maximum negative offset of 0.120 dex from
the mean log$(\epsilon)$.

Cr: We derived the Cr abundance from a maximum of 9 neutral Cr lines 4789.3 Å,
4936.3 Å, 4964.9 Å, 5247.6 Å, 5296.7 Å, 5300.7 Å, 5345.8 Å, 5348.3 Å, 5409.8 Å
all of which have NLTE corrections aside from 5300.7 Å from Bergemann &
Cescutti (2010). All lines have reliable transition probabilities but only
4936.3 Å, 5296.7 Å, and 5348.3 Å are unblended. Using just these lines give a
similar scatter of 0.08 dex but increases the mean abundance from -0.12 dex to
-0.11 dex. We examine the star 2M11193441+4957223 which has a [Cr/Fe] = -0.15
$\pm$ 0.12 dex from APOGEE and -0.16 $\pm$ 0.03 dex from our analysis. All 9
lines are present for this star. There is a slight decreasing trend in
log$(\epsilon)$ with wavelength, where the log$(\epsilon)$ from the 4936.3 Å
line is higher by 0.190 dex compared to the mean log$(\epsilon)$ while the
log$(\epsilon)$ from the 5409.8 Å line is lower by 0.305 dex. Upon inspection,
the 4936.3 Å and 5409.8 Å lines are on the extreme ends of the equivalent
widths range at 10.4 mÅ and 106 mÅ, respectively.

Mn: We used a maximum of 6 neutral lines for Mn namely 4783.4 Å, 5394.7 Å,
5420.3 Å, 5432.5 Å, 6013.5 Å, 6021.8 Å which all have NLTE corrections from
Bergemann & Gehren (2008). All the lines considered have reliable transition
probabilities but only 5420.3 Å and 6021.8 Å are unblended. Mn has HFS data
from Handrich et al. (1969); Davis et al. (1971); Luc & Gerstenkorn (1972);
Dembczyński et al. (1979); Johann et al. (1981); Brodzinski et al. (1987);
Başar et al. (2003); Lefèbvre et al. (2003); Blackwell-Whitehead et al. (2005)
that are included in the line list (Heiter et al., 2021). We examine the
individual line abundances from the target 2M01575297-0316508 which has
[Mn/Fe] = -0.15 $\pm$ 0.09 dex from APOGEE and [Mn/Fe] = -0.14 $\pm$ 0.04 dex
from our analysis. The [Mn/Fe] for this star was derived from the lines 5420.3
Å, 5432.5 Å, 6013.5 Å, and 6021.8 Å where the log$(\epsilon)$ from the 5420.3
Å line is higher by 0.089 dex, and from the 5432.5 Å line lower by 0.085 dex
compared to the mean log$(\epsilon)$; both are strong lines with equivalent
widths $>$ 110 mÅ.

Co: We use a maximum of 7 neutral Co lines, 5212.7 Å, 5331.40 Å, 5369.6 Å,
5530.8 Å, 5647.2 Å, 5915.5 Å, 6771 Å, to derive Co abundance, all of which
have NLTE corrections from Bergemann et al. (2010). All lines have accurate
transition probabilities but only 5331.40 Å, 5647.2 Å, and 6771 Å are
unblended. The whole sample has mean [Co/Fe] = 0.22 dex with scatter 0.11 dex,
and the NLTE corrections increase both mean and scatter to 0.52 $\pm$ 0.23
dex. Co has HFS data from Pickering (1996) that are included in the line list
(Heiter et al., 2021). We examined the individual line abundances for the
target 2M13141390+1817489 which has [Co/Fe] = -0.26 $\pm$ 0.06 dex from APOGEE
and [Co/Fe] = 0.16 $\pm$ 0.04 dex from this study, which is representative of
the optical-IR offset and the mean error value for the whole sample. For this
star, the 5212.7 Å line exhibits a -0.148 dex offset while the 6771 Å line a
+0.115 dex offset from the mean log$(\epsilon)$ value. Upon inspection, the
continuum region around the 5212.7 Å line and the near-saturation of the 6771
Å line appear to affect the measured abundance.

Ni: We use a maximum of 10 neutral Ni lines to derive its abundance, namely
4873.4 Å, 5003.7 Å, 5035.4 Å, 5137.1 Å, 5435.9 Å, 5587.8 Å, 6176.8 Å, 6482.8
Å, 6643.6 Å, and 6767.8 Å. With this line selection, we derive a mean [Ni/Fe]
= -0.03 dex with a scatter of 0.07 dex for the blob stars. All the lines have
reliable transition probabilities aside from 6482.8 Å where the quality of the
data is undecided (Heiter et al., 2021). The lines 4873.4 Å, 5003.7 Å, 5035.4
Å, 5137.1 Å, and 5587.8 Å are sometimes blended. Considering just the lines of
highest quality (i.e., 5435.9 Å, 6176.8 Å, 6643.6 Å, and 6767.8 Å), the
modified mean abundance is 0.03 $\pm$ 0.06 dex. We examined the individual
line abundances for the target 2M15410952+3014067 which has [Ni/Fe] = 0.05
$\pm$ 0.04 from APOGEE and [Ni/Fe] = 0.01 $\pm$ 0.05 from this study. There is
a slight increasing log$(\epsilon)$ with wavelength, where the line at 5035.4
Å gives a log$(\epsilon)$ that is 0.270 dex below the mean log$(\epsilon)$
while the line at 6643.6 Å gives a log$(\epsilon)$ that is 0.257 dex above the
mean value. Upon inspection, the 6643.6 Å line is near saturation and has an
equivalent width of 151 mÅ, likely causing the overestimation in abundance.

Cu: We use a maximum of 4 neutral Cu lines, 5105.5 Å, 5218.2 Å, and 5700.2 Å,
5782.1 Å, in deriving its abundance. All lines considered have accurate
transition probabilities but are flagged as prone to blending (Heiter et al.,
2021). HFS data for Cu were taken from Fischer et al. (1967); Bergström et al.
(1989); Hermann et al. (1993). We analyze the individual line abundances for
2M16445645+4230263 which has [Cu/Fe] = 0.21 $\pm$ 0.05 dex from APOGEE and
[Cu/Fe] = -0.44 $\pm$ 0.05 dex from this study, which is representative of the
total sample with respect to the errors and the optical-to-IR abundance
offset. Although the measured [Cu/Fe] from the optical and IR are starkly
different for this star, it is actually representative of the overall offset
as well as the mean error in [Cu/Fe] for the entire sample. The 5700.2 Å line
has log$(\epsilon)$ lower by 0.117 dex than the mean while the 5782.1 Å line
has log$(\epsilon)$ higher by -0.107 dex, and both lines are reliable upon
visual inspection.

Zn: We only use one neutral Zn line at 4810.5 Å, which has reliable transition
probability but is marked as blended (Heiter et al., 2021) which drives the
scatter.

Y: We used 4 singly-ionized Y lines, 5087.4 Å, 5200.4 Å, 5205.7 Å, and 5289.8
Å to derive [Y/Fe]. All the lines considered have accurate transition
probabilities but 5200.4 Å and 5205.7 Å are possibly prone to blending. We
inspect the individual line abundances for the target 2M09381836+3706176
([Y/Fe] = 0.05 $\pm$ 0.04 dex) and find that the log$(\epsilon)$ from the
5289.8 Å line generally increases the total abundance, and is 0.142 dex higher
than the mean log$(\epsilon)$. This line also has the lowest equivalent width
(i.e., 16.3 mÅ) of the lines available.

Zr: We use 4 singly-ionized Zr line, 4317.3 Å, 6127.4 Å, 6134.6 Å, and 6143.2
Å in the abundance determination. The 4317.3 Å line can sometimes be
saturated, but all the other lines are unblended and have reliable transition
probabilities (Heiter et al., 2021). We inspect the individual line abundances
for the target 2M16153915+4712530 which has [Zr/Fe] = 0.19 $\pm$ 0.10 dex from
our analysis, representative of the mean [Zr/Fe] abundance and error for our
sample. The 4317.3 Å line has a log$(\epsilon)$ higher by 0.125 dex compared
to the mean log$(\epsilon)$ which upon inspection, we realize is due to the
continuum normalization in the spectral window.

Ba: We derive Ba abundance from only one singly-ionized line at 5853.7 Å which
is deemed reliable from (Heiter et al., 2021). HFS data for Ba were taken from
Becker et al. (1981); Silverans et al. (1986); Villemoes et al. (1993) for the
Gaia-ESO line list.

La: We used the singly-ionized La lines 4322.5 Å, 4333.8 Å, 4804 Å, 5303.5 Å,
5805.8 Å, and 6390.5 Å to determine La abundance. All the lines considered
could be prone to blending through our visual inspection and from flags
determined from (Heiter et al., 2021). This blending as well as the continuum
normalization, especially in the bluer part of the spectrum, can skew the
abundance as we have examined for the star 2M16064562-2247445 ([La/Fe] = 0.21
$\pm$ 0.04 dex), where the 4322.5 Å line is 0.183 dex lower and the 4333.8 Å
line is 0.214 dex higher than the mean log$(\epsilon)$.

Ce: We use only one line to determine Ce abundance, 5247.2 Å, which is flagged
as reliable (Heiter et al., 2021). This gives a mean [Ce/Fe] value of 0.31 dex
$\pm$ 0.22, which is higher compared to the mean [Ce/Fe] from APOGEE (-0.04
dex $\pm$ 0.32). Taking into account that our Ce solar abundance is higher by
0.31 dex compared to Asplund et al. (2009) would make our derived [Ce/Fe]
agree with the literature. However, for consistency, especially in deriving
the neutron-capture element-to-element abundance ratios, we use the solar
abundance that we derived independently.

Nd: We obtain Nd abundances from a maximum of 4 singly-ionized Nd lines at