# Extending the Chemical Reach of the H3 Survey: Detailed Abundances of the
Dwarf-galaxy Stellar Stream Wukong/LMS-1††thanks: This paper includes data
gathered with the 6.5 meter Magellan Telescopes located at Las Campanas
Observatory, Chile.

Guilherme Limberg,1,2,3 Alexander P. Ji,2,3 Rohan P. Naidu,4 Anirudh Chiti,2,3
Silvia Rossi,1 Sam A. Usman,2,3 Yuan-Sen Ting (丁源森),5,6,7 Dennis Zaritsky,8
Ana Bonaca,9 Lais Borbolato,1 Joshua S. Speagle (沈佳士),10,11,12,13 Vedant
Chandra,14 Charlie Conroy14

1 Universidade de São Paulo, IAG, Departamento de Astronomia, SP 05508-090,
São Paulo, Brazil
2 Department of Astronomy & Astrophysics, University of Chicago, 5640 S Ellis
Avenue, Chicago, IL 60637, USA
3 Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL
60637, USA
4 Department of Physics and Kavli Institute for Astrophysics and Space
Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
5 Research School of Astronomy & Astrophysics, Australian National University,
Weston, ACT 2611, Canberra, Australia
6 School of Computing, Australian National University, Acton, ACT 2601,
Canberra, Australia
7 Department of Astronomy, The Ohio State University, 140 West 18th Avenue,
Columbus, OH 43210, USA
8 Steward Observatory, University of Arizona, 933 N. Cherry Ave., Tucson, AZ
85721-0065, USA
9 Observatories of the Carnegie Institution for Science, 813 Santa Barbara
Street, Pasadena, CA 91101, USA
10 Department of Statistical Sciences, University of Toronto, Toronto, ON M5G
1Z5, Canada
11 David A. Dunlap Department of Astronomy & Astrophysics, University of
Toronto, Toronto, ON M5S 3H4, Canada
12 Dunlap Institute for Astronomy & Astrophysics, University of Toronto,
Toronto, ON M5S 3H4, Canada
13 Data Sciences Institute, University of Toronto, Toronto, ON M5G 1Z5, Canada
14 Center for Astrophysics $\mid$ Harvard & Smithsonian, 60 Garden Street,
Cambridge, MA 02138, USA E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ )

###### Abstract

We present the first detailed chemical-abundance analysis of stars from the
dwarf-galaxy stellar stream Wukong/LMS-1 covering a wide metallicity range
($-3.5<\rm[Fe/H]\lesssim-1.3$). We find abundance patterns that are
effectively indistinguishable from the bulk of Indus and Jhelum, a pair of
smaller stellar streams proposed to be dynamically associated with
Wukong/LMS-1. We confirmed a carbon-enhanced metal-poor star ($\rm[C/Fe]>+0.7$
and $\rm[Fe/H]\sim-2.9$) in Wukong/LMS-1 with strong enhancements in Sr, Y,
and Zr, which is peculiar given its solar-level [Ba/Fe]. Wukong/LMS-1 stars
have high abundances of $\alpha$ elements up to $\rm[Fe/H]\gtrsim-2$, which is
expected for relatively massive dwarfs. Towards the high-metallicity end,
Wukong/LMS-1 becomes $\alpha$-poor, revealing that it probably experienced
fairly standard chemical evolution. We identified a pair of N- and Na-rich
stars in Wukong/LMS-1, reminiscent of multiple stellar populations in globular
clusters. This indicates that this dwarf galaxy contained at least one
globular cluster that was completely disrupted in addition to two intact ones
previously known to be associated with Wukong/LMS-1, which is possibly
connected to similar evidence found in Indus. From these $\geq$3 globular
clusters, we estimate the total mass of Wukong/LMS-1 to be
${\approx}10^{10}M_{\odot}$, representing ${\sim}1$% of the present-day Milky
Way. Finally, the [Eu/Mg] ratio in Wukong/LMS-1 continuously increases with
metallicity, making this the first example of a dwarf galaxy where the
production of $r$-process elements is clearly dominated by delayed sources,
presumably neutron-star mergers.

###### keywords:

stars: abundances – Galaxy: halo – Galaxy: kinematics and dynamics – galaxies:
Local Group

††pubyear: 2023††pagerange: Extending the Chemical Reach of the H3 Survey:
Detailed Abundances of the Dwarf-galaxy Stellar Stream Wukong/LMS-1††thanks:
This paper includes data gathered with the 6.5 meter Magellan Telescopes
located at Las Campanas Observatory, Chile.–References

##  1 Introduction

In a cold dark matter-dominated cosmology, massive Milky Way-like halos are
built up through successive accretion of dwarf galaxies (Searle & Zinn, 1978;
Faber & Gallagher, 1979; White & Frenk, 1991; Kauffmann et al., 1993;
Johnston, 1998; Springel et al., 2006). Therefore, a fundamental prediction of
this hierarchical paradigm is that satellite galaxies around any massive host
present themselves as intact dwarfs, phase-mixed substructures, or in an
intermediary stage as stellar streams (Bullock & Johnston, 2005; Cooper et
al., 2010, 2013; Pillepich et al., 2015; Morinaga et al., 2019).

Because the evolution of these dwarf galaxy streams and substructures was
interrupted due to the shutdown of their star formation at the moment of their
accretion, they provide a unique local window into the properties of galaxies
that existed at high redshift (Boylan-Kolchin et al., 2015; Boylan-Kolchin et
al., 2016). Also, as these systems sample a wide range of stellar masses
($10^{6}\lesssim M_{\star}/M_{\odot}<10^{9}$; see Naidu et al. 2022 and Sharpe
et al. 2022), they provide a laboratory for us to test the universality of
galaxy formation/evolution processes as we can compare them with observations
of intact dwarfs in the Local Group (Tolstoy et al. 2009 and Simon 2019 for
reviews). Conveniently, this approach comes with the advantage that member
stars of these disrupted dwarfs are typically much closer and, hence, brighter
than their counterparts located in surviving Milky Way satellites. This makes
them more easily accessible to high-resolution ($\mathcal{R}\geq 20{,}000$)
spectroscopy, from which detailed chemical abundances can be obtained for
significant amounts of stars, allowing us to understand the properties of
their progenitor systems. This “near-field” approach to galaxy evolution at
the smallest scales is even more appealing given that not even current and
future facilities (such as JWST or 20–30 m ground telescopes) will be able to
spatially resolve such low-mass galaxies at the redshift range ($0.5<z\leq
2.0$) probed by these halo debris (Myeong et al., 2018, 2019; Koppelman et
al., 2019a; Forbes, 2020; Kruijssen et al., 2020; Naidu et al., 2020;
Callingham et al., 2022, see also Naidu et al. 2021 for a relevant
discussion).

The advent of astrometric information for more than a billion stars due to the
Gaia space mission (Gaia Collaboration et al., 2016a, b, 2018, 2021, 2022), in
particular its second and third data releases (DR2 and DR3, respectively), in
combination with large-scale photometric and spectroscopic surveys, has
allowed the discovery of a myriad of accreted substructures in the Galactic
halo (see Koppelman et al. 2019b, Malhan et al. 2022 and the stellar-stream
compilation by Mateu 2023). Out of these, the most well-characterized
disrupted dwarfs with detailed chemistry are, by far, Gaia-Sausage/Enceladus
(GSE; Belokurov et al., 2018; Haywood et al., 2018; Helmi et al., 2018) and
Sagittarius stream (e.g., Majewski et al., 2003), the tidal tails of
Sagittarius dwarf spheroidal (dSph) galaxy (Ibata et al., 1994). Examples of
such efforts include, but are not limited to, Monty et al. (2020), Aguado et
al. (2021b), Matsuno et al. (2021), and Buder et al. (2022) for GSE,
Hasselquist et al. (2019) and Hayes et al. (2020) for Sagittarius, and
Hasselquist et al. (2021) and Horta et al. (2023) for both. Apart from these
major substructures, other disrupted dwarfs with available high-resolution
spectroscopy include Helmi streams (Helmi et al. 1999; see Roederer et al.
2010, Aguado et al. 2021a, Limberg et al. 2021, and Matsuno et al. 2022b for
abundances), Orphan stream (Belokurov et al. 2006, 2007; e.g., Casey et al.
2014 and Hawkins et al. 2023), and Sequoia111Although we list Sequoia as an
independent disrupted dwarf, we recognize the current dispute in the
literature regarding whether or not this population could simply be part of
the more massive GSE (Koppelman et al., 2020; Amarante et al., 2022; Limberg
et al., 2022; Horta et al., 2023). (Myeong et al. 2019; Matsuno et al. 2019,
2022a). For smaller stellar streams, the largest homogeneous study was
presented by Ji et al. (2020a).

In this contribution, we present the first detailed chemical abundance
analysis of Wukong/LMS-1 (Naidu et al., 2020; Yuan et al., 2020; Malhan et
al., 2021). This substructure was identified by Yuan et al. (2020) who named
it the “low-mass stellar-debris stream 1” (LMS-1). Independently, Naidu et al.
(2020) identified “Wukong”222Named after Sun Wukong, the celestial Monkey King
from Journey to the West. See Naidu et al. (2020) for the complete rationale.,
a prominent group of stars in integrals-of-motion space apparently dissociated
from any previously known disrupted dwarf. The connection between LMS-1 and
Wukong was quickly recognized for their indistinguishable dynamics, including
the association with at least two globular clusters, NGC 5024 (M53) and NGC
5053, and two other stellar streams, Indus and Jhelum (Shipp et al., 2018;
Bonaca et al., 2019; Bonaca et al., 2021; Malhan et al., 2022). Out of the
known disrupted dwarf galaxies, some listed above, Wukong/LMS-1 is especially
interesting due to its predicted relatively high stellar mass of
${\sim}10^{7}\,M_{\odot}$ (Malhan et al., 2021), which is similar to classical
Milky Way satellites such as Sculptor and Fornax dSph galaxies (McConnachie,
2012). Therefore, our goal is to constrain Wukong/LMS-1’s star-formation
history, its production of the heaviest elements via prompt and/or delayed
sources of neutron-capture processes, and even look for signatures of
dissolved globular clusters in it. Then, we put our results in context by
comparing with known Milky Way satellite galaxies of similar mass as well as
chemical-evolution models.

This work is organized as follows. Section 2 includes all things related to
our observations, data reduction, and radial velocity (RV) measurements. Our
methodology for obtaining stellar parameters and abundances from high-
resolution spectra is described in Section 3. Section 4 is reserved for the
presentation of our results. In Section 5, we provide our concluding remarks
and a brief discussion.

Star |  Gaia DR3 source_id | R.A. | Decl. |  RVMIKE | $S/N$ | $S/N$ | $T_{\mathrm{eff}}$ | $\sigma_{T_{\mathrm{eff}}}$ | $\log\,g$ | $\sigma_{\log\,g}$ | $v_{\mathrm{t}}$ | $\sigma_{v_{\mathrm{t}}}$ | [M/H] | $\sigma_{\mbox{[M/H]}}$
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
|  | (deg) | (deg) |  (km s-1) | (4500Å) | (6500Å) | (K) | (K) | (cgs) | (cgs) |  (km s-1) |  (km s-1) |  |
Wuk_1 | 2721020906259820416 | 332.6634 |  6.6813 |  $-$245.22 | 44 | 85 | 4887 | 103 | 2.12 | 0.50 | 1.58 | 0.11 |  $-$1.75 | 0.24
Wuk_2 | 2671790891601429376 | 322.1504 |  $-$5.4919 |  $-$96.59 | 30 | 68 | 4623 | 102 | 1.48 | 0.50 | 2.14 | 0.12 |  $-$1.91 | 0.25
Wuk_3 | 2616761777740644864 | 329.9007 |  $-$10.9341 |  $-$173.24 | 31 | 60 | 4866 | 104 | 1.90 | 0.51 | 1.62 | 0.12 |  $-$2.32 | 0.26
Wuk_4 | 4424978984005490304 | 240.3206 |  3.6775 |  87.79 | 30 | 60 | 5101 | 118 | 2.30 | 0.53 | 1.79 | 0.11 |  $-$2.89 | 0.24
Wuk_5 | 6337489231846231296 | 222.7506 |  $-$4.8440 |  2.70 | 37 | 72 | 4670 | 102 | 1.50 | 0.50 | 1.59 | 0.11 |  $-$2.41 | 0.25
Wuk_6 | 4415232603696493696 | 230.8720 |  $-$2.0148 |  $-$180.10 | 30 | 59 | 5307 | 148 | 3.15 | 0.57 | 1.51 | 0.16 |  $-$3.57 | 0.22
Wuk_7 | 3614246079443061376 | 210.9729 |  $-$11.2984 |  $-$56.56 | 21 | 46 | 5095 | 159 | 2.43 | 0.59 | 0.93 | 0.10 |  $-$2.93 | 0.28
Wuk_8 | 3635197617107624448 | 201.3197 |  $-$4.8245 |  233.76 | 34 | 56 | 5312 | 111 | 2.75 | 0.51 | 1.43 | 0.12 |  $-$1.98 | 0.26
Wuk_9 | 3625337025031068544 | 199.5284 |  $-$7.8565 |  98.30 | 30 | 53 | 4974 | 106 | 2.22 | 0.51 | 1.80 | 0.11 |  $-$2.01 | 0.26
Wuk_10 | 3810150429850681984 | 168.4136 |  0.8518 |  193.73 | 39 | 64 | 4814 | 101 | 1.90 | 0.50 | 1.55 | 0.11 |  $-$1.98 | 0.23
Wuk_11 | 1225051430189620864 | 213.3937 |  10.0073 |  4.00 | 39 | 71 | 4706 | 102 | 1.18 | 0.50 | 1.96 | 0.11 |  $-$2.37 | 0.23
Wuk_12 | 3727823702151504896 | 209.6407 |  12.8460 |  25.68 | 33 | 58 | 4842 | 103 | 1.82 | 0.50 | 1.77 | 0.11 |  $-$2.09 | 0.25
Wuk_13 | 3737533184394415232 | 197.0257 |  12.7782 |  93.73 | 34 | 61 | 4923 | 103 | 2.15 | 0.50 | 1.70 | 0.11 |  $-$1.87 | 0.27
Wuk_14 | 3696527104395430016 | 187.9680 |  0.0382 |  49.87 | 43 | 68 | 5099 | 100 | 2.60 | 0.51 | 1.60 | 0.14 |  $-$1.23 | 0.22
Table 1: Observational information, RVs, and stellar parameters for
Wukong/LMS-1 stars analysed in this work. The reported $S/N$ values are per
pixel. Model atmosphere metallicity values ([M/H]) can be larger than [Fe/H]
by up to 0.03 dex.

##  2 Data

Figure 1: Wukong/LMS-1 stars in projected action-space diagram. The horizontal
axis corresponds to $J_{\phi}/J_{\rm total}$, where $J_{\rm
total}=J_{R}+|J_{\phi}|+J_{z}$ (see text). The vertical axis is
$(J_{z}-J_{R})/J_{\rm total}$. Larger symbols with thick black edges are those
observed with MIKE; circles for H3 targets (Wuk_1 through _13) and square for
the APOGEE one (Wuk_14). Triangles with thin black edges are the “high-$S/N$”
sample of Wukong/LMS-1 members from Johnson et al. (2022). Smaller circles
without edges are the “LMS-1” stars from Yuan et al. (2020, see text). Grey
dots are metal-poor ($\rm[Fe/H]<-1$) stars from APOGEE DR17. Star symbols with
red edges are the Wukong/LMS-1 globular clusters NGC 5024 (M53) and NGC 5053.

###  2.1 Observations

We observed 13 Wukong/LMS-1 targets (Wuk_1 to _13)333Throughout this work, we
use the “Wuk” prefix followed by a natural number as unique names for stars in
our sample (see Table 1)., which were selected as best-suited for covering a
wide metallicity range within the telescope time allocation available. These
were originally identified by Naidu et al. (2020) using data from the
Hectochelle in the Halo at High Resolution (H3) survey (Conroy et al., 2019),
including orbital energy and angular momentum criteria, but also an
$\rm[Fe/H]<-1.45$ cut to avoid contamination by GSE stars. The observed sample
is also contained in the “high signal-to-noise” (high-$S/N$) sample of
Wukong/LMS-1 stars from Johnson et al. (2022), also with H3 data, who refined
Naidu et al.’s (2020) selection. All stars are also bright enough ($15<$
Gaia’s $G$ $\lesssim 16$) for high-resolution spectroscopy with our setup (see
below). We collected spectra for an extra metal-rich ($\rm[Fe/H]\sim-1.3$)
Wukong/LMS-1 star (Wuk_14; Table 1) at $G\approx 15$ found in the Apache Point
Observatory Galactic Evolution Experiment (APOGEE; Majewski et al., 2017) DR17
catalog (Abdurro’uf et al., 2022). In order to guarantee that this additional
target is a genuine Wukong/LMS-1 member, not a GSE interloper, we searched
APOGEE for stars that respected the combined criteria from Naidu et al. (2020)
and Johnson et al. (2022) as well as Yuan et al. (2020), which was developed
independently from the H3 survey papers. The full criteria is written below.
Because GSE-like mergers are not expected to deposit debris on such acute
polar orbits (see Amarante et al., 2022, Limberg et al. 2023 for discussion),
we can be confident that our APOGEE metal-rich target is a genuine member of
Wukong/LMS-1.

In Figure 1, we exhibit all our targets in projected action space within the
McMillan (2017) Galactic model potential. The action vector is written as
$\mathbf{J}=(J_{R},J_{\phi},J_{z})$, where $J_{R}$, $J_{\phi}$, and $J_{z}$
are the radial, azimuthal, and vertical components in a cylindrical frame.
Both of the above-mentioned Wukong/LMS-1 samples and the globular clusters NGC
5024 and NGC 5053 are also plotted. For these orbit calculations, we
integrated for 20 Gyr forward using the AGAMA library (Vasiliev, 2019).
Positions and proper motions on the sky are from Gaia DR3. RVs were determined
by us for the stars we observed (see below). Other RVs employed were taken
from their parent samples. Distances come from spectro-photometric fits,
MINESweeper (Cargile et al., 2020) for H3 and StarHorse (Queiroz et al., 2020,
2023) for APOGEE. For NGC 5024 and NGC 5053, all phase-space information is
from Vasiliev & Baumgardt (2021). We realized each orbit 100 times in a Monte
Carlo scheme assuming Gaussian uncertainties for these quantities. The final
adopted values are the medians of the resulting distributions. The adopted
distance from the Sun to the Galactic center is 8.2 kpc (Bland-Hawthorn &
Gerhard, 2016), the circular velocity at this position is
232.8$\mathrm{\,km\,s^{-1}}$ (McMillan, 2017), and the assumed peculiar motion
of the Sun is $(U,V,W)_{\odot}=(11.10,12.24,7.25)$$\mathrm{\,km\,s^{-1}}$
(Schönrich et al., 2010).

We note that the model potential as well as Galactic fundamental parameters
adopted here are different from previous H3 survey works (Naidu et al., 2020;
Johnson et al., 2022). Therefore, the criteria used by these authors to select
Wukong/LMS-1 stars become slightly different after our above-described
calculations. In the spirit of making this paper self-sufficient, we provide
updated values for the kinematic/dynamical quantities that define the
Wukong/LMS-1 structure below. Nevertheless, we reinforce that the original
target selection was made simply based on the H3 survey samples from Naidu et
al. (2020) and Johnson et al. (2022) plus covering the largest possible
metallicity range within the available telescope allocation.

Following Johnson et al. (2022), we have:

  * •

$(J_{z}-J_{R})/J_{\rm total}>0.3$444We call the attention to the difference in
definition of $J_{\rm total}$ between ours and Naidu et al.’s (2020) work,
also Johnson et al. (2022). These authors assumed the vectorial definition
$J_{\rm total}=\sqrt{J_{R}^{2}+J_{\phi}^{2}+J_{z}^{2}}$. and

  * •

$90^{\circ}<\theta<120^{\circ}$,

where $J_{\rm total}=J_{R}+|J_{\phi}|+J_{z}$ (Figure 1) and
$\theta=\arccos{(L_{z}/L)}$ refers to the orbital inclination, which
characterizes the direction of the angular momentum vector
$\mathbf{L}=(L_{x},L_{y},L_{z})$ in a Galactic Cartesian frame. Within these
definitions, $L=\sqrt{L_{x}^{2}+L_{y}^{2}+L_{z}^{2}}$ is the total angular
momentum and $L_{z}\equiv J_{\phi}$ is the vertical component of it. These
criteria are accompanied by those from Naidu et al. (2020):

  * •

$-1000<L_{z}/({\rm kpc\mathrm{\,km\,s^{-1}}})<0$ and

  * •

$E<-1.15\times 10^{5}\,{\rm km^{2}\,s^{-2}}$,

where $E$ is the total orbital energy. Apart from these cuts, Naidu et al.
(2020) also removed possible Sagittarius stream interlopers using the simple
method of Johnson et al. (2020), which has been shown to be likely complete
(Peñarrubia & Petersen, 2021). Hence, when selecting for Wukong/LMS-1, one can
use

  * •

$L_{y}>-2000\,{\rm kpc\mathrm{\,km\,s^{-1}}}$,

fully eliminating Sagittarius contamination within its $L_{z}$ range. Naidu et
al. (2020) also included a cut in orbital eccentricity to eliminate GSE stars.
However, this is redundant with the action-space selection of Johnson et al.
(2022) that requires $J_{z}>J_{R}$.

Figure 2: Top panel: comparison between MIKE and survey RVs, either H3
(circles) or APOGEE (square). The vertical axis shows $\Delta_{\rm RV}$, which
corresponds to MIKE RVs minus H3/APOGEE ones. The black line shows
$\Delta_{\rm RV}=0$ and the grey shaded region covers
${\pm}1$$\mathrm{\,km\,s^{-1}}$, the systematic RV uncertainty for MIKE
measurements. Bottom panel: $\log\,g$ versus $v_{\mathrm{t}}$ relation (see
text). Colored lines are empirical quadratic fits to various samples of low-
metallicity stars (Barklem et al., 2005; Marino et al., 2008; Kirby et al.,
2009; Cohen et al., 2013; Roederer et al., 2014; Jacobson et al., 2015, see Ji
et al. 2023a). The black line was used to determine the $v_{\mathrm{t}}$ for
the most metal-poor star analysed (Wuk_6; see text). Wuk_4 is shown with red
edges in both panels (see Section 4.1).

We observed all the Wukong/LMS-1 stars with the Magellan Inamori Kyocera
Echelle (MIKE; Bernstein et al., 2003) spectrograph installed in the Magellan
Clay telescope (6.5 m) located at Las Campanas Observatory, Chile. For all
stars over all observing runs (June 2022 for H3 follow-up and May 2023 for
APOGEE), we used $0.7\arcsec$ slit and $2{\times}2$ on-chip binning. This
configuration leads to resolving powers of $\mathcal{R}\sim 35{,}000$ and
$28{,}000$ for the blue (wavelength $\lambda<5000$ Å) and red ($\lambda>5000$
Å) arms of MIKE spectra, respectively. All data were reduced using the
CarPy555https://code.obs.carnegiescience.edu/mike. package (Kelson, 2003). The
final $S/N$ reached was typically 30–40 per pixel at 4500 Å and 50–70 at 6500
Å (Table 1).

###  2.2 Radial velocities and spectra normalization

We derived RVs for all Wukong/LMS-1 stars by cross-correlating against a
high-$S/N$ MIKE spectrum of the metal-poor standard HD 122563 using the
Labeling Echelle Spectra with SMHR and Payne
(LESSPayne666https://github.com/alexji/LESSPayne.; A. P. Ji, in preparation)
code. In a nutshell, LESSPayne combines Spectroscopy Made Harder
(smhr777https://github.com/andycasey/smhr.; Casey 2014) with
Payne4MIKE888https://github.com/alexji/Payne4MIKE. (Ting et al.,
2019)999https://github.com/tingyuansen/Payne4MIKE and consolidates it into a
single package. As of now, the RV measurement routine within LESSPayne is a
carbon-copy of smhr’s. The formal statistical uncertainty of RVs from MIKE
spectra (“${\rm RV}_{\rm MIKE}$” in the top panel of Figure 2 and Table 1)
could, in principle, reach ${\sim}0.1$$\mathrm{\,km\,s^{-1}}$. However, a
systematic error of ${\sim}1$$\mathrm{\,km\,s^{-1}}$ is introduced due to slit
centering and wavelength calibration (see discussion by Ji et al., 2020b). For
the purpose of this work, we are satisfied that the membership of our stars
does not depend on the choice of RV value, either MIKE or H3/APOGEE. Indeed,
at this RV precision, distances are the dominant source of errors for orbital
parameters. The maximum difference between our MIKE RVs and H3 ones is
${\approx}10$$\mathrm{\,km\,s^{-1}}$ (Wuk_4), but is usually
${<}2$$\mathrm{\,km\,s^{-1}}$ (Figure 2). See Section 4.1 for the possibility
that Wuk_4 is in a binary system. For the APOGEE star Wuk_14, the difference
in RV is 0.5$\mathrm{\,km\,s^{-1}}$.

With the reduced data and RVs at hand, we proceed to stitch orders and
normalize the MIKE spectra using cubic spline functions. LESSPayne initializes
smhr-like files from the best-fitting Payne4MIKE synthetic spectrum. This
procedure drastically accelerates the normalization and equivalent width
measurements, as it identifies where absorption features occur and masks them.
This method is identical to the one described in Ji et al. (2023b), with the
difference that, now, the whole process has been packaged into LESSPayne. The
entire spectrum was inspected for all stars, but the LESSPayne continuum
needed minor fixes only at the bluest orders, where $S/N$ is lower, or when
prominent wide absorption was present, such as Ca ii K/H (3900–4000 Å) and/or
the C-H G band (${\sim}4300$ Å).

Figure 3: Comparisons between our derived stellar parameters from MIKE spectra
(horizontal axes; Table 1) and the values from the spectroscopic surveys
(vertical), either H3 (circles) or APOGEE (square). Left: $T_{\mathrm{eff}}$.
Middle: $\log\,g$. Right: [Fe/H]. One-to-one lines are shown in black. Grey
shaded areas represent the systematic uncertainties adopted. The red line in
the right panel shows the average difference between our derived metallicities
and those from H3.

##  3 Methods

For this project, we considered the atomic and molecular line list from Ji et
al. (2020a), which was adapted from the linemake
101010https://github.com/vmplacco/linemake. compilation (Placco et al., 2021).
This line list was also used by Ji et al. (2020a) to analyze the Indus and
Jhelum streams that could be associated with Wukong/LMS-1 and which we compare
to in Section 4. We rejected all lines at ${<}3860$ Å in our analysis due to
the lower $S/N$ at the bluest portions of the MIKE spectra. For our equivalent
width measurements, we assumed Gaussian profiles. Lines that required Voigt
profiles were rejected, with the exception of those in the Mg i triplet
(5150–5200 Å). Abundances for Mg from these strong lines are consistent with
others considered. Overall, we fitted between 70 (for our most metal-poor
star) and 380 (most metal-rich) lines in each MIKE spectrum. Individual line
measurements are provided in supplementary online tables.

###  3.1 Stellar Parameters

We computed fully spectroscopic stellar parameters for all stars under the
assumption of local thermodynamic equilibrium (LTE) using LESSPayne, which
wraps the radiative transfer code MOOG (Sneden, 1973), specifically a well-
tested version111111https://github.com/alexji/moog17scat. that includes
appropriate treatment of scattering (Sobeck et al., 2011). We employed
$\alpha$-enhanced ($\rm[\alpha/Fe]=+0.4$) 1D plane-parallel model atmospheres
(Castelli & Kurucz, 2003) in our analysis.

Effective temperatures ($T_{\mathrm{eff}}$) were estimated by balancing the
abundances of Fe i lines against their excitation potential. Surface gravity
values ($\log\,g$) were found by minimizing the difference between Fe i and Fe
ii abundances. Microturbulence velocities ($v_{\mathrm{t}}$) were determined
by reducing the trend between Fe ii abundances and reduced equivalent widths;
Fe ii lines are preferred as they cover a wider range of reduced equivalent
width values in red giants and are less affected by non-LTE (NLTE) effects
(see Ji et al., 2020a). For the most metal-poor star in our sample (Wuk_6;
model atmosphere metallicity $\rm[M/H]=-3.57$), only three Fe ii lines were
available. Hence, for this star, we obtained $v_{\mathrm{t}}$ from the
empirical relation with $\log\,g$ based on the work of Barklem et al. (2005,
see appendix B of  and bottom panel of Figure 2).

Lastly, we recalibrated the $T_{\mathrm{eff}}$ for each star to the
“photometric scale” of Frebel et al. (2013) and, then, rederived $\log\,g$ and
$v_{\mathrm{t}}$ by repeating the same steps described above. We reanalysed
from scratch a couple of stars from Ji et al. (2020a) with our method and
verified that these authors’ photometric stellar parameters are compatible
($1\sigma$) with those revised with the Frebel et al. (2013) correction. On
average, $T_{\mathrm{eff}}$ values become $\approx$200 K hotter after this
step. For $\log\,g$ and [M/H], the corrected values are, on average, 0.67 dex
and 0.24 dex larger, respectively. For $v_{\mathrm{t}}$, the final values are
0.07$\mathrm{\,km\,s^{-1}}$ lower on average. Note that we do not just apply
constant offsets, but rather the stellar parameters of each star change
independently according to their recalibrated $T_{\mathrm{eff}}$ and these
listed values are simply the average corrections. In Table 1 (also all
figures), we provide only corrected parameters. Stellar parameters prior to
recalibration are provided as online supplementary material. Throughout the
remainder of this work, we consider only recalibrated stellar parameters,
including for the abundance analysis (Section 3.2).

Apart from just statistical uncertainties, which come from the fitting process
of individual lines as well as from the slopes of the excitation/ionization
balance fits, it is crucial to consider systematics that can affect our
stellar parameters and which are propagated into abundances. Systematic errors
in stellar spectroscopic analysis come, in principle, from departures from the
1D LTE assumption, i.e., 3D and/or NLTE effects, which are especially relevant
for metal-poor giants (Asplund, 2005). In order to obtain empirically
motivated systematic errors, we looked at the sample of low-metallicity stars
analysed by Ezzeddine et al. (2020), which spans a wide range of stellar
parameters that completely encompasses our sample; $4600<T_{\mathrm{eff}}/{\rm
K}\lesssim 5300$, $1<\log\,g\lesssim 3$, $-3.50\lesssim{\rm[Fe/H]}<-1.25$, and
$1<v_{\rm t}/({\rm km\ s^{-1}})\lesssim 2$. These authors provided different
sets of stellar parameters for each of their stars, including 1D LTE with the
Frebel et al. (2013) correction and 1D NLTE. We verified that the average
differences between these stellar parameter estimates are 100 K, 0.5 dex,
0.1$\mathrm{\,km\,s^{-1}}$, and 0.2 dex for $T_{\mathrm{eff}}$, $\log\,g$,
$v_{\mathrm{t}}$, and [Fe/H] and these values are adopted as systematic
errors, summing in quadrature with the statistical ones to obtain final
uncertainties for these quantities. For Wuk_6, we adopted a $v_{\mathrm{t}}$
statistical uncertainty of 0.12$\mathrm{\,km\,s^{-1}}$, which is the intrinsic
scatter from the quadratic fit to the $\log\,g$ versus $v_{\mathrm{t}}$
relation. We note that, despite the apparently excessively large $\log\,g$
errors, $T_{\mathrm{eff}}$ continues to have the most important impact on
abundance uncertainties.

A comparison between our MIKE parameters and those from the H3
survey/MINESweeper is provided in Figure 3. For $T_{\mathrm{eff}}$ and
$\log\,g$, these are compatible ($1\sigma$) for all stars. For [Fe/H], H3
values are larger by ${\sim}0.3$ dex, but this level of systematics can be
attributed to NLTE effects (see figure 2 of Ezzeddine et al., 2020). In
comparison to APOGEE parameters, we found $T_{\mathrm{eff}}$ and $\log\,g$
differences of ${\sim}300$ K and ${\sim}0.7$ dex, respectively, but with
equivalent [Fe/H] values (also Figure 3). We note, however, that, before
applying the Frebel et al. (2013) photometric correction, our purely
spectroscopic $T_{\mathrm{eff}}$ and $\log\,g$ would be compatible ($1\sigma$)
with APOGEE values. With respect to the H3 values, this survey adopts spectro-
photometric fits to obtain stellar parameters from broad-band photometry and
model isochrones. Henceforth, it is not unexpected that our photometrically
recalibrated $T_{\mathrm{eff}}$ and $\log\,g$ are similar, as is the case
between ours and Ji et al.’s (2020a) photometric stellar parameters.

Figure 4: [X/Fe] versus [Fe/H] plots for all elements estimated in this work
for our Wukong/LMS-1. In this figure, Fe is always Fe i. The top right corner
of each panel shows the X element represented. Filled symbols are measured
abundances, while open ones are upper limits. Circles correspond to stars
followed-up from H3 (Wuk_1 to _13) and the square is from APOGEE (Wuk_14).
Dotted lines at $\rm[X/Fe]=0$ show the solar level. The red dashed line at
$\rm[C/Fe]=+0.7$ in the top left panel delineates the boundary for the
definition of CEMP star (see text). The symbol with red edge is Wuk_4. In all
panels, the grey dots in the background are metal-poor stars from our SAGA
data base compilation (see text).

###  3.2 Abundances

We obtained abundances for up to 29 species of 24 elements. Equivalent widths
were used for the abundances of Na i, Mg i, Si i, K i, Ca i, Ti i, Ti ii, Cr
i, Cr ii, Ni i, Zn i, and Sr i, as well Fe i and Fe ii. For heavily blended
features, molecular features, or those requiring hyperfine splitting, we
defaulted to spectral synthesis. For the task, LESSPayne performs a $\chi^{2}$
minimization over local continuum with RV and abundance as free parameters, as
well as a smoothing parameter to account for resolution. This approach was
employed for C-H and C-N molecules, Al i, Sc ii, V i, V ii, Mn i, Co i, Sr ii,
Y ii, Zr ii, Ba ii, La ii, Eu ii, and Dy ii. We also synthesized the Si i line
at 3905Å due to substantial blending. Additionally, we applied this technique
to derive $5\sigma$ upper limits for O i, as well as other elements, for all
our stars. For C-H and C-N, we adopted ${}^{12}{\rm C}/^{13}{\rm C}=9$. For Ba
and Eu, solar $r$-process isotopic ratios were assumed (Sneden et al., 2008).
For [Ti/Fe], [V/Fe], [Cr/Fe], and [Sr/Fe] ratios, we adopt Ti ii, V i, Cr i,
and Sr ii as our fiducial values (Figure 4).

Final abundances were calculated as inverse-variance weighted averages, taking
into account uncertainties from individual lines for each species. Our adopted
procedure is similar to Ji et al. (2020b), which neglects correlations between
stellar parameters (McWilliam et al., 2013). The one difference between our
methodology and these authors’ is the inclusion of an error floor on a line-
by-line basis ($\sigma_{\rm sys}$), which should encapsulate additional
unknowns coming from, for instance, atomic data or the 1D model atmospheres
(see Ji et al., 2020a). For this purpose, we adopted a constant $\sigma_{\rm
sys}=0.1$ dex floor for most lines. For some species with hyperfine splitting,
where the smoothing kernel might be degenerate with abundance, such as Sc, Mn,
and Ba, we add an extra 0.1 dex, i.e., $\sigma_{\rm sys}=0.2$ dex for all
lines. For the C-N molecular band, which is located in the bluest part of MIKE
spectra (3865–3885 Å) where the $S/N$ is low and the continuum placement is
difficult, we implemented $\sigma_{\rm sys}=0.3$ dex. The Al line at 3961 Å,
which is the only one considered for this element, not only suffers from the
same caveats as the C-N, but is also at the wing of a hydrogen line
(H$\epsilon$), so we employed $\sigma_{\rm sys}=0.3$ dex for it as well. We
provide the relevant equations below, which are analogous to equations 1 to 5
in Ji et al. (2020b), but incorporating our modification and with updated
terminology.

For a certain line $i$ of a given element/specie X, its total uncertainty
($\sigma_{i}$) of the associated abundance ($A_{i}$) can be written as the
quadrature sum of the different sources of error, i.e.,

$\sigma_{i}^{2}=\sigma_{i,\rm stat}^{2}+\sigma_{i,\rm SP}^{2}+\sigma_{i,\rm
sys}^{2},$ (1)

where $\sigma_{i,\rm stat}$ is the statistical error, which comes from
spectrum noise and the line-fitting procedure, and $\sigma_{\rm SP}$ is the
total stellar-parameter error budget;

$\sum_{\rm SP}\delta_{i,{\rm SP}}^{2}=\sigma_{i,{\rm
SP}}^{2}=\delta_{i,T_{\mathrm{eff}}}^{2}+\delta_{i,\log\,g}^{2}+\delta_{i,v_{\mathrm{t}}}^{2}+\delta_{i,\rm[M/H]}^{2}.$
(2)

In this equation, $\delta_{i,T_{\mathrm{eff}}}$, $\delta_{i,\log\,g}$,
$\delta_{i,v_{\mathrm{t}}}$, and $\delta_{\rm i,[M/H]}$ are abundance offsets
associated with uncertainties in $T_{\mathrm{eff}}$, $\log\,g$,
$v_{\mathrm{t}}$, and [M/H], respectively, as listed in Table 1. Because these
quantities retain their sign, we refer to them as “$\delta_{i,\cdots}$”.
Finally, the inverse-variance weights can be assigned to each line,

$w_{i}=\dfrac{1}{\sigma_{i}^{2}},$ (3)

and the final abundance can be computed as

$A({\rm X})=\dfrac{\sum^{N}_{i}w_{i}A_{i}}{\sum^{N}_{i}w_{i}},$ (4)

where $N$ is the total amount of lines available for X.

Uncertainties in $A({\rm X})$, as well as abundance ratios, are propagated in
an identical fashion to Ji et al. (2020b). Again, to make this paper self-
sufficient, we reproduce these authors’ equations 6 through 10 (see their
appendix) below.

$\sigma^{2}_{\rm stat}=\dfrac{\sum^{N}_{i}w_{i}[A_{i}-A({\rm
X})]^{2}}{\sum^{N}_{i}w_{i}}+\dfrac{1}{\sum^{N}_{i}w_{i}},$ (5)

where this total statistical uncertainty for abundance $A({\rm X})$ includes
the weighted standard error across abundances $A_{i}$ for $N$ different lines
$i$ of element/specie X as well as spectrum noise. Note that when $N=1$, the
first term of Equation 5 goes to zero and, in that situation, the second term
is fully responsible for propagating line-by-line errors (including our
$\sigma_{\rm sys}$) to the final $\sigma_{\rm stat}$ through the weights pre-
computed by Equation 3. For stellar parameters,

$\delta_{\rm SP}=\dfrac{\sum^{N}_{i}w_{i}\delta_{i,{\rm
SP}}}{\sum^{N}_{i}w_{i}}.$ (6)

We recall that covariance between stellar parameters ($T_{\mathrm{eff}}$,
$\log\,g$, $v_{t}$, and [M/H]) is neglected (see McWilliam et al., 2013).
Then, the total error budget for an abundance ratio [X/H] between
element/specie X and hydrogen is obtained by summing statistical and stellar-
parameter uncertainties in quadrature:

$\sigma^{2}_{\rm[X/H]}=\sigma^{2}_{\rm stat}+\sum_{\rm SP}\delta^{2}_{\rm
SP}.$ (7)

Finally, the uncertainty of an abundance ratio between elements/species X and
Y accounts for covariance between X and Y through stellar parameters:

$\sigma^{2}_{\rm[X/Y]}=\sigma^{2}_{\rm X,stat}+\sigma^{2}_{\rm
Y,stat}+\sum_{\rm SP}(\delta_{\rm X,SP}-\delta_{\rm Y,SP})^{2}.$ (8)

Our abundance inventory is shown in Figure 4. Our Wukong/LMS-1 stars (yellow
symbols) are plotted against a compilation of metal-poor stars (grey dots)
from the Stellar Abundances for Galactic Archaeology (SAGA) database (Suda et
al., 2008, 2017), including the works of Fulbright (2000), Barklem et al.
(2005), Cohen et al. (2013), Yong et al. (2013), Roederer et al. (2014),
Jacobson et al. (2015), and Li et al. (2022). All abundance information, both
ours and SAGA’s, was normalized to the solar composition of Asplund et al.
(2009). Whenever we mention the ratio between an element X and Fe ([X/Fe]), we
adopt Fe i as reference. We highlight the red dashed line in the upper left
panel of Figure 4, which delineates the boundary for “carbon-enhanced metal-
poor” stars (CEMP; $\rm[C/Fe]>+0.7$ and $\rm[Fe/H]<-1$; Beers & Christlieb
2005, Aoki et al. 2007, Frebel & Norris 2015, Frebel 2018). Dotted lines
portray the solar-level abundances ($\rm[X/Fe]=0$) in all panels.

Figure 5: Abundance plots for some neutron-capture elements: [Sr, Y, Zr, Ba,
La/Fe] versus [Fe/H]. Yellow symbols are our Wukong/LMS-1 stars with detected
abundance for the given element in each panel. Empty symbols are upper limits.
The marker with red edge represents the CEMP star in our sample (Wuk_4). The
yellow square is the metal-rich star from APOGEE (Wuk_14). Pink and purple
crosses are stars from Indus and Jhelum stellar streams, respectively. Grey
dots in the background are the metal-poor stars from the SAGA data base
compilation with normal carbon enrichment ($\rm[C/Fe]\leq+0.7$). Regular CEMP
stars are marked as orange diamonds ($\rm[C/Fe]>+0.7$ and
$\rm[Ba/Fe]\leq+1.0$). CEMP-$s$ stars ($\rm[C/Fe]>+0.7$ and $\rm[Ba/Fe]>+1.0$)
are shown in blue triangles (see blue dashed line in the bottom left panel).
The solar abundance level is shown as dotted black lines in all panels.

##  4 Results

Throughout this section, we compare our derived abundance information for
Wukong/LMS-1 with literature results, also with the aid of SAGA data base
(Suda et al., 2008, 2017), but not limited to, for other dwarf galaxies,
accreted substructures, and stellar streams. We gathered data for three dSph
galaxies, namely Sculptor (Scl, Shetrone et al., 2003; Geisler et al., 2005;
Jablonka et al., 2015; Simon et al., 2015; Hill et al., 2019), Fornax (Fnx,
Shetrone et al., 2003; Letarte et al., 2010), and Draco (Dra, Shetrone et al.,
2001; Cohen & Huang, 2009; Tsujimoto et al., 2015). We also consider
Sagittarius (Sgr) dSph$+$stream (Hayes et al., 2020, updated to APOGEE DR17).
We also took data for Reticulum II (Ret II, Ji et al., 2016a, b) ultra-faint
dwarf (UFD). We adopt the sample of “low-$\alpha$” stars from Nissen &
Schuster (2010, 2011), representing GSE, as an example of phase-mixed accreted
dwarf.

For Indus and Jhelum stellar streams, we use the line measurements from Ji et
al. (2020a), but we recomputed the average abundance ratios using our
described methodology (Section 3.2) rather than the weights from their paper.
We proceed into this section with the assumption that our analysed abundances
for Wukong/LMS-1, Indus, and Jhelum are on a consistent scale and with the
understanding that these stellar streams are all associated through a common
progenitor dwarf galaxy. If these hypotheses hold true, the bulk of their
chemical-abundance patterns should be effectively indistinguishable from each
other. Having said that, we caution that, although chemistry is a great tool
for falsifying associations between substructures, similar abundance patterns
do not automatically confirm common origins, especially if these are not too
different from the underlying halo population.

###  4.1 A CEMP star with peculiar neutron-capture signatures

It has been known for at least a couple of decades that the fraction of CEMP
stars increase as function of decreasing metallicity (Beers et al., 1992;
Norris et al., 1997; Rossi et al., 1999; Rossi et al., 2005; Lucatello et al.,
2006; Lee et al., 2013; Placco et al., 2014; Placco et al., 2018; Yoon et al.,
2018, and see Arentsen et al. 2022 for a compilation). The evolution of the
CEMP fraction with [Fe/H] appears to be identical between the Milky Way’s halo
and UFD galaxies (Ji et al., 2020b). However, detailed studies for some more
massive dwarfs, such as classical dSph ones, show that some discrepancy might
exist with the Milky Way, in particular for Sculptor (Skúladóttir et al.,
2015; Skúladóttir et al., 2021, 2023; Chiti et al., 2018) and, possibly,
Sagittarius (Chiti & Frebel, 2019; Chiti et al., 2020, but see Limberg et al.
2023).

In this context, we confirm that Wuk_4, one of our most metal-poor
Wukong/LMS-1 members ($\rm[Fe/H]=-2.89\pm 0.19$), is a CEMP star
($\rm[C/Fe]=+0.74\pm 0.25$; top left panel of Figure 4, symbol with red edge).
The carbon-abundance correction for evolutionary effects is only ${+}0.01$ dex
(Placco et al., 2014). After, applying the carbon correction to all other
stars in our Wukong/LMS-1 sample, none of them turned out to be CEMP. The
corrected [C/Fe] values for all stars are provided alongside the full
abundance table as supplementary material. Wuk_4 had already been identified
as a CEMP candidate by Lucey et al. (2023) through spectro-photometric data
from Gaia DR3. Wuk_4 also shows strong enhancement in Sr, Y, and Zr
($+0.5\lesssim\rm[X/Fe]\leq+1.0$; upper panels of Figure 5). Interestingly,
this is not accompanied by significant enrichment in either Ba
($\rm[Ba/Fe]=+0.12\pm 0.24$) or La (only upper limit found) as would be
expected if Wuk_4 was a “typical” CEMP-$s$ star (Beers & Christlieb, 2005;
Frebel, 2018), i.e., a CEMP star also enhanced in the slow ($s$-) neutron
capture process (defined as $\rm[Ba/Fe]>+1.0$). Apart from Wuk_4, other
Wukong/LMS-1 stars have effectively identical chemical compositions to the
bulk of Indus and Jhelum stars in all abundance panels in Figure 5 (Sr, Y, Zr,
Ba, La).

Figure 6: Abundance trends of $\alpha$-elements Mg (left and middle) and Ca
(right) in $\rm[\alpha/Fe]$ versus [Fe/H] format. Yellow symbols are our
Wukong/LMS-1 stars. The marker with red edge represents the CEMP star in our
sample (Wuk_4). The yellow square is the most metal-rich star followed-up from
APOGEE (Wuk_14). Pink and purple crosses with white edges are stars from Indus
and Jhelum stellar streams, respectively. In the left panel, blue (dotted),
orange (dashed), and green (solid) lines are chemical evolution trajectories
for galaxies with stellar masses $M_{\star}/M_{\odot}$ of $10^{6}$, $10^{7}$,
and $10^{8}$, respectively (Wanajo et al., 2021, see text). In the middle and
right panels, the black line shows the median abundances from the SAGA data
base compilation of metal-poor stars in bins of 0.25 dex in [Fe/H]. The grey
band represents $16^{\rm th}$ and $84^{\rm th}$ percentiles within the same
bins. Stars from Sagittarius (Sgr), Sculptor (Scl), Fornax (Fnx), and Draco
(Dra) dSph galaxies, Reticulum II (Ret II) UFD, as well as GSE disrupted
dwarf, are exhibited for comparison. See text for details on our abundance
compilation for these dwarf galaxies. The solar abundance level is shown as
dotted black lines in all panels. The black error bars in the top right corner
of the middle and right panels show statistical uncertainties alone in [Mg/Fe]
and [Ca/Fe], respectively, as well as [Fe/H].

In Figure 5, we exhibit the same SAGA data base low-metallicity compilation
from Figure 4, but, now, dividing into carbon-normal (grey points), regular
CEMP (orange diamonds), and CEMP-$s$ (blue triangles) stars. From the top
panels, it becomes clear that CEMP-$s$ stars are also preferentially enhanced
in Sr, Y, and Zr. Nevertheless, there are a few examples of ordinary CEMP
stars with high values of [Sr/Fe], [Y/Fe], and/or [Zr/Fe] similar to Wuk_4. In
any case, it is also rather suspicious that Wuk_4 is the only star with
significant (${\approx}10$$\mathrm{\,km\,s^{-1}}$, ${\gtrsim}5\sigma$) RV
difference between H3’s and our measurement (Section 2.2), possibly indicating
a binary system. Indeed, binarity is believed to be the conventional pathway
for the formation of CEMP-$s$ stars as they would experience mass transfer
from an asymptotic giant branch companion (e.g., Lucatello et al. 2005 and
Hansen et al. 2016 for RV monitoring studies and Travaglio et al. 2004 for
nucleosynthesis). Nevertheless, CEMP-no stars, those without any signatures of
$s$-process enhancement ($\rm[Ba/Fe]<0.0$) are also, sometimes, found in long
period binaries (Arentsen et al., 2019; Bonifacio et al., 2020). Deciphering
whether or not mass transfer in a binary can create the excess of Sr, Y, and
Zr in Wuk_4 without high Ba will demand a systematic investigation of other
CEMP stars with similar abundance patterns in the future.

###  4.2 $\alpha$ elements reveal a relatively massive dwarf galaxy

Figure 7: Top: $\rm[Na/Fe]_{\rm NLTE}$ versus [N/Fe]. Bottom: $\rm[Na/Fe]_{\rm
NLTE}$ versus [Fe/H]. In both panels, $\rm[Na/Fe]_{\rm NLTE}$ represents our
sodium-to-iron ratios corrected with the NLTE departures from Lind et al.
(2011, see text). Yellow symbols are Wukong/LMS-1 stars in our sample. The
marker with red edge represents the CEMP star in our sample (Wuk_4). The
yellow square is the most metal-rich star followed-up from APOGEE (Wuk_14).
Star symbols represent the N-/Na-rich stars (Wuk_5 and Wuk_11). Transparent
symbols without edges in the background correspond the same Wukong/LMS-1
stars, but without the NLTE corrections to Na. Pink and purple crosses with
white edges are stars from Indus and Jhelum stellar streams, respectively.
Indus_0, which is also N-/Na-rich, is tagged in both panels. The solar
abundance level is shown as dotted black lines in both panels.

Now, we look at the [$\alpha$/Fe] ratios in Wukong/LMS-1 stars, specifically
the abundances of Mg and Ca. We only derived upper limits for O and Si is less
reliable than Mg and Ca in the low-metallicity regime (see discussion in Ji et
al. 2020a). The behaviour of $\alpha$ abundances is a great tracer of the
overall star-formation history of a galaxy (Tinsley, 1979; Matteucci, 2012).
More massive systems are expected to enrich themselves (i.e., reach higher
metallicities) via core-collapse supernovae before the occurrence of Type Ia
supernovae, which is delayed by ${\gtrsim}100$ Myr (e.g., Maoz & Mannucci,
2012; de los Reyes et al., 2022). Because core-collapse supernovae produces
mostly $\alpha$ elements while the Type Ia create almost exclusively iron-peak
elements (for a review, see Nomoto et al., 2013), a characteristic downturn in
[$\alpha$/Fe] is expected at a certain metallicity (referred to as the “knee”;
Matteucci & Greggio 1986). The location of this knee in [Fe/H] depends on the
star-formation and outflow efficiency, hence the mass, of a given galaxy
(e.g., Matteucci & Brocato 1990 and Tolstoy et al. 2009). This is illustrated
in Figure 6 (left panel) by the simulated chemical-evolution trajectories of
Wanajo et al. (2021, their figure 4, case 1) for dwarf galaxies with different
stellar masses ($10^{6}\leq M_{\star}/M_{\odot}\leq 10^{8}$) at redshift
$z=0$, similar to canonical dSph Milky Way satellites and encompassing the
expected value for Wukong/LMS-1’s progenitor. We note that we subtracted 0.25
dex from their model’s [Mg/H] values so the “plateau” is positioned at about
$+0.4$ dex. These recalibrated versions of the models will also be used in
Section 4.4.

In Wukong/LMS-1, our derived abundances of both Mg and Ca reveal that the
[$\alpha$/Fe] ratio remains high ($\sim$0.3–0.4 dex) up to
$\rm[Fe/H]\gtrsim-2$ (Figure 6). This is, indeed, similar to somewhat massive
surviving Milky Way satellites (Kirby et al., 2011; Reichert et al., 2020).
Before our analysis, the evidence for Wukong/LMS-1’s progenitor being a
relatively massive dwarf ($M_{\star}\sim 10^{7}M_{\odot}$) came from tentative
dynamical $N$-body modeling (Malhan et al., 2021), the scaling relation
between the total mass of its globular clusters and a galaxy’s mass (also
Malhan et al., 2021), or simple star counts (Naidu et al., 2022). Hence, we
provide the first evidence in favor of this hypothesis from chemistry. An
identical $\alpha$-element abundance pattern is seen in Indus and Jhelum (pink
and purple crosses, respectively, in Figures 5 and beyond; Ji et al., 2020a).
As previously mentioned, although this chemical similarity between these
streams does not fully confirm their association, it still corroborates such
scenario.

Although the models in Figure 6 exemplify how a galaxy’s mass correlates with
its chemical evolution, we do not claim to be actually measuring the stellar
mass of Wukong/LMS-1 from abundances. Systematics make the uncertainties of
our [Mg/Fe] and [Ca/Fe] estimates to be typically 0.2 dex. For reference, the
median statistical uncertainties are $\approx$0.1 dex for these [$\alpha$/Fe]
ratios (top right corner in middle and right panels of Figure 6). Not only
this precision does not allow us to differentiate between those models, but
the models themselves carry potentially even worse systematics such as
supernovae and/or NSM yields. Nevertheless, we reinforce that the constant,
within errors, [$\alpha$/Fe] up to $\rm[Fe/H]\sim-2$ is in conformity with the
behaviour seen in the data of nearby massive ($M_{\star}/M_{\odot}\geq
10^{6}$) dwarfs.

It is also relevant that the most metal-rich star ($\rm[Fe/H]=-1.26\pm 0.20$,
Wuk_14; yellow square in all figures) in the sample has lower [Mg/Fe] and
[Ca/Fe] than the bulk of our observed Wukong/LMS-1 members
($\rm[Fe/H]\leq-1.75$) by 0.1–0.2 dex (middle and right panels of Figure 6).
This is, perhaps, not a particularly surprising result given that we observed
this additional star specifically with the goal of testing the standard
chemical enrichment scenario as discussed above. Nevertheless, we notice that
Jhelum also contains a low-$\alpha$ star at $\rm[Fe/H]=-1.45$, which adds to
the emerging picture where Wukong/LMS-1 progenitor experienced quite a simple
chemical evolution pathway. It is also informative that Wukong/LMS-1 shows no
evidence for additional bursts of star formation, which would cause the
[$\alpha$/Fe] to actually increase at higher [Fe/H], a phenomenon that happens
to some dwarfs, such as Sagittarius, Fornax, and the Magellanic Clouds (see
Nidever et al. 2020 and Hasselquist et al. 2021), and is expected to be caused
by their interaction with their massive host (in this case, the Milky Way). We
did not find any trustworthy Wukong/LMS-1 candidates at metallicities higher
than Wuk_14 neither in H3 nor in APOGEE.

###  4.3 A pair of stars with abundances reminiscent of multiple stellar
populations in globular clusters

Almost all globular clusters are known to contain more than just a single,
sometimes several, well-defined sequences in optical/ultraviolet color-
magnitude diagrams (Piotto et al., 2015; Milone et al., 2017). Color
differences between these distinct tracks are caused by star-to-star
variations in their abundances of light elements, including correlated
enhancements in N and Na (e.g., Gratton et al., 2004). Such phenomenon is
referred to as “multiple stellar populations” (Bastian & Lardo, 2018; Milone &
Marino, 2022). Star clusters with multiple stellar populations have been
detected not only in the Milky Way, but also other galaxies in the Local
Group, including the Magellanic Clouds (Mucciarelli et al., 2009; Dalessandro
et al., 2016) and even Fornax dSph (Larsen et al., 2014). Most recently,
evidence has been provided for multiple stellar populations in globular-
cluster stellar streams (Balbinot et al., 2022; Martin et al., 2022; Usman et
al., 2024). Interestingly, a clear detection of a N-/Na-rich star was actually
first made in Indus (Ji et al., 2020a), which holds even after NLTE
corrections to Na (Hansen et al., 2021).

Wukong/LMS-1 contains an additional pair of N-/Na-rich stars (top panel of
Figure 7), reinforcing the idea that its progenitor dwarf galaxy had not only
NGC 5024 and NGC 5053 as globular clusters, but also at least one other that
has been fully disrupted (Hansen et al., 2021), which is not unexpected for
its mass (Eadie et al., 2022). In order to guarantee that this result is
robust against NLTE effects, we performed corrections following Lind et al.
(2011). In practice, we corrected Na abundances line by line and, then,
recomputed the weighted averages using our formalism (Section 3.2). In this
process, uncertainties and weights remain unchanged. For consistency, we
applied the same approach to both Indus and Jhelum stars. As can be
appreciated from Figure 7, NLTE corrections to Na exacerbate the differences
between the bulk of our Wukong/LMS-1 members and its enriched stars; original
LTE abundances are plotted in the background as transparent symbols. We note
that both NGC 5024 and NGC 5053 are also very metal-poor
($\rm[Fe/H]\lesssim-2$; Kruijssen et al. 2019 and references therein) and
contain multiple stellar populations (see their ultraviolet color-magnitude
diagrams in Piotto et al., 2015)

From the bottom panel of Figure 7, it is intriguing that both of our N-/Na-
rich Wukong/LMS-1 stars (Wuk_5 at $\rm[Fe/H]=-2.42\pm 0.25$ and Wuk_11 at
$\rm[Fe/H]=-2.37\pm 0.20$) have metallicities compatible ($1\sigma$) to their
analog in Indus (Indus_0; $\rm[Fe/H]=-2.32\pm 0.22$). We speculate that this
could indicate that all these stars originated from a single disrupted
globular cluster, though there is still not enough evidence to make a clear
association. Nevertheless, if more stars at this metallicity of
${\approx}{-}2.4$ dex are found to have excess of N and Na in Indus, Jhelum,
and the large Wukong/LMS-1, the scenario where they all belonged to the same,
now completely disrupted, globular cluster would be reinforced. Furthermore,
this underscores the exciting possibility of identifying more enriched
globular-cluster stars embedded within other dwarf-galaxy streams, which would
be further evidence in favor of the multiple stellar populations phenomenon
being ubiquitous across different environments.

Now that we have strong indication that Wukong/LMS-1 had ${\geq}3$ globular
clusters, we can utilize this information as independent constraint on the
total mass of this dwarf (e.g., Forbes 2020 and Callingham et al. 2022). We
employ the relationship between the total number of globular clusters in a
galaxy and its halo virial mass from Burkert & Forbes (2020, their equation
1). This exercise gives a total mass of ${\approx}10^{10}M_{\odot}$ for
Wukong/LMS-1. This value, indeed, translates into a stellar mass of
${\sim}10^{7}$ assuming the stellar-to-halo mass relation from Rodríguez-
Puebla et al. (2017) at redshift $z=1$ (${\sim}8$ Gyr ago in Planck
Collaboration et al. 2020 cosmology), consistent with expectations for
Wukong/LMS-1 (Malhan et al., 2021; Naidu et al., 2022). From this line of
reasoning, Wukong/LMS-1 might have contributed with ${\sim}1$% of the present-
day total mass of the Milky Way (e.g., Bland-Hawthorn & Gerhard, 2016).

###  4.4 The rise of the $r$-process in Wukong/LMS-1

Finally, we look at the abundance patterns of rapid ($r$-) neutron capture
process elements in Wukong/LMS-1. In 2017, the electromagnetic counterpart of
the neutron-star merger (NSM) event GW170817 (Abbott et al., 2017a, b, c)
provided confirmation that this site is capable of producing copious amounts
of heavy elements via the $r$-process (Drout et al., 2017; Kilpatrick et al.,
2017; Shappee et al., 2017). Notwithstanding, although NSMs could be the only
site for the $r$-process, evidence has been presented that additional sources
are involved (see the review by Cowan et al., 2021), in particular a prompt
source might be needed to explain the full abundance patterns of both the
Milky Way (Côté et al., 2019; Haynes & Kobayashi, 2019; Kobayashi et al.,
2020; Tsujimoto, 2021) and some of its dSph satellites (Skúladóttir et al.,
2019; Reichert et al., 2020; Skúladóttir & Salvadori, 2020). The timescales
for $r$-process enrichment embedded into the chemical abundances of stars hold
clues to its dominant astrophysical site(s).

As can be seen in the top panel of Figure 8, the [Eu/Fe] ratio, where Eu is
mostly produced by the $r$-process (see Sneden et al., 2008), increases from
${<}{+}0.1$ dex at $\rm[Fe/H]\sim-2.4$ all the way up to ${>}{+}0.7$ dex at
$\rm[Fe/H]\sim-1.3$. The [Ba/Eu] ratio of Wukong/LMS-1 stars is effectively
constant at ${\sim}{-}0.4$ dex, confirming that the production of these
elements is dominated by the $r$-process. For reference, a “pure” $r$-process
signature is close to $\rm[Ba/Eu]=-0.8$ (e.g., Bisterzo et al., 2014). These
abundances overlap with both Indus and Jhelum, although the data for these
other stellar streams do not cover as large of a metallicity interval. We also
recall the existence of the extremely $r$-process rich star Indus_13 (Hansen
et al., 2021), which is labeled in Figure 8. The previously mentioned Wanajo
et al. (2021) chemical-evolution sequences (Section 4.2) are plotted in the
background of Figure 8. These models contain $r$-process production
exclusively from NSMs. The current data for Wukong/LMS-1 seems compatible with
this scenario, without the need for a prompt source (such as core-collapse
supernovae) where [Eu/Fe] (or [Eu/Mg] as in the bottom panel of Figure 8)
would be constant over the low-metallicity regime. Note that we do not claim
that NSMs are the only source of $r$-process in Wukong, but rather the
dominant one within the metallicity range probed by our current data.

An increasing trend of [Eu/Fe] with [Fe/H] has also been claimed to exist in
UMi dSph (Cohen & Huang, 2010). However, this behaviour is accompanied by a
huge scatter, which suggests that UMi actually experiences stochastic
$r$-process enrichment, which, indeed, would be in line with its lower stellar
mass ($M_{\star}\sim 10^{5}M_{\odot}$) in comparison to Sculptor, Fornax, and
Sagittarius dSph galaxies ($M_{\star}>10^{6}M_{\odot}$). Similar observations
have also been made in another dwarf-galaxy stellar stream, the so-called
“Typhon” (Tenachi et al., 2022; Dodd et al., 2023, and Ji et al. 2023b for
abundances). Nevertheless, the available data for that stream covers a shorter
metallicity interval and the differences in [Eu/Fe] are smaller than in
Wukong/LMS-1. Also, in Typhon, this result depends on a single star at
$\rm[Fe/H]<-2$. Therefore, Wukong/LMS-1 constitutes the first example of a
dwarf galaxy, though in the form of a stellar stream, with $r$-process
enrichment that is clearly dominated by delayed sources, presumably NSMs. Of
course, additional measurements of Eu at lower metallicities
($\rm[Fe/H]<-2.5$) will be necessary to test for the presence of a prompt
$r$-process source in Wukong/LMS-1. Unfortunately, all stars analysed in this
work at such low-metallicity regime are relatively hot
($T_{\mathrm{eff}}\gtrsim 5100$ K; Table 1, Wuk_4, 6, and 7), which impedes us
from obtaining detections of Eu with the lines considered (4129Å, 4205Å,
4435Å, 4522Å, and 6645Å).

Figure 8: Top: [Eu/Fe] versus [Fe/H]. Bottom: [Eu/Mg] versus [Mg/H]. Yellow
symbols are Wukong/LMS-1 stars in our sample. Empty symbols are upper limits.
The marker with red edge represents the CEMP star in our sample (Wuk_4). The
yellow square is the most metal-rich star followed-up from APOGEE (Wuk_14).
Pink and purple crosses with white edges are stars from Indus and Jhelum
stellar streams, respectively. Indus_13, which is an extremely $r$-process
enhanced star is tagged in the top panel. In both panels, blue (dotted),
orange (dashed), and green (solid) lines are chemical evolution trajectories
for galaxies with stellar masses $M_{\star}/M_{\odot}$ of $10^{6}$, $10^{7}$,
and $10^{8}$, respectively (Wanajo et al., 2021, see text). The solar
abundance level is shown as dotted black lines in both panels.

##  5 Conclusions

We presented results from the first spectroscopic follow-up campaign for stars
in the Wukong/LMS-1 dwarf-galaxy stellar stream with the Magellan Clay/MIKE
combination. These targets were originally identified as members from the H3
(Naidu et al., 2020; Johnson et al., 2022) or APOGEE (Section 2.1) surveys.
From these high-resolution MIKE spectra, we obtained RVs, stellar parameters,
and detailed chemical abundances for 14 stars in Wukong/LMS-1 covering an
extensive metallicity range ($-3.5<\rm[Fe/H]\lesssim-1.3$). We also
recalculated average abundances for a pair of stellar streams, Indus and
Jhelum (Ji et al., 2020a), which have been suggested to be associated with the
larger Wukong/LMS-1 (Bonaca et al., 2021; Malhan et al., 2021; Malhan et al.,
2022), in order to guarantee a consistent scale across samples. Our main
results are summarized below.

  * •

Wukong/LMS-1 is chemically indistinguishable from Indus and Jhelum. Although
this is not enough to confirm that they originated in the same parent dwarf
galaxy, this is certainly evidence in favor of this hypothesis.

  * •

We confirmed a CEMP star in Wukong/LMS-1 (Wuk_4; $\rm[Fe/H]=-2.89\pm 0.19$ and
$\rm[C/Fe]=+0.74\pm 0.25$) with evidence for RV variation (${>}5\sigma$ level)
as well as peculiar enhancements ($+0.5\lesssim\rm[X/Fe]\leq+1.0$) in Sr, Y,
and Zr, which is reminiscent of the CEMP-$s$ class, but without the expected
high [Ba/Fe] ratio.

  * •

The $\rm[\alpha/Fe]$ ratios (Mg, Ca) in Wukong/LMS-1 remain high
($\sim$0.3–0.4 dex) up to $\rm[Fe/H]\gtrsim-2$, which is similar to relatively
massive surviving dSph satellites of the Milky Way. This is in conformity with
other works in the literature that estimated the mass of Wukong/LMS-1’s
progenitor with other methods (Malhan et al., 2021; Naidu et al., 2022).
Moreover, the most metal-rich star in our sample (Wuk_14; $\rm[Fe/H]=-1.26\pm
0.20$), as well as a Jhelum star at $-1.45$ dex, has lower [$\alpha$/Fe] by
0.1–0.2 dex in comparison to the bulk of Wukong/LMS-1 stars, suggesting that
this dwarf galaxy likely experienced fairly standard chemical evolution.

  * •

Wukong/LMS-1 contains a pair of stars (Wuk_5 and Wuk_11) that are both N- and
Na-rich in comparison to the bulk of the sample, which is a telltale sign that
that these were born in a globular cluster with multiple stellar populations.
This favors the hypothesis that Wukong/LMS-1 likely contained at least one
globular cluster that has been completely disrupted. Interestingly, both of
these Wukong/LMS-1 members plus a previously known N-/Na-rich Indus star all
have compatible ($1\sigma$) metallicities ($\rm[Fe/H]\equiv 2.4$).

  * •

Because Wukong/LMS-1 is also associated with a couple of intact globular
clusters, NGC 5024 (M53) and NGC 5053, plus the disrupted one, we used this
information to estimate the halo virial mass of the progenitor system. For
${\geq}3$ globular clusters, a galaxy is expected to have a total mass of
${\approx}10^{10}$, which corresponds to ${\sim}1$% of the present-day Milky
Way.

  * •

The [Eu/Fe] ratio in Wukong/LMS-1 stars increases as a function of metallicity
within $-2.5<\rm[Fe/H]\lesssim-1.3$, which can be reproduced by chemical-
evolution models for similarly massive dwarfs with NSMs as the only source for
the $r$-process (Wanajo et al., 2021), i.e., without the need for a prompt
source. Wukong/LMS-1 is, in this context, the first example of dwarf galaxy
with $r$-process enrichment clearly dominated by delayed sources.

This paper provides a powerful demonstration of how detailed abundances can be
used to unveil the evolution of disrupted dwarf galaxies, which, given their
low masses and high accretion redshift, can not be spatially resolved, or
detected (depending on the exact redshift), even by JWST. The combination
between Gaia and complementary spectroscopic surveys can be employed to
confidently identify members of streams/substructures if one is well-informed
regarding potential interlopers, in particular from GSE and Sagittarius
stream. We envision that the next step for Galactic archaeology will be to
obtain samples covering larger metallicity ranges for these
streams/substructures. Towards the low-metallicity regime, the number of
available targets drastically diminishes. In the metal-rich end, Milky Way’s
halo foreground contamination is difficult to deal with. Therefore, dedicated
searches for these targets will be necessary for us to continue advancing our
knowledge about the fundamental building blocks of our Galaxy.

## Acknowledgements

This paper includes data gathered with the 6.5 meter Magellan Telescopes
located at Las Campanas Observatory, Chile. This work benefited from
discussions conducted during the “Non-LTE workshop” supported by the National
Science Foundation under Grant No. OISE-1927130 (IReNA), the Kavli Institute
for Cosmological Physics, and the University of Chicago Data Science
Institute. G.L. is particularly thankful for discussions with Christian Hayes,
Keith Hawkins, Kim Venn, and Vini Placco. G.L. is also indebted to Ása
Skúladóttir for her inspiring talk, as well as afterward conversations, at the
2023 CeNAM Frontiers in Nuclear Astrophysics meeting. G.L. also thanks Zhen
Yuan for providing the original LMS-1 members and Ting Li for pointing out the
connection between Wukong/LMS-1 and Indus/Jhelum. G.L. is also sincerely
grateful to Yutaka Hirai and Shinya Wanajo for providing the chemical-
evolution models.

We thank the anonymous referee whose comments and suggestions contributed to
the quality of this paper. G.L. acknowledges FAPESP (procs. 2021/10429-0 and
2022/07301-5). A.P.J. acknowledges support by the National Science Foundation
under grants AST-2206264 and AST-2307599. A.C. is supported by a Brinson Prize
Fellowship at UChicago/KICP. S.R. thanks support from FAPESP (procs.
2015/50374-0 and 2020/15245-2), CAPES, and CNPq. Y.S.T. acknowledges financial
support from the Australian Research Council through DECRA Fellowship
DE220101520. L.B. acknowledges CAPES/PROEX (proc. 88887.821814/2023-00).

This work has made use of data from the European Space Agency (ESA) mission
Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing
and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement. This research has made use
of NASA’s Astrophysics Data System Bibliographic Services.

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-IV acknowledges support and resources from
the Center for High Performance Computing at the University of Utah. The SDSS
website is www.sdss.org. SDSS-IV is managed by the Astrophysical Research
Consortium for the Participating Institutions of the SDSS Collaboration.

## Data Availability

The individual line measurements as well as full abundance tables are provided
as supplementary material. All the data, including reduced spectra, plus full
line measurements and abundance tables are available at
zenodo.org/records/10932808. The code to generate complete abundance tables
from smhr/LESSPayne outputs, as well as the redetermined abundances for Indus
and Jhelum, can be found at github.com/guilimberg/abund-tables.

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