# A new member of the Milky Way’s family tree:
Characterizing the Pontus merger of our Galaxy

Khyati Malhan Humboldt Fellow and IAU Gruber Fellow  Max-Planck-Institut für
Astronomie, Königstuhl 17, D-69117, Heidelberg, Germany

###### Abstract

We study the Pontus structure – a recently discovered merger that brought in
$\sim 7$ globular clusters in the course of the hierarchical build-up of the
Milky Way’s halo. Here, we analyse the stellar population of Pontus and
examine (1) its phase-space distribution using the ESA/Gaia dataset, (2) its
metallicity and chemical abundances (i.e., [Fe/H], [$\alpha$/Fe], [Mg/Fe],
[Al/Fe]) using the spectroscopic catalogue of APOGEE DR17, and (3) the color-
magnitude diagram that shows interesting features, including a possibly double
horizontal branch and a small population of blue stragglers. In sum, the
Pontus stars show some unique properties that suggest they likely originated
from the merging of an independent satellite galaxy; future analysis will shed
more light on the true nature of this structure. This chemo-dynamical analysis
of Pontus stars is another step forward in our bigger quest to characterize
all the merging events of our Milky Way.

Galaxy: halo – Galaxy: structure – Galaxy: kinematics and dynamics – chemical
abundances – surveys

††journal: ApJL

##  1 Introduction

The advent of the data of the Gaia  mission (Gaia Collaboration et al., 2016;
Lindegren et al., 2018; Gaia Collaboration et al., 2021) has allowed us to
detect and characterize many sub-structures in the Milky Way halo (Belokurov
et al., 2018; Helmi et al., 2018; Myeong et al., 2019; Matsuno et al., 2019;
Koppelman et al., 2019a; Mackereth et al., 2019; Yuan et al., 2020; Ibata et
al., 2020; Ramos et al., 2020; Naidu et al., 2020; Malhan et al., 2021). These
sub-structures are remnants of those progenitor galaxies that merged with the
Milky Way and contributed to the stellar (and dark matter) population of the
Galactic halo. Here, our aim is to specifically analyse one of these sub-
structures, namely Pontus111In Greek mythology, “Pontus” (meaning “the Sea”)
is the name of one of the first children of the Gaia deity., and study the
dynamical and chemical properties of its stellar population.

Figure 1: Action-Energy ($\mathbf{J},E$) space of the Milky Way showing stars
that form part of our halo sample (see Section 2 and 3). The left panel shows
$J_{\phi}(\equiv L_{z})$ vs $J_{R}$, where stars are colored by their $J_{z}$
values. The right panel shows $J_{\phi}$ vs $E$, that is represented by a 2D
histogram colored by the logarithm of the number of stars per bin. In both the
panels, the boxes describe the dynamical volumes occupied by different mergers
as per Malhan et al. (2022). Stars belonging to Pontus possess low energy
($E\sim-1.65\times 10^{5}{\rm\,km^{2}\,s^{-2}}$) and slightly retrograde
motion ($J_{\phi}\sim 200{\rm\,kpc}{\rm\,km\,s^{-1}}$).

Pontus was recently discovered by Malhan et al. (2022) as a grouping of $7$
globular clusters that are tightly-clumped in the action-energy
($\mathbf{J},E$) space of the Milky Way. This group possesses low energy
(i.e., the orbits of its components are more tightly bound to the Milky Way
compared to other merger groups) and slightly retrograde motion (this is also
shown in Figure 1 that we explain below). The member globular clusters include
NGC 288, NGC 5286, NGC 7099/M 30, NGC 6205/M 13, NGC 6341/M 92, NGC 6779/M 56,
NGC 362; there exist two additional (tentative) associations, namely NGC
6864/M 75 and NGC 7089/M 2. In addition to being tightly-clumped in the
($\mathbf{J},E$) space, these globular clusters also show a tight age-
metallicity relation – again supporting the accretion scenario from a
gradually enriched satellite galaxy.

While Malhan et al. (2022) could only analyse the globular cluster population
of Pontus, our central objective here is to analyse its general, unbound
stellar population. This is important to understand, for instance: how are the
Pontus stars distributed in the phase-space of the Milky Way? What are their
metallicity ([Fe/H]) and chemical abundances ([X/Fe])? What can we learn about
this sub-structure by inspecting its color-magnitude diagram (CMD)? When did
the (hypothesized) Pontus galaxy merge with the Milky Way? Here, we make a
first attempt to answer these questions by analysing the Pontus stars.

This article is structured as follows. In Section 2, we first describe our
procedure to construct a sample of halo stars using the Gaia  dataset. Next,
in Section 3, we compute the orbits of these stars to specifically select the
Pontus population. In Section 4, we analyse the Pontus population to examine
its phase-space distribution, chemical abundances and CMD. Finally, we discuss
our findings and conclude in Section 5.

##  2 Selecting the halo stars using Gaia

We first construct a sample of “halo” stars – those stars that possess
kinematic very different from the local disk stars. For this, we use the Gaia
EDR3 dataset, but consider only those stars that possess radial velocity
measurements from the Gaia  DR2 dataset. This dataset provides 6D phase-space
information for $7,209,831$ sources in the heliocentric coordinates: on-sky
positions ($\alpha,\delta$), parallaxes ($\varpi$), proper motions
($\mu^{*}_{\alpha},\mu_{\delta}$) and line-of-sight velocities ($v_{\rm
los}$), along with their associated uncertainties. This dataset also provides
the $G$, $G_{\rm BP}$ and $G_{\rm RP}$ magnitudes.

To select the halo population, we follow a similar prescription described by
Koppelman et al. (2019b), but with slight modification. We select those stars
that follow the criteria: (1) $|\mathbf{V}-\mathbf{V_{\rm LSR}}|\geq
210{\rm\,km\,s^{-1}}$; where $\mathbf{V}$ is the velocity vector of a given
star in the Galactocentric cartesian coordinates (this we obtain by
transforming the heliocentric coordinates into cartesian coordinates using the
Sun’s velocity from Drimmel & Poggio 2018 as
$(V_{X,\odot},V_{Y,\odot},V_{Z,\odot})=(12.9,245.6,7.78){\rm\,km\,s^{-1}}$ and
the Sun’s location from Gravity Collaboration et al. 2018 as
$R_{\odot}=8.112{\rm\,kpc}$) and $\mathbf{V_{\rm LSR}}$ is the velocity vector
of the local standard of rest (LSR) that we adopt from Drimmel & Poggio (2018)
as $(V_{\rm X,LSR},V_{\rm Y,LSR},V_{\rm
Z,LSR})=(1.8,233.4,0.53){\rm\,km\,s^{-1}}$. (2) $\varpi>0$; this condition
ensures that the parallaxes can be directly inverted to obtain heliocentric
distances as $D_{\odot}=1/\varpi$ (this condition was implemented after
correcting for the parallax zero-point of each star using the code222See
https://gitlab.com/icc-ub/public/gaiadr3_zeropoint . provided by Lindegren et
al. 2021, and henceforth all the parallaxes are zero-point corrected). (3)
parallax_over_error$\geq 5$; this quality cut ensures that our resulting
sample contains well measured parallaxes with relative parallax error of $\leq
20\%$. (4) phot_bp_rp_excess_factor$\leq 1.27$; this condition removes some of
the not so well-behaved globular cluster stars, and hence, we do not apply a
colour-dependent correction (Arenou et al., 2018). (5) RUWE$<1.4$; this value
has been prescribed as a quality cut for “good” astrometric solutions by
Lindegren et al. (2021). We note that the RUWE parameter was not considered by
Koppelman et al. (2019b), and has also been ignored by many previous studies
that had the similar objective of constructing a halo sample.

This halo selection renders $41,861$ data points. In other words, $\sim 0.5\%$
of our Gaia  sample corresponds to the halo population; at least as per our
definition of halo.

##  3 Computing the orbits

For the above halo stars, we compute their $\mathbf{J},E$ and also other
orbital parameters (e.g., apocentre, $r_{\rm apo}$, pericentre, $r_{\rm
peri}$, eccentricity, $ecc$). This is a necessary first step to particularly
select the Pontus stars using a specified range of orbital parameters; this
range is described below. To compute the orbits, we adopt the Galactic
potential model of McMillan (2017); similar to that used by Malhan et al.
(2022). This is a static and axisymmetric model comprising a bulge, disk
components and an NFW halo. To set this potential model, and to compute the
orbital parameters, we make use of the galpy module (Bovy, 2015).

Figure 1 shows the resulting $\mathbf{J}$ distribution (left panel) and
$(J_{\phi},E)$ distribution (right panel) of all the stars from our halo
sample. The actions are represented in the cylindrical coordinates, i.e.,
$\mathbf{J}\equiv(J_{R},J_{\phi},J_{z})$, where $J_{\phi}$ corresponds to the
z-component of angular momentum (i.e., $J_{\phi}\equiv L_{z}$) and negative
$J_{\phi}$ represents prograde motion. Components $J_{R}$ and $J_{z}$ describe
the extent of oscillations in cylindrical radius and $z$ directions,
respectively. In this figure, the boxes are drawn using the prescription
provided by Malhan et al. (2022) and they describe the dynamical volumes
occupied by different merger groups.

We particularly focus on Pontus that corresponds to the dynamical region
described by: $E=[-1.72,-1.56]\times 10^{5}{\rm\,km^{2}\,s^{-2}}$,
$J_{R}=[245,725]{\rm\,km\,s^{-1}}{\rm\,kpc}$,
$J_{\phi}=[-5,470]{\rm\,km\,s^{-1}}{\rm\,kpc}$,
$J_{z}=[115,545]{\rm\,km\,s^{-1}}{\rm\,kpc}$, $ecc=[0.5,0.8]$, $r_{\rm
peri}=[1,3]{\rm\,kpc}$, $r_{\rm apo}=[8,13]{\rm\,kpc}$. These dynamical ranges
are described using the values provided by Malhan et al. (2022), who found
that the member globular clusters of Pontus lie in this range333Since the
member globular clusters of Pontus are contained within this dynamical range,
it is reasonable to assume that a significant fraction of its stellar
population must also be contained within this range. Although, we note that
the “true” extent out to which the Pontus stars are distributed in the phase-
space of the Milky Way could be larger.. This implies that Pontus stars are
located in the low-energy part of the halo, and they possess slightly
retrograde motion and moderately eccentric orbits. We employ these strict
dynamical parameters to make a box selection that yields $1311$ stars, and we
refer to this sample as Pontus444The reason for making cuts in this $7$ (non-
independent) dimensions is to obtain a high-confidence (even though
restricted) sample of Pontus stars. While one may argue that making cuts only
in the $\mathbf{J}$ space should be sufficient (since an orbit only has three
integrals of motions), we supplement this criteria with additional orbital
parameters in order to minimise the contamination. Although, even this
restricted selection results in a few contaminants in our Pontus sample; as we
see below..

Figure 2: Phase-space distribution of the Pontus stars (in “magenta” color) in
the Galactocentric coordinates. The top panels show the spatial distribution
of stars and the bottom panels show the velocity distribution. The “star”
markers correspond to the member globular clusters of Pontus. For comparison,
we show the halo sample (in “gray”) and also the Gaia-Sausage/Enceladus stars
(in “blue”).

##  4 Analysing the Pontus stars

We now analyse the Pontus stars to examine their phase-space distribution in
the Milky Way (Section 4.1), their metallicity and chemical abundances
(Section 4.2) and their CMD (Section 4.3).

###  4.1 Phase-space distribution

Figure 2 shows the phase-space distribution of the Pontus stars.

In Figure 2, panels $a-c$ show the spatial distribution of the Pontus stars in
the Galactocentric cartesian coordinates. For comparison, we also show the
stars from our halo sample. First, we note that Pontus shows far fewer stars
at small Galactocentric radii, although there is no obvious signature of a
spatial overdensity. This implies that the Pontus stars are almost completely
phase-mixed in the Galaxy. This argument is further supported by the fact that
these stars possess small $E$ values, implying that they orbit the inner
region of the Galaxy which has small mixing timescales. In this figure, we
also show the member globular clusters of Pontus (as found by Malhan et al.
2022). At first, it may seem strange that the clusters are distributed out to
large heliocentric distances compared to the stars. However, this is because
our Gaia  dataset contains very bright stars (with $G\lower
2.15277pt\hbox{$\;\buildrel<\over{\sim}\;$}14$ mag555This is because radial
velocity measurements are present for only those sources in Gaia  DR2 that are
brighter than $G\approx 14$ mag.), and therefore, many of the distant (and
fainter) stars are missing from our sample.

In Figure 2, panels $d-f$ show the velocity distribution of stars in the
Galactocentric cylindrical coordinates. First, it can be seen that Pontus
stars occupy very limited region in this space – very similar to the
distribution of simulated sub-structures in Helmi & de Zeeuw (2000). The
reason that the Pontus stars appear so confined in the velocity space is
admittedly because of our narrow Pontus (vs. halo) selection in the orbital
parameter space. Secondly, the Pontus population is stretched along the
$V_{R}$ direction (and also along the spherical $V_{r}$ direction, that we
independently checked), implying that these stars move along radial orbits; as
expected from their moderately high $J_{R}$ and $ecc$ values (Figure 1, left
panel). Moreover, for the Pontus stars, we estimate the average and standard
deviation of their $V_{\phi}$ distribution as $28\pm 25{\rm\,km\,s^{-1}}$;
implying a retrograde structure with fairly low dispersion in $V_{\phi}$.
Furthermore, we note that all the member globular clusters overlap with the
stars in this velocity space, and this is expected because of the
$\mathbf{J}$, $E$ cut that we made to select the Pontus stars.

We also make comparison of the Pontus stellar population with that of Gaia-
Sausage/Enceladus (Belokurov et al., 2018; Helmi et al., 2018) because these
two structures are located close to each other in the ($J_{\phi},E$) space and
we are interested to examine – do these two structures represent different
merging events, or they simply correspond to two different fragments of the
same merger? In this regard, Malhan et al. (2022) argues that Pontus and Gaia-
Sausage/Enceladus are independent structures, since the member globular
clusters of each group occupy different locations in the ($\textbf{J},E$)
space (and consequently in phase-space) and they also possess different age-
metallicty relation. Here, we want to examine whether this scenario is also
favoured by their stellar population.

The sample of Gaia-Sausage/Enceladus population is constructed in the same way
as described for Pontus in Section 3, except using a different set of
dynamical range as described by Malhan et al. (2022):
$E\sim[-1.44,-1.16]\times 10^{5}{\rm\,km^{2}\,s^{-2}}$,
$J_{R}\sim[935,2075]{\rm\,km\,s^{-1}}{\rm\,kpc}$,
$J_{\phi}\sim[-715,705]{\rm\,km\,s^{-1}}{\rm\,kpc}$,
$J_{z}\sim[85,1505]{\rm\,km\,s^{-1}}{\rm\,kpc}$, $ecc\sim[0.7,0.9]$, $r_{\rm
peri}\sim[1,4]{\rm\,kpc}$, $r_{\rm apo}\sim[16,30]{\rm\,kpc}$. We note that
this $E$ and $J_{\phi}$ range, that has been independently proposed by Malhan
et al. (2022), is similar to that previously used by Koppelman et al. (2019a)
to select and study the Gaia-Sausage/Enceladus stars. These stars are shown in
panels $d-f$ of Figure 2. As can be seen, the Gaia-Sausage/Enceladus and
Pontus stars occupy very different regions in the velocity space, although
with small overlapping in the $V_{\phi}-V_{z}$ space. Previous studies that
made similar $\mathbf{J}$ and $E$ selections to simultaneously analyse
multiple structures have found that different structures can in fact highly
overlap in the velocity space (e.g., Koppelman et al. 2019a). Furthermore, for
Gaia-Sausage/Enceladus we estimate $V_{\phi}=-8\pm 55{\rm\,km\,s^{-1}}$,
suggesting that this population has almost no retrgroade component and
possesses larger $V_{\phi}$ dispersion than Pontus.

Figure 3: Analysing chemical abundances of Pontus stars using the APOGEE
dataset. Panel ‘a’ shows the [Fe/H] vs. [$\alpha/$Fe] distribution. The
background shows 2D histograms constructed using the entire APOGEE dataset
(darker the bin, higher is the number of stars in that bin). The bars at the
bottom of the panel indicate the median error at that [Fe/H]. For comparison,
we also show the Gaia-Sausage/Enceladus stars. Panel ‘b’ shows the [Fe/H] vs.
[Mg/Fe] distribution and panel ‘c’ shows the [Fe/H] vs. [Al/Fe] distribution.

###  4.2 Metallicity and chemical abundances

We now analyse the metallicity and chemical abundances for the Pontus stars.
To this end, we cross-match our sample with the APOGEE DR17 catalogue
(Abdurro’uf et al., 2021) and find $88$ matches. We particularly analyse the
following quantities: [Fe/H], [$\alpha$/Fe], [Mg/Fe] and [Al/Fe].

The Pontus stars are shown in Figure 3. From the [Fe/H] vs. [$\alpha$/Fe]
distribution, we note that the Pontus stars clearly show an anti-correlation
sequence that is indicative of their accretion (dwarf galaxy) origin. A few of
the Pontus stars overlap with the disk region, suggesting that our sample
contains some disk contaminants. Secondly, we observe a similar anti-
correlation sequence in [Fe/H] vs. [Mg/Fe], which is expected since Mg is an
$\alpha$ element. On the other hand, a correlation sequence is observed in
[Fe/H] vs. [Al/Fe]. This distribution reveals that some of the Pontus stars
overlap with the halo region, suggesting that our sample contains some halo
contaminants.

For the Pontus stars, we compute the means and dispersions of their
distributions in [Fe/H], [$\alpha$/Fe], [Mg/Fe] and [Al/Fe], and these are
provided in Table 1. These values are computed following our own Metropolis-
Hastings based MCMC algorithm, based on Malhan et al. (2021), where the log-
likelihood function is taken to be:

$\ln\mathcal{L}=\sum_{\rm data}\Big{[}-\ln\sigma_{\rm
Y_{obs}}-0.5\Big{(}\dfrac{\rm Y_{0}-Y_{\rm d}}{\sigma_{\rm
Y_{obs}}}\Big{)}^{2}\Big{]}\,.$ (1)

Here, $Y$ corresponds to the quantity of interest (e.g., [Fe/H] or [X/Fe]),
${\rm Y_{d}}$ is the measured quantity, and the Gaussian dispersion
$\sigma_{\rm Y_{obs}}$ is the sum in quadrature of the intrinsic dispersion of
the model together with the observational uncertainty of each data point
($\sigma^{2}_{\rm Y_{obs}}=\sigma^{2}_{\rm Y}+\sigma^{2}_{\rm Y_{d}}$). For
this inference, we first impose conservative cuts so that our resulting sub-
sample has a reduced contamination. In doing so, we retain only those stars
that possess [Fe/H]$<-0.75$ (to reduce disk contaminants), [$\alpha$/Fe]$>0$
and [Al/Fe]$<0$ (to reduce halo contaminants). This selection renders $60$
stars, and this sub-sample is used to compute the values provided in Table 1.
Table 1 quotes the mean and the standard deviation corresponding to the
posterior PDFs of different quantities.

Table 1: Metallicity and chemical abundances of the Pontus, Gaia-Sausage/Enceladus and halo populations. Param. | Pontus | GSE | Halo
---|---|---|---
$\rm{[Fe/H]}$ | $-1.403\pm 0.047$ | $-1.274\pm 0.03$ | $-1.185\pm 0.009$
$\rm{\sigma_{[Fe/H]}}$ | ($0.368\pm 0.035$) | ($0.253\pm 0.021$) | ($0.497\pm 0.007$)
$\rm{[\alpha/Fe]}$ | $0.235\pm 0.008$ | $0.216\pm 0.006$ | $0.239\pm 0.002$
$\rm{\sigma_{[\alpha/Fe]}}$ | ($0.057\pm 0.006$) | ($0.05\pm 0.005$) | ($0.085\pm 0.001$)
$\rm{[Mg/Fe]}$ | $0.211\pm 0.012$ | $0.193\pm 0.008$ | $0.246\pm 0.002$
$\rm{\sigma_{[Mg/Fe]}}$ | ($0.09\pm 0.01$) | ($0.06\pm 0.006$) | ($0.111\pm 0.002$)
$\rm{[Al/Fe]}$ | $-0.228\pm 0.014$ | $-0.237\pm 0.009$ | $-0.037\pm 0.005$
$\rm{\sigma_{[Al/Fe]}}$ | ($0.103\pm 0.011$) | ($0.074\pm 0.007$) | ($0.285\pm 0.004$)
Table 2: Results corresponding to the two-sample Kolmogorov-Smirnov (KS) test performed on Pontus and halo populations, Gaia-Sausage/Enceladus and halo populations, and Pontus and Gaia-Sausage/Enceladus populations. Param. | Pontus-Halo | GSE-Halo | Pontus-GSE
---|---|---|---
$\rm{[Fe/H]}$ | $<0.001\,(>4.5\sigma)$ | $<0.001\,(>5.0\sigma)$ | $0.028\,(>2.0\sigma)$
$\rm{[\alpha/Fe]}$ | $<0.001\,(>3.5\sigma)$ | $<0.001\,(>5.5\sigma)$ | $0.414\,(>0.5\sigma)$
$\rm{[Mg/Fe]}$ | $<0.001\,(>4.5\sigma)$ | $<0.001\,(>7.0\sigma)$ | $0.254\,(>0.5\sigma)$
$\rm{[Al/Fe]}$ | $<0.001\,(>6.5\sigma)$ | $<0.001\,(>8.0\sigma)$ | $0.358\,(>0.5\sigma)$

For comparison, we also show the Gaia-Sausage/Enceladus stars in Figure 3.
These stars appear to follow similar sequences as that of Pontus in [Fe/H] vs.
[$\alpha$/Fe] and [Fe/H] vs. [Mg/Fe], except they are slightly less scattered.
The measured parameters for Gaia-Sausage/Enceladus stars are provided in Table
1, and these were computed in a similar way as described above for the Pontus
population (where we imposed similar quality cuts to construct the sub-
sample). Table 1 also shows the measurements for our halo sample. These
measurements were obtained by first cross-matching our halo sample with the
APOGEE dataset, and then using equation 1. In doing so, note that we did not
impose any quality cuts on [Fe/H], [$\alpha$/Fe] or [Al/Fe] as above. This
analysis indicates that the Pontus population possesses somewhat similar
distribution in [$\alpha$/Fe] as that of the halo population, while they
differ in [Fe/H], [Mg/Fe] and [Al/Fe]. Furthermore, the comparison between the
Pontus and Gaia-Sausage/Enceladus populations indicate that while their
distributions are somewhat similar in [$\alpha$/Fe], [Mg/Fe] and [Al/Fe], they
slightly differ in [Fe/H]. In particular, the Pontus stars on an average are
slightly more metal-poor than the Gaia-Sausage/Enceladus stars.

Table 2 summarises the result from the Kolmogorov-Smirnov (KS) test that we
perform to compare the [Fe/H], [$\alpha$/Fe], [Mg/Fe] and [Al/Fe]
distributions of Pontus and Gaia-Sausage/Enceladus, Pontus and halo, and Gaia-
Sausage/Enceladus and halo. The KS test is performed for the null hypothesis
that the two given samples are drawn from the same distribution. For instance,
a value of $>5\sigma$ in Table 2 implies that the null hypothesis can be
rejected at the $>5\sigma$ level666Similar KS-test has also been previously
used to examine chemical distributions of different halo sub-structures (e.g.,
Malhan et al. 2019).. This comparison shows: (1) The [Fe/H], [$\alpha$/Fe],
[Mg/Fe] and [Al/Fe] distributions of both Pontus and Gaia-Sausage/Enceladus is
very different than that of the halo population. (2) For the Pontus and Gaia-
Sausage/Enceladus populations, their distributions in [$\alpha$/Fe], [Mg/Fe]
and [Al/Fe] are quite similar (as the null hypothesis can only be rejected at
the $>0.5\sigma$ level). (3) The null hypothesis that – the two [Fe/H] samples
for Pontus and Gaia-Sausage/Enceladus are drawn from the same distribution –
can be rejected at the $>2\sigma$ level.

Figure 4: The CMD of the Pontus stars. Panel ‘a’ shows Pontus stars in magenta
and the halo population in gray. We also plot a stellar population model that
is similar to the average metallicity of Pontus. Panel ‘b’ is similar to panel
‘a’, except Pontus stars are now colored by their [Fe/H] values. To make this
plot, we also cross-match our Pontus sample with the LAMOST DR5 dataset (Zhao
et al., 2012; Xiang et al., 2019).

###  4.3 Stellar population

Figure 4a shows the CMD of the Pontus population. To construct this figure, we
first correct Gaia  magnitudes for dust extinction using Schlegel et al.
(1998) maps and assuming the extinction ratios $A_{G}/A_{V}=0.86117$, $A_{\rm
BP}/A_{V}=1.06126$, $A_{\rm RP}/A_{V}=0.64753$ (as listed on the web interface
of the PARSEC isochrones, Bressan et al. 2012). Henceforth, all magnitudes and
colors refer to these extinction-corrected values. Next, we transform these
corrected apparent magnitudes ($G_{\rm BP,0},G_{\rm RP,0},G_{0}$) into
absolute magnitudes ($M_{G_{\rm BP,0}},M_{G_{\rm RP,0}},M_{G_{0}}$) using
heliocentric distances of stars ($D_{\odot}$). For comparison, we also show
the CMD of the halo population.

From Figure 4a, we first notice that the Pontus population contains more of
intrinsically brighter stars than fainter stars, and this is likely due to our
quality cuts that can give rise to such asymmetries (e.g., Koppelman et al.
2019b). The broadness of the Pontus CMD indicates that these stars do not
resemble a single stellar population, but rather favour a wide [Fe/H]
distribution (as we also found in Section 4.2) and possibly also wide age
distribution. The mean of this age distribution is likely $\sim 12{\rm\,Gyr}$
– this point is illustrated by plotting an isochrone model corresponding to
([Fe/H], Age)=($-1.3$ dex, $12{\rm\,Gyr}$) that fits the CMD reasonably well.

The CMD of Pontus shows some interesting features. For instance, Figure 4a
shows the possibility of two horizontal branches and a small population of
blue stragglers. In order to examine whether these features are really
representative of the Pontus population, or they are the Milky Way
interlopers, we inspect Figure 4b that shows the CMD colored by the [Fe/H]
measurements. As can be seen, we do not possess substantial number of [Fe/H]
measurements for the horizontal branch stars, and therefore, we can not
confidently confirm the presence of a double horizontal branch. However, a few
of these stars do possess [Fe/H] measurements that are consistent with the
average [Fe/H] of Pontus. On the other hand, for the blue stragglers, we
possess [Fe/H] measurement for only one star, and it is slightly more metal-
rich than the average [Fe/H] of Pontus.

##  5 Conclusion and Discussion

We have performed the chemo-dynamical analysis of the stellar population of
the recently discovered Pontus structure. For this, we used the Gaia  dataset
to analyse its phase-space distribution, and further used the APOGEE dataset
to examine its metallicity and chemical abundances.

In regard to the dynamical properties: the Pontus stars possess low-energy and
slightly retrograde motion (see Figure 1b) and they move on moderately
eccentric orbits. This implies that the (hypothesized) progenitor galaxy would
have merged on a radial, and slightly retrograde, orbit. This argument is also
supported by the fact that the Pontus stars are stretched in the velocity
space along the radial direction (see Figure 2).

In regard to the metallicity and chemical abundances: the Pontus population is
metal-poor and $\alpha$-enhanced (see Table 1), that is indicative of its
accretion (dwarf galaxy) origin. Based on this, we argue that Pontus likely
merged with the Milky Way $>5-6{\rm\,Gyr}$ ago. This can be argued using the
observations of the Sagittarius merger (Ibata et al., 1994). For Sagittarius,
we know that its stars possess [Mg/Fe]$=-0.03$ (Hayes et al., 2020) and that
this merging occured $\sim 5-6{\rm\,Gyr}$ ago (Ruiz-Lara et al., 2020). Given
that Pontus is more Mg-enhanced than Sagittarius, this tentatively suggests
that the Pontus galaxy must have accreted earlier than Sagittarius and
therefore it did not get sufficient time to get enriched in Fe (via Type Ia
supernovae) and ended up retaining more of Mg (and also other $\alpha$
elements). This early accretion scenario for Pontus is also supported by its
very low-energy, implying that the progenitor galaxy was likely accreted very
early on when the Milky Way was much smaller in size (than today), and
therefore, any merging galaxy would have ended up populating the very inner
(low-energy) regions of the Galaxy. Moreover, given the [Fe/H] of Pontus, it
appears that the progenitor galaxy must have been a massive system (with
$M_{\star}\sim 10^{7}{\rm\,M_{\odot}}$; this value is obtained using Kirby et
al. 2013 relation).

The CMD of the Pontus stars shows some interesting features (Figure 4). These
include a possibly double horizontal branch and a small popuation of blue
stragglers. We note that similar twin horizontal branch feature has also been
observed in the globular cluster NGC 6205/M 13 (Grundahl et al., 1998) that is
associated with the Pontus galaxy (Malhan et al., 2022). Although, we note
that Grundahl et al. (1998) discusses $\sim 0.4$ mag “overluminous” horizontal
branch for only blue stars in M 13, and here we observe a gap of $\sim 1$ mag
between the two branches. In Pontus, if the brighter branch is a real feature,
it may correspond to the post horizontal branch stars (e.g., Sandquist et al.
2010; Davis et al. 2022).

During our analysis, we also made comparisons between the stellar populations
of Pontus and Gaia-Sausage/Enceladus. This was done because these two groups
are located close to each other in the ($J_{\phi},E$) space and we were
interested to examine whether they represent different merging events or two
fragments of the same merger.

It is interesting to note both the differences and similarities between Pontus
and Gaia-Sausage/Enceladus structures. First, Figure 1 shows that – while
these two structures are located close to each other in the orbit-space, their
difference in this dynamical space is still larger compared to the difference
between other structures that are also located close to each other (e.g.,
Sagittarius–Cetus or Cetus–LMS-1/Wukong or Arjuna-Sequoia-I’itoi).
Nonetheless, it is not unexpected for the stellar debris of a single massive
merger to span a large range of distribution in $L_{z}-E$ space (e.g., Helmi
et al. 2018). However, this last point is difficult to confirm because the
true dynamical boundaries for Gaia-Sausage/Enceladus and Pontus are currently
unknown (in terms of observations). Secondly, for Gaia-Sausage/Enceladus, we
deem that our orbit selection criteria (that is based on Malhan et al. 2022)
does not necessarily underestimate the dynamical extent of this structure, as
previous studies have also used similar range of $L_{z}-E$ to select and study
the Gaia-Sausage/Enceladus population (e.g., Koppelman et al. 2019a).
Moreover, we find that these two populations show different behaviour in the
velocity space (Figure 2); although, this is a consequence of our orbit
selection criteria. Furthermore, while these two populations possess similar
[$\alpha$/Fe], [Mg/Fe] and [Al/Fe] distributions, they somewhat differ in
their [Fe/H] distributions (see Table 1 and 2). Also, as shown in Malhan et
al. (2022), the member globular clusters of Pontus and Gaia-Sausage/Enceladus
possess slightly different age-metallicity relations.

For future analysis of Pontus, it will be useful to run detailed N-body
simulations to better understand how this merging event would have taken
place, and to predict the present-day phase-space distribution of its stars in
the Milky Way. Moreover, building chemical evolution model for Pontus will be
crucial to constrain its star formation history and the ages of its stars
(e.g., Vincenzo et al. 2019). These constraints, together, will also be useful
to confirm more confidently whether Pontus is the low-energy (low $J_{R}$)
fragment of Gaia-Sausage/Enceladus, or that they truly are the remnants of
independent merging events. Furthermore, this will also shed light on the
similar or distinct origin of Pontus and Thamnos (Koppelman et al., 2019a),
that is another structure that lies close to Pontus in the ($J_{\phi},E$)
space. These future steps should be easy to explore with the upcoming Gaia
DR3 RVS dataset (that will be $2$ mag deeper than DR2 RVS) and the
spectroscopic datasets of WEAVE (Dalton et al., 2014) and 4MOST (de Jong et
al., 2019) surveys that will enable us to gather high quality phase-space and
chemical abundance information for a larger sample of Pontus stars. Therefore,
future analysis of Pontus, and its comparison with the other mergers, will
allow us to gain a more comprehensive understanding of the formation of the
Milky Way’s vast stellar halo.

## Acknowledgements

We thank our referee for reviewing this manuscript. It is a pleasure to thank
Hans-Walter Rix, Morgan Fouesneau, Jianhui Lian and Anke Arentsen for their
help and suggestions. KM acknowledges support from the Alexander von Humboldt
Foundation at Max-Planck-Institut für Astronomie, Heidelberg and is also
grateful to the IAU’s Gruber Foundation Fellowship Programme for their
finanacial support.

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.

Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the
Participating Institutions, the National Science Foundation, and the U.S.
Department of Energy Office of Science. The SDSS-III web site is
http://www.sdss3.org/.

SDSS-III is managed by the Astrophysical Research Consortium for the
Participating Institutions of the SDSS-III Collaboration including the
University of Arizona, the Brazilian Participation Group, Brookhaven National
Laboratory, Carnegie Mellon University, University of Florida, the French
Participation Group, the German Participation Group, Harvard University, the
Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA
Participation Group, Johns Hopkins University, Lawrence Berkeley National
Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for
Extraterrestrial Physics, New Mexico State University, New York University,
Ohio State University, Pennsylvania State University, University of
Portsmouth, Princeton University, the Spanish Participation Group, University
of Tokyo, University of Utah, Vanderbilt University, University of Virginia,
University of Washington, and Yale University.

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