# An old, metal-rich accreted stellar component in the Milky Way stellar disk

Diane K. Feuillet Lund Observatory, Department of Astronomy and Theoretical
Physics,
Box 43, SE-221 00 Lund, Sweden  Sofia Feltzing Lund Observatory, Department of
Astronomy and Theoretical Physics,
Box 43, SE-221 00 Lund, Sweden  Christian Sahlholdt Lund Observatory,
Department of Astronomy and Theoretical Physics,
Box 43, SE-221 00 Lund, Sweden  Thomas Bensby Lund Observatory, Department of
Astronomy and Theoretical Physics,
Box 43, SE-221 00 Lund, Sweden

(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We study the possibility that the Milky Way’s cool stellar disc includes
mergers with ancient stars. Galaxies are understood to form in a hierarchical
manner, where smaller (proto-)galaxies merge into larger ones. Stars in
galaxies, like the Milky Way, contain in their motions and elemental
abundances tracers of past events and can be used to disentangle merger
remnants from stars that formed in the main galaxy. The merger history of the
Milky Way is generally understood to be particularly easy to study in the
stellar halo. The advent of the ESA astrometric satellite Gaia has enabled the
detection of completely new structures in the halo such as the Gaia-Enceladus-
Sausage. However, simulations also show that mergers may be important for the
build-up of the cool stellar disks. Combining elemental abundances for $\sim
100$ giant branch stars from APOGEE DR17 and astrometric data from Gaia we use
elemental abundance ratios to find an hitherto unknown, old stellar component
in the cool stellar disk in the Milky Way. We further identify a small sample
of RR Lyrae variables with disk kinematics that also show the same chemical
signature as the accreted red giant stars in the disk. These stars allows us
to date the stars in the accreted component. We find that they are exclusively
old.

The Galaxy: disk, abundances, stellar content

##  1 Introduction

Galaxies are understood to form in a hierarchical manner, where smaller
(proto-)galaxies/haloes merge into larger ones (Lacey & Cole, 1993; Naab &
Ostriker, 2017). Each galaxy will have a unique star formation history and
hence also a unique chemical evolution history. Different elements are
released to the inter-stellar medium by stars with different masses and
therefore on different timescales (Arnett, 1996; Nomoto et al., 1997). This
means that the elemental abundances are able to tell us about the past history
of the gas that the stars formed out of. Low-mass stars retain, in their outer
atmospheres, an imprint of the composition of the gas from which they formed
(Lambert, 1989; Freeman & Bland-Hawthorn, 2002). By analysing the spectra of
such stars we can trace the chemical evolution of a stellar population over
time. One important aspect of star formation is that it proceeds faster in
heavier systems and slower in smaller systems (Matteucci & Greggio, 1986).
This in turn means that smaller galaxies that merged with the Milky Way have
different elemental abundance patterns compared to the stars that formed in
situ in the large galaxy. Several elements are affected but it has been shown
that the abundance of aluminum relative to iron is empirically lower in local
dwarf galaxy or accreted stellar populations over a range of iron abundances (
$-2.0<[$Fe/H$]<0.0$, Hawkins et al., 2015; Hasselquist et al., 2019, 2021).
Thus, we infer that stars in galaxies, like the Milky Way, contain in their
motions and elemental abundances tracers of past events and can be used to
disentangle merger remnants from stars that formed in the main galaxy.

The merger history of the Milky Way is generally understood to be more visible
in the stellar halo as the fraction of in situ stars is lower than in the disk
(Helmi, 2020). The advent of the ESA astrometric satellite Gaia (Gaia
Collaboration et al., 2018) has enabled astronomers to find completely new
structures in the halo, such as the Gaia-Enceladus-Sausage that is believed to
be the dissolved stellar population of a massive accretion event (Helmi et
al., 2018; Belokurov et al., 2018; Myeong et al., 2019; Feuillet et al.,
2020).

Table 1: APOGEE fields removed from consideration

`47TUC` | `ANDR*` | `BOOTES1` | `Berkeley*` | `CARINA` | `COL261` | `CygnusX*` | `DRACO`
---|---|---|---|---|---|---|---
`FL_2020` | `FORNAX` | `GD1-*` | `IC342_NGA` | `IC348*` | `INTCL_N*` | `JHelum*` | `LAMBDAORI-*`
`LMC*` | `M10` | `M107` | `M12-N` | `M12-S` | `M13` | `M15` | `M2`
`M22` | `M3` | `M3-RV` | `M33` | `M35N2158` | `M35N2158_btx` | `M4` | `M5`
`M53` | `M54SGRC*` | `M55` | `M5PAL5` | `M67*` | `M68` | `M71*` | `M79`
`M92` | `N1333*` | `N1851` | `N188*` | `N2204` | `N2243*` | `N2264` | `N2298`
`N2420` | `N2808` | `N288` | `N3201*` | `N362` | `N4147` | `N5466` | `N5634SGR2`
`N5634SGR2-RV_btx` | `N6229` | `N6388` | `N6397` | `N6441` | `N6752` | `N6791` | `N6819*`
`N752_btx` | `N7789` | `NGC188_btx` | `NGC2420_btx` | `NGC2632_btx` | `NGC6791*` | `NGC7789*` | `ORION*`
`ORPHAN-*` | `Omegacen*` | `PAL*` | `PLEIADES*` | `SCULPTOR` | `SEXTANS` | `SGR*` | `SMC*`
`Sgr*` | `TAUL*` | `TRIAND-*` | `TRUMP20` | `Tombaugh2` | `URMINOR` | `moving_groups` | `ruprecht147`
`sgr_tidal*` |  |  |  |  |  |  |

  * •

Note. — Strings corresponding to the APOGEE DR17 parameter FIELD. The asterisk
(*) is used as a wild card character, indicating multiple possible names.

Table 2: APOGEE programs removed from consideration

`Drout_18b` | `Fernandez_20a` | `Geisler_18a` | `beaton_18a` | `cluster_gc` | `cluster_gc1` | `cluster_gc2` | `cluster_oc`
---|---|---|---|---|---|---|---
`clusters_gc2` | `clusters_gc3` | `geisler_18a` | `geisler_19a` | `geisler_19b` | `geisler_20a` | `halo2_stream` | `halo_dsph`
`halo_stream` | `kollmeier_19b` | `magclouds` | `monachesi_19b` | `sgr` | `sgr_tidal` | `stream_halo` | `stutz_18a`
`stutz_18b` | `stutz_19a` |  |  |  |  |  |

  * •

Note. — Strings corresponding to the APOGEE DR17 parameter PROGRAMNAME. We
list only unique programs but some stars belong to multiple programs.

However, simulations show that mergers may be important also for the build-up
of the cool stellar disks (Read et al., 2008; Gómez et al., 2017). So far, the
empirical evidence for significant merger remnants present in the Milky Way
stellar disk is inconclusive (Ruchti et al., 2014, 2015). With the arrival of
the Gaia parallaxes and proper motions for over a billion stars (Gaia
Collaboration et al., 2018) in combination with radial velocity data for
bright stars from Gaia and for fainter stars from ground-based stellar
spectroscopic surveys, it is now feasible to study how stars move in the Milky
Way. Such studies have successfully found accreted populations in the stellar
halo, such as Gaia-Enceladus-Sausage and many smaller systems, as well as new
streams in the disk (Necib et al., 2020; Ratzenböck et al., 2020). These
potential mergers present in the disk are either on non-circular orbits, very
young, or present only in the outer parts of the disk. To find mature merger
remnants in the stellar disk with disk-like, circular orbits is a more subtle
task where we need additional information in the form of elemental abundances
(Ruchti et al., 2015; Necib et al., 2020). Such data is provided by large
ground-based, high-resolution, spectroscopic surveys, such as APOGEE (Majewski
et al., 2017), the Gaia-ESO Survey (Gilmore et al., 2012; Randich et al.,
2013), and GALAH (De Silva et al., 2015).

In this paper we make use of the astrometric data from the Gaia satellite in
combination with data from APOGEE and the literature to hunt for accreted
populations in the stellar disk. We supplement the APOGEE observations with a
small sample of disk RR Lyrae stars, which are known to be old, that have low
measured aluminum abundances and so may be associated with an accreted
population, giving an estimate of age (Liu et al., 2013).

##  2 Data and methods

###  2.1 Stellar data from APOGEE DR17

####  2.1.1 Spectroscopic data

We make use of high-quality elemental abundances for 136701 red giant star
from APOGEE Data Release 17 (APOGEE DR17, Majewski et al., 2016; Abdurro’uf et
al., 2022) and Gaia Early Data Release 3 (Gaia EDR3, Gaia Collaboration et
al., 2016, 2021) to hunt for merger remnants in the Milky Way stellar disk.
The sample was selected to contain only stars with $\sigma_{\pi}/\pi<0.2$. For
quality control of the stellar parameters and elemental abundances, the
following selection criteria for the spectroscopic data were applied:

  * •

SNREV > 80

  * •

AL_FE_FLAG = 0

  * •

TEFF < 6000 K

  * •

TEFF > 4000 K

  * •

LOGG < 2.8

  * •

Remove any VERY_BRIGHT_NEIGHBOR and PERSIST_HIGH bit set in STARFLAG

  * •

Remove any STAR_BAD, CHI2_BAD, M_H_BAD, and CHI2_WARN bit set in ASPCAPFLAG

  * •

Remove duplicate observations of a single target that have bit 4 of EXTRATARG
set

The upper effective temperature limit was imposed to remove stars at the hot
edge of the main stellar atmospheric model grids used in the APOGEE analysis.
For some of these stars, the effective temperatures derived have
preferentially discrete values. The lower effective temperature limit was
imposed to remove cool red giant stars with suspected problems with the
derivation of the aluminium and magnesium elemental abundances. The sample was
further limited to giant stars in order to avoid any possible effects of an
over-density of stars seen in the [Al/Fe] of metal-rich dwarfs stars. For more
details on the APOGEE DR17 data quality see the SDSS DR17 documentation
available on the web111https://www.sdss.org/dr17/ and a detailed discussion of
DR16 in Jönsson et al. (2020).

The dataset has been cleared of all fields and programs targeting known
stellar clusters, accreted stellar populations, and stars outside the Milky
Way (Santana et al., 2021; Beaton et al., 2021). The full lists of the removed
fields and program names are given in Tables 1 and 2, respectively.

####  2.1.2 Calculation of kinematic data

Astrometric measurements from Gaia EDR3 are available for the APOGEE sample
and the RR Lyrae stars (see Sect. 2.2). We use the more precise APOGEE
spectroscopic radial velocity measurements when calculating kinematics for the
APOGEE sample. Galactic positions and velocities are calculated for all stars
using Astropy (Astropy Collaboration et al., 2013a, 2018a) and galpy (Bovy,
2015). We use the actionAngleStaeckel approximation (Bovy & Rix, 2013; Binney,
2012) with the MWPotential14 Milky Way potential (Bovy & Rix, 2013), delta of
0.4, and default values for other parameters. The mean uncertainties for our
sample are 0.030 km s-1 in radial velocity, 0.020 mas year-1 in RA proper
motion, and 0.018 mas year-1 in Dec proper motion. We expect the resulting
uncertainties on the calculated kinematics to be small, specifically the
uncertainty in rotational velocity ($V$), which we use as a selection
parameter, is $\sim 10$ km s-1. The photogeometric distance from Bailer-Jones
et al. (2021) is used for all stars.

####  2.1.3 Identification of the population

Figure 1: a) [Al/Fe] as a function of [Fe/H]. This figure illustrates the
defining cut in [Al/Fe]. Symbols as indicated in the inset. A discussion of
the different cuts in [Al/Fe] used for the APOGEE DR17 and RR Lyrae samples
can be found in Sect. 2.2.1. b) [Mg/Fe] as a function of [Fe/H]. Symbols as
indicated in the inset. c) [Mg/Mn] as a function of [Al/Fe]. Symbols as
indicated in the inset. Note the different scales on each axis.

Figure 2: a) Rotational velocity ($V$) as a function of [Fe/H]. Symbols as
indicated in the inset. b) Positions of the stars in the Milky Way, vertical
position ($z$) as a function of distance from the Galactic center ($R$).
Symbols as indicated in the inset. Figure 3: Observed spectra for two pairs of
stars illustrating the reality that the aluminum lines are weaker in the stars
with low-[Al/Fe]. In each panel we show two stars with similar stellar
parameters. The red spectra have [Al/Fe] values typical of the stellar disk,
whilst the black spectra have low [Al/Fe] values. The blue line shows the
spectrum of the low-[Al/Fe] star divided by that of the [Al/Fe]-normal star,
emphasizing the difference in the strength of the aluminum lines, indicated by
the vertical dotted lines, that are otherwise remarkably similar.

Through the following investigation, we have identified “disk” stars to have
[Fe/H] $>-0.8$ and $V>110$ km s-1. We first looked for stars with low-[Al/Fe]
and disk-like metallicities ([Fe/H] $>-0.8$). Fig. 1a shows that such stars
exist and are identified as black points. We define a low-[Al/Fe] star to have
$\rm[Al/Fe]<-0.2$. This cut is somewhat arbitrary but is informed by the locus
of accreted stars at lower metallicities found in previous studies (Hawkins et
al., 2015; Das et al., 2020; Feuillet et al., 2021).

The properties of these stars are further explored in Fig. 1b,c and Fig. 2. In
these figures, the cleaned APOGEE DR17 data is shown as the orange-scale
density and yellow points; low-[Al/Fe], low metallicity stars ([Al/Fe]
$<-0.2$, [Fe/H] $<-0.8$) are shown as gray triangles; low-[Al/Fe] disk-like
stars are shown as black points; low-[Al/Fe] stars with disk-like metallicity
but halo-like velocity are shown as pink points; and the RR Lyrae sample is
shown as blue points.

We see that stars identified as “disk-stars” using a cut in the $V$ \-
metallicity plane ( $V>110$ km s-1, Fig. 2a) follow the typical thin disk
trend for [Mg/Fe] (Fig. 1b) and that they are essentially confined to the
plane of the Milky Way (Fig. 2b). These stars are also separate from the halo-
like accreted stars in [Mg/Mn]-[Al/Fe] space, Fig. 1c. Known accreted halo
stellar populations, such as Gaia-Sausage-Enceladus, have been found to occupy
a distinct region of this elemental abundance space (e.g. Das et al., 2020).
The dotted lines in Fig. 1c show the approximate separation of accreted, thick
disk, and thin disk stars in this space. We note that previous studies have
included only the halo-like stars with [Mg/Mn] $>0.1$ as the accreted region.
These chemical, spatial, and kinematics properties give us confidence that we
have identified a sample of stars that are kinematically integrated with the
disk, have anomalously low aluminum abundances, but are chemically distinct
from previously identified accreted halo populations.

####  2.1.4 Checking that the low-[Al/Fe] abundances are real

To check if the low-[Al/Fe] measurements for stars with disk-like
metallicities are robust and not the product of problems in the elemental
abundance determination we performed an ocular inspection of the stellar
spectra of all the low-[Al/Fe] stars with [Fe/H] $>-0.8$. We compared each
low-[Al/Fe] spectrum with the spectrum of another star with the same stellar
atmospheric parameters but with ordinary [Al/Fe] values. Fig. 3 shows two
examples of these comparisons. They show that indeed the aluminum lines in the
low-[Al/Fe] stars, marked by the vertical dotted lines, are shallower than in
the stars with ordinary [Al/Fe] values. This comparison also shows that our
finding is not the result of NLTE effects that may not have been accounted for
by the APOGEE DR17 analysis. The direct comparison of stars with the same
stellar parameters shows the difference to be real.

Figure 4: The low-[Al/Fe] APOGEE stars in the $\log g-T_{\rm eff}$ plane.
Stars with disk-like kinematic properties are identified by triangles and
stars with halo-like properties with points. Those stars shown with [Fe/H]
$>-0.8$ have passed spectral inspection. The distribution of the full APOGEE
sample is shown in gray for comparison.

In Fig. 4 we show the APOGEE stars identified as low-[Al/Fe] stars ([Al/Fe]
$<-0.2$) in the $\log g-T_{\rm eff}$ plane with the full APOGEE sample in gray
for comparison. It is clear that the more metal-rich disk-like stars have
cooler temperatures whilst the halo like stars are warmer, indicating a color-
difference such that the halo is blue and the disk red. The color-coding
indicates the signal-to-noise ratio (SNR) in the APOGEE spectra used for the
abundance analysis. As can be seen, the spectra have good SNR.

We have also inspected the derived abundances as a function of $T_{\rm eff}$,
$\log g$, SNR, and microturbulence and find no obvious trends for any of the
APOGEE subsamples used.

To summarize, the spectra for the low-[Al/Fe] stars are of good quality and we
have no reason to believe that the results are the result of poor quality
spectra. Combined with the visual inspection of all the metal-rich low-[Al/Fe]
spectra, we have weeded out all spectra that were not reliable and what
remains is a clean sample.

###  2.2 Sample of RR Lyrae variables

Table 3: Summary of available data for the nine known RR Lyrae variables with measured aluminum abundances. Elemental abundances are from Liu et al. (2013) (Liu) and Marsakov et al. (2019) (Marsakov). Masses are taken from (Marsakov et al., 2019). We indicate which stars have Gaia radial velocities available. For those without Gaia radial velocities we use values from Layden (1994). The last column indicates if we identify the star as an accreted star based on elemental abundance criteria.  Star | [Fe/H] | [Mg/Fe] | [$\alpha$/Fe] | [Al/Fe] | [Mn/Fe] | Mass [M☉] |  Gaia RV | Layden RV | Accr.
---|---|---|---|---|---|---|---|---|---
| Liu | Marsakov | Liu | Marsakov | Liu | Liu | Marsakov |  |  |
AA Aql | –0.32 | –0.32 |  –0.21 |  –0.18 | –0.18 | –0.31 | 0.56 |  | ✓ | ✓
CN Lyr | –0.04 | –0.04 | –0.05 | –0.01 | –0.14 | –0.20 | 0.54 | ✓ |  | ✓
DM Cyg |  –0.03 |  –0.03 | –0.01 | –0.06 | –0.23 | –0.13 | 0.54 | ✓ |  | ✓
DX Del | –0.14 | –0.31 |  –0.08 | –0.02 | –0.19 | –0.18 | 0.54 | ✓ |  | ✓
KX Lyr | –0.27 | –0.42 |  –0.12 |  –0.09 | –0.04 | –0.17 | 0.58 | ✓ |  |
RS Boo | –0.12 | –0.21 |  –0.07 |  –0.03 | –0.16 | –0.16 | 0.53 | ✓ |  | ✓
SW And | –0.07 | –0.22 |  –0.07 |  –0.00 | –0.11 | –0.15 | 0.53 |  | ✓ | (✓)
TV Lib | –0.43 | –0.43 |  –0.30 |  –0.29 |  –0.23 | –0.23 | 0.54 |  | ✓ |
V445 Oph |  –0.14 |  –0.11 |  –0.04 | –0.05 | –0.20 | –0.09 | 0.52 | ✓ |  | ✓

####  2.2.1 Spectroscopic data and population identification

RR Lyrae variable stars are known to be old and are often used to characterize
accreted populations in the Milky Way (Dambis et al., 2013). Liu et al. (2013)
identify a sample of 23 RR Lyrae stars belonging to the disk of the Milky Way.
To complement the sample of low-[Al/Fe] APOGEE disk stars, we make use of this
RR Lyrae sample. We select the nine stars with aluminum measurements to use in
our analysis. Table 3 lists the sub-sample and compiled parameters used in
this work. The [Fe/H], [Mg/Fe], [Al/Fe], and [Mn/Fe] abundance ratios are
derived by Liu et al. (2013). For comparison, we include [Fe/H] and
[$\alpha$/Fe] values compiled in Marsakov et al. (2019). Four of the stars
have identical [Fe/H] in the two studies. In those cases, the magnesium and
$\alpha$ abundances (calculated as the average of magnesium, calcium, silicon,
and titanium) are also almost identical. For four stars there is a large
difference in the [Fe/H] values in the two studies. In this work we use
exclusively the data from Liu et al. (2013), which presents data from an
homogeneous analysis.

To investigate if any of the selected RR Lyrae variables are accreted disk
stars we make use of two elemental abundance diagnostics: 1) A cut in [Al/Fe]
at $-0.14$ dex, Fig. 1a, and 2) the diagnostic plot in the [Mg/Mn] - [Al/Fe]
plane, Fig. 1c, proposed by Hawkins et al. (2015). The exact cut in [Al/Fe]
must remain arbitrary, in particular since we have no way of knowing if the
APOGEE DR17 and the data from Liu et al. (2013) are on the same absolute
scale. We have chosen to set the cut at $-0.14$ dex for the RR Lyrae
variables. Accreted stellar populations have been empirically found to occupy
a different region of the [Mg/Mn] - [Al/Fe] abundance plane than Milky Way
stellar populations (Das et al., 2020). There is some theoretical motivation
for this (see Hawkins et al., 2015) and initial chemical evolution models
confirm a different evolutionary sequence through this space for a population
similar to the Gaia-Sausage-Enceladus (Horta et al., 2021).

It should be noted that some elemental abundances can change in RR Lyrae
variables as a function of the pulsation phase (For et al., 2011; Liu et al.,
2013). Examining Table 6 in Liu et al. (2013) we see that some abundances, for
example manganese and magnesium, remain stable throughout the phases whilst
others may have some changes, notably aluminum. In the two stars with [Al/Fe]
measurements at different phases, the variation in [Al/Fe] is as large as
$0.15$ dex. Our understanding of this effect is that the change in abundance,
if anything, makes it harder to identify the accreted stars (i.e. they may
have higher [Al/Fe] in one phase). Thus our identification of low-[Al/Fe]
variable stars should be conservative.

A few of the RR Lyrae in Table 3 are not included in our sample of accreted
stars. Of the nine stars one, TV Lib, shows thick disk elemental abundances
with elevated [Mg/Fe] and [Al/Fe]. We do not associate KX Lyr with the
accreted sample as it has approximately solar [Al/Fe]. The [Al/Fe] value for
SW And falls just short of our (arbitrary) cut at $-0.14$ dex, we therefore
include it in our accreted sample, but use caution when drawing conclusions
that may be influenced by its presence. AA Aql, has low [Al/Fe] but higher
[Mg/Fe]. When examined in the [Mg/Mn]-[Al/Fe] plane the star clearly falls in
the accreted halo region (see Fig. 1c). This star also has a rotational
velocity ($V$) more associated with thick disk/halo kinematics than with thin
disk kinematics (Table 3). The remaining five stars have a high [Fe/H],
centered near solar values and all have low-[Al/Fe] and fall in the disk
region in Fig. 2a. Our final classification of accreted and non-accreted for
the nine RR Lyrae stars can be found in Table 3. In total we are able to
identify six stars with low-[Al/Fe], suggesting they could be accreted, with a
seventh very close to the cut in [Al/Fe]. Six of the seven have kinematics
consistent with the thin disk.

####  2.2.2 Estimating masses of RR Lyrae variable stars

RR Lyrae variables are stars that have evolved from the main sequence, along
the giant branch and have descended onto the horizontal branch and are
currently crossing the instability strip (a good explanation of this from the
point of view of population synthesis is given in Savino et al., 2020). If we
know the mass of an RR Lyrae variable and how much mass it loses along the red
giant branch then we can infer its mass on the main-sequence. This mass
relates directly to the age of the stellar population of which that the RR
Lyrae variable is a member.

Mass-loss along the red giant branch is difficult to measure, but recent
studies enabled by a large data-set for globular clusters and dwarf spheroidal
galaxies have been able to show that the mass-loss along the red giant branch
measured empirically is dramatically different from many of the older
theoretical estimates (Tailo et al., 2020; Savino et al., 2020).

Current mass estimates are available for all stars from Marsakov et al.
(2019). We note that the [Fe/H] values for two of the accreted stars are not
the same in the study that derived the elemental abundances and the
compilation used to derive the stellar masses (compare Table 3). However, the
differences are not large enough to change the masses of these stars
drastically and certainly not large enough to make the stars much heavier
(Marsakov et al., 2019).

The current masses for the RR Lyrae variables in our sample are all around 0.5
to 0.6 M⊙ (Table 3). Using the recent mass-loss laws by Tailo et al. (2020) we
estimate the mass-loss for our low-[Al/Fe] RR Lyrae variables and find that
their turn-off masses are not in excess of 0.85 M⊙. Such masses indicate an
old stellar population, approximately 10-12 Gyr.

###  2.3 Kinematic data

Figure 5: a) Orbits for the full sample of selected APOGEE DR17 red giant
branch stars with [Al/Fe] < -0.2, [Fe/H] < -0.8 (gray lines), [Al/Fe] < -0.2,
V < 110 (magenta lines) and [Al/Fe] < -0.2, V > 110 (black lines), and RR
Lyrae variables (blue lines). b) Cumulative histogram of orbital
eccentricities. c) Cumulative histogram of orbit z max values.

All nine RR Lyrae stars have astrometric measurements from Gaia EDR3 are
available. Six of the RR Lyrae stars have Gaia RVS measurements. We prefer to
use Gaia RV measurements when possible to keep the dataset homogeneous and
because multiple measurements, such as done by Gaia, reduces the uncertainty
in the mean RV of these pulsating stars. The RV uncertainty is 4-5 km s-1. For
the remaining three RR Lyrae, the radial velocities are taken from new data
table of Layden (1994), which uses at least two measurements. The RV
uncertainty is 15-20 km s-1. The distance for all RR Lyrae is calculated from
the Gaia parallax measurement using the astropy Distance function.

Fig. 2b shows the Galactic positions of the low-[Al/Fe] stars in comparison to
the full sample. We see that the stars with disk-like kinematics (Fig. 2a) are
spread across the whole disk, but are mainly confined to the plane. Of the
APOGEE stars with disk-like kinematics, 12 stars out of 92 low-[Al/Fe] have
current vertical positions larger than 1 kpc from the Galactic plane. For
low-[Al/Fe] stars with halo kinematics these numbers are 1873 stars out of
2077 stars.

The orbits for the low-[Al/Fe] stars were integrated using galpy in the
MWPotential14 Milky Way potential (Bovy & Rix, 2013) for 500 Myr. The orbital
trajectories of the low-[Al/Fe] stars are shown in Fig. 5a with disk stars
(blue) and halo stars (black) compared to the RR Lyrae stars (red). Fig. 5
also shows cumulative histograms of the orbital eccentricity (b) and z max (c)
of the APOGEE sub-samples as well as the RR Lyrae. The orbits of the
low-[Al/Fe] stars identified as belonging to the cool disk are confined to the
Galactic plane, further strengthening their association with the disk. These
stars are seen to be on mainly circular orbits with no orbits reaching inside
about $R_{\mbox{Gal}}=4$ kpc.

##  3 Results and discussion

###  3.1 Accreted disk stars identified in APOGEE DR17

Fig. 1 shows three plots of elemental abundance data for our sample as well as
the RR Lyrae stars with likely accreted origins. Panel a in Fig. 1 shows
[Al/Fe] as a function of [Fe/H]. This plot is used to define the low-[Al/Fe]
stars, which we propose may have accreted origins. Empirically, several dwarf
galaxies and known accreted stellar populations in the Milky Way have low
[Al/Fe] abundances. This is nicely demonstrated in Hasselquist et al. (2021,
see their Fig. 5), which shows APOGEE elemental abundances of the Large
Magellanic Cloud, Small Magellanic Cloud, Gaia-Sausage-Enceladus accreted
population, Sagittarius dwarf galaxy, and Fornax dwarf galaxy in comparison to
Milky Way disk stars with a similar range of effective temperature and surface
gravity. These five ex situ stellar populations all have [Al/Fe] abundance
ratios well below the Milky Way at a given [Fe/H]. Of particular relevance to
our study is the Sagittarius dwarf galaxy, which maintains a low [Al/Fe],
$\sim-0.4$ dex, even at metallicities approaching solar values. This supports
the possibility of low-[Al/Fe] stars forming at high [Fe/H] in a dwarf galaxy
environment.

Beyond using [Al/Fe] alone as an indicator of ex situ origins, the [Mg/Mn] vs
[Al/Fe] space has been identified as holding high diagnostic power in this
effort (Das et al., 2020; Hawkins et al., 2015; Horta et al., 2021). Although
the cause of the low [Al/Fe] abundance ratios found in ex situ populations is
not well understood, the theoretical motivation for using the [Mg/Mn] vs
[Al/Fe] elemental abundance space as detailed by Hawkins et al. (2015) and Das
et al. (2020) can inform our discussion. We therefore seek some understanding
in the known formation channels of aluminum, magnesium, and manganese (see
Kobayashi et al. (2020) for a detailed modeling of element production in a
Milky Way environment). Magnesium is produced primarily in type II supernovae
(SNII) and in a small amount by Asymptotic Giant Branch (AGB) stars. Mangenese
is primarily produced in type Ia supernovae (SNIa), with small contributions
from SNII and AGB stars. Aluminum is produced primarily in SNII with small
contributions from AGB stars. In contrast to the low-[Al/Fe] disk stars
presented in this work, the five dwarf galaxy or accreted populations
discussed in Hasselquist et al. (2021) maintain [Mg/Fe] abundance ratios below
that of the Milky Way disk at any given [Fe/H]. McWilliam et al. (2013)
conclude that the low [$\alpha$/Fe] abundance ratios in the Sagittarius dwarf
galaxies are an indication of a lack of high-mass stars or a top-light initial
mass function. They argue that the low [Al/Fe] supports this finding as
aluminum is formed during hydrostatic carbon and neon burning in massive stars
Woosley & Weaver (1995).

Panel b of Fig. 1 shows [Mg/Fe] as a function of [Fe/H]. The low-[Al/Fe] stars
with [Fe/H] less than about -0.6 dex essentially all fall on the lower [Mg/Fe]
sequence, which has been associated with accreted populations generally
(Nissen & Schuster, 2010; Hayes et al., 2018) and specifically the Gaia-
Enceladus-Sausage and Sequoia merger events (Helmi, 2020; Matsuno et al.,
2020; Feuillet et al., 2021). At higher [Fe/H] the low-[Al/Fe] stars either
fall on the thin disk sequence or below the main sample. Only two APOGEE stars
and one RR Lyrae fall on what is commonly referred to as the thick disk trend
([Mg/Fe] > 0.2 dex). Hasselquist et al. (2021) find that the Sagittarius
population reaches similarly high [Fe/H] and low [Al/Fe], but does not have
[Mg/Fe] consistent with the Milky Way thin disk.

Fig. 2 shows [Fe/H] as a function of the tangential velocity ($V$) for all
low-[Al/Fe] stars. The low-[Al/Fe] stars fall into two groups; one with
typical disk-like kinematics and one with halo-like kinematics. The latter are
centered around $V=0$ km s-1, in fact they are somewhat retrograde, consistent
with findings of the kinematics of the major remnants in the Milky Way halo
(Helmi, 2020; Feuillet et al., 2020). We have calculated the orbits of the
low-[Al/Fe] stars and find that the stars with [Fe/H] greater than about
$-0.8$ dex all have orbits that are kinematically cool, i.e. confined to the
Galactic plane, and with mainly circular orbits, see Fig. 5.

The fraction of accreted stars sitting in the disk is a very difficult
parameter to estimate because of selection effects in the APOGEE survey and
our selection of this particular dataset. In addition, although we have
identified a population of stars that are likely accreted based on their
low-[Al/Fe], there are an unknown number of merger events contributing to this
population. Given the small number of stars we have robustly identified as
low-[Al/Fe] and disk-like out of the full APOGEE sample, the fraction of
accreted stars in the Milky Way disk that can be identified through [Al/Fe] is
likely very small.

To roughly estimate this fraction, we consider only stars with $6<R<11$ kpc
and $|z|<0.5$ kpc in order to reduce possible spatial biases from the APOGEE
lines of sight. Within this spatial region, we limit our estimate to stars
with [Fe/H] $>-0.8$ and $V>110$ km s-1, as was required of the low-[Al/Fe]
disk stars. The fraction of these stars that have [Al/Fe] $<-0.2$ is $0.073$%.
We tested how this fraction changes as a function of galactocentric radius and
[Fe/H] as well as effects of removing any $z$ constraint. The resulting
low-[Al/Fe] fraction varies between $0.11$% and $0.046$%, with no continuous
trends. We stress that these fractions are calculated with very small numbers
of low-[Al/Fe] stars and so are very uncertain. The conclude that the stars we
identify as accreted disk stars represent approximately $0.07$% of the APOGEE
disk sample.

###  3.2 Age dating the accreted component and the time of the merging

Our main sample consists of red giant branch stars. Such stars are difficult
to determine an age for without access to asteroseismology (Montalbán et al.,
2021). Another possibility to obtain an age for the newly identified
population would be to find stars associated with this population but
currently in an evolutionary stage that allow for them to be dated (Soderblom,
2010). Instead of directly calculating ages for the red giant stars in our
main sample, we have found a sample of intrinsically old stars that are
kinematically and chemically associated with the low-[Al/Fe] disk giants.

Recent studies have found RR Lyrae variables with kinematics typical of the
cool thin disk and metallicities ranging from a tenth of that of the sun to
solar values (Marsakov et al., 2019; Prudil et al., 2020; Iorio & Belokurov,
2021). In Sect. 2.2.1 we describe the construction of a small sample of RR
Lyrae variables that are associated with the kinematic thin disk and have
elemental abundances available in the literature. Some of these stars show the
low-[Al/Fe] characteristic for our disk-like accreted sample.

In Sect. 2.2.2 we derive the masses at turn-off for the RR Lyrae variables. We
find that they all have masses consistent with an old stellar population with
an age around 10 Gyr. With an extreme mass-loss of 0.5 M⊙ the stars would be
somewhat younger, but still several billion years old (Bono et al., 1997). We
should expect fewer metal-rich RR Lyrae variables than metal-poor as the mass-
range for when a star is in the instability strip is dependent on metallicity,
being very small for the metal-rich stars and requiring significant mass-loss,
perhaps as extreme as 0.5 M⊙ to become a variable star (see Taam et al.,
1976).

By using kinematic data and elemental abundances we have been able to
associate stars of known ages (i.e. our RR Lyrae sample) with our newly
identified accreted stellar population (i.e. our disk-like, low-[Al/Fe]
sample). These RR Lyrae stars are all old. This implies that the stellar
population that was accreted formed its stars before that time.

Another way to age-date a stellar population in the stellar disk is to study
the velocity dispersions (Nordström et al., 2004; Sharma et al., 2021). The
idea is that stars that formed in the stellar disk and via encounters with
other objects, their velocities change over time such that older stars have
more “heated” orbits. Using the largest kinematic-only (i.e. no elemental
abundances) sample of RR Lyrae variables it has been shown that their velocity
dispersions are consistent with models indicating that the sample has an age
of about 2 billion years (Iorio & Belokurov, 2021). This finding appears
incompatible with our new accreted disk stellar population. However, what is
measured based on the kinematics is not the age of the stars but the age of
the population since it became part of a cool stellar disk. Thus, we argue
that the two findings are compatible in a scenario where a stellar population
consisting of stars formed up to 10 billion years ago merged with the Milky
Way stellar disk about 2 billion years ago. The population was dragged into
the plane, onto very circular orbits and has since been heated.

Is such a scenario plausible? Simulations show that it is possible to accrete
stellar systems into the Milky Way and, given the right inclination of the
merger, via plane-dragging deposit the stars into the stellar disk on disk-
like, essentially circular orbits (Read et al., 2008; Gómez et al., 2017).
However, it is difficult to make a quantitative comparison between our data
and such models due to the small observational sample and the resolution of
the models.

Donlon et al. (2020) present evidence from stellar overdensity shell
structures of a dwarf galaxy passage through the Milky Way center 2.7 billion
years ago, suggesting the progenitor galaxy could have been the Gaia-Sausage-
Enceladus or another unknown galaxy. Such timing is compatible with the
"heating age" of the RR Lyrae.

It is difficult to assess the size of the galaxy that merged with ours and
later deposited its stars into the local stellar disk. Mass-metallicity
relations that evolve with redshift would, because of the high metallicity of
the stars, indicate a merger as massive as M${}_{\star}=10^{11}$ to $10^{12}$
M⊙ (Ma et al., 2016). This assumes that the merging galaxy retained all of its
stars at the time of the merger. Assuming that the merger took place about 2
billion years ago and the stars are up to 10 billion years old, this leaves
about 8 billion years of evolution from formation to merger. This means that
the merging galaxy continued to evolve in the Local Group and thanks to its
proximity to the Milky Way it may have been stripped of some of its stars and
only a smaller portion of it merged with the Milky Way disk.

##  4 Conclusions and outlook

Using elemental abundances from APOGEE DR17 (Majewski et al., 2016; Abdurro’uf
et al., 2022) we have identified sample of stars that have chemical signatures
of an accreted origin and also have kinematics similar to the Milky Way
stellar disk. We have further identified a small sample of RR Lyrae variables
that share the properties with this possibly-accreted component. The RR Lyrae
variables offer the possibility to obtain an independent age estimate of this
new stellar component. We find that most likely we are looking at an ancient
stellar population that formed outside the Milky Way and was later accreted
and dragged into the stellar disk. Only by combining elemental abundances,
kinematics and different age dating techniques are we able to confirm its
existence.

Looking forward there are both on-going and up-coming large massive
spectroscopic surveys that will enable us to identify larger samples of stars
with chemical signatures of an accreted origin. In particular, the 4MOST
survey will target several million disk stars, including a specific survey to
target RR Lyrae stars. At the same time, theoretical models of aluminum
enrichment are needed to improve our understanding of how a galactic system
might maintain low [Al/Fe] at high [Fe/H].

## Acknowledgements

We thank the anonymous referee for their helpful comments and suggestions. We
thank Eric Andersson, Oscar Agertz, and Justin Read for their contributions to
this work and discussions about galaxy mergers. Henrik Jönsson is thanked for
his guidance on inspection of the APOGEE spectra and unknown lines.

DF, SF, and CLS were partly supported by the grant 2016-03412 from the Swedish
Research Council. TB was supported by grant 2018-04857 from the Swedish
Research Council.

This research has made use of NASA’s Astrophysics Data System, the SIMBAD
database and the VizieR catalogue access tool, operated at CDS, Strasbourg,
France, matplotlib, a Python library for publication quality graphics (Hunter,
2007), TOPCAT, an interactive graphical viewer and editor for tabular data
(Taylor, 2005), Astropy, a community-developed core Python package for
Astronomy (Astropy Collaboration et al., 2018b, 2013b), pandas (McKinney,
2010, 2011), and NumPy (Harris et al., 2020). This work has made use of the
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. The acknowledgements were
compiled using the Astronomy Acknowledgement Generator.

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 including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, Center for Astrophysics | Harvard & Smithsonian, the Chilean Participation Group, the French Participation Group, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.

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