An enquiry on the origins of N-rich stars in the inner Galaxy basedon APOGEE chemical compositions
Shobhit Kisku, Ricardo P. Schiavon, Danny Horta, Andrew Mason, J. Ted Mackereth, Sten Hasselquist, D. A. Garcia-Hernandez, Dmitry Bizyaev, Joel R. Brownstein, Richard R. Lane, Dante Minniti, Kaike Pan, Alexandre Roman-Lopes
MMNRAS , 1–11 (2021) Preprint 16 February 2021 Compiled using MNRAS L A TEX style file v3.0
An enquiry on the origins of N-rich stars in the inner Galaxy basedon APOGEE chemical compositions
Shobhit Kisku ★ , Ricardo P. Schiavon , Danny Horta , Andrew Mason ,J. Ted Mackereth , , Sten Hasselquist , , D. A. García-Hernández , ,Dmitry Bizyaev , , Joel R. Brownstein , Richard R. Lane , Dante Minniti ,Kaike Pan , Alexandre Roman-Lopes Astrophysics Research Institute, Liverpool John Moores University, 146 Brownlow Hill, Liverpool L3 5RF, UK Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 St. George Street, Toronto, ON M5S 3H8, Canada Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4, Canada Department of Physics and Astronomy, University of Utah, 115 S. 1400 E., Salt Lake City, UT 84112, USA NSF Astronomy and Astrophysics Postdoctoral Fellow Instituto de Astrofísica de Canarias (IAC), E-38205 La Laguna, Tenerife, Spain Universidad de La Laguna (ULL), Departamento de Astrofísica, E-38206 La Laguna, Tenerife, Spain Apache Point Observatory and New Mexico State University, P.O. Box 59, Sunspot, NM, 88349-0059, USA Sternberg Astronomical Institute, Moscow State University, Moscow Instituto de Astronomía y Ciencias Planetarias de Atacama, Universidad de Atacama, Copayapu 485, Copiapó, Chile Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuna Mackenna 4860, 782-0436 Macul, Santiago, Chile Departamento de Física, Facultad de Ciencias, Universidad de La Serena, Cisternas 1200, La Serena, Chile
Accepted XXX. Received YYY; in original form ZZZ
ABSTRACT
Recent evidence based on APOGEE data for stars within a few kpc of the Galactic centresuggests that dissolved globular clusters (GCs) contribute significantly to the stellar massbudget of the inner halo. In this paper we enquire into the origins of tracers of GC dissolution,N-rich stars, that are located in the inner 4 kpc of the Milky Way. From an analysis ofthe chemical compositions of these stars we establish that about 30% of the N-rich starspreviously identified in the inner Galaxy may have an accreted origin. This result is confirmedby an analysis of the kinematic properties of our sample. The specific frequency of N-rich starsis quite large in the accreted population, exceeding that of its in situ counterparts by near anorder of magnitude, in disagreement with predictions from numerical simulations. We hopethat our numbers provide a useful test to models of GC formation and destruction.
Key words:
Globular Clusters: general – Galaxy: formation – Galaxy: bulge – Galaxy:kinematics and dynamics – Galaxy: abundances
One of the main consequences of the current cosmologicalparadigm, Lambda Cold Dark Matter ( Λ -CDM), is that galaxiesgrow through the process of hierarchical mass assembly, wherebysmaller galaxies are accreted to form larger more massive systems.Such theoretical predictions are in line with the identification ofphase-space substructures residing in the Galactic stellar halo, suchas Gaia-Enceladus/Sausage (GE/S, Belokurov et al. 2018; Haywoodet al. 2018; Helmi et al. 2018; Mackereth et al. 2019) and Sequoia(Myeong et al. 2019). As well as halo stellar streams (Helmi et al.1999; Ibata et al. 2016; Belokurov et al. 2018) and ongoing accre- ★ E-mail: [email protected] tion, such as the Sagittarius dwarf spheroidal (Sgr dSph, Ibata et al.1994). The longer dynamical timescales of less dense regions, suchas the outer halo, preserves phase-space information and thereforeallows the reconstruction of the integrals of motion (IOM) of theseaccreted systems. The situation is not as simple in the inner halodue to the shorter dynamical timescales. Moreover, large extinctiontowards the inner Galaxy and crowding by more massive metal-rich Galactic components, such as the thick and thin disk, and thebar, make observational access to the inner halo difficult. Thesedifficulties have recently been overcome by the APOGEE survey(Majewski et al. 2017), which obtained detailed chemistry based onNIR spectroscopy for over 10 stars in the inner Galaxy, leading upto the discovery of a large population of N-rich stars within a few © a r X i v : . [ a s t r o - ph . GA ] F e b S. S. Kisku kpc of the Galactic centre, and the recent identification of Heracles(Horta et al. 2021a).In addition to phase-space substructure, stellar streams andongoing accretion events in the Galactic stellar halo, ancient Glob-ular Clusters (GC) are also thought to contribute relevantly to thetotal stellar halo mass budget (Martell et al. 2016; Schiavon et al.2017; Koch et al. 2019; Reina-Campos et al. 2020; Hughes et al.2020; Horta et al. 2021b). Such contribution arises from the disso-lution and/or evaporation of GCs, which are disrupted via differentprocesses (e.g. tidal shocks, evaporation and disruption by encoun-ters with massive molecular clouds, Gnedin 2001; Elmegreen 2010;Kruijssen et al. 2011), so that stars resulting from GC dissolutioncan be found in the field of the stellar halo.Detection of the remnants of GC dissolution in the field ismade possible by the the presence of stars with chemically peculiarchemical compositions in GCs. These systems have been found tohost multiple stellar populations with distinct abundance patterns(for a detailed description, see a review by Bastian & Lardo 2018).Stars that display the same abundances patterns as the field popu-lation are dubbed "First Generation" (FG) stars, whereas those thatshow enhancements in He, N and Na, and show lower O and Care referred to as "Second Generation" (SG) stars. Since abundancepatterns of FG stars are indistinguishable from those of field popu-lations, stars with abundance patterns typical of SG population areused as tracers of the contribution of dissolved GCs to the stellarmass budget of the Galaxy.Field stars that display abundance patterns typical of SG GCstars have been identified in the stellar halo by several groups(Martell & Grebel 2010; Lind et al. 2015; Martell et al. 2016;Koch et al. 2019; Tang et al. 2019, 2020). Using APOGEE DR12data, Schiavon et al. (2017) identified a large population of N-richstars in the inner ∼ ∼
15 kpc by Horta et al. (2021b). The largepopulation of N-rich stars identified by Schiavon et al. (2017) issuggested to contribute a minimum of 19-25% to the stellar massin the inner ∼ . Looking at the halo stars with | 𝑧 | >
10 kpc, Martell et al. (2016) find the contribution to the stellarmass budget due to GC dissolution to be ∼ ∼ + − % and ∼ + − . % atR 𝐺𝐶 ∼ . 𝐺𝐶 ∼
15 kpc, respectively.With the availability of
Gaia’s high-quality parallaxes and theresulting 6D phase-space information, orbital parameters and IOMfor Milky Way stars can be estimated. Since these properties areessentially invariant in low density regions of the Milky Way, theycan be used to group stars according to orbital properties that areassociated to those of the progenitor system. Recent studies con-cerning the origins of enriched stars in the halo which show similarabundances to those of SG GCs have investigated the likelihood thatthese enriched stars originate from GCs (Carollo et al. 2013; Savino& Posti 2019; Tang et al. 2020; Hanke et al. 2020). Savino & Posti(2019) directly compare the IOM of 57 CN-strong field stars, ob-served in SEGUE and SEGUE-2 surveys, to those of known MilkyWay globular clusters. They find that ∼
70% of their sample of fieldstars have halo-like orbital properties, with only 20 stars having a To obtain these numbers, Schiavon et al. (2017) applied the Besançonmodels (Robin et al. 2012, 2014) in order to estimate the contribution of theinner stellar halo to the mass budget of the inner Galaxy. likely orbital association with an existing globular cluster. They do,however, claim that the orbital properties of halo stars seem to becompatible with the globular cluster escapee scenario. Similarly,Tang et al. (2020) compare the kinematics of ∼
100 N-rich stars inLAMOST DR5 to N-normal metal-poor field stars. They concludethat the orbital parameters of N-rich field stars indicate that most ofthem are inner-halo stars, and that the kinematics of these stars sup-port a possible GC origin. Note that an alternative way to producethese N-rich stars has been proposed by Bekki (2019)In this paper, we aim to constrain the origin of N-rich starslocated in the Galactic bulge, on the basis of their chemo-dynamicalproperties. Identifying a population of accreted and in situ
N-richstars defined chemically, which are also confirmed by kinematics,we find that the ratio of N-rich to N-normal differ substantiallybetween accreted and in situ populations.This paper is organised as follows: In Section 2 we describethe data and the criteria for our sample. The results are presentedand discussed in Section 3, and our conclusions are summarised inSection 4.
The results in this paper are based on elemental abundances, ra-dial velocities and stellar parameters from Data Release 16 of theAPOGEE-2 survey (Majewski et al. 2017; Blanton et al. 2017; Ahu-mada et al. 2020) and proper motions from
Gaia -DR2 (Gaia Col-laboration et al. 2016, 2018). We make use of the publicly availablecode galpy (Bovy 2015; Mackereth & Bovy 2018) to calculate or-bital parameters adopting a McMillan (2017) potential. We also usedistances from Leung & Bovy (2019b) which are generated usingthe astroNN python package (Leung & Bovy 2019a). The distancesare determined using a training set that comprises APOGEE spectraand Gaia -DR2 parallax measurements for the purpose of predictingstellar luminosity from spectra. The model is able to simultane-ously predict distances and accounts for the parallax offset presentin
Gaia -DR2, producing high precision, accurate distance estimatesfor APOGEE stars, which match well with external catalogues andstandard candles.
APOGEE-2, one of the four SDSS-IV (Blanton et al. 2017; Ahu-mada et al. 2020) experiments, has obtained near-infrared (NIR),high SNR (S/N > 100 pixel − ) and high resolution (R ∼ , http://github.com/jobovy/galpy MNRAS000
APOGEE-2, one of the four SDSS-IV (Blanton et al. 2017; Ahu-mada et al. 2020) experiments, has obtained near-infrared (NIR),high SNR (S/N > 100 pixel − ) and high resolution (R ∼ , http://github.com/jobovy/galpy MNRAS000 , 1–11 (2021) he origins of N-rich stars in the inner Galaxy and Chemical Abundance Pipeline (ASPCAP; García Pérez et al.2016; Jönsson et al. 2020), which uses libraries of synthetic spectra(Zamora et al. 2015; Holtzman et al. 2018; and Jönsson et al. 2020)calculated using customised H -band line list (Shetrone et al. 2015);Smith et al .in prep, from which outputs are analysed, calibrated andtabulated (Holtzman et al. 2018; Jönsson et al. 2020). We restrict our sample to stars that have
ASPCAPFLAG = 0, SNR > 70and distance uncertainty < 20% (i.e. d 𝑒𝑟𝑟 / d < 0.2). By performingthese cuts, we obtain a reduced sample of APOGEE DR16 for whichwe can obtain reliable chemo-dynamic information. A further cutof log 𝑔 < 𝑅 𝐺𝐶 < < 𝑇 eff < 𝑇 eff limit isadopted to avoid very cool stars whose elemental abundances areaffected by important systematic effects. The upper limit aims toeliminate from the sample C and N abundances that are uncertaindue the weakness of CN and CO lines in spectra of warm starswith relatively low metallicity ([Fe/H] < − ASPCAPFLAG = 0(ii) 𝑅 𝐺𝐶 < d 𝑒𝑟𝑟 / d < 0.2(iv) 3250 K < 𝑇 eff < 𝑔 < . 𝜎 from a 4th orderpolynomial fit to the data in the bulge sample. The polynomial isgiven by: [ N / Fe ] = . + . [ Fe / H ] − . [ Fe / H ] − . [ Fe / H ] − . [ Fe / H ] (1)We further restrict these N-rich stars to those with [C/Fe] < . 𝜎 to define N-rich stars than the 4 𝜎 threshold adopted by Schiavonet al. (2017). In both cases, the threshold decision was informed bythe distribution of N-rich stars in abundance planes such as thosein Figure 4, where N-rich stars display (anti-)correlations betweenvarious abundance ratios. The threshold was chosen so as to cleanthe N-rich sample from contaminants due to abundance errors andstatistical fluctuations. That philosophy is aimed at prioritising N-rich sample purity over completeness. That our threshold is morestringent than that adopted by Schiavon et al. (2017) reflects thefact that our parent sample is considerably larger, requiring a largerthreshold to minimise contamination by outliers due to statisticalfluctuations. [Fe/H] [ N / F e ] BulgeN-rich
Figure 1.
Distribution of sample stars in [N/Fe]-[Fe/H] plane. The smallgrey dots show the bulge population as selected in Section 2.2. The redtriangles indicate the N-rich stars, defined as stars which deviate from the4 𝑡ℎ order polynomial fit (black line) by more than 5 . 𝜎 and have [C/Fe] < . We also look at the possible contamination to our sample ofN-rich stars by AGB stars, which can also present an abundancepattern characterised by Nitrogen enrichment and Carbon depletion(Renzini & Voli 1981; Charbonnel & Lagarde 2010; Ventura et al.2013). We identified 5 N-rich AGB candidates by their position onthe log 𝑔 − 𝑇 eff plane, hand picking those that have low log 𝑔 , high 𝑇 eff and relatively high [Fe/H] compared to other stars in their neigh-bourhood, corresponding to ∼
6% of the sample, in agreement withtheoretical expectations (Girardi et al. 2010). Due to the difficulty ofindividually selecting AGBs in our large sample of bulge field stars,we decide to keep the N-rich AGBs in our sample for consistency.We note that the results of this paper are largely unaffected by thepresence of these N-rich AGBs.
In this section, we discuss how our sample of accreted and in situ populations are selected, employing methods used in Mackerethet al. (2019). We then discuss how these populations differ fromeach other in orbital space, and show the similarities of the N-richstars to GC members in chemical space. in situ stars
In order to split our sample into accreted and in situ groups, westudy the distribution of stars in the 𝛼 -Fe plane. Mackereth et al.(2019) achieved that by examining the distribution of their samplein the Mg-Fe plane, whereas Horta et al. (2021a) focused on thedistribution in the [Mg/Mn] vs [Al/Fe] plane. We cannot proceed inthe same way, because the abundances of Al and Mg are affectedby the multiple populations phenomenon in GCs (e.g., Bastian &Lardo 2018; Mészáros et al. 2015, 2020), so that the positions ofN-rich stars in chemical planes involving those elements cannot beinterpreted in the same way as those of normal stars. Therefore, weuse Si as the tracer of 𝛼 -element abundances, because this elementdoes not present substantial star-to-star variations in Galactic GCs. MNRAS , 1–11 (2021)
S. S. Kisku [Fe/H] [ S i / F e ] BulgeN-rich 0.40.50.60.70.80.91.0 [ N / F e ] Figure 2.
Distribution of sample stars in [Si/Fe]-[Fe/H] plane. The grey points show the distribution of the bulge stars, and the triangles, coloured accordingto the [N/Fe] residuals of the polynomial fit shown in Figure 1, show the N-rich stars distribution in this plane. The solid black line is the cut made to separatethe accreted stars from the in situ stars shown in Mackereth et al. (2019), adjusted to account for the metallicity gradient of disk populations between the outerand inner halo. The cut of [Fe/H] < − . The data in Figure 2 show that the N-rich star populationoccupies the same locus in the Si-Fe plane as the overall bulge fieldpopulation. Following Mackereth et al. (2019), we split the samplebetween accreted and in situ populations. To determine where thedividing line is drawn in the [Si/Fe] vs [Fe/H] plane, we proceed asfollows: 1) Following Mackereth et al. (2019), we choose a slopethat approximately matches the mean slope of the high- and low- 𝛼 populations, slightly adjusting it to minimise the contamination ofthe accreted populations by low- 𝛼 disk stars; 2) We calculate thedistance in [Fe/H] between the dividing line and the mean value ofthe low-Mg disk population and adjust the zero-point so that thedistance is the same in the [Si/Fe] vs [Fe/H] plane; 3) We furthershift the zero-point by +0.2 dex in [Fe/H], to account for the diskmetallicity gradient (e.g., Hayden et al. 2015). The resulting linearrelation is given by: [ Si / Fe ] = − . ([ Fe / H ] + . ) + . ± < − .
8, to minimise contamination from disk stars.This latter cut removes 38 bulge stars from our accreted popula-tion, bringing the total number of bulge stars down to 14,410. Wehenceforth refer to stars below (above) and to the left (right) of thedividing line as "accreted" ( in situ ) populations. The resulting ac-creted and in situ general bulge samples comprise 428 and 13,982stars, respectively, with 25 N-rich stars being located in the accretedlocus, and 58 located in the in situ region. Thus, we conclude thatroughly ∼
30% of the N-rich stars in the inner Galaxy have an ac-creted origin. We emphasise here that stars in each sub-sample arefound across the entire inner Galaxy.Figure 3 shows where these sub-samples lie in the [Al/Fe]-[N/Fe] plane. By placing stars in this plane, former GC memberscan be identified as those that follow a positive correlation between those two abundance ratios. When displaying our sample on thisplane, we can see that the accreted and in situ bulge populationsoccupy slightly different loci. While N and Al abundances of N-rich stars are correlated in both in situ and accreted sub-samples, thecorrelations in each sub-sample are slightly different. The [Al/Fe]ratios of N-normal stars in the accreted sample, save for a handful ofoutliers, are lower than those in their in situ counterparts, on averageby ∼ insitu populations, since the accreted stars with first-generation-likeabundance patterns (i.e., those not affected by multiple populationeffects) are consistent with a dwarf galaxy origin (e.g., Mackerethet al. 2019; Helmi 2020; Das et al. 2020; Horta et al. 2021a).We identify a group of Si-rich stars, with [Si/Fe] > ∼ +0.5 inthe metallicity range -1.3<[Fe/H]<-0.9. They are similar to thosespotted by Masseron et al. (2019) within the MW GCs M92, M15and M13. Those authors showed that, in the most metal-poor GCs,M92 and M15, Si-rich stars are characterised by very low [Mg/Fe],whereas stars in M13 had normal [Mg/Fe]. The Si-rich stars inour sample have normal [Mg/Fe], resembling those Masseron et al.(2019) identified in M13. We ascribe a GC origin to these fieldSi-rich stars and discuss their kinematic properties in Section 3.3. To confirm the association of the field N-rich stars with GCs, weoverplot our sample of N-rich stars on data for GC members fromHorta et al. (2020) in three different chemical planes. We show thecorrelations of GC stars in Mg-Al, Al-N and N-C space. In eachpanel the N-rich stars lie on the same locus as SG GC stars, whichsupports our assumption that they are, in fact, former GC mem-bers. For clarity, the accreted and in situ populations are plottedon different panels of Figure 4 because they span different metal-licity regimes. Abundances of field stars in each set of panels arecompared with those of members of GCs whose mean chemical
MNRAS000
MNRAS000 , 1–11 (2021) he origins of N-rich stars in the inner Galaxy [N/Fe] [ A l / F e ] In situ BulgeAccreted Bulge In situ N-richAccreted N-rich
Figure 3.
Distribution of in situ bulge (small grey dots), accreted bulge (blackdots), in situ
N-rich (blue triangles) and accreted N-rich (red triangles) starsin [Al/Fe]-[N/Fe] plane. The N-rich stars show a correlation between [N/Fe]and [Al/Fe], which is also observed in SG GC stars. However, the correlationsare slightly different between the accreted and in situ populations. Theaccreted bulge stars are seen to occupy a lower locus in [Al/Fe] than the insitu by ∼ . compositions locate them in the accreted and in situ loci of theSi-Fe plane. For the comparison with accreted N-rich stars we se-lect NGC5904 (258 stars, <[Fe/H]> = -1.14, <[Si/Fe]> = 0.18) andNGC6205 (119 stars, <[Fe/H]> = -1.44, <[Si/Fe]> = 0.19), and forthe in situ N-rich stars we select NGC6553 (52 stars, <[Fe/H]> =-0.04, <[Si/Fe]> = 0.06) and NGC104 (333 stars, <[Fe/H]> = -0.67,<[Si/Fe]> = 0.21)On the plots in the first row, the anti-correlation between Aland Mg appears to differ sunstantially between the metal-poor andmetal-rich sub-samples of GCs. The metal-rich GC sub-sampleshows a smaller scatter in both [Al/Fe] and [Mg/Fe] than thoseshown by the metal-poor sub-sample. Therefore, while the anti-correlation is easily visible in the metal-poor sample, it is not evidentin the metal-rich sample. This is similarly shown in the Al-N plots.Where, though the correlation can be seen in the metal-rich GCs,it is more easily identified in the metal-poor GC sub-sample. For amore detailed discussion, see Mészáros et al. (2015) and Nataf et al.(2019).In a recent paper, Fernández-Trincado et al. (2019) claim thatN-rich stars must have [Al/Fe] > +0.5 to be considered SG GC mem-bers. Application of that criterion would remove large numbers ofN-rich stars from our sample. However, we argue that our sampleof field N-rich are indeed akin to SG GC members for the followingreason: the bottom panels of Figure 4 show a clear bimodality in the[N/Fe]-[C/Fe] plane, with the SG GC stars located and higher [N/Fe]above their FG GC counterparts. The dividing line between the twopopulations is located roughly at [N/Fe] = +0.5 for [C/Fe] = –0.5,and gently decreasing [N/Fe] for increasing [C/Fe]. This bimodal-ity is also present in both the [Al/Fe]-[Mg/Fe] and [Al/Fe]-[N/Fe],showing that there are SG GC stars with [Al/Fe]<0.5 all the wayto below solar. In fact, application of an [Al/Fe] > +0.5 cut wouldremove a large fraction of the SG stars in GCs themselves, particu-larly in the low metallicity regime (left panels of Figure 4). It is alsowell known that, although SG GCs typically present enhancementsin N, Al and Na (Bastian & Lardo 2018), not all stars in GCs that are enhanced in N are also enhanced in Al. Indeed, as mentionedabove, the Al-Mg anti-correlation is dependent on metallicity, beingsubstantially weaker in metal-rich GCs (e.g., Mészáros et al. 2015;Nataf et al. 2019; Mészáros et al. 2020), and mass (Massari et al.2017).
In this sub-section we check whether our definition of accreted and in situ stars, which is based solely on chemistry, maps into distinctproperties in kinematic space. To do this, we make comparisonsbetween the distributions of our samples in a kinematic diagram,which is used to distinguish components of the Galaxy on the basisof their kinematic signatures (e.g., Venn et al. 2004; Bonaca et al.2017; Helmi et al. 2018; Koppelman et al. 2019). The x-axis of thekinematic diagram is the tangential velocity, 𝑣 𝜙 , while the y-axis isthe quadrature sum of the radial and vertical velocities, √︁ 𝑣 𝑅 + 𝑣 𝑍 .The accreted and in situ populations are displayed on the kine-matic diagram separately on the upper and lower panels of Figure5, respectively. Since the velocities are in Galactocentric coordi-nates, this places the origin of the coordinate system at the GalacticCentre, therefore the velocity of the Sun is at v 𝐿𝑆𝑅 ∼
220 km/s.In both panels normal stars are displayed as black/gray dots andN-rich stars as coloured triangles. Visual examination of these plotssuggests the following interesting trend: Accreted stars, both normaland N-rich, have on average more retrograde orbits (v 𝜙 <
0) thantheir in situ counterparts, whose orbits are predominantly prograde.This is clearly shown by the difference in the 𝑣 𝜙 distribution of the in situ and accreted samples of N-rich stars, with the mean of thelatter being ∼
80 km/s lower than that of the former.The above visual impressions must be confirmed by a quantita-tive statistical evaluation. The Kolmogorov-Smirnov (KS) statisticis a nonparametric test used to assess the similarity between twosamples. We use the python package ndtest to make 2D com-parisons between the distributions in 𝑣 𝜙 and √︁ 𝑣 𝑅 + 𝑣 𝑍 of thefollowing sub-samples, as shown in Table 1: accreted N-rich vs.accreted normal, in situ N-rich vs. in situ normal, accreted N-richvs. in situ
N-rich and, accreted normal vs. in situ normal. The KStests result in a rejection of the null hypothesis, with 𝑝 -value < 0.1for all four comparisons. The clear kinematic distinction betweenthe accreted and in situ populations confirms our chemical selec-tion of these groups. We also note the difference between accretedN-rich vs. accreted normal sub-samples. This result can be under-stood by examination of Figure 6. In that plot it can be seen thatthe accreted normal stars show a clump of slightly prograde starsaround 𝐸 / ∼ − . s − , without a clear counterpart in theN-rich accreted group. We suspect that this prograde population islikely due to contamination from the disk. In addition, the accretednormal population hosts a number of stars forming a cloud with 𝐸 / > ∼ − .
85 km s − , where no N-rich stars can be found. Thatis the locus occupied by stars belonging to the GE/S system, as wellas other possible accretion events (Ibata et al. 1994; Helmi et al.1999; Ibata et al. 2016; Belokurov et al. 2018; Haywood et al. 2018;Helmi et al. 2018; Mackereth et al. 2019; Horta et al. 2021a). Con-versely, most of the N-rich stars occupy the same locus as Heraclesidentified recently by Horta et al. (2021a), with a couple of starsdisplaying kinematics suggestive of disk-like orbits.Interestingly, the KS test rejects the null hypothesis for simi-larity between the in situ N-rich vs. in situ normal sub-samples. We https://github.com/syrte/ndtest MNRAS , 1–11 (2021)
S. S. Kisku [ A l / F e ] GC stars (NGC5904 & NGC6205)Accreted N-rich 0.4 0.2 0.0 0.2 0.4 0.6[Mg/Fe]1.00.50.00.51.01.5 [ A l / F e ] GC stars (NGC6553 & NGC104) In situ N-rich0.0 0.5 1.0 1.5[N/Fe]1.00.50.00.51.01.5 [ A l / F e ] [ A l / F e ] [ N / F e ] [ N / F e ] Figure 4.
Coloured dots and triangles indicate GC stars (Horta et al. 2020) and N-rich stars (see Section 2.2), respectively, colour coded by their [Fe/H]abundance. The graphs on the left show the accreted N-rich stars plotted on top of stars in NGC5904 and NGC6205, and the right graphs show the in situ
N-rich stars plotted on top of stars in NGC6553 and NGC104, both using the same metallicity colour scale. Each plot shows the mean errorbar for the N-richstars in the bottom right corner. The 1 𝑠𝑡 row shows these stars in the [Al/Fe]-[Mg/Fe] plane to show the Al-Mg anti-correlation in GCs. The 2 𝑛𝑑 row showsthe distribution in the [Al/Fe]-[N/Fe] plane to show the Al-N correlation in GCs. The 3 𝑟𝑑 row shows the distribution in the [N/Fe]-[C/Fe] plane to show theN-C anti-correlation in GCs. Each plot shows that our sample of N-rich stars lies on the same locus as SG GC members, supporting the idea they have possibleGC origin. MNRAS000
N-rich stars plotted on top of stars in NGC6553 and NGC104, both using the same metallicity colour scale. Each plot shows the mean errorbar for the N-richstars in the bottom right corner. The 1 𝑠𝑡 row shows these stars in the [Al/Fe]-[Mg/Fe] plane to show the Al-Mg anti-correlation in GCs. The 2 𝑛𝑑 row showsthe distribution in the [Al/Fe]-[N/Fe] plane to show the Al-N correlation in GCs. The 3 𝑟𝑑 row shows the distribution in the [N/Fe]-[C/Fe] plane to show theN-C anti-correlation in GCs. Each plot shows that our sample of N-rich stars lies on the same locus as SG GC members, supporting the idea they have possibleGC origin. MNRAS000 , 1–11 (2021) he origins of N-rich stars in the inner Galaxy
400 200 0 200 400 v (km/s) v R + v Z ( k m / s ) Bulge < v > = 50.58 Bulge ( V ) = 109.01N-rich < v > = -0.6 N-rich ( V ) = 109.94 B u l g e < v R v Z > = . B u l g e ( v R v Z ) = . N - r i c h < v R v Z > = . N - r i c h ( v R v Z ) = . Accreted normal Accreted N-rich400 200 0 200 400 v (km/s) v R + v Z ( k m / s ) Bulge < v > = 111.63 Bulge ( V ) = 91.71N-rich < v > = 83.97 N-rich ( V ) = 88.7 B u l g e < v R v Z > = . B u l g e ( v R v Z ) = . N - r i c h < v R v Z > = . N - r i c h ( v R v Z ) = . In situ normal In situ N-rich
Figure 5.
Distribution in √︁ 𝑣 𝑅 + 𝑣 𝑍 vs. 𝑣 𝜙 of accreted and in situ starson the top and bottom panel respectively. Top Panel:
Accreted N-rich stars(red triangles) and the accreted bulge stars (black dots).
Bottom Panel: insitu
N-rich stars (blue triangles) and in situ bulge stars (grey dots). Anythingwith 𝑣 𝜙 > 0 has a prograde orbit, similar to that of the disk, and anythingwith 𝑣 𝜙 < 0 has a retrograde orbit. We also show on these plots the meanand standard deviation of the sub-samples for each axis. suggest that the difference between these two sub-samples is due tothe presence of disk stars within 4 kpc of the Galactic centre. Thisis further discussed in Section 3.4The stars in the accreted sample have on average lower metal-licities than their in situ counterparts. Thus, the differences en-countered could be due to the dependence of kinematics on themetallicity of stellar populations. To test that hypothesis, we redothe KS tests to assess the similarity between the accreted and insitu sub-samples, this time limiting the comparison to stars with[Fe/H] < − .
8. The results from this comparison are shown inTable 1. The difference between the N-rich and normal accretedpopulations remain unchanged since they were already restrictedto [Fe/H] < − .
8. We do, however, see a big change in the com-
Comparison 𝑝 -value Accreted N-rich vs. Accreted normal 0.024
In situ
N-rich vs.
In situ normal 0.028Accreted normal vs.
In situ normal < . In situ
N-rich 0.009
Comparison ( [Fe/H] < –0.8 ) 𝑝 -value Accreted N-rich vs. Accreted normal 0.024
In situ
N-rich vs.
In situ normal 0.294Accreted normal vs.
In situ normal 0.038Accreted N-rich vs.
In situ
N-rich 0.027
Comparison ( Zero-point +0.1 dex ) 𝑝 -value Accreted N-rich vs. Accreted normal 0.066
In situ
N-rich vs.
In situ normal 0.062Accreted normal vs.
In situ normal < . In situ
N-rich 0.040
Comparison ( Zero-point –0.1 dex ) 𝑝 -value Accreted N-rich vs. Accreted normal 0.172
In situ
N-rich vs.
In situ normal 0.006Accreted normal vs.
In situ normal < . In situ
N-rich 0.223
Table 1.
Results obtained from performing a 2D KS test between the differentsub-samples shown in Figure 5.
First Panel: 𝑝 -values for the comparisonsbetween sub-samples as defined in Section 3.1. Second Panel: 𝑝 -valuesfor the comparisons between the sub-samples with [Fe/H] < − . Third& Fourth Panel:
Result when shifting the zero-point of the dividing line,Equation 2, by ± 𝑝 -value of 0.1. So, a 𝑝 -value < 0.1 results in a rejection of the null hypothesis, whereas a 𝑝 -value> 0.1 means the null hypothesis cannot be rejected. parison between the in situ populations, where the 𝑝 -value = 0.294tells us that the null hypothesis cannot be rejected. This is due tothe removal of high metallicity disk stars from our sample of insitu normal stars. Regarding the comparison between accreted and in situ populations, for both the N-rich and normal samples, thenull hypothesis is rejected even when the comparison is limited tometal-poor sub-samples. In short, accreted and in situ samples arekinematically different populations even when only metal-poor starsare considered.We checked whether our results are sensitive to the definition ofthe line separating accreted and in situ populations in Figure 2. Forthat purpose, we shifted the zero-point of the relation given by theEquation 2 by ± (i) accreted normal vs. accreted N-rich stars. This result is dueto the removal of a small number of retrograde N-rich stars andthe reduction in the contribution of prograde normal stars (whichwe conjectured in Section 3.3 to be due to disk contamination); (ii) accreted N-rich vs. in situ N-rich stars. This happens becausethe above mentioned retrograde N-rich stars that are moved fromthe accreted to the in situ sub-sample, make the two groups moresimilar kinematically. Since this exercise leads to a reduction of thesize of the N-rich accreted population, we deem these result of littlestatistical significance. The matter will have to be revisited on thebasis of larger samples.
MNRAS , 1–11 (2021)
S. S. Kisku
Lz/ (kpc km s ) E / ( k m s ) Accreted normal Accreted N-rich
Figure 6.
Accreted N-normal (black dots) shows a population of stars in thesame locus as GE/S stars at high energies, whilst the accreted N-rich stars(red triangles) occupy the low energy region similar to Heracles.
Again, we check the dependence of kinematics on metallicityby limiting the comparison to stars with [Fe/H] < − .
8, as doneabove, after shifting the relation by ± in situ N-rich and in situ normal sub-samples. In both cases, when movingthe zero-point towards higher of lower [Fe/H], the null hypothesiscannot be rejected when comparing these two sub-samples. Also inthis case the statistical significance of the results is small due to thereduced sample sizes.Finally, we examine the kinematic properties of Si-rich starsmentioned in Section 3.1 separately. When comparing their prop-erties to those of N-rich and N-normal, the KS tests only yieldeda statistically significant difference with the accreted N-rich, p-value=0.022. This suggests that this population is likely to resultfrom the dissolution of in situ
GCs and in the remainder of thisanalysis they will be treated as such.In summary, the results above show that the chemistry-baseddefinition of accreted and in situ sub-samples maps into distinctkinematic properties. Both N-rich and N-normal in situ sampleswith 𝑅 GC < in situ stars. However, the differencespersist even when controlling for the dependence of kinematics onmetallicity, which argues in favour of our interpretation of the originof the accreted N-rich sample. in situ samples An important clue to the origin of N-rich stars is their frequency, 𝑓 𝑁 𝑟 , defined as the ratio between the number of such stars and thetotal field population (e.g., Martell et al. 2016; Schiavon et al. 2017;Koch et al. 2019; Horta et al. 2021b). We measured this frequency inboth the accreted and in situ sub-samples, and henceforth express itin terms of percentages. In the accreted group we find 𝑓 𝑁 𝑟 = . ± . in situ group, the measured frequency is anorder of magnitude lower, 𝑓 𝑁 𝑟 = . ± . 𝑓 𝑁 𝑟 = . ± . 𝛼 stars are considered. If we account for the Si-rich starsidentified in Section 3.1, ascribing them to an in situ GC origin based [Fe/H]
Figure 7.
Metallicity distribution functions (MDFs) for the in situ high- 𝛼 N-rich stars (top panel) and in situ high- 𝛼 normal field (bottom panel). TheMDFs of the two populations are not very different. The N-rich MDF peaksat a slightly lower [Fe/H], but is substantially broader, overlapping the highmetallicity end of the N-normal MDF. on their kinematics, the frequency of the in situ group increases to 𝑓 𝑁 𝑟 = . ± . 𝑓 𝑁 𝑟 = . ± .
10% if only high- 𝛼 stars areconsidered. Thus, consideration of Si-rich stars does not alter ourfinding of a large difference between accreted and in situ N-richstars.This difference cannot be easily understood. According to theprevailing scenario for GC formation and destruction, (Kruijssen2014, 2015; Pfeffer et al. 2019) Galactic GCs originate from twodifferent channels. The ex situ , or accreted, channel would consistof GCs that were accreted to the Galaxy along with their hostgalaxies. Those accretion episodes occurred predominantly, thoughnot exclusively, in the early stages of the Milky Way assembly, assuggested by various lines of evidence (e.g., Deason et al. 2014;Mackereth et al. 2018, 2019; Pfeffer et al. 2019; Schiavon et al.2020; Hughes et al. 2020). Conversely, the in situ population wouldbe comprised of GCs that were formed in the turbulent disk of theMilky Way at 𝑧 ∼ −
3. According to this scenario, in situ
GCswould have been destroyed very efficiently by tidal interaction withgiant molecular clouds in the early disk (the so-called “cruel cradleeffect”, see Kruijssen et al. 2012), whereas destruction of accretedGCs via tidal stripping and evaporation was less efficient, havinghappened on a much longer timescale. Given these predictions, wewould naively expect the frequency of in situ
N-rich stars to behigher, not lower than that of the accreted population.One possible way out of this conundrum is to invoke that theratio between integrated star formation in the form of GCs overtotal was lower in the in situ than in the accreted population. Thiscould be achieved, for instance, if the in situ population under-went a longer star formation episode than that leading up to theformation of the accreted population. If in situ star formation wasextended further in time, after the cessation of the main episodeof GC formation/destruction, a low in situ 𝑓 𝑁 𝑟 could possibly beaccommodated. In such a situation, however, one would expect themetallicity distribution function (MDF) of the in situ normal popu-lation to have more power towards higher metallicities than that ofthe in situ
N-rich population.This qualitative prediction does not seem to be supported bythe metallicity distribution functions (MDFs) of the N-rich and N-normal bulge in situ samples, shown in Figure 7. For simplicity, welimit our comparison to high- 𝛼 N-rich and normal field stars, asthose are understood to have undergone a coherent chemical evolu-
MNRAS000
MNRAS000 , 1–11 (2021) he origins of N-rich stars in the inner Galaxy tion path that is independent of the low- 𝛼 disk population (Mack-ereth et al. 2018). In that figure, one can see that the MDFs of thehigh- 𝛼 N-rich and N-normal in situ samples are not very different.The MDF of the high- 𝛼 N-rich population peaks at [Fe/H] ∼ –0.8,whereas that of the high- 𝛼 N-normal population peaks at a slightlyhigher metallicity, around [Fe/H] ∼ –0.5. That difference in the modeof the two MDFs is slightly offset by the fact that the N-rich popula-tion has a broader MDF, with FWHM ∼ in situ population has FWHM ∼ 𝛼 stellar populations in the inner Galaxy, which is attested bytheir predominantly old ages (e.g., Hasselquist et al. 2020).This result prompts interesting considerations on the origin ofthe accreted N-rich stars currently inhabiting the inner Galaxy. Thefrequency of metal-poor N-rich stars as a function of Galactocentricdistance has been shown by Horta et al. (2021b) to undergo a steepdecrease towards growing 𝑅 GC (see also Martell et al. 2016; Kochet al. 2019). At 𝑅 GC ∼
15 kpc, Horta et al. (2021b) found 𝑓 𝑁 𝑟 ∼ + − . %, which is considerably lower than the ratio we find forthe accreted population. Since the population of N-rich stars inour sample at low metallicity is dominated by accreted stars, thisresult leads to the conclusion that GC destruction associated withsatellite mergers must have been very efficient in the early stagesof the Galaxy’s formation. Indeed it has been shown by Pfefferet al. (2020) that GCs associated with the earliest accretion eventsended up in strongly bound orbits, driven by dynamical friction.That is the case for Heralces (Horta et al. 2021a), a ∼ × M (cid:12) satellite that likely merged with the MW over 10 Gyr ago (see alsoKruijssen et al. 2020). Given the coincidence between the positionsof our bulge N-rich stars in integrals of motion space and thoseof Heracles stars (Figure 6), we speculate that the bulge N-richpopulation is partly made of members of GCs that were originallyassociated with Heracles, and were mostly destroyed during theaccretion event. It is also possible that those accreted N-rich starswere already in the field of Heracles, before they were accreted tothe MW, however there currently is no evidence for the presence ofN-rich stars in the fields of dwarf satellites of the MW.Hughes et al. (2020) used the E-MOSAICS simulations (Pf-effer et al. 2019) to calculate the contribution of destroyed GCsto field populations in the bulges of MW-like galaxies, comparingthe predictions with the measurements by Schiavon et al. (2017).They show that, for most of the MW-like galaxies in their simulatedvolume, the prediction for 𝑓 𝑁 𝑟 of the metal-poor stellar populationis lower than the observations by factors of ∼ 𝑓 𝑁 𝑟 are in good agreement with the observations. Like the MW, thedisk populations of those galaxies are characterised by a bimodaldistribution in the 𝛼 -Fe plane, which is a distinctive feature of theMW disk populations (e.g., Hayden et al. 2015; Mackereth et al.2017). Mackereth et al. (2018) showed that this feature is associatedwith an atypical accretion history, characterised by intense mergingin early times and relative calm since 𝑧 ∼ − .
5. It is noteworthy,however, that Hughes et al. (2020) predictions for these few MW-likegalaxies differ from our measurements with regards to the depen-dence of 𝑓 𝑁 𝑟 on position in the 𝛼 -Fe plane. The high frequency ofex-GC stars in the field of simulated galaxies is predominantly dueto high- 𝛼 in situ GC formation and destruction, whereas our datashow that the high 𝑓 𝑁 𝑟 in the MW bulge is due to the contribution by the dissolution of low- 𝛼 accreted GCs. This discrepancy wouldbe alleviated if some of the stars in the accreted region in Figure 2were in fact formed in situ , (see Figure 2 of Hughes et al. 2020),but it is not clear that accounting for such a contamination wouldcompletely eliminate the disagreement.
The results presented in this paper make use of elemental abun-dances from APOGEE DR16 along with data from
Gaia
DR2 tostudy the chemical and kinematic properties of 146 N-rich starslocated within the inner 4 kpc of the Galaxy. Our conclusions canbe summarised as follows: • We find that there are likely accreted and in situ components tothe N-rich population within 4 kpc of the Galactic centre, identifiedvia chemistry by making a cut in [ 𝛼 /Fe]-[Fe/H] space towards lowmetallicities (as shown in Figure 2) (e.g. Hayes et al. 2018; Mack-ereth et al. 2019; Das et al. 2020). By making this cut and removingstars without proper motions in Gaia , we select 428 and 13,982bulge stars that lie in the accreted and in situ positions, respectively,with 25 N-rich stars being located in the accreted, and 58 located inthe in situ locus. • We show that our sample of N-rich stars occupies the samelocus as so-called second-generation GC stars, supporting the ideathat they are the by-products of GCs destruction/evaporation. • We find that there is a significant difference in the kinematicproperties of chemically defined accreted and in situ populations.This shows that our chemistry-based distinction of these populationsmaps into differences in kinematic space. We also find that theaccreted bulge field population includes stars which share orbitalproperties with the GE/S system, although no N-rich stars occupythat locus of orbital parameter space. The absence of N-rich starsassociated with GE/S in the bulge is likely due to their low frequency,combined with the relatively small number of GE/S stars found inthe bulge (see Horta et al. 2021a) • We find that the frequency of N-rich stars differs by an order ofmagnitude between the accreted ( 𝑓 𝑁 𝑟 = . ± . in situ ( 𝑓 𝑁 𝑟 = . ± . 𝛼 in situ populations (Hughes et al. 2020). Wespeculate that the higher frequency of N-rich stars among accretedpopulations is due to early merger events, such as Heracles (Hortaet al. 2021a), which likely had their GCs destroyed very efficientlyduring the merger with the MW. • The identification of an accreted population of N-rich stars inthe bulge raises the question of whether the GCs from which theyoriginate were destroyed in their host dwarf galaxies or during themerger. If the former hypothesis is correct, we would expect thatN-rich stars would be present in the field of current Milky Waysatellites. Norris et al. (2017) did not find a Na-O anti-correlation,which is typical of GC stars, in Carina dwarf spheroidal field stars.However, their study is based on a sample of 63 stars, which isrelatively small. Since the observed frequency of N-rich stars in thehalo is ∼
3% one would expect to find ∼ MNRAS , 1–11 (2021) S. S. Kisku
ACKNOWLEDGEMENTS
We thank all those professionals who have been working tirelesslyduring these difficult times so that people like ourselves can worksafely from home. The authors thank Nate Bastian and MeghanHughes for helpful discussion. SSK acknowledges an STFC doc-toral studentship. The anonymous referee is thanked for an insight-ful review of the original manuscript. JTM acknowledges supportfrom the ERC Consolidator Grant funding scheme (project ASTE-ROCHRONOMETRY,
DATA AVAILABILITY
Most of the data upon which this paper is based are publicly availableas part of the 16th data release of the Sloan Digital Sky Survey(SDSS-IV) collaboration. For part of the sample, the data are stillproprietary and will be made publicly available as part of the 17thdata release. Once the latter data are publicly available they will beaccessible via the usual channels.
REFERENCES
Ahumada R., et al., 2020, ApJS, 249, 3Bastian N., Lardo C., 2018, ARA&A, 56, 83Bekki K., 2019, MNRAS, 490, 4007Belokurov V., Erkal D., Evans N. W., Koposov S. E., Deason A. J., 2018,MNRAS, 478, 611 Blanton M. R., et al., 2017, AJ, 154, 28Bonaca A., Conroy C., Wetzel A., Hopkins P. F., Kereš D., 2017, ApJ, 845,101Bovy J., 2015, ApJS, 216, 29Bowen I. S., Vaughan A. H. J., 1973, Appl. Opt., 12, 1430Carollo D., Martell S. L., Beers T. C., Freeman K. C., 2013, ApJ, 769, 87Charbonnel C., Lagarde N., 2010, A&A, 522, A10Das P., Hawkins K., Jofré P., 2020, MNRAS,Deason A. J., Belokurov V., Koposov S. E., Rockosi C. M., 2014, ApJ, 787,30Elmegreen B. G., 2010, ApJ, 712, L184Fernández-Trincado J. G., Beers T. C., Tang B., Moreno E., Pérez-VillegasA., Ortigoza-Urdaneta M., 2019, MNRAS, 488, 2864Gaia Collaboration et al., 2016, A&A, 595, A1Gaia Collaboration et al., 2018, A&A, 616, A1García Pérez A. E., et al., 2016, AJ, 151, 144Girardi L., et al., 2010, ApJ, 724, 1030Gnedin O. Y., 2001, Astronomical and Astrophysical Transactions, 20, 39Gunn J. E., et al., 2006, AJ, 131, 2332Hanke M., Koch A., Prudil Z., Grebel E. K., Bastian U., 2020, A&A, 637,A98Hasselquist S., et al., 2020, ApJ, 901, 109Hayden M. R., et al., 2015, ApJ, 808, 132Hayes C. R., et al., 2018, ApJ, 852, 49Haywood M., Di Matteo P., Lehnert M. D., Snaith O., Khoperskov S., GómezA., 2018, ApJ, 863, 113Helmi A., 2020, ARA&A, 58, 205Helmi A., White S. D. M., de Zeeuw P. T., Zhao H., 1999, Nature, 402, 53Helmi A., Babusiaux C., Koppelman H. H., Massari D., Veljanoski J., BrownA. G. A., 2018, Nature, 563, 85Holtzman J. A., et al., 2015, AJ, 150, 148Holtzman J. A., et al., 2018, AJ, 156, 125Horta D., et al., 2020, MNRAS, 493, 3363Horta D., et al., 2021a, MNRAS, 500, 1385Horta D., et al., 2021b, MNRAS, 500, 5462Hughes M. E., Pfeffer J. L., Martig M., Reina-Campos M., Bastian N., CrainR. A., Kruijssen J. M. D., 2020, MNRAS, 491, 4012Ibata R. A., Gilmore G., Irwin M. J., 1994, Nature, 370, 194Ibata R. A., Lewis G. F., Martin N. F., 2016, ApJ, 819, 1Jönsson H., et al., 2018, AJ, 156, 126Jönsson H., et al., 2020, AJ, 160, 120Koch A., Grebel E. K., Martell S. L., 2019, A&A, 625, A75Koppelman H. H., Helmi A., Massari D., Price-Whelan A. M., StarkenburgT. K., 2019, A&A, 631, L9Kruijssen J. M. D., 2014, Classical and Quantum Gravity, 31, 244006Kruijssen J. M. D., 2015, MNRAS, 454, 1658Kruijssen J. M. D., Pelupessy F. I., Lamers H. J. G. L. M., Portegies ZwartS. F., Icke V., 2011, MNRAS, 414, 1339Kruijssen J. M. D., Maschberger T., Moeckel N., Clarke C. J., Bastian N.,Bonnell I. A., 2012, MNRAS, 419, 841Kruijssen J. M. D., et al., 2020, MNRAS, 498, 2472Leung H. W., Bovy J., 2019a, MNRAS, 483, 3255Leung H. W., Bovy J., 2019b, MNRAS, 489, 2079Lind K., et al., 2015, A&A, 575, L12Mackereth J. T., Bovy J., 2018, PASP, 130, 114501Mackereth J. T., et al., 2017, MNRAS, 471, 3057Mackereth J. T., Crain R. A., Schiavon R. P., Schaye J., Theuns T., SchallerM., 2018, MNRAS, 477, 5072Mackereth J. T., et al., 2019, MNRAS, 482, 3426Majewski S. R., et al., 2017, AJ, 154, 94Martell S. L., Grebel E. K., 2010, A&A, 519, A14Martell S. L., et al., 2016, ApJ, 825, 146Massari D., et al., 2017, MNRAS, 468, 1249Masseron T., et al., 2019, A&A, 622, A191McMillan P. J., 2017, MNRAS, 465, 76Mészáros S., et al., 2015, AJ, 149, 153Mészáros S., et al., 2020, MNRAS, 492, 1641 MNRAS000
Ahumada R., et al., 2020, ApJS, 249, 3Bastian N., Lardo C., 2018, ARA&A, 56, 83Bekki K., 2019, MNRAS, 490, 4007Belokurov V., Erkal D., Evans N. W., Koposov S. E., Deason A. J., 2018,MNRAS, 478, 611 Blanton M. R., et al., 2017, AJ, 154, 28Bonaca A., Conroy C., Wetzel A., Hopkins P. F., Kereš D., 2017, ApJ, 845,101Bovy J., 2015, ApJS, 216, 29Bowen I. S., Vaughan A. H. J., 1973, Appl. Opt., 12, 1430Carollo D., Martell S. L., Beers T. C., Freeman K. C., 2013, ApJ, 769, 87Charbonnel C., Lagarde N., 2010, A&A, 522, A10Das P., Hawkins K., Jofré P., 2020, MNRAS,Deason A. J., Belokurov V., Koposov S. E., Rockosi C. M., 2014, ApJ, 787,30Elmegreen B. G., 2010, ApJ, 712, L184Fernández-Trincado J. G., Beers T. C., Tang B., Moreno E., Pérez-VillegasA., Ortigoza-Urdaneta M., 2019, MNRAS, 488, 2864Gaia Collaboration et al., 2016, A&A, 595, A1Gaia Collaboration et al., 2018, A&A, 616, A1García Pérez A. E., et al., 2016, AJ, 151, 144Girardi L., et al., 2010, ApJ, 724, 1030Gnedin O. Y., 2001, Astronomical and Astrophysical Transactions, 20, 39Gunn J. E., et al., 2006, AJ, 131, 2332Hanke M., Koch A., Prudil Z., Grebel E. K., Bastian U., 2020, A&A, 637,A98Hasselquist S., et al., 2020, ApJ, 901, 109Hayden M. R., et al., 2015, ApJ, 808, 132Hayes C. R., et al., 2018, ApJ, 852, 49Haywood M., Di Matteo P., Lehnert M. D., Snaith O., Khoperskov S., GómezA., 2018, ApJ, 863, 113Helmi A., 2020, ARA&A, 58, 205Helmi A., White S. D. M., de Zeeuw P. T., Zhao H., 1999, Nature, 402, 53Helmi A., Babusiaux C., Koppelman H. H., Massari D., Veljanoski J., BrownA. G. A., 2018, Nature, 563, 85Holtzman J. A., et al., 2015, AJ, 150, 148Holtzman J. A., et al., 2018, AJ, 156, 125Horta D., et al., 2020, MNRAS, 493, 3363Horta D., et al., 2021a, MNRAS, 500, 1385Horta D., et al., 2021b, MNRAS, 500, 5462Hughes M. E., Pfeffer J. L., Martig M., Reina-Campos M., Bastian N., CrainR. A., Kruijssen J. M. D., 2020, MNRAS, 491, 4012Ibata R. A., Gilmore G., Irwin M. J., 1994, Nature, 370, 194Ibata R. A., Lewis G. F., Martin N. F., 2016, ApJ, 819, 1Jönsson H., et al., 2018, AJ, 156, 126Jönsson H., et al., 2020, AJ, 160, 120Koch A., Grebel E. K., Martell S. L., 2019, A&A, 625, A75Koppelman H. H., Helmi A., Massari D., Price-Whelan A. M., StarkenburgT. K., 2019, A&A, 631, L9Kruijssen J. M. D., 2014, Classical and Quantum Gravity, 31, 244006Kruijssen J. M. D., 2015, MNRAS, 454, 1658Kruijssen J. M. D., Pelupessy F. I., Lamers H. J. G. L. M., Portegies ZwartS. F., Icke V., 2011, MNRAS, 414, 1339Kruijssen J. M. D., Maschberger T., Moeckel N., Clarke C. J., Bastian N.,Bonnell I. A., 2012, MNRAS, 419, 841Kruijssen J. M. D., et al., 2020, MNRAS, 498, 2472Leung H. W., Bovy J., 2019a, MNRAS, 483, 3255Leung H. W., Bovy J., 2019b, MNRAS, 489, 2079Lind K., et al., 2015, A&A, 575, L12Mackereth J. T., Bovy J., 2018, PASP, 130, 114501Mackereth J. T., et al., 2017, MNRAS, 471, 3057Mackereth J. T., Crain R. A., Schiavon R. P., Schaye J., Theuns T., SchallerM., 2018, MNRAS, 477, 5072Mackereth J. T., et al., 2019, MNRAS, 482, 3426Majewski S. R., et al., 2017, AJ, 154, 94Martell S. L., Grebel E. K., 2010, A&A, 519, A14Martell S. L., et al., 2016, ApJ, 825, 146Massari D., et al., 2017, MNRAS, 468, 1249Masseron T., et al., 2019, A&A, 622, A191McMillan P. J., 2017, MNRAS, 465, 76Mészáros S., et al., 2015, AJ, 149, 153Mészáros S., et al., 2020, MNRAS, 492, 1641 MNRAS000 , 1–11 (2021) he origins of N-rich stars in the inner Galaxy Myeong G. C., Vasiliev E., Iorio G., Evans N. W., Belokurov V., 2019,MNRAS, 488, 1235Nataf D. M., et al., 2019, AJ, 158, 14Nidever D. L., et al., 2015, AJ, 150, 173Norris J. E., Yong D., Venn K. A., Gilmore G., Casagrande L., Dotter A.,2017, ApJS, 230, 28Pfeffer J., Bastian N., Kruijssen J. M. D., Reina-Campos M., Crain R. A.,Usher C., 2019, MNRAS, 490, 1714Pfeffer J. L., Trujillo-Gomez S., Kruijssen J. M. D., Crain R. A., HughesM. E., Reina-Campos M., Bastian N., 2020, MNRAS,Reina-Campos M., Hughes M. E., Kruijssen J. M. D., Pfeffer J. L., BastianN., Crain R. A., Koch A., Grebel E. K., 2020, MNRAS, 493, 3422Renzini A., Voli M., 1981, A&A, 500, 221Robin A. C., Marshall D. J., Schultheis M., Reylé C., 2012, A&A, 538, A106Robin A. C., Reylé C., Fliri J., Czekaj M., Robert C. P., Martins A. M. M.,2014, A&A, 569, A13Savino A., Posti L., 2019, A&A, 624, L9Schiavon R. P., et al., 2017, MNRAS, 465, 501Schiavon R. P., Mackereth J. T., Pfeffer J., Crain R. A., Bovy J., 2020,in Bragaglia A., Davies M., Sills A., Vesperini E., eds, IAU Sympo-sium Vol. 351, IAU Symposium. pp 170–173 ( arXiv:2002.08380 ),doi:10.1017/S1743921319007889Shetrone M., et al., 2015, ApJS, 221, 24Tang B., Liu C., Fernández-Trincado J. G., Geisler D., Shi J., Zamora O.,Worthey G., Moreno E., 2019, ApJ, 871, 58Tang B., Fernández-Trincado J. G., Liu C., Yu J., Yan H., Gao Q., Shi J.,Geisler D., 2020, ApJ, 891, 28Venn K. A., Irwin M., Shetrone M. D., Tout C. A., Hill V., Tolstoy E., 2004,AJ, 128, 1177Ventura P., Di Criscienzo M., Carini R., D’Antona F., 2013, MNRAS, 431,3642Wilson J. C., et al., 2019, PASP, 131, 055001Zamora O., et al., 2015, AJ, 149, 181Zasowski G., et al., 2017, AJ, 154, 198
APPENDIX A: TABLE OF APOGEE IDS FOR N-RICHSTARS
Table A1 shows only the publicly available DR16 APOGEE ID’s,RA and DEC for the N-rich stars selected in this paper.
This paper has been typeset from a TEX/L A TEX file prepared by the author.MNRAS , 1–11 (2021) S. S. Kisku
Table A1.
N-rich stars identified in the inner Galaxy. APOGEE_ID RA DEC2M16051144-2330557 241.297673 -23.5154842M16180906-2442217 244.537768 -24.7060362M16304650-2949522 247.693763 -29.8311732M16314726-2945273 247.946932 -29.7575912M16333703-3028333 248.404329 -30.4759432M16335569-1344044 248.482062 -13.7345572M17024730-2210387 255.697092 -22.1774432M17271907-2718040 261.829481 -27.3011262M17281699-3024573 262.070794 -30.4159282M17285196-2013080 262.2165 -20.2189082M17293012-3006008 262.375515 -30.1002462M17293730-2725594 262.405434 -27.4331822M17303980-2330234 262.665839 -23.5065232M17305251-2651528 262.718823 -26.8646722M17305645-3030155 262.73523 -30.5043092M17325943-3034281 263.247636 -30.574492M17330999-1034023 263.291625 -10.5673092M17333623-2548156 263.400967 -25.8043612M17334418-3033313 263.434107 -30.5586952M17334704-3034136 263.446029 -30.5704562M17335209-3011013 263.467059 -30.1837042M17340261-2616237 263.51091 -26.2732562M17343807-2557555 263.658637 -25.9654292M17350460-2856477 263.769185 -28.9465872M17354063-3339547 263.919305 -33.6652032M17404143-2714570 265.172631 -27.2491722M17494963-2318560 267.4568 -23.3155712M17504980-2255083 267.70754 -22.918982M17511127-3406383 267.796969 -34.1106452M17523300-3027521 268.137518 -30.4644952M17534571-2949362 268.44047 -29.8267442M17552461-0122088 268.852559 -1.3691362M17554454-2123058 268.93562 -21.3849532M17555660-3238250 268.985848 -32.6402822M17560439-3246181 269.01833 -32.7717212M17571419-3328194 269.309144 -33.4720732M17573951-2908334 269.414629 -29.1426282M17595598-3117393 269.983287 -31.2942642M18013879-2924112 270.411633 -29.4031182M18014007-2649505 270.416966 -26.8307192M18014786-2749080 270.449436 -27.8189072M18015592-2749451 270.483011 -27.8292222M18033529-2911240 270.897062 -29.190022M18035944-2908195 270.997669 -29.1387582M18044803-2752467 271.200154 -27.8796542M18050144-3005149 271.256017 -30.0874842M18054875-3122407 271.453164 -31.3779752M18061308-2522503 271.554505 -25.3806552M18062975-2855357 271.623993 -28.9266012M18072810-2459356 271.867096 -24.9932292M18100924-3733319 272.538504 -37.558882M18101932-0930066 272.580527 -9.501842M18120031-1350169 273.001326 -13.8380312M18121957-2926310 273.081553 -29.4419542M18315425-2328124 277.976045 -23.4701212M18334592-2903253 278.441366 -29.0570342M18360807-2314389 279.033649 -23.2441652M18364041-3402389 279.168375 -34.0441472M18425902-3007370 280.74595 -30.1269492M18442352-3029411 281.098036 -30.4947642M18475308-2602331 281.971167 -26.0425282M18562844-2814085 284.118507 -28.235722M18594405-3651518 284.933562 -36.8643912M19175998-2919360 289.499952 -29.326691 MNRAS000