arXiv:1901.09302v1 [astro-ph.GA] 27 Jan 2019 c ecie bv.Hg-eouinsetocp ( spectroscopy address High-resolution to above. capabilities described their ics exploit fully to necessary 200 is al. et Roškar (e.g. 2 migration 2017). al. al. radial et et or dy- time Anders Cantat-Gaudin 2016) and (e.g. with al. 2011), et orbits evolution Reddy Pancino individual & Carrera its al e.g. et 2011; Netopil namics, and al. 2016; et 2017) Andreuzzi al. the (e.g. al. et Friel both Jacobson et (e.g. Casamiquela trace 2015a; the gradient 2016; to al. in et metallicity used Donati everywhere disk widely found 2002; e.g. been are chemistry, o and have disk ages they loss, of disk, mass range Galactic stragglers, wide blue a initia cover of function, di creation mass atomic the individual initial fraction, varie both as a nary such of investigate to topics understanding play allowing systems astrophysical evolution our These stellar in (2016). group al. and role et Liu fundamental also chemi- a see only al. but et the 2016) Silva probably Bovy De few (e.g. are populations a stellar They homogeneous place. and cally c and 10 a birth-time with between features mon of chemo-dynamical share groupings that stars are thousand (OCs) clusters Open Introduction 1. vr o oeOsteesuishv enlmtdt h de- the to how- limited abundances; been have chemical studies obtain these to OCs way some for direct ever, most the is aur 9 2019 29, January Astronomy .Carrera R. ealdcaatrsto fteOsceia compositio chemical OCs the of characterisation detailed A h ubro ytm ihceia bnacsdtrie f determined abundances chemical with systems of number the pcrsoyw sdpbil vial aaouso surv of catalogues available publicly used we spectroscopy aeas eemndaeaeaudne o a g l i C Si, words. Al, Key Mg, 9 Na, For for abundances literature. average the determined in also determinations have previous have our To not respectively. do samples, GALAH and resolutio APOGEE high from from systems determination velocity radial first the Results. Methods. Aims. Context. oselreouinr oes nwn hi metallicity their Knowing models. evolutionary stellar to aarlae ihsasfrwihhg-rbblt astrom release. high-probability data which second for stars with releases data eevd;accepted ; Received 1 2 4 3 NFOsraoi srnmc iPdv,vcl dell’Oss e-mail: vicolo Padova, di Astronomico INAF-Osservatorio NFOsraoi iAtosc cez el pzo vi Spazio, dello Scienza e Astrofisica di INAF-Osservatorio aoaor ’srpyiu eBreu,Ui.Bordeaux, Univ. Bordeaux, de d’Astrophysique Laboratoire ntttd inisdlCso,Uiesttd acln ( Barcelona de Universitat Cosmos, del Ciències de Institut ff so mn tes hnst h atta OCs that fact the to Thanks others. among usion oices h ubro pncutr ihrda velociti radial with clusters open of number the increase To & 1 pncutr r da aoaoist netgt varie a investigate to laboratories ideal are clusters Open ailvlcte aebe eemndfr11ad1 cluste 14 and 131 for determined been have velocities Radial .Bragaglia A. , [email protected] pncutrsashv enietfidi h PGEadGALA and APOGEE the in identified been have stars cluster Open Astrophysics Combining tr:audne aay pncutr n associations and clusters open Galaxy: - abundances Stars: pncutr nAOE n GALAH and APOGEE in clusters Open aucitn.apogee_galah_astroph no. manuscript 2 .Cantat-Gaudin T. , Gaia n rudbsdsetocpcsurveys spectroscopic ground-based and Jordi 3 3 .Vallenari A. , R .Sordo R. , ≥ h top- the 20,000) pcr o 6sses rnaudne aebe obtained been have abundances Iron systems. 16 for spectra n n osbydtie hmclaudne steeoeimp therefore is abundances chemical detailed possibly and ti ebrhphsbe eie nmn lseso h bas the on clusters many in derived been has membership etric 2007; y ncmiainwith combination in eys tal. et of ty bi- l n lsesi h PGEadGLHsmls respectivel samples, GALAH and APOGEE the in clusters 7 and 0 016; ABSTRACT om- ECU) at rnus1 -82 acln,Spain Barcelona, E-08028 1, Franquès i Martí IEEC-UB), .Gbti93 Gobetti P. a raoi ,312Pdv,Italy Padova, 35122 5, ervatorio 8; o ihrslto pcrsoyi tl small. still is spectroscopy resolution high rom NS 1N lé Geo allée B18N, CNRS, ,C,M,adNi. and Mn, Cr, a, n r . 1 n .Soubiran C. and , yo srpyia ois rmtepoete fteGalac the of properties the from topics, astrophysical of ty nweg 6o hs lses(7i PGEad9i GALAH) in 9 and APOGEE in (57 clusters these of 66 knowledge 1 h emmtliiyi loue orfrt h vrl abun overall [M the as to denoted refer helium, to than heavier used elements also is metallicity term the rtr.Tgte ihteio bnac,tpclydenot typically abundance, iron the with Together erature. oin.Ti ssplmne yvr ihacrc all-sk high-accuracy brightes the Gaia very prop for and by Additionally, measurements. parallaxes supplemented photometric positions, is unprecedente quality This an high motions. providing of astronomy volume in large revolution a out ing metallicit as known widely content, iron the of termination n nteftr twl rvd oeifrainaotthei about information some 2013). provide al. will et (Bailer-Jones it composition future chemical the in and s to thanks likel the discovered a like are being et that are Kos clusters objects new for but e.g. clusters), 2018, (see al. clusters et real Cantat-Gaudin as 3 2018b; confirmed (2002, these be of to al. many need et only cluster objects Dias not real unknown; The by largely still MWSC). compilations is (2013, population al. OCs et used Kharchenko and versions most DAML) updated two the to the 2014; according OCs the of al. known represent et 3000 They 2016). Heiter about al. the et 2012; of Netopil compilations 2015a; al. al. literature et Yong et the Donati 2011; e.g. Pancino (see sligh & for objects Carrera performed 100 been than has analysis more of kind this Moreover, 1 sadceia bnacsdtrie rmhg resolution high from determined abundances chemical and es .Balaguer-Núñez L. , hr ssm miut nteueo h emo ealct i metallicity of term the of use the in ambiguity some is There The general : sfo PGEadGLHdt,rsetvl.Ti is This respectively. data, GALAH and APOGEE from rs sas rvdn ailvlcte Sroet ta.2018 al. et (Sartoretti velocities radial providing also is Gaia / Gaia ,419Blga Italy Bologna, 40129 3, pcrsoi uvy ycosmthn hi latest their cross-matching by surveys spectroscopic H iso selater). (see mission Gaia iso Gi olbrto ta.21)i carry- is 2016) al. et Collaboration (Gaia mission 4 ff o an-iar,F365Psa,France Pessac, F-33615 Saint-Hilaire, roy data. 3 .Bossini D. , 1 ril ubr ae1o 20 of 1 page number, Article .Casamiquela L. , / H]. rat However, ortant. so the of is o 0ad14 and 90 for
c i disk tic da [Fe as ed S 2019 ESO ac fall of dance ,we y, Gaia h lit- the n 4 urveys stars t C. , not y 10% 000 / H], y tly by er 1 l. y d r ) . A&A proofs: manuscript no. apogee_galah_astroph
Complementing the limited spectroscopic capabilities of Table 1. Number of stars with a membership probability above a given Gaia is the motivation of the several ongoing and forthcom- cut, and the corresponding number of OCs with at least one star. ing ground-based high-resolution spectroscopic surveys provid- p ing radial velocities and chemical abundances for more than Nr Stars Nr OCs 20 chemical species. At the moment the Gaia-ESO Survey 0.1 1638 175 ≥0.2 1559 164 (GES Gilmore et al. 2012; Randich et al. 2013) is the only high- ≥ resolution survey which has dedicated a significant fraction of 0.3 1494 152 ≥0.4 1447 138 time to target open clusters. Gaia-ESO is providing an ho- ≥ mogeneous set for about 80 clusters (see e.g. Jacobson et al. 0.5 1406 131 ≥0.6 1370 129 2016; Randich et al. 2018, and references therein) observed ex- ≥ tensively (100-1000 stars targeted in each of them). The other 0.7 1315 124 ≥0.8 1222 119 two high-resolution surveys with data published until now, ≥ APOGEE (Apache Point Observatory Galactic Evolution Exper- 0.9 1082 108 =≥ iment; Majewski et al. 2017) and GALAH (Galactic Archaeol- 1.0 852 84 ogy with HERMES; De Silva et al. 2015), do not have such a large and specific program on OCs, although they are targeting some of them, also for calibration purposes (see e.g. Donor et al. We refer the reader to that paper for details on how the prob- 2018; Kos et al. 2018a). Their latest data releases include about abilities are assigned. 277,000 (Holtzman et al. 2018) and 340,000 (Buder et al. 2018) stars, respectively. 2.1. APOGEE This paper is the third of a series devoted to the study of OCs on the basis of Gaia DR2. In the first one, membership probabil- In the framework of the third and fourth phases of the Sloan ities for OCs were derived from the Gaia DR2 astrometric solu- Digital Sky Survey (Eisenstein et al. 2011; Blanton et al. 2017), tions (Cantat-Gaudin et al. 2018). In the second, the Gaia DR2 APOGEE (Majewski et al. 2017) obtained R 22,500 spectra in ∼ radial velocities were used to investigate the distribution of OCs the infrared H-band, 1.5-1.7 µm. The fourteenth Data Release in the 6D space (Soubiranet al. 2018). The goal of this paper (DR14, Abolfathi et al. 2018; Holtzman et al. 2018) includes is to search for cluster stars hidden in both the APOGEE and about 277,000 stars and provides RVs with a typical uncertainty 1 GALAH catalogues2 in order to increase the number of OCs of 0.1 kms− (Nidever et al. 2015). Because APOGEE tries to ∼ with radial velocities and chemical abundances derived from observe each star at least three times, the RV uncertainty, called high resolution spectroscopy. To do so, we use the astromet- RV_scatter and defined as the scatter among the individual RV ric membership probabilities obtained by Cantat-Gaudin et al. determinations, provides a possible indication of stellar bina- (2018). rity. Stellar parameters and abundances for 19 chemical species This paper is organized as follows. The observational mate- are determined with the APOGEE stellar parameter and chem- rial utilized in the paper is described in Sect. 2. The radial veloc- ical abundance pipeline (ASPCAP; García Pérez et al. 2016). ities are discussed in Sect. 3. The iron and other elements abun- Briefly, ASPCAP works in two steps: it first determines stellar dances are presented in Sect. 4 and 5, respectively. An example parameters using a global fit over the entire spectral range by of the usefulness of the results obtained in previous sections to comparing the observed spectrum with a grid of synthetic spec- investigate the radial and vertical chemical distribution of OCs tra, and then it fits sequentially for individual elemental abun- in the Galactic disk is shown in Sect.6. Finally, the main conclu- dances over limited spectral windows using the initially derived sions of this paper are discussed in Sect. 7. parameters. APOGEE has observed a few OCs to serve as calibra- tors (see Holtzman et al. 2018). Other OC stars have been ob- served in the framework of the Open Cluster Chemical Abun- 2. The Data dances and Mapping (OCCAM) survey (Frinchaboy et al. 2013; The Gaia DR2 provides 5-parameter astrometric solution (posi- Donor et al. 2018) when the clusters were in the field of view of tions, proper motions µα , µδ, and parallaxes ̟; Lindegren et al. a main survey pointing. Finally, there may be also cluster stars ∗ 2018) and magnitudes in three photometric bands (G, GBP observed by chance among the survey targets. The latter is the and GRP; Evans et al. 2018) for more than 1.3 billion sources main goal of this paper. (Gaia Collaboration et al. 2018), plus radial velocities (RV) for We cross-matched the Gaia DR2 high probability OC mem- more than 7 million stars (Katzet al. 2018). On the basis of bers with the whole APOGEE DR14 dataset. We excluded those Gaia DR2, Cantat-Gaudin et al. (2018) determined membership objects flagged in STARFLAG as having: many bad pixels ( ≥ probabilities for stars in 1229 OCs, 60 of which are new clusters 40%), low signal-to-noise ratio ( 50 per half-resolution ele- ≤ serendipitously discovered in the fields analysed. Because of the ment), or potentially binary stars with significant RV variation 1 large uncertainties of the proper motion and parallax determi- among visits (RV_scatter 5 kms− ). We rejected also those ≥ nations for faint objects, the analysis was limited to stars with objects that are clearly out of the cluster sequences, which usu- G 18, corresponding to a typical uncertainty of 0.3 masyr 1 ally have low probabilities, p 0.6. Finally, a dozen of stars were − ≤ and≤ 0.15mas in proper motion and parallax, respectively. To rejected because they have been reported as non cluster members assign the membership probabilities, p, they used the unsu- on basis of their radial velocities in the literature. This step re- pervised photometric membership assignment in stellar clusters jects one cluster, Berkeley 44, where the observed star has an (UPMASK) developed by Krone-Martins & Moitinho (2014). astrometric membership of 0.6 but it is a field object according to Hayes & Friel (2014). In fact the RV of this star is quite differ- 2 We also searched the public Gaia-ESO catalogue (DR3, see ent from the mean value derived for this cluster in the literature. https://www.eso.org/qi/) for unrecognised cluster stars but found Cantat-Gaudin et al. (2018) provide discrete astrometric only one additional star in one cluster, so we did not proceed further. probabilities p for each star to belong to its parent cluster. It takes
Article number, page 2 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH
8 STDDEV 2010; Sheinis et al. 2015). HERMES provides simultaneous MAD spectra of up to 392 objects with a resolution power of ]
-1 MEAN 6 28,000 in four wavelength bands: 4713-4903Å (blue arm),
[km s 5648-5873Å (green arm), 6478-6737Å (red arm), and 7585- 1.0 4
-RV 7887Å (infrared arm). The GALAH second Data Release (DR2 i
RV 2 Buder et al. 2018) includes about 340,000 stars. Radial veloci- ties and their uncertainties in GALAH are computed by cross- 0 correlating the observed spectra with 15 synthetic AMBRE 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 probability spectra (de Laverny et al. 2012). The typical RV uncertainty 1 in GALAH DR2 is 0.1kms− (Zwitter et al. 2018). GALAH Fig. 1. Run of standard deviation (STDDEV, red), median absolute de- chemical analysis is∼ performed in two steps (see Buder et al. viation (MAD, green), and mean (blue) of the difference between the 2018, for details). Briefly, the stellar parameters and abundances ff mean RV obtained using di erent probability cuts and those obtained of a training set of about 10,500 stars are first found by spec- only for stars with p=1 for the 30 clusters with 4 or more stars with the highest probability. tral synthesis with the Spectroscopy Made Easy code (SME, Valenti & Piskunov 1996; Piskunov & Valenti 2017). The ob- tained results are then used to train the The Cannon (Ness et al. values between 0.1, least likely, and 1.0, most likely, with a step 2015) data-driven algorithm to find stellar parameters and abun- of 0.1. The derived average RV and chemical abundances can dances for the whole GALAH sample. significantly change as a function of the probability threshold According to Buder et al. (2018), open clusters are not part used to select the most probable members. Moreover, the total of the fields already released by GALAH but are observed by number of OCs for which a mean RV, and also chemical compo- several separate programmes with HERMES, i.e. with the same sition, can be computed also depends on the adopted probability instrument. Some OCs were used in Buder et al. (2018) as a test cut, as shown in Table 1. Although using a low probability cut of the GALAH results (see later for further details). Kos et al. can add stars and clusters to the analysis, it also increases the dis- (2018a) combined Gaia DR2 and GALAH to study five candi- persion of the derived values since some low probability mem- date low-density, high-latitude clusters, finding that only one of bers are not real members. It is necessary, therefore, to find an them, NGC 1901, can be considered a cluster, while the others optimal selection threshold. To do so, the strategy developed in are only chance projections of stars. Similar results have been Soubiran et al. (2018) has been followed computing the average found by Cantat-Gaudin et al. (2018) for many high-latitude RV for the 30 clusters with 4 or more stars with p =1 using dif- candidate clusters. ferent probability cuts. The mean RV values have been obtained using While GALAH and the linked private projects are target- ing OCs on purpose, there may be also cluster stars observed serendipitously and we looked for them. After cross-matching RVi gi RV = i × (1) the Cantat-Gaudin et al. (2018) high-probability members (p g 0.5) with GALAH DR2 we found122 stars in 14 OCs. We list in≥ P i i Table A.2 parameters from Gaia (G, GBP-GRP, ̟, µα , µδ) and where RVPi is the individual RV derived by APOGEE with the GALAH (RV, T , log g, v sin i, [Fe/H]) for the individual∗ stars. 2 eff weight gi defined as gi = 1/(RV_scatteri) , where, RV_scatteri Among them, we selected those stars without problems during is the radial velocity scatter provided by APOGEE. The Cannon analysis, labelled as flag_cannon=0, or that need In Fig. 1 we have plotted the standard deviation (STDDEV, only some extrapolation, flag_cannon=1 (see Buder et al. 2018, red), median absolute deviation (MAD; green), and mean (blue) for more details). After applying these constrains we are left with of the difference between the mean RV obtained using differ- 82 stars in 14 clusters. ent probability cuts, RVi, and the value obtained using only stars Since the majority of the clusters are young,the stars targeted with p=1, RV1.0.Themeanof thedifference does not change sig- nificantly for the different cuts, but we see a decrease at p > 0.5. are mostly on the main-sequence (MS; there are giants only in The MAD is almost flat for p 0.4 and it differs significantly be- NGC 2243 and NGC 2548). Furthermore, they are often of early tween p=0.3 and p=0.4. The≥ same trend is observed in the stan- spectral types and may show high rotational velocities. Their RV dard deviation but in this case the main increase is observed be- determination is then less reliable (the same is valid for metallic- tween p=0.4 and p=0.5. As a result of this analysis we limit our ity, see Sect. 4.2) and we tried to keep only the stars with v sin i 1 analysis to those stars with p 0.5. We note that Soubiran et al. values lower than 20 km s− . In addition, candidate members ac- (2018) considered members with≥ probabilities p 0.4 based on cording to astrometry show discrepant RVs in some clusters (see other reference values from the literature. ≥ Table A.2). To select only the highest probability cluster mem- In total we found 1406 stars with p 0.5 belonging to bers based both on astrometry and RV, we used the average clus- 131 open clusters in common between APOGEE≥ DR14 and ter RVs determined by Soubiran et al. (2018) using Gaia DR2 Gaia-DR2 (Cantat-Gaudin et al. 2018). These 131 systems are data (at least 4 stars were sampled in all these OCs). This af- listed in Table 2. A few examples of colour-magnitude diagrams fects only five clusters: ASCC 21, Alessi 24, Alessi-Teutsch 12, (CMD) of these clusters are shown in Fig. 2. The individual stars NGC 5640, and Turner 5. One discrepant radial velocity star are listed in Table A.1. have been discarded in each of them. After all this weeding we ended up with 29 stars in 14 clus- 2.2. GALAH ters; in half of the cases only one star survived the selections. The properties of these stars are summarised in Table A.3, Fig. 3 The GALAH survey (De Silva et al. 2015; Martell et al. 2017) is shows the CMD of the 14 OCs and the stars used in our analysis a Large Observing Program using the High Efficiency and Res- indicated, while Table 3 lists the 14 OCs and their mean RV and olution Multi-Element Spectrograph (HERMES, Barden et al. metallicity.
Article number, page 3 of 20 A&A proofs: manuscript no. apogee_galah_astroph
Table 2. The 131 open clusters in common between APOGEE DR14 and Cantat-Gaudin et al. (2018).
b Cluster Star RV σRV eRV Nr RVlit σRV,lit Nrlit RVGDR2 σGDR2 NrGDR2 [Fe/H] σ[Fe/H] e[Fe/H] Nr [Fe/H]lit σ[Fe/H],lit Nrlit Ref. a 1 1 1 type (km s− ) (km s− ) (km s− ) (dex) (dex) Alessi 20 MS -14.89 0.37 1 -11.5 0.01 2 -5.04 3.3 7 1 ASCC 124 MS -23.35 0.54 0.38 2 ASCC 16 MS 17.41 0.62 1 23.18 3.4 15 ASCC 21 MS 16.30 5.66 1.30 19 18.57 2.12 9 18.7 4.45 9 0.01 0.09 0.03 10 2 Basel 11b RGB 2.68 0.06 0.04 2 3.43 1.46 3 0.014 0.05 0.04 2 Berkeley 17 RGB -73.34 0.41 0.13 9 -73.4 0.4 7 -71.95 1.77 7 -0.10 0.04 0.01 9 -0.11 0.03 7 3 Berkeley 19 RGB 17.44 0.0 0.08 1 17.65 0.42 1 -0.22 0.01 1 Berkeley 29 RGB 25.27 0.53 0.30 3 24.8 1.13 11 50.58 0.94 1 1 Berkeley 31 RGB 57.87 0.65 0.46 2 61.0 3.75 17 -0.305 0.037 0.026 2 -0.31 0.06 2 1,12 Berkeley 33 RGB 77.80 0.56 0.28 4 76.6 0.5 5 78.82 1.12 4 -0.23 0.11 0.05 4 2 Berkeley 43 RGB 29.712 0.136 1 29.15 1.42 9 0.00 0.01 1 Berkeley 53 RGB -35.77 0.82 0.29 8 -36.3 0.5 4 -34.9 1.81 7 -0.02 0.03 0.01 6 0.00 0.02 5 3
References. (1) Kharchenko et al. (2013); (2) Dias et al. (2002); (3) Donor et al. (2018); (4) Casamiquela et al. (2016); (5) Carrera et al. (2017); (6) Donati et al. (2015b); (7) Magrini et al. (2017); (8) Schiappacasse-Ulloa et al. (2018); (9) Blanco-Cuaresma et al. (2015); (10) Heiter et al. (2014); (11) Zacsˇ et al. (2011); (12) Friel et al. (2010); (13) Monroe & Pilachowski (2010). Notes. (a) Type of stars used in the analysis: (RGB) red giant branch, (MS) main-sequence, or both. . (b) From Soubiran et al. (2018). The entire version will be available on-line.
Table 3. Properties of the 14 open clusters in common between GALAH DR2 and Cantat-Gaudin et al. (2018).
a b Cluster Star RV σRV eRV v sin i star Nr RVGDR2 σGDR2 NrGDR2 [Fe/H] σ[Fe/H] e[Fe/H] Nr [Fe/H]lit σ[Fe/H],lit Nrlit Ref. h1 i 1 type (km s− ) (km s− ) (dex) (dex) Alessi 24 MS 10.44 0.11 11.63 1 12.32 2.24 14 -0.13 0.07 1 Alessi 9 MS -5.64 0.11 5.70 1 -6.44 1.14 39 -0.06 0.07 1 Alessi-Teutsch 12 MS -11.00 0.12 5.35 1 -5.88 3.54 6 0.40 0.08 1 ASCC 16 MS 22.01 0.17 38.82c 1 23.18 3.40 15 -0.08d 0.06 1 ASCC 21 MS 20.05 1.06 19.99c 1 18.70 4.45 9 -0.13d 0.08 1 Collinder 135 MS 17.080.960.68 18.31 2 16.03 2.21 51 -0.09 0.03 0.02 2 Collinder 359 MS 8.30 1.79 57.53c 1 5.28 3.25 12 -0.66d 0.08 1 Mamajek4 MS -28.092.190.98 6.95 5 -26.32 3.17 34 0.09 0.17 0.08 5 NGC2243 RGB 59.320.570.23 7.36 6 59.63 1.06 4 -0.31 0.05 0.02 6 -0.43 0.04 16 1 NGC2516 MS 26.01 1.400.81 34.10c 3 23.85 2.01 132 -0.26d 0.05 0.03 3 0.06 0.05 13 1 NGC2548 RGB 8.45 0.400.28 5.20 2 8.85 1.08 14 0.16 0.01 0.04 2 NGC3680 MS 2.98 1.99 33.54c 1 1.74 1.36 30 -0.26d 0.07 1 -0.01 0.06 10 2 NGC5460 MS -5.16 0.310.22 23.79c 2 -4.61 2.77 5 -0.32d 0.15 0.11 2 Turner5 MS -2.83 0.090.07 11.77 2 -3.49 1.93 6 0.02 0.17 0.12 2
References. (1) Magrini et al. (2017); (2) Netopil et al. (2016) Notes. (a) Mean of the individual values for those clusters with more than one stars. (b) From Soubiran et al. (2018) (c) Values for clusters where 1 (d) 1 v sin i > 20 km s− are considered uncertain. [Fe/H] uncertain because v sin i > 20 km s− . h i h i
3. Radial Velocities values are listed in Table 2. In total we have determined mean 3.1. APOGEE RV for 131 clusters. For 78 of them, about 65% of the total, this RV determination is based on less than 4 stars and the values The mean RV for each cluster has been computed using equa- have to be taken with caution. For the other 53 systems the RV tion 1 described above. The internal velocity dispersion is de- is determined from 4 stars or more. In principle these values are rived as more reliable except if they show a large σRV . Large σRV values can be due to undetected binaries but also by residual field stars contamination. 2 n i gi (RVi RV) σRV = × − (2) n 1 × gi s − P i For the majority of the OCs the RV determination is based on either giant or MS stars. In general, the systems whose RVs with an uncertainty of P have been determined from MS stars have larger σRV values be- σRV cause of the larger RV uncertainties for these stars. There are eRV = (3) √n 9 clusters with both kind of stars sampled: Berkeley 71, Berke- ley 85, Berkeley 9, King 7, NGC 1664, NGC 1857, NGC 2682, For those clusters with only one star sampled we did not NGC 6811, and NGC 7782. Except for NGC 1664, at least 5 compute σRV and we assumed eRV = RV_scatteri. The obtained stars have been observed in each of them. There are not signifi-
Article number, page 4 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH
5 Alessi 20 ASCC 124 ASCC 16 ASCC 21
10 Gmag
15
5 Basel 11b Berkeley 17 Berkeley 19 Berkeley 29
10 Gmag
15
5 Berkeley 31 Berkeley 33 Berkeley 43 Berkeley 53
10 Gmag
15
5 Berkeley 66 Berkeley 71 Berkeley 7 Berkeley 85
10 Gmag
15
0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4
GBP-GRP GBP-GRP GBP-GRP GBP-GRP
Fig. 2. Gaia DR2 colour-magnitude diagrams for OCs with stars in common with APOGEE DR14. Grey circles are Gaia DR2 stars with a membership probability above 0.5. Open red squares are stars in common with APOGEE DR14 used in the RV determination (see text for details). Filled blue squares are objects used in the [Fe/H] analysis. cant differences in the mean RV values if we use only MS stars based on the Gaia DR2 catalogue and the RVs obtained with the or giants. Gaia RVS instrument, using a pre-selection done on our same as- trometric membership probabilities (Cantat-Gaudin et al. 2018). There are 104 clusters in common with the recent work by The top panel of Fig. 4 shows the comparison between the Soubiran et al. (2018). They derived mean RVs for 861 OCs
Article number, page 5 of 20 A&A proofs: manuscript no. apogee_galah_astroph
5 Alessi 24 Alessi 9 Alessi Teutsch 12 ASCC 16
10 Gmag
15
5 ASCC 21 Collinder 135 Collinder 359 Mamajek 4
10 Gmag
15
5 NGC 2243 NGC 2516 NGC 2548 NGC 3680
10 Gmag
15
5 NGC 5460 Turner 5
10 Gmag
15
0 1 2 3 4 0 1 2 3 4
GBP-GRP GBP-GRP
Fig. 3. As in Fig. 2 for the 14 clusters in the GALAH sample. Note that one star in NGC 2516 and one in Turner 5 have no colour information and were arbitrarily plotted at GBP-GRP=0.
RV for the 104 clusters in common. The RV differences, ∆RV, median difference between Gaia DR2 and our APOGEE sam- 1 1 defined as RVGaia DR2 RVAPOGEE , are shown in the bottom ple is 0.4kms− with a median absolute deviation of 3.2kms− . panel of Fig. 4. In general,− there is a very good agreement However, there are a few cases that show significantly differ- between both samples for most of the clusters in spite of the ent RVs. All these clusters have only a few sampled stars ei- 1 Gaia DR2 typical uncertainties being larger than 2.5kms− . The ther in our APOGEE sample or in the Gaia DR2 sample. For
Article number, page 6 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH
50 50 ] ] -1 -1 [km s 0 [km s 0 literature Gaia DR2
RV Trumpler 2
RV Czernik 20 IC 4996 NGC 457 -50 -50 ] ]
-1 20 -1 20 10 10 0 0
RV [km s -10 RV [km s -10 ∆ -20 ∆ -20 -50 0 50 -50 0 50 -1 -1 RVAPOGEE [km s ] RVAPOGEE [km s ]
Fig. 4. Comparison between RV derived from APOGEE DR14 and Fig. 5. Comparison between RV derived from APOGEE DR14 and lit- Gaia DR2. Blue points are clusters with 4 or more stars while red points erature. Blue and red points have the same meaning as in Fig 4. are systems with less then 4 stars.
to derive their mean RV and given their small σRV , we believe example, in the case of the system with the largest difference, that our determinations are reliable. For the remaining clusters IC 4996, the values in both samples have been obtained for the RV determinations are based on one star only, with the ex- only one candidate member. The RV from the star observed by ception of ASCC 124 and Czernik 18 with two and three stars, 1 APOGEE is 78.5 0.3kms− , while in Gaia DR2, from a differ- respectively. As commented before, their RV are less reliable. ± 1 1 ent star, the obtained value is -29.1 2.9kms− . None of them Eight systems have σRV values larger than 6kms− . The ± 1 is similar to the value of -2.5 5.7kms− based on 4 stars cited largest internal dispersion is obtained for NGC 366 with ± 1 1 in Kharchenko et al. (2013), or to the value of 12 5 km s− σRV 21kms− . This value has been obtained from 4 stars with found from pre-main-sequence stars by Delgado− et± al. (1999). p 0.9∼ but with very different individual RV. In the case of ≥ 1 More data are required in cases such as this. NGC 2183 we found σRV 13kms− . This value is obtained ∼ 1 In addition to the Soubiran et al. (2018) work, we have com- from 5 stars with RVs between 7.4 and 43.1 kms− . However piled other RV determinations in the literature using the updated the two stars with the highest priorities, p=1 and 0.8, have RV of 28.9 0.2 and 25.4 0.1kms 1, respectively. All the stars in version of the DAML and MWSC catalogues as starting point ± ± − and adding recent determinations available in the literature. In NGC 2183 have only one APOGEE visit and therefore the RV total we have compiled RVs for 75 of the 131 OCs in our sam- determinations are more uncertain. The remaining six clusters ple (see Table 2 where also references are indicated). The com- (Koposov 36, NGC 2304, NGC 7086, Rosland 6, Trumpler 2, 1 parison between the RV values obtained in this work and the and Trumpler 3) have σRV between6 and 10kms− . The number literature is shown in the top panel of Fig. 5, while the bottom of potential members sampled by APOGEE in these systems is panel shows the behaviour of the differences between them. As between 4 and 8 stars. Almost all the stars in these clusters have higher membership probabilities, p 0.8. Since all of them are before, the largest discrepancies are generally observed for those ≥ clusters with less than 4 stars sampled (red points). In fact, the main-sequence stars, their individual RV determination can be literature determinations for these clusters are also based on 4 affected by the large rotational velocities. Three of these clusters objects or less, with the exception of NGC 457. In Czernik 20 have determination of their RV in the literature (see Table 2). In and Trumpler 2 we have 7 and 5 stars, respectively. For Trum- spite of the large RV dispersion observed in two of these clusters, pler 2 we found a large σRV which implies that our RV determi- NGC 2304 and NGC 7086, we find a good agreement with the nation is not very reliable (see below). In the case of Czernik 20 values listed in the literature (Wu et al. 2009; Kharchenko et al. the literature value has been obtained from a single star with an 2013). 1 uncertainty of 10kms− . This value is much larger than the in- ternal dispersion found in our work from 7 stars. For this reason 3.2. GALAH we consider our RV determination more reliable. To our knowledge this is the first RV determination for The same procedure followed above for APOGEE has been used 16 clusters: ASCC 124, Berkeley 7, Berkeley 98, Czernik 18, to derive the mean RV, internal velocity dispersion, and uncer- Dolidze 3, FSR 0826, FSR 0941, Kronberger 57, L 1641S, tainty for the 14 OCs in the GALAH sample. The obtained val- NGC 1579, NGC 6469, Ruprecht 148, Stock 4, Teutsch 1, ues are listed in Table 3. Teutsch 12, and Tombaugh 4. In the case of L 1641S our RV Radial velocities for all the clusters in the GALAH sam- determination is based on 43 stars with an internal dispersion ple have been determined previously by Soubiran et al. (2018) 1 σRV 2kms− . Two clusters, Berkeley 98 and Teutsch 12, have from Gaia DR2. The comparison between the RVs measured by ∼ 1 5 potential members with a σRV of 3.3 and 2.3kms− , respec- GALAH and those by Gaia DR2 for the 14 clusters is shown in tively. Due to the number of objects used in these three systems Fig. 6. The median difference between Gaia DR2 and GALAH
Article number, page 7 of 20 A&A proofs: manuscript no. apogee_galah_astroph
gravity, and microturbulent velocity. In this paper we focus on the individual iron abundances. In contrast with the RV case, the average [Fe/H] of each cluster has been obtained as the un- weighted mean of the individual iron abundances. We have com- puted also σ[Fe/H] as the un-weighted standard deviation and e σ[Fe/H] 3 [Fe/H] as √n . Again for those clusters with only one sampled star we did not compute the standard deviation, σ[Fe/H], and we assume the uncertainty e[Fe/H], as the uncertainty for this star, σ[Fe/H],i. The obtained values are listed in Table 2. For 32 systems our [Fe/H] determination is based on 4 stars or more. Except for Berkeley 33, the σ[Fe/H] is lower than 0.1 dex, the typical uncertainty in the APOGEE [Fe/H] determination. The [Fe/H] determination for the other 58 clusters is based on less than 4 stars and typically on only one object. Fig. 6. Comparison between RV derived from GALAH DR2 and Gaia DR2, colour-coded according to v sin i . To our knowledge there are previous determinations of iron h i abundances from high resolution spectra for a third of the total sample. The comparison between the values derived here and 1 1 is 0.3kms− with a median absolute deviation of 1.5km s− . the literature (see Table 2 for references) is shown in Fig. 7. In The RVs are in reasonable agreement taken into account that general,there is a very good agreement,with a median difference the individual RV uncertainties in the Gaia DR2 are on aver- 0.00dex with a median absolute deviation of 0.02dex. This is 1 age of 2.5kms− . The largest differences for some clusters (e.g. not unexpected since several OCs have been used as reference to Collinder 359 and NGC 2517) are explained by their large aver- calibrate the whole APOGEE sample assuming values available age v sin i values. in the literature (see Holtzman et al. 2018, for details). h i The clusters NGC 2243 and NGC 2516 have been observed For the 57 clusters not studied previously only in 9 of them 1 also by Gaia-ESO and their mean RV are +60.2 (rms 1.0)km s− the metallicity determination is based on 4 or more stars. Two or 1 and +23.6 (rms 0.8)km s− , respectively (Jackson et al. 2016; three stars have been sampled for 16 of these systems. Finally, 1 Magrini et al. 2017). For NGC 2243 we obtained 59.3km s− the metallicity determination for 32 previously unstudied clus- 1 with σRV =0.6km s− from 6 giant stars. The values are in good ters is based on a single star. agreement within the uncertainties. In the case of NGC 2516 we 1 1 obtained 26.0km s− with σRV =1.4km s− from 3 MS stars. The difference between GALAH and Gaia-ESO mean RV could be 4.2. GALAH due to the fact that the three stars in the GALAH sample have 1 In the case of GALAH the constraints applied initially also en- vsin i larger than 29km s− . sure that the iron abundance has been determined for all the stars Four of the GALAH clusters are also among the APOGEE in the sample. The average metallicities for the clusters in the systems discussed in previous section. These clusters are GALAH sample has been derived using the same procedure as ASCC 16, ASCC 21, Collinder 359, and NGC 2243. In the case in the case of APOGEE. The obtained values are listed in Ta- of NGC 2243 there is a good agreement between the values ob- ble 3. tained from both samples in spite of the APOGEE value being Only in two clusters (Mamajek 4 and NGC 2243) our anal- based on only one star. For the other three clusters the differences ysis is based on more than 4 stars. The value obtained here for between GALAH and APOGEE are of the order of 4kms 1. − NGC 2243 is in good agreement with the result obtained by e.g. This is not a large difference taken into account that all± the stars Magrini et al. (2017) and other literature sources. This cluster sampled in these clusters by GALAH have v sin i larger than is also among the clusters studied in the previous section from 20kms 1. − APOGEE. Although the APOGEE analysis is based on a single star, the values are in agreement within the uncertainties. 4. Metallicity Due to the early spectral type and high rotational velocity of the members, we judged as unreliable the metallicity deter- 4.1. APOGEE mination for 6 clusters (ASCC 16, ASCC 21, Collinder 359, Before deriving average metallicity we excluded the stars for NGC 2516, NGC 3680, and NGC 5460). Moreover, their [Fe/H] which the ASPCAP pipeline is not able to find a proper so- values have been determined from 3 stars or less. One of these lution (or not a solution at all) because they are outside of or clusters, ASCC 21, has been also analysed from APOGEE data. close to the edges of the synthetic library used in the analysis, The values obtained from APOGEE and GALAH samples show e.g. hotstars (see García Pérez et al. 2016; Holtzman et al. 2018, a difference of only 0.1dex, in spite of the large v sin i and for details). In this case the stars are flagged in ASPCAPFLAG as STAR_BAD or NO_ASPCAP_RESULT, respectively. After re- 3 Other alternatives have been checked because several clusters can jecting these objecys, the sample is reduced to 862 stars belong- be affected by contamination of non-members such as the weighted ing to 90 clusters. Most of the rejected stars are fast rotating or mean or a Montecarlo simulation. In the first case we used the individ- low gravity objects. ual metallicity uncertainties as weights. For the Montecarlo simulation half of the stars in a given cluster were selected randomly and com- Together with the individual iron abundance [Fe/H] for each puted their mean and standard deviation. This procedure was repeated star, APOGEE DR14 provides the scaled-solar general metal- 103 times and the cluster mean and σ where obtained as the mean of licity, [M/H]. The former is obtained from individual Fe lines the individual means and standard deviations. In any case the differ- whereas the latter is determined as a fundamental atmospheric ences between the obtained values and those derived in the paper are no parameter at the same time as effective temperature, surface larger than 0.02 dex. ± Article number, page 8 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH
have excluded the stars flagged by ASPCAP with problems in 0.4 the abundance determination. We have been able to determine abundances for all the 90 clusters with iron abundances for the majority of elements: Mg, 0.2 Si, Ca, Mn, and Ni (Table A.4). Aluminum abundances have been derived for 89 systems (the missing cluster, IC 1805, has [dex] 0.0 only one star). Several stars have been rejected in the determina- literature tion of chromium content so that the abundances of this element have been determined for 84 systems. Sodium is the element for
[Fe/H] -0.2 which we reject more stars, with Na abundances obtained for only 65 of the 90 clusters. The abundance of Na is determined in APOGEE from two weak and probably blended lines, that -0.4 are easily measured only in GK giants (see Jönsson et al. 2018, for details). Therefore, Na abundances cannot be determined for 0.10 many stars in the sample because they are outside this range. 0.05 0.00 As before, the values obtained here should be used with cau- -0.05 tion. Only the abundances obtained for at least 4 stars and with
[Fe/H] [dex] small internal dispersion can be considered reliable. Owing to
∆ -0.10 -0.4 -0.2 0.0 0.2 0.4 the large heterogeneity of the abundance determinations avail-
[Fe/H]APOGEE [dex] able in the literature we have not tried a comparison. In Fig. 8 we show trends of the abundance ratios obtained Fig. 7. Comparison between [Fe/H] derived from APOGEE DR14 and with [Fe/H] and among all other elements. The most discrepant literature. Red and blue points are clusters with less and more than 4 values are due to clusters with less than 4 stars sampled (grey stars, respectively. points). Clusters with more than 4 stars analysed show, in gen- eral, a scatter compatible with the typical uncertainties. The exceptions are Na and in less degree Cr. The well know dif- high temperature of the only star in GALAH DR2 for this clus- ferences of Na abundances between dwarfs and giants due ter. Other two of these clusters, NGC 2516 and NGC 3680, to extra-mixing can explain this scatter. There is one cluster, have been studied previously in the literature Magrini et al. NGC 2168, for which we obtained [Ca/Fe]=-0.17dex from 10 (e.g. 2017) and Netopil et al. (2016). In comparison with these stars. Although this value is lower than the bulk, its dispersion works, the [Fe/H] values obtained here are about 0.25dex lower. of σ[Ca/Fe]=0.21dex (probably due to the difficulties in measur- Buder et al. (2018) discussed possible shortcomings of GALAH ing main-sequence stars in APOGEE) makes it still compatible DR2 catalogue. They note that the double-step analysis is tai- with the majority. lored on single, non-peculiar stars of F, G, and K spectral types and that some systematic trends may be present. In particular, they note difficulties for hot stars (i.e., hotter than late-F spec- 5.2. GALAH tral type) because they have weaker metal lines, often rotate sig- nificantly, and are not present in the training set; all stars hot- The GALAH DR2 provides abundances for 23 chemical ele- ter than 7000K are then in extrapolation. Furthermore, there is ments including iron (see Buder et al. 2018). For homogeneity a trend in the derived temperatures, with hotter stars showing with the APOGEE sample, we computed average abundances lower temperatures than the comparison samples (e.g. the Gaia for the same 8 elements than above. Following the Buder et al. Benchmark stars or stars for which the IRFM was available, their (2018) recommendations we only use those stars that do not Fig. 14). In turn, this implies a trend towards lower metallici- have problems in the determination of the abundance of a given element (i.e. flag_X_FE=0). Moreover, we also excluded those ties. This is noticeable, for instance, in the Teff, log g diagrams 1 for open clusters (their Fig. 19), with brighter MS stars showing clusters with v sin i >20kms− because the values obtained for systematically lower abundances. This is also what we found for these stars are not reliable. As a result of this, abundances have NGC 2516 and NGC 3680. been determined for only 7 clusters and not for all elements. The obtained values are listed in Table A.5. In summary, the GALAH DR2 sample provides the first The GALAH ratios have been plotted in Fig. 8 as cyan (less [Fe/H] determination for 10 clusters although with different de- than 4 stars) and blue (more than 4 objects) filled circles. Al- grees of reliability because of the large rotational velocities of though the GALAH sample is small, we see that there are no some of the stars analysed. significant differences between APOGEE and GALAH sam- ples for any of the elements studied. Only the metal-poor clus- ter NGC 2243 seems to have a large [Ni/Fe] ratio, +0.22dex 5. Other elements (σ[Ni/Fe]=0.14dex) obtained from 5 stars, in comparison with 5.1. APOGEE other APOGEE clusters of the same [Fe/H]. This cluster is the only one in common with the APOGEE sample with re- Although APOGEE DR14 provides abundances for 22 chem- liable abundances in GALAH. For direct comparison, in the ical elements, not all of them are completely reliable (see case of APOGEE we obtained [Ni/Fe]=0.01dex from a sin- Jönsson et al. 2018; Holtzman et al. 2018). For this reason we gle star with e[Ni/Fe]=0.02dex. Also for Si we found a differ- limit our analysis to the elements that show small systematic dif- ence larger than the the uncertainties: [Si/Fe]=0.09 and -0.04dex ferences in comparison with other literature samples according from APOGEE and GALAH, respectively. Again the APOGEE to Jönsson et al. (2018). This includes α-elements (Mg, Si, and value has been derived from a single star with e[S i/Fe]=0.03dex Ca) and proton-captureelements (Na and Al) as well as elements while the GALAH one has been determined from 4 stars with of the iron-peak group (Cr, Mn and Ni). For each element we σ[Ni/Fe]=0.04dex. For the other elements studied the ratios ob-
Article number, page 9 of 20 A&A proofs: manuscript no. apogee_galah_astroph
0.4
0.0 [Na/Fe] -0.4
0.4
0.0 [Mg/Fe] -0.4
0.4
0.0 [Al/Fe] -0.4
0.4
0.0 [Si/Fe] -0.4
0.4
0.0 [Ca/Fe] -0.4
0.4
0.0 [Cr/Fe] -0.4
0.4
0.0 [Mn/Fe] -0.4
0.4
0.0 [Ni/Fe] -0.4
-0.4 0.0 0.4 -0.4 0.0 0.4 -0.4 0.0 0.4 -0.4 0.0 0.4 -0.4 0.0 0.4 -0.4 0.0 0.4 -0.4 0.0 0.4 -0.4 0.0 0.4 [Fe/H] [Na/Fe] [Mg/Fe] [Al/Fe] [Si/Fe] [Ca/Fe] [Cr/Fe] [Mn/Fe]
Fig. 8. Plot of the abundance ratios for APOGEE and GALAH clusters. Grey and black circles are APOGEE clusters with less and more than 4 stars in the determination of [Fe/H], respectively. Cyan and blue circles are GALAH clusters with less and more than 4 stars in the determination of [Fe/H], respectively. Typical error bars have been plotted in top-right corners. tained from APOGEE and GALAH samples are in agreement produced in approximately equal measure by core collapse and within the uncertainties. type Ia supernovae. Additionally, we present here the behaviour of magnesium as best representative of the α-elements. Not only the production of magnesium is dominated by core collapse su- 6. Galactic trends pernovae, but also the Mg abundances derived by APOGEE and As commented in Sect. 1, information about the chemical com- GALAH show the best agreement with external measurements position of OCs is necessary to address a variety of astrophys- in comparison with other elements of this group (Jönsson et al. ical topics. A clear example of the applicability of the sample 2018; Buder et al. 2018). Given the much larger number of clus- obtained in this work is the study of the chemical gradients in ters involved, the APOGEE data dominate the following discus- the Galactic disk. Generally the chemical gradients in the Galac- sion. The run of [Fe/H] as a function of Galactocentric distance, tic disk are studied using iron (e.g. Netopil et al. 2016), which is Rgc, is plotted in the bottom panel of Fig. 9, while the top panel
Article number, page 10 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH shows the behaviour of [Mg/Fe] with Rgc. Galactocentric dis- tances have been computed by Cantat-Gaudin et al. (2018) from Gaia-DR2 parallaxes; we refer the reader to that paper for details 0.2 about the distance determination. NGC 6791 0.0 The clusters with 4 or more stars, with more trustful mea- NGC 6705 surements (blue symbols), cover a range in Rgc between 6.5 [Mg/Fe] ∼ and 13kpc. Grey symbols are clusters with less reliable mea- -0.2 surements.∼ There is no full agreement about the slope of the gra- dient in this Rgc range and we can found in the literature val- -0.4 d[FeH] 1 ues between -0.035dex kpc− (Cunha et al. 2016) and - dRgc 0.4 NGC 6791 1 ∼ 0.1dexkpc− (Jacobson et al. 2016). Using all the clusters in the APOGEE and GALAH samples with at least 4 stars we found 0.2 d[Fe/H] 1 NGC 6705 =-0.052 0.003dexkpc− (red dashed line). The slope of -0.0 dRgc ± the gradients may depend on the presence of the innermost clus- [Fe/H] ter in the sample, NGC 6705, and the most metal-rich one, -0.2 NGC 6791. Both are peculiar clusters. NGC 6705 is a young -0.4 metal-rich system (see e.g. Cantat-Gaudin et al. 2014) with -0.6 an unexpected high α-elements abundance (Casamiquela et al. 6 8 10 12 14
2018; Magriniet al. 2017). On the contrary, NGC 6791 is an Rgc [kpc] intriguing old very metal-rich and massive system located al- most 1kpc above the Galactic plane. It has been suggested that Fig. 9. Gradient in [Mg/Fe] (top) and [Fe/H] (bottom) as a function of NGC 6791 has likely migrated to its current location from its Rgc for APOGEE (circles) and GALAH (triangles) clusters. Grey sym- bols are clusters with less than four stars. Blue symbols are clusters with birth position (Linden et al. 2017) or even has an extragalactic 4 or more stars sampled. Filled symbols are the clusters for which this origin (Carraro et al. 2006) although both claims are disputed. is the first metallicity determination from high resolution spectroscopy. If we exclude these two clusters from the analysis, the [Fe/H] Green and orange lines show different linear fits (see text for details). 1 gradient flattens to -0.047 0.004dexkpc− . This does not imply The positions of NGC 6705 and NGC 6791 have been marked. that former value is preferred.± It only shows how the gradient changes as a function of the outliers. If we separate the clusters in two groups inside and higher value of [Mg/Fe]=+0.14 0.07dex, in agreement with the d[Fe/H] 1 ± outside Rgc =11kpc we find =-0.077 0.007dexkpc− Gaia-ESO result of +0.10 0.07 (Magrini et al. 2017). There dRgc ± ± d[Fe/H] 1 is a group of clusters at 8kpc which [Mg/Fe] are compati- in the inner region and =0.018 0.009dexkpc− for ∼ dRgc ± ble with the solar one within the uncertainties. At Rgc 8.5kpc the outer region. A similar result has been reported pre- the [Mg/Fe] is clearly lower than the solar. From there∼ the viously (e.g. Carrera & Pancino 2011; Andreuzzi et al. 2011; [Mg/Fe] ratio increases until 10kpc and it flattens from thereof. Frinchaboyet al. 2013; Cantat-Gaudinet al. 2016, among This behaviour has been reported∼ previously in the literature many). If we exclude the two metal-poor cluster at Rgc 11kpc ∼ (e.g. Cantat-Gaudin et al. 2016; Magrini et al. 2017) and it has (NGC 2243 and Trumpler 5) the slope increases until d[Fe/H] =- dRgc been predicted by Galactic chemical evolution models (e.g. 1 Minchev et al. 2014; Kubryk et al. 2015b,a; Grisoni et al. 2018). 0.04 0.01dexkpc− . Therefore, the behaviour in the outermost region± is highly dependent on these clusters. All these results The existence of a vertical gradient is also controversial. are in good agreement with Donor et al. (2018) who also used Several authors do not find any trend of [Fe/H] with the chemical abundances obtained from APOGEE DR14 with a dif- distance to the Galactic plane, Z (e.g. Jacobson et al. 2011; ferent cluster membership selection. Furthermore, the observed Carrera & Pancino 2011). Instead, other studies reported the ex- gradient may change as a function of the age of the clusters istence of a vertical gradient with a slope between -0.34 and 1 used in the analysis (e.g. Friel et al. 2002; Andreuzzi et al. 2011; -0.25dexkpc− (e.g Piatti et al. 1995; Carraro et al. 1998). In Carrera & Pancino 2011; Jacobson et al. 2016). However, age is Fig.10 we plot [Fe/H] and [Mg/Fe] as a function of Z (bottom yet unknown for a large fraction of our clusters and we postpone and upper panel, respectively). In both cases there are no hints to a forthcoming paper a detailed analysis of the evolution of the of the existence of vertical gradients in agreement with most gradient with the age of the clusters. previous studies. We also confirm that clusters located at larger The run of α-element abundances as a function of Galacto- Galactocentric distances cover a larger range of Z. The exception centric radiusis still an open discussion (e.g. Donati et al. 2015a; is NGC 6791 located at Rgc 8kpc and with a height above the plane of Z 900pc. We have∼ already commented that this is a Cantat-Gaudin et al. 2016). Donor et al. (2018) reported a mild ∼ positive gradient for magnesium and other α-elements such as peculiar and not well understood system. oxygen or silicon. On contrast, Yong et al. (2012) and Friel et al. (2014) did not found any dependence with Rgc. A similar re- sult has been found by Cantat-Gaudin et al. (2016) and also by Magrini et al. (2017) using OCs and field stars homogeneously 7. Summary analysed by the Gaia-ESO survey. The top panel of Fig. 9 does Using Gaia DR2 Cantat-Gaudin et al. (2018) determined astro- notshowa cleartrend.Theslopeofthe linearfit (reddashedline) metric membership probabilities for stars belonging to 1229 d[Mg/Fe] 1 to the whole range of Rgc is =0.003 0.002dexkpc− . open clusters. We have cross-matched this catalogue with the dRgc ± The clusters within Rgc 10kpc have, in general, a [Mg/Fe] latest data releases of two of the largest Galactic high-resolution below the solar one. This∼ includes the innermost cluster, spectroscopic surveys, APOGEE and GALAH, with the goal of NGC 6705, for which Casamiquela et al. (2018) has reported a finding high probability OC members.
Article number, page 11 of 20 A&A proofs: manuscript no. apogee_galah_astroph
for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This work has 0.2 made use of APOGEE data. 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 0.0 acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org. [Mg/Fe] SDSS-IV is managed by the Astrophysical Research Consortium for the -0.2 Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon -0.4 University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de 14 0.4 Canarias, The Johns Hopkins University, Kavli Institute for the Physics and 12 Mathematics of the Universe (IPMU) / University of Tokyo, the Korean 0.2 Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut 10 [kpc]
gc für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA -0.0 8 R Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max- Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical [Fe/H] 6 -0.2 Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State -0.4 University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de -0.6 México, University of Arizona, University of Colorado Boulder, University of -1000 -500 0 500 1000 Oxford, University of Portsmouth, University of Utah, University of Virginia, Z [pc] University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. This work has made use of GALAH data, based on data Fig. 10. The run of [Mg/Fe] (top) and [Fe/H] (bottom) as a function of acquired through the Australian Astronomical Observatory, under programmes: the distance to the Galactic plane Z. Symbols are as in Fig. 9. A/2013B/13 (The GALAH pilot survey); A/2014A/25, A/2015A/19, and A2017A/18 (The GALAH survey). We acknowledge the traditional owners of the land on which the AAT stands, the Gamilaraay people, and pay our respects – In the case of APOGEE we have detected stars belonging to elders past and present.This research has made use of Vizier and SIMBAD, to 131 clusters for which we have determined average radial operated at CDS, Strasbourg, France, NASA’s Astrophysical Data System, and TOPCAT (http://www.starlink.ac.uk/topcat/, Taylor 2005). This research made velocities. For 46 systems our determination is based on 4 or use of the cross-match service provided by CDS, Strasbourg. This work was more stars. To our knowledge this is the first radial velocity partly supported by the MINECO (Spanish Ministry of Economy) through grant determination for 16 systems. For the other clusters there isa ESP2016-80079-C2-1-R (MINECO/FEDER, UE) and MDM-2014-0369 of good agreement between the obtained values and those avail- ICCUB (Unidad de Excelencia ’María de Maeztu’). A.B. acknowledges funding able in the literature. [Fe/H] has been obtained for 90 open from PREMIALE 2015 MITiC. clusters, almost two thirds of them without previous determi- nations in the literature. Finally, for the same 90 clusters we have also determined abundances for six elements: Na, Mg, References Al, Si, Ca, Cr, Mn, and Ni. Abolfathi, B., Aguado, D. S., Aguilar, G., et al. 2018, ApJS, 235, 42 – In the case of GALAH we have found stars belonging to 14 Anders, F., Chiappini, C., Minchev, I., et al. 2017, A&A, 600, A70 clusters for which we have determined both radial veloci- Andreuzzi, G., Bragaglia, A., Tosi, M., & Marconi, G. 2011, MNRAS, 412, 1265 ties and iron abundances. Except for two clusters, NGC 2243 Bailer-Jones, C. A. L., Andrae, R., Arcay, B., et al. 2013, A&A, 559, A74 and NGC 2548, the GALAH sample is composed by main- Barden, S. C., Jones, D. J., Barnes, S. I., et al. 2010, in Proc. SPIE, Vol. 7735, Ground-based and Airborne Instrumentation for Astronomy III, 773509 sequence stars, in some cases with significant v sin i values. Blanco-Cuaresma, S., Soubiran, C., Heiter, U., et al. 2015, A&A, 577, A47 These 14 clusters have previous radial velocity determina- Blanton, M. R., Bershady, M. A., Abolfathi, B., et al. 2017, AJ, 154, 28 tion from Gaia DR2. Excluding the two clusters in common Bovy, J. 2016, ApJ, 817, 49 with APOGEE sample, nine of these systems do not have Buder, S., Asplund, M., Duong, L., et al. 2018, MNRAS, 478, 4513 Cantat-Gaudin, T., Donati, P., Vallenari, A., et al. 2016, A&A, 588, A120 previous determinations in the literature from high resolution Cantat-Gaudin, T., Jordi, C., Vallenari, A., et al. 2018, A&A, 618, A93 spectroscopy. For seven clusters we have determined abun- Cantat-Gaudin, T., Vallenari, A., Zaggia, S., et al. 2014, A&A, 569, A17 dances for the same chemical elements that in the case of Carraro, G., Ng, Y. K., & Portinari, L. 1998, MNRAS, 296, 1045 APOGEE. Carraro, G., Villanova, S., Demarque, P., et al. 2006, ApJ, 643, 1151 Carrera, R. & Pancino, E. 2011, A&A, 535, A30 Carrera, R., Rodríguez Espinosa, L., Casamiquela, L., et al. 2017, MNRAS, 470, In summary, to our knowledge this is the first RV determi- 4285 nation from high resolution spectra for 16 open clusters. In the Casamiquela, L., Carrera, R., Balaguer-Núñez, L., et al. 2018, A&A, 610, A66 same way, we provide for the first time iron abundances for 39 Casamiquela, L., Carrera, R., Blanco-Cuaresma, S., et al. 2017, MNRAS, 470, open clusters, 30 from APOGEE and 9 from GALAH, respec- 4363 Casamiquela, L., Carrera, R., Jordi, C., et al. 2016, MNRAS, 458, 3150 tively. Cunha, K., Frinchaboy, P. M., Souto, D., et al. 2016, Astronomische Nachrichten, The obtained catalogue of chemical abundances has been 337, 922 used to investigate the existence of radial and vertical trends us- de Laverny, P., Recio-Blanco, A., Worley, C. C., & Plez, B. 2012, A&A, 544, ing the distances computed from Gaia DR2. Our findings are in A126 De Silva, G. M., Freeman, K. C., Asplund, M., et al. 2007, AJ, 133, 1161 agreement with previous investigations where the radial [Fe/H] De Silva, G. M., Freeman, K. C., Bland-Hawthorn, J., et al. 2015, MNRAS, 449, gradient appears to flatten in the outer region. We do not find 2604 any hint, at least above the 1σ level, of the existence of a vertical Delgado, A. J., Miranda, L. F., & Alfaro, E. J. 1999, AJ, 118, 1759 metallicity gradient. Dias, W. S., Alessi, B. S., Moitinho, A., & Lépine, J. R. D. 2002, A&A, 389, 871 Donati, P., Bragaglia, A., Carretta, E., et al. 2015a, MNRAS, 453, 4185 Acknowledgements. This work has made use of data from the European Donati, P., Cocozza, G., Bragaglia, A., et al. 2015b, MNRAS, 446, 1411 Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), Donor, J., Frinchaboy, P. M., Cunha, K., et al. 2018, AJ, 156, 142 processed by the Gaia Data Processing and Analysis Consortium (DPAC, Eisenstein, D. J., Weinberg, D. H., Agol, E., et al. 2011, AJ, 142, 72 https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding Evans, D. W., Riello, M., De Angeli, F., et al. 2018, A&A, 616, A4
Article number, page 12 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH
Friel, E. D., Donati, P., Bragaglia, A., et al. 2014, A&A, 563, A117 Friel, E. D., Jacobson, H. R., & Pilachowski, C. A. 2010, AJ, 139, 1942 Friel, E. D., Janes, K. A., Tavarez, M., et al. 2002, AJ, 124, 2693 Frinchaboy, P. M., Thompson, B., Jackson, K. M., et al. 2013, ApJ, 777, L1 Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2018, A&A, 616, A1 Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1 García Pérez, A. E., Allende Prieto, C., Holtzman, J. A., et al. 2016, AJ, 151, 144 Gilmore, G., Randich, S., Asplund, M., et al. 2012, The Messenger, 147, 25 Grisoni, V., Spitoni, E., & Matteucci, F. 2018, MNRAS, 481, 2570 Hayes, C. R. & Friel, E. D. 2014, AJ, 147, 69 Heiter, U., Soubiran, C., Netopil, M., & Paunzen, E. 2014, A&A, 561, A93 Holtzman, J. A., Hasselquist, S., Shetrone, M., et al. 2018, ArXiv e-prints [arXiv:1807.09773] Jackson, R. J., Jeffries, R. D., Randich, S., et al. 2016, A&A, 586, A52 Jacobson, H. R., Friel, E. D., Jílková, L., et al. 2016, A&A, 591, A37 Jacobson, H. R., Pilachowski, C. A., & Friel, E. D. 2011, AJ, 142, 59 Jönsson, H., Allende Prieto, C., Holtzman, J. A., et al. 2018, ArXiv e-prints [arXiv:1807.09784] Katz, D., Sartoretti, P., Cropper, M., et al. 2018, ArXiv e-prints [arXiv:1804.09372] Kharchenko, N. V., Piskunov, A. E., Schilbach, E., Röser, S., & Scholz, R.-D. 2013, A&A, 558, A53 Kos, J., Bland-Hawthorn, J., Freeman, K., et al. 2018a, MNRAS, 473, 4612 Kos, J., de Silva, G., Buder, S., et al. 2018b, MNRAS Krone-Martins, A. & Moitinho, A. 2014, A&A, 561, A57 Kubryk, M., Prantzos, N., & Athanassoula, E. 2015a, A&A, 580, A126 Kubryk, M., Prantzos, N., & Athanassoula, E. 2015b, A&A, 580, A127 Lindegren, L., Hernández, J., Bombrun, A., et al. 2018, A&A, 616, A2 Linden, S. T., Pryal, M., Hayes, C. R., et al. 2017, ApJ, 842, 49 Liu, F., Yong, D., Asplund, M., Ramírez, I., & Meléndez, J. 2016, MNRAS, 457, 3934 Magrini, L., Randich, S., Kordopatis, G., et al. 2017, A&A, 603, A2 Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94 Martell, S. L., Sharma, S., Buder, S., et al. 2017, MNRAS, 465, 3203 Minchev, I., Chiappini, C., & Martig, M. 2014, A&A, 572, A92 Monroe, T. R. & Pilachowski, C. A. 2010, AJ, 140, 2109 Ness, M., Hogg, D. W., Rix, H.-W., Ho, A. Y. Q., & Zasowski, G. 2015, ApJ, 808, 16 Netopil, M., Paunzen, E., Heiter, U., & Soubiran, C. 2016, A&A, 585, A150 Nidever, D. L., Holtzman, J. A., Allende Prieto, C., et al. 2015, AJ, 150, 173 Piatti, A. E., Claria, J. J., & Abadi, M. G. 1995, AJ, 110, 2813 Piskunov, N. & Valenti, J. A. 2017, A&A, 597, A16 Randich, S., Gilmore, G., & Gaia-ESO Consortium. 2013, The Messenger, 154, 47 Randich, S., Tognelli, E., Jackson, R., et al. 2018, A&A, 612, A99 Reddy, A. B. S., Lambert, D. L., & Giridhar, S. 2016, MNRAS, 463, 4366 Roškar, R., Debattista, V. P., Quinn, T. R., Stinson, G. S., & Wadsley, J. 2008, ApJ, 684, L79 Sartoretti, P., Katz, D., Cropper, M., et al. 2018, A&A, 616, A6 Schiappacasse-Ulloa, J., Tang, B., Fernández-Trincado, J. G., et al. 2018, AJ, 156, 94 Sheinis, A., Anguiano, B., Asplund, M., et al. 2015, Journal of Astronomical Telescopes, Instruments, and Systems, 1, 035002 Soubiran, C., Cantat-Gaudin, T., Romero-Gómez, M., et al. 2018, A&A, 619, A155 Taylor, M. B. 2005, in Astronomical Society of the Pacific Conference Se- ries, Vol. 347, Astronomical Data Analysis Software and Systems XIV, ed. P. Shopbell, M. Britton, & R. Ebert, 29 Valenti, J. A. & Piskunov, N. 1996, A&AS, 118, 595 Wu, Z.-Y., Zhou, X., Ma, J., & Du, C.-H. 2009, MNRAS, 399, 2146 Yong, D., Carney, B. W., & Friel, E. D. 2012, AJ, 144, 95 Zacs,ˇ L., Alksnis, O., Barzdis, A., et al. 2011, MNRAS, 417, 649 Zwitter, T., Kos, J., Chiavassa, A., et al. 2018, MNRAS, 481, 645
Appendix A: Tables
Article number, page 13 of 20 ] H / Fe [ σ H] / [Fe g log σ g log ff Te σ ff Te RV σ RV p RP G − BP G G δ µ σ
2293265210654 9.92051 0.12712765 0.5 -18.1821 0.673 A&A proofs: manuscript no. apogee_galah_astroph δ µ ∗ α µ σ 90783982 0.06885027846654153 -2.0589048051205565 0.066 ∗ α DR2 (Cantat-Gaudin et al. 2018). µ Gaia ̟ mbers in ̟ σ 0968 1.3276718736945818 0.04611155225642544 0.29969173 Information on APOGEE DR14 stars in common with candidate me 4613588 1982689777242358912 341.26249155537 46.2330047 + Table A.1. Cluster star_id source_id RA DEC ASCC 124 2M22450300
Article number, page 14 of 20 i R. Carrera et al.: Open clusters in APOGEE and GALAH sin v σ i sin v ] H / Fe [ σ H] / [Fe g log σ g log ff Te σ 7 48 4.45 0.14 -0.25 0.06 23.92 0.83 ff f_c Te RV σ RV p RP G − BP G G δ µ σ δ µ ∗ α µ σ DR2 (Cantat-Gaudin et al. 2018). ∗ α µ Gaia ̟ .058 1.187 0.09 -0.546 0.075 10.041 0.231 0.6 19.85 0.18 1 755 ers in ̟ σ 0231412 3234352820498417024 81.3172531 2.5281074 2.809 0 + CLUSTER star_id source_id RA DEC ASCC 16 05251613
Article number, page 15 of 20 Information on GALAH DR2 stars in common with candidate memb Table A.2. cannon flag i sin v H] / 574922209433.6240327478691 1 [Fe
A&A proofs: manuscript no. apogee_galah_astroph g log ff e 4529617 5870.960626083559 4.205298815473945 -0.0778783 RV T RP G − BP alysis. G G 0126492 3222160885813451776 11.044314 0.81302357 22.010 + Individual stars in the GALAH DR2 clusters retained in the an Cluster star_id source_id ASCC 16 05242648 Table A.3.
Article number, page 16 of 20 R. Carrera et al.: Open clusters in APOGEE and GALAH Ni Nr N .02 10 e Ni σ Ni Mn Nr Mn e Mn σ Mn Cr Nr Cr e Cr σ Cr Ca Nr Ca e Ca σ .04 0.07 0.03 8 -0.21 0.12 0.08 2 -0.09 0.04 0.01 10 -0.07 0.05 0 Ca Si Nr Si e Si σ Si] Al Nr Al e Al σ Al Mg Nr Mg e Mg σ Mg Na Nr Na e Na σ Cluster Na ASCC 21 -0.07 0.04 0.01 10 0.04 0.12 0.04 10 -0.02 0.06 0.02 10 0
Article number, page 17 of 20 Abundances obtained for OCs in the APOGEE sample. Table A.4. A&A proofs: manuscript no. apogee_galah_astroph Ni Nr N e 0.06 1 Ni σ Ni Mn Nr Mn e Mn σ Mn Cr Nr Cr e Cr σ Cr Ca Nr Ca e Ca σ Ca Si Nr Si e 0 0.07 1 0.12 0.0 0.05 1 -0.01 0.0 0.05 1 -0.03 0.0 0.06 1 0.01 0.0 Si σ Si] Al Nr Al e Al σ Al Mg Nr Mg e Mg σ Mg Na Nr Na e Na σ ClusterAlessi 24 Na 0.11 0.0 0.05 1 -0.11 0.0 0.07 1 -0.1 0.0 0.04 1 0.07 0. Fe] abundance ratios for the GALAH clusters. Article/ number, page 18 of 20 Mean [X Table A.5. R. Carrera et al.: Open clusters in APOGEE and GALAH 1 2 3 1 2 3 3 3 2 1 2 2 2 2 2 2 2 2 2 5 3 3 2 3 1 3 4 1 2 1 1 1 2 1 2 2 2 2 10 2,3 2,8 1,9 1,9 2,4 2,7 Ref. 1,12 1,10 2,10 2,13 1,10 lit Nr lit , ] H / Fe [ σ (dex) lit H] / -0.2 0.03 7 -0.1 0.2 1 0.00 0.02 5 0.03 0.11 1 0.11 0.04 8 0.22 0.09 5 -0.11 0.03-0.31 7 0.06-0.13 2 0.02 6 -0.08 0.05 13 -0.11-0.05 0.02 0.02 5 4 -0.01-0.09 0.05-0.22 0.17-0.06 12 0.01 1 0.02 2 23 -0.18-0.08 0.02 0.02-0.06 9 -0.15 5 0.03 0.03 5 -0.38 18 0.04-0.22 16 0.07 2 [Fe Nr ] H / Fe [ e ] H / Fe [ (dex) σ H] / 0.01 0.09 0.03 10 0.00 0.01 1 0.11 0.01 1 0.210.03 0.01 0.01 0.01 1 2 0.32 0.01 1 0.020.08 0.07 0.04 0.01 3 1 0.13 0.05 0.01 21 0.040.01 0.014 1 0.01 1 -0.02 0.01-0.51 1 0.01 1 -0.15 0.03 0.01 18 -0.10-0.22 0.04 0.01-0.23 9 0.11-0.02 0.01-0.12 0.05 0.03 1 -0.20 0.01 4 0.01 0.03 0.01 6 0.01 5 6 -0.01-0.03 0.06-0.13 0.02-0.12 0.10 0.01-0.24 0.04 0.01-0.25 24 0.01 0.06 2 0.02 3 0.01 7 3 0.01-0.07-0.19 1 -0.30-0.14-0.18-0.23 0.01-0.27 0.01-0.12 1 1 0.01-0.10 0.01 1 0.01-0.02 1 0.01-0.05 1 0.01 0.01 1 0.01 0.05 1 0.01 1 0.01 0.01-0.01 3 -0.05 1 19 0.01-0.28 0.01-0.11 2 -0.04 0.02 0.01 0.04 0.01 1 0.01 0.01 5 1 7 -0.09 0.02-0.25-0.06 0.01 0.01 0.903-0.04 5 0.01-0.22 0.01-0.18 27 2 -0.01-0.18-0.08 0.02-0.12 0.01 0.01 0.01 0.01 1 0.01-0.05 1 0.01-0.07 10 0.01 0.01 1 0.02 1 0.01-0.13 2 0.01-0.08 0.01 1 0.07 3 0.08-0.41 2 0.02-0.23 0.06 11 0.09-0.09 2 0.09 0.06-0.15 0.01 2 0.05 0.04 1 6 0.02 6 0.014 0.05 0.04 2 0.033 0.02 0.01 5 0.061 0.08 0.01 217 -0.305 0.037 0.026 2 -0.172 0.18 0.10 3 -0.285 0.02 0.01 2 -0.126 0.008 1 [Fe 2 GDR Nr 2 GDR ) 1 σ − b 2 (km s GDR 2.5 3.55 2 -7.5 0.0 1 -0.1 2.05 126 -7.9 0.75 14 18.73.43 4.45 1.46 9 3 5.2829.18.47 3.25 3.24 4.74 12 29 2 22.8 0.0 1 5.92 1.35 212 1.92 5.916.382.66 1 0.40.49 0.822.78 0.76 2 4 0.69 6 6 8.66 0.06 2 -3.33 1.47 9 -5.04 3.3 7 -34.9 1.81-26.7 4.19 7 1 -17.4 0.51 3 -20.4 0.33 4 -2.12-53.2 5.64 2.0 2 -9.57 27 1.25 12 -5.02 2.-29.6 94 1.06 1 19 -41.7-1.49 0.96 3.57 27 3 57.05 0.0 1 13.68 1 23.18 3.417.65 15 50.58 0.42 0.9478.8229.15 1 1.12 1 1.42 4 9 45.5213.09 1.64 10.31 2 2 11.1815.28 0.031.88 1.1159.76 1 0.028.35 2 1.2 5.36 1 1 15 19.71 1.57 6 52.2651.26 1 1.65 21 66.07 1.22 40 26.6527.11 2.425.3559.63 12.2 3.3975.18 12 20.22 1.06 2 53.29 3.14 16 8.51 4 41.76 6.72 3 2 2.2 2 7 -71.95 1.77 7 -76.19 3.28-33.72 1 1.4-45.11 18 2.41 2 -34.63-27.32-22.98 4.13-63.93 1.88 1.11 3 0.0 2 12 1 -48.25-39.82 2.17-42.39 3.81 1.28 9 4 -65.81 2 1.27-44.39 3 2.39 14 -83.24 0.51-37.89-47.38 6.84 1 5.46 2 1 -29.11 2.94 1 RV lit Nr lit , ) RV 1 σ − t-Gaudin et al. (2018). lit (km s 5.5 0.33 106 7.5 0.05 2 2.31.0 0.5 0.58 5 1 -8.7 2.3 7 -8.6 1.88 2 -8.9 0.74 1 -5.0 20.5 3 -3.6 1.65 2 -1.0 3.0 2 -1.4 0.65 90 -2.0 1.7 9 -2.5 5.75 4 24.861.0 1.1376.6 3.75 11 17 0.5 5 79.9 1.5 17 18.1 3.5 4 50.1 0.14 11 26.9 1.926.6 27 0.7720.7 4 43.4 1.53 0.35 10 2 RV -11.5 0.01 2 -73.4 0.4 7 -36.3-50.1 0.5 0.3 4 6 -5.37 2.46-11.0 10 7.4 1 -35.0 0.0 1 -40.5-48.5 1.5 6.11 15 6 -53.1 3.1-44.3-11.9 28 1.5 2.0 5 4 -82.0-29.2 10.39-38.0 4 0.8 0.82 23 5 -8.17 0.22 3 -60.3 0.01 2 18.57 2.12 9 31.38 1.42 4 65.31 0.09 31 59.8430.67 0.41 2.3 2 12 41.81 0.25 8 -25.54 2.6 2 -29.97 10.0 1 -42.35 0.05 472 -144.25 5.92 7 Nr RV e ) 1 − RV σ (km s RV 2.68 0.06 0.04 2 1.98 5.42 2.049 7 3.61 0.05 0.03 3 2.117.33 0.07 0.05 2 0.05 1 4.23 9.33 4.17 5 0.216.57 2.04 3.06 0.59 0.17 12 308 6.702.55 0.04 1.05 0.03 0.33 2 2.56 10 0.18 0.10 3 8.26 0.03 1 -9.63 0.38 0.16 6 -7.65-6.18 1.87 1 2.50 1 -4.08-6.21 0.07 1 0.09 1 -5.48 0.35 0.25 2 -1.18-7.09-1.57 0.12 1 0.11 0.05 1 1 -1.00 5.68 1.80-0.65 10 0.71-6.37 0.50 0.54 2 0.14 15 17.4116.30 5.66 1.3017.44 19 0.6225.27 0.057.87 1 0.53 0.0877.80 0.65 0.30 1 0.56 0.46 3 0.28 2 4 18.73 1.15 1 27.4516.24 4.00 0.43 0.3730.85 118 0.3144.92 0.7517.75 2 0.67 0.2881.29 0.39 7 0.50 3 0.35 0.04 2 1 15.0720.1729.0656.8127.26 0.0759.65 0.05 1 0.06 1 0.13 1 1 15.83 0.0178.51 0.16 2.61 1 1 0.25 11 0.3 1 22.11 2.08 0.3250.83 43 0.42 0.19 5 15.76 2.6711.02 0.42 40 66.20 1.11 1 0.0427.37 1.76 1 23.99 0.4125.77 13.67 18 6.1160.1133.61 5 21.65 1.2139.49 1.78 0.70 0.11 9.92 0.3543.95 3 0.3 1 4.05 25 3.36 1 6 1.37 6 -14.89-23.35 0.54 0.38 0.37-73.34 2 0.41 1 0.13 9 -35.77-50.14 0.82 0.21 0.29 0.09 8 -34.93 5 0.37 0.12-51.37 9 -67.22-18.47 3.27 1.77 1.46 0.07 0.79 5 1 5 -15.01 0.49 0.28 3 -37.78-38.41-26.58-23.26 0.03-74.09 1 0.10 3.12 1 0.16 1 0.16 1 1 -48.83-39.85 0.09-40.60 2.07 0.05 0.48 3 19 -64.80 0.21-52.43 1 -43.78-10.29 0.08 0.93 1.43 0.01 0.42 1 0.41 1 5 12 -71.39-85.16-29.38 0.18-35.67 0.47 0.13 0.09-52.13 0.4 2 27 51 0.09 1 0.06-41.82 1 0.71 0.15 21 29.712 0.136 1 151.90 0.83 1 -135.79 0.04 1 a type ner4 RGB ff ASCC 124Basel11b MS Berkeley 19 RGB RGB Berkeley 31 RGB Berkeley 43 RGB Berkeley 66Berkeley 71 RGB Berkeley 7 both MS Berkeley 87Berkeley 91 MS RGB Collinder 69Collinder 95Czernik 18 MS MS Czernik 21 MS Dolidze RGB 3Feibelman 1FSR 0306 MS MS RGB FSR 0941 RGB IC 4996King2 MS King 7King8Koposov 36 RGB MS both RGB NGC 129NGC 1333 MS MS NGC1817 RGB NGC1912NGC2158NGC 2168NGC RGB 2183 RGB MS MS NGC2304NGC2318 RGB RGB ClusterAlessi20ASCC Star 16ASCC 21 MS Berkeley 17 MS MS RGB Berkeley 29 RGB Berkeley 33 RGB Berkeley 53 RGB Berkeley 85Berkeley 86 both MS Berkeley 98Berkeley 9 RGB Collinder 359 MS both Czernik 20Czernik 23Czernik RGB 30Dolidze RGB 5 RGB FSR 0336FSR MS 0496FSR 0542FSR 0667FSR MS 0716 RGB FSR 0826 RGB FSR 0883 RGB RGB FSR 0942 RGB FSR 1063 RGB Gulliver 23Gulliver 6 RGB Ha RGB RGB IC 1369IC 166 MS IC 348 RGB IC 5146King RGB 15King1 MS King5 MS RGB RGB Koposov 63 RGB Kronberger 57 RGB RGB L 1641SMelotte 20Melotte 71 MS MS NGC1193 RGB NGC1245 RGB NGC136 RGB NGC 1579NGC 1664NGC1798 RGB MS both NGC188 RGB NGC1907 RGB RGB NGC 2232NGC2243NGC MS 2264 RGB NGC2324 MS RGB IC 1805 MS Melotte 22Negueruela 1 MS MS NGC 1857 both NGC 2244 MS
Article number, page 19 of 20 The 131 open clusters in common between APOGEE DR14 and Canta Table A.6. A&A proofs: manuscript no. apogee_galah_astroph 1 2 2 2 2 2 2 1 2 1 3 2 7 2 1 11 2,4 2,4 2,3 2,3 2,4 2,4 1,4 1,10 2,10 0.0 0.06 52 -0.4 0.01 3 -0.1 0.04 7 0.170.42 0.040.09 0.03 8 0.03 31 6 0.020.06 0.02 0.05 7 7 -0.05 0.08 3 -0.01 0.02 4 -0.28 0.03 5 0.16 0.03 0.01 12 0.02 0.07 0.010.08 174 0.40 0.070.10 0.010.04 0.01 0.04 1 0.12 0.02 35 0.010.04 0.011 0.04 44 0.01 3 0.020.01 4 0.09 0.010.10 0.02 1 0.01 21 1 0.01 1 0.13 0.06 0.04 2 -0.36 0.02 0.01 8 -0.11-0.12 0.02 0.01 0.01 16 1 -0.01 0.04 0.01 9 -0.18 0.01 0.01 2 -0.30-0.14 0.02-0.28 0.04 0.01-0.47 0.01 4 0.02 1 -0.22 5 0.01 1 0.01 1 0.278 0.05 0.03 2 7.7 0.43 10 33.8 1.06 64 3.31 1.93 48 5.69 0.88 94 8.194.79 1.771.72 0.09 183 5.56.49 2 2 3.73 1 -7.59 0.48 4 -8.37-8.87 2.09 0.92 9 4 -9.64 5.75 16 -4.12 0.28 11 51.33 1.4 16 36.8574.22 1.7283.14 0.93 6 15.82 14 1 36.01 1.612.83 16 0.86 3 -45.85 1.64 8 -16.78-22.05-22.34 3.53 3.35 4.4 5 -54.15 5 -21.67 1.53-12.89 4 -11.51 1.18 5.92 153 4.28 1 -65.59 51 -11.67 14 -19.51 0.4 2.08 2.91 16 1 30 -19.46 3.59 5 2.3 0.04 537 1.8 1.82 27 -9.6 0.16 2 -2.6 0.32 13 35.1 0.14 9 6.68 0.08 5 5.54 0.14 54 17.0 1.4 5 -32.7 3.47-8.18-14.7 7 0.09-8.59 5.12 4 0.2-47.4 9 0.13 4 193 -19.6 1.9 6 -24.0-54.7 5.2 0.13 88 1 -8.16 10.0 1 -27.5-8.58 11.5 1.12 2 2 49.46 1.84 3 73.5733.62 0.15 0.08 18 148 35.08 0.32 15 13.68 0.06 2 -18.95 0.76 1 1.54 4.53 1.857.622.78 6 0.46 1.17 0.14 0.17 10 45 6.13 0.90 0.52 3 2.47 4.49 2.01 5 7.081.183.94 0.095.05 1 0.01 0.08 1 0.8 1 0.57 2 -0.09 21.64 10.82-3.32 4 0.13 1 -7.28-6.09-6.58 8.24 0.80 4.09 4.12 1 2.05 4 4 -8.10-5.15 0.15 9.03 0.11 4.04 2 5 35.2874.2633.92 0.25 1.32 0.06 0.10 16 0.03 179 1 35.34 1.16 0.34 12 12.55 0.67 0.39 3 15.49 0.0313.08 1 51.1816.29 2.3217.13 0.86 1.04 0.59 1 5 0.26 0.07 5 18.52 1 49.99 6.20 1.34 3.10 0.47 4 8 -11.57 0.88-31.73 0.44-18.22 4 1.85 1.31-47.46 0.01 2 1.08 1 0.18 37 -17.42-19.58-22.26 0.15-20.14 0.07 6.87 3.04 4 2.43-54.49 1 0.14 8 -12.91 1.22 1 0.25 23 0.21-66.10-16.16 0.80 1 -10.22 4.53 0.57 2.03 2 5 0.47 1 -89.84 0.36 1 NGC 6469NGC 6531 MS NGC6705NGC6791 MS RGB RGB NGC 6913NGC 7058 MS NGC 752 MS NGC 7789Roslund MS 6 both MS Stock 1Stock 4 MS MS Teutsch7Trumpler RGB 2Trumpler 3Trumpler 5 MS MS RGB NGC2355NGC2420 RGB NGC 366 RGB NGC 457NGC 6494 MS NGC MS 6649 MS MS NGC7062NGC 7086 RGB MS RSG 7RSG 8Ruprecht 148SAI16 MS Stock 10 MS Stock 2 MS Stock RGB 7 MS Teutsch 10Teutsch 12Teutsch 1 MS Teutsch RGB 51 both MS Tombaugh 4 RGB MS Trumpler 26 RGB RGB NGC 2682 both NGC 6811NGC6819NGC6866 both RGB RGB NGC 7788Roslund 3 MS MS
Article number, page 20 of 20 This figure "fig_rv_comp_galah_gdr2.png" is available in "png" format from:
http://arxiv.org/ps/1901.09302v1