Mon. Not. R. Astron. Soc. 000, 1–12 (0000) Printed 12 May 2010 (MN LATEX style file v2.2) arXiv:1005.1912v1 [astro-ph.GA] 11 May 2010 Characterisation of 15 overlooked Ruprecht clusters with ages within 400 Myr and 3 Gyr. C. Bonatto1 and E. Bica1 1 Departamento de Astronomia, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves 9500 Porto Alegre 91501-970, RS, Brazil 12 May 2010 ABSTRACT We derive fundamental, structural, and photometric parameters of 15 overlooked Ruprecht (hereafter Ru) star clusters by means of 2MASS photometry and field-star decontamination. Ru 1, 10, 23, 26, 27, 34, 35, 37, 41, 54, 60, 63, 66, and 152 are located in the third Galactic quadrant, while Ru 174 is in the first. With the constraints imposed by the field-decontaminated colour-magnitude diagrams (CMDs) and stellar radial density profiles (RDPs), we derive ages in the range 400 Myr — 1 Gyr, except for the older Ru 37, with ∼ 3 Gyr. Distances from the Sun are within 1.5 . d⊙ (kpc) . 8.0. The RDPs are well-defined and can be described by a King-like profile for most of the radial range, except for Ru 23, 27, 41, 63, and 174, which present a conspicuous stellar density excess in the central region. The clusters dwell between (or close to) the Perseus and Sagittarius-Carina arms. We derive evidence in favour of cluster size increasing with distance to the Galactic plane (ZGP ), which is consistent with a low frequency of tidal stress associated with high-|ZGP | regions. The clusters are rather faint even in the near-infrared, with apparent integrated J magnitudes within 6.4 . mJ . 9.8, while their absolute magnitudes are −6.6 . MJ . −2.6. Extrapolation of the relation between MV and MJ , derived for globular clusters, suggests that they are low-luminosity optical clusters, with −5 . MV . −1. Key words: (Galaxy:) open clusters and associations:general; Galaxy: structure 1 INTRODUCTION In general, open clusters (OCs) are formed and evolve in or close to - the Galactic disk. As a consequence of their orbits, they are constantly suffering tidal stress from Galactic substructures and undergoing different degrees of mass loss that, in most cases, might lead to cluster dissolution. Indeed, the vast majority of the OCs do not survive even the embedded phase (e.g. Lada & Lada 2003), and few reach ages older than ∼ 108 yr (e.g. Goodwin & Bastian 2006). As systems in which the balance between velocity dispersion and escape velocity plays a vital role, OC stellar distributions change continually as a function of time because of mass segregation and evaporation, tidal interactions with the disk and/or bulge, encounters with giant molecular clouds, as well as mass loss associated with stellar evolution. On average, these processes tend to accelerate the cluster dynamical evolution and change the internal structure in varying degrees. Indeed, near the solar circle, theoretical and observational evidence (e.g. Spitzer 1958; Oort 1958; Baumgardt & Makino 2003; Goodwin & Bastian 2006; Lamers & Gieles 2006; Khalisi, Amaro-Seoane & Spurzem 2007; Piskunov et al. 2007) suggest a mass dependent disruption time scale of a few 108 yr. As a consequence, most OCs end up completely dissolved in the Galactic stellar field (e.g. Lamers et al. 2005) or leave only poorly-populated remnants (Pavani & Bica 2007 and references therein), long before reaching ∼ 1 Gyr of age. Reflecting the above age/dissolution effect, only ≈ 13% of the ≈ 1100 OCs with known age listed in WEBDA1 are older than 1 Gyr, while ≈ 45% have an age between 100 Myr and 1 Gyr, and ≈ 42% are younger than 100 Myr. So, besides the obvious importance of deriving reliable astrophysical parameters for as yet unstudied clusters, the unambiguous characterisation of OCs older than several 108 yr will increase the statistics of objects undergoing the dissolution phase. This, in turn, can be used for better determining the time scale for cluster dissolution in the Galaxy. Cluster databases such as WEBDA still contain many unstudied objects that, over the years, have been identified as star cluster candidates, usually based on the appearance in optical images. Not surprisingly, close investigations of 1 obswww.univie.ac.at/webda 2 C. Bonatto and E. Bica some of these overlooked objects have uncovered a number of actual OCs (e.g. Carraro, Janes & Eastman 2005; Carraro et al. 2006; Carraro, Subramaniam & Janes 2006). Besides, since young OCs are relatively easy to identify (because of the presence of bright stars) even at relatively large distances, the overlooked clusters, in general, are as old as several 108 yr, sometimes reaching a few Gyr (e.g. the ∼ 4 Gyr old OC Berkeley 56 - Carraro, Subramaniam & Janes 2006). Based on the optical Catalogue of Star Clusters and Associations of Alter et al. (1970), WEBDA lists the coordinates of 171 OC candidates originally found by J. Ruprecht (classified as Ruprecht clusters; hereafter Ru). However, only 79 have been so far confirmed as OCs, having determinations of fundamental parameters, such as the age, reddening, and distance from the Sun. In the present paper we derive fundamental and structural parameters for 15 of these overlooked Ruprecht OCs, 12 of these not previously studied, and the remaining 3 with inconsistent determinations (Sects. 4 and 5). Steps taken in the present work can be summarised as follows: (i) 2MASS2 photometry is extracted in a wide circular region centred on a given cluster, (ii) we apply field-star decontamination to uncover the intrinsic colour-magnitude diagram (CMD) morphology, which is essential for a proper derivation of reddening, age, and distance from the Sun, and (iii) we apply colour-magnitude filters to produce more contrasted stellar radial density profiles (RDPs). In particular, field-star decontaminated CMDs constrain the fundamental parameters more than the raw (observed) photometry, especially for low-latitude and/or bulge-projected OCs (e.g. Bica, Bonatto & Camargo 2008, and references therein). This paper is organised as follows. In Sect. 2 we present optical images of the sample objects. In Sect. 3 we discuss the 2MASS photometry and build the field-star decontaminated CMDs. In Sect. 4 we derive fundamental cluster parameters. In Sect. 5 we derive structural parameters. In Sect. 6 we investigate relations among parameters and with respect to their location in the Galaxy. Concluding remarks are given in Sect. 7. 2 THE SAMPLE OF OVERLOOKED RUPRECHT CLUSTERS We started by examining the optical images of the objects in order to identify the best candidates to be further studied with 2MASS photometry (Sect. 3). In short, the selection criteria were (i) a relatively conspicuous stellar density excess (typical of a star cluster), (ii) a foreground/background not excessively dense, and (iii) an angular size larger than ∼ 1′ (a smaller size might indicate an excessively distant object, too faint to be detected with 2MASS). The goal was to focus on objects that would result in reliable determinations of fundamental (Sect. 4) and structural (Sect. 5) parameters. The above search resulted in 12 unstudied OCs. Besides these, we also included 3 other cases somewhat studied, but with inconsistent parameters (Sects. 4 and 5). The sample of Ruprecht clusters that came up from 2 The Two Micron All Sky Survey, Sky data release (Skrutskie et al. 1997) http://www.ipac.caltech.edu/2mass/releases/allsky/ All - the above search is shown in 5′ × 5′ B images (Figs. 1-2), taken from LEDAS3 . Note that the images are centred on different coordinates (Table 1) than those given in WEBDA. By default, we start the 2MASS analyses by assuming the WEBDA coordinates as cluster centre. However, in most cases the RDPs built after field decontamination - to maximise membership probability (Sect. 5), presented a dip in the innermost radial bin. So, the central coordinates were computed again to match the absolute maximum in the stellar surface density (e.g. Fig. 3). In most cases, the difference between the original and recomputed central coordinates is slight, of the order of 1′ , thus well within the estimated optical diameter (col. 7 of Table 1). The images match our selection criteria in different degrees. For instance, the highest compactness levels occur with Ru 35, 37, 41, 54, 60, 63, and 152. Ru 1, 10, 23, and 27 are projected on the least contaminated fields, with Ru 174 in the densest. Note that the bright (foreground) star 6 Pup (K 3 III) is located at ≈ 2′ to the northwest of the central coordinates of Ru 37. 3 PHOTOMETRIC ANALYSIS Photometry for the sample clusters was extracted from VizieR4 in a circular field of radius Rext = 60′ . Such a wide extraction area provides the required statistics for the determination of the background level (Sect. 5) and the colour/magnitude characterisation of the field stars (see below). To preserve the photometric quality and, at the same time, work with a statistically significant number of stars, only stars with J, H, and Ks errors lower than 0.15 mag were used. Reddening corrections are based on the absorption relations AJ /AV = 0.276, AH /AV = 0.176, AKS /AV = 0.118, and AJ = 2.76×E(J − H) given by Dutra, Santiago & Bica (2002), with RV = 3.1, considering the extinction curve of Cardelli, Clayton & Mathis (1989). Except for Ru 174 (at ℓ ≈ 78◦ , near the border between the 1st and 2nd quadrants), the remaining clusters belong to the 3rd Galactic quadrant (Table 1), which would make field-star contamination a minor issue (e.g. Bica, Bonatto & Camargo 2008). However, given the relatively poorly-populated nature of the present sample (Figs. 1 - 2), it is important to take the field-star contamination into account to derive more constrained parameters. In particular, we wish to work with CMDs in which cluster evolutionary sequences and field stars are disentangled. For this purpose, we work with a statistical decontamination algorithm that has been developed by our group for the proper identification and characterisation of star clusters, especially those near the Galactic equator and/or with important fractions of faint stars. The algorithm is applied to the 2MASS photometry, which can provide the spatial and photometric uniformity required for wide extractions and high star-count statistics. Working with the wide circular extractions, we start by 3 Leicester Database and Archive Service (LEDAS) DSS/DSS-II service on ALBION; http://ledas-www.star.le.ac.uk/DSSimage. 4 http://vizier.u-strasbg.fr/viz-bin/VizieR?-source=II/246 Overlooked Ruprecht clusters 3 Figure 1. All panels display 5′ × 5′ DSS-I B images. From left to right: Ru 1, 10, and 23 (top); Ru 26, 27, and 34 (middle); Ru 35, 37 (with the bright K 3 III star 6 Pup at ≈ 2′ to the northwest), and Ru 41 (bottom). Plate flaws show up in the image of Ru 41. Orientation: North at the top and east at left. defining the cluster and comparison field regions5 . CMDs extracted from the cluster region for our objects are shown in Figs. 3-5 (top panels). These can be contrasted with the representative (i.e. equal-area) comparison field CMDs (middle 5 This step is iterative, since we first have to build the RDP (Sect. 5) to estimate the cluster size and the location of the comparison field. After applying the algorithm, we build the colourmagnitude filters for the decontaminated cluster CMD. Then we re-build the RDP, re-compute the cluster size and run again the decontamination algorithm. panels). It is important to note that the equal-area field extraction is used only for qualitative comparisons, since the algorithm uses the wide surrounding area (as defined above) for more statistical representativeness. Our approach implicitly assumes that the field colour-magnitude distribution (i) is statistically representative of the cluster contaminants, and (ii) is rather spatially uniform. These assumptions are somewhat matched in the 3rd Galactic quadrant. A detailed description of the decontamination algorithm can be found in Bonatto & Bica (2007b) and Bonatto & Bica (2010). For clarity, we provide below only a sketch on how it works. The cluster CMD is divided into a 3D grid of cells 4 C. Bonatto and E. Bica Figure 2. Same as Fig. 1 for the remaining clusters. From left to right: Ru 54, 60, and 63 (top); Ru 66, 152, and 174 (bottom). Plate flaws show up in the image of Ru 54. Table 1. Fundamental parameters Cluster α(2000) (1) (hms) (2) δ(2000) (◦ ′ ′′ ) WEBDA Age E(B − V ) d⊙ (3) (Myr) (4) (mag) (5) (kpc) (6) D (′ ) (7) α(2000) (hms) (8) δ(2000) (◦ ′ ′′ ) (9) ℓ (◦ ) (10) b (◦ ) (11) This work Age (Myr) (12) E(B − V ) (mag) (13) d⊙ (kpc) (14) (kpc) (15) Ru 1 06:36:25 −14:10:48 580 0.15 1.1 5.0 06:36:21.63 −14:08:48.75 223.95 −9.68 500 ± 100 0.26 ± 0.06 Ru 10 Ru 23 Ru 26 Ru 27 07:06:25 07:30:41 07:37:11 07:37:30 −20:05:00 −23:23:00 −15:38:59 −26:31:42 — — 30 250 — — 0.10 0.15 — — 1.4 0.6 4.0 4.0 24.0 21.6 07:06:29.05 07:30:38.80 07:37:11.10 07:37:40.89 −20:06:31.50 −23:23:36.00 −15:39:46.50 −26:31:45.50 232.55 238.08 232.06 241.60 −5.85 −2.40 +2.68 −2.53 500 ± 100 600 ± 100 400 ± 50 900 ± 100 0.64 0.54 0.35 0.03 ± ± ± ± 0.06 0.06 0.06 0.06 2.34 3.06 1.82 1.49 ± ± ± ± 0.22 0.29 0.17 0.14 1.62 2.00 1.24 0.82 ± ± ± ± 0.14 0.16 0.11 0.07 Ru 34 Ru 35 Ru 37 Ru 41 07:45:55 07:46:13 07:49:54 07:53:49 −20:23:00 −31:17:00 −17:17:00 −26:58:00 — — — — — — — — — — — — 6.0 1.5 4.0 2.0 07:45:56.22 07:46:13.64 07:49:47.53 07:53:48.38 −20:23:24.00 −31:16:47.25 −17:14:46.50 −26:57:39.00 237.20 246.66 234.94 243.78 +2.16 −3.25 +4.53 +0.37 1000 ± 100 400 ± 100 3000 ± 1000 700 ± 100 0.00 0.45 0.00 0.13 ± ± ± ± 0.06 0.10 0.06 0.10 2.63 3.91 5.25 3.15 ± ± ± ± 0.25 0.56 0.74 0.45 1.70 2.26 3.87 1.84 ± ± ± ± 0.14 0.28 0.45 0.23 Ru 54 Ru 60 Ru 63 Ru 66 08:11:21 08:24:27 08:32:40 08:40:33 −31:57:00 −47:13:00 −48:18:00 −38:04:00 — — — — — — — — — — — — 3.0 3.0 3.0 2.0 08:11:20.92 08:24:26.29 08:32:39.60 08:40:33.82 −31:56:49.50 −47:12:51.01 −48:18:19.50 −38:04:47.99 250.03 264.10 265.80 258.49 +0.96 −5.51 −5.02 +2.28 800 400 500 600 ± ± ± ± 0.13 0.64 0.61 0.90 ± ± ± ± 0.10 0.10 0.10 0.10 5.47 6.16 3.76 3.76 ± ± ± ± 0.78 0.88 0.37 0.54 3.22 2.74 1.16 1.56 ± ± ± ± 0.43 0.54 0.17 0.24 Ru 152 Ru 174 07:54:30 20:43:30 −38:14:00 +37:03:00 — — — — — — 3.0 8.0 07:54:28.35 20:43:30.48 −38:14:14.26 +37:01:26.26 253.54 78.02 −5.30 −3.39 600 ± 100 800 ± 100 100 100 100 100 0.67 ± 0.10 0.32 ± 0.06 1.72 ± 0.16 ∆RSC 8.02 ± 1.15 2.11 ± 0.20 1.31 ± 0.12 5.00 ± 0.73 −0.13 ± 0.07 Table Notes. Col. 7: diameter estimated from optical images (Dias et al. 2002); Col. 14: distance from the Sun; col. 15: distance from the Solar circle. with axes along the J magnitude and the (J − H) and (J − Ks ) colours. Then, we compute the probability of a given star to be found in a particular cell (i.e., for a star with measured magnitude and colour uncertainties J ± σJ , (J − H) ± σ(J −H) , and (J − Ks ) ± σ(J −KS ) , the probability is proportional to the difference between the error function computed at the J, (J − H), and (J − Ks )-borders of the cell). This step is done for all stars and cells, resulting in a number density of member + field stars for each cell (ηtot ). The same steps are applied to the comparison field CMD, from which we estimate the field number density (ηf s ) for each cell. Next, for each cluster cell we subtract the corresponding field number density to obtain a decontaminated number density (ηmem = ηtot −ηf s ). Finally, ηf s is converted back into number of stars and subtracted from each cell, and cell the Nclean stars that remain in the cell are identified. We also compute the subtraction efficiency (fsub ), which is the sum over all cells of the difference between the expected Overlooked Ruprecht clusters 5 6 6 Ru1 (R=6’) Ru10 (R=4‘) Ru23 (R=4‘) Ru26 (R=5‘) Ru27 (R=5‘.5) 8 8 Ru34 (R=4‘.5) Ru35 (R=3‘) Ru37 (R=1‘.5) Ru41 (R=3‘.5) Ru54 (R=2‘.5) 10 10 12 12 14 14 6 6 16 8 8 10 J J 10 12 12 14 14 6 16 6 8 8 10 10 12 12 14 14 16 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 1.2 0 0.4 0.8 1.2 0 0.4 0.8 1.2 0 0.4 0.8 1.2 0 0.4 0.8 1.2 (J−H) (J−H) Figure 4. Same as Fig. 3 for Ru 34, 35, 37, 41, and 54. Figure 3. J ×(J − H) CMDs of Ru 1, 10, 23, 26, and 27, showing the observed photometry for representative regions (top panels) and the equal-area comparison fields (middle). The decontaminated CMDs are shown in the bottom panels, together with the isochrone solution (solid line) and colour-magnitude filter (shaded polygon). Note that, for most stars, the error bars are smaller than the symbol. 8 Ru60 (R=3‘.5) Ru63 (R=2‘.5) Ru66 (R=3‘.5) Ru152 (R=3‘) Ru174 (R=4‘.5) 10 12 14 8 10 J number of field stars (which usually is fractional) and the number of stars effectively subtracted (integer). In all cases we obtained fsub > 90%. The above procedure is repeated for 729 different setups (allowing for variations on cell size and grid positioning). Each produces a total number of member stars Psetup cell Nmem = cell Nclean , from which we compute the expected total number of member stars hNmem i by averaging out Nmem over all setups. Stars (identified above) are ranked according to the number of times they survive all runs, and only the hNmem i highest ranked stars are considered cluster members and transposed to the respective decontaminated CMD. The decontaminated J × (J − H) CMDs of the present sample are shown in Figs. 3-5 (bottom panels). Our decontamination approach relies upon differences in the stellar surface density measured in CMD cells of separate (cluster and comparison field) spatial regions. For a star cluster, which can be characterised by a single-stellar population projected against a (rather uniform) Galactic stellar field, the decontaminated surface density is expected to present a marked excess at the assumed cluster position. We illustrate this point by means of the stellar surface density (σ, in units of stars arcmin−2 ) of Ru 1 (Fig. 6), before (top-left panel) and after (top-right) decontamination. The respective isopleths are also shown (bottom), in which 12 14 8 10 12 14 0 0.4 0.8 1.2 0 0.4 0.8 1.2 0 0.4 0.8 1.2 0 0.4 0.8 1.2 0 0.4 0.8 1.2 (J−H) Figure 5. Same as Fig. 3 for Ru 60, 63, 66, 152, and 174. 6 C. Bonatto and E. Bica 3 1 2 0.5 1 0 30 15 ∆δ 0 -15 -30 -15 0 15 ∆(α cosδ) -30 30 ∆δ 30 30 0 -15 -30 -15 0 15 ∆(α cosδ) -30 30 30 15 ∆δ 15 15 ∆δ 0 0 -15 -15 -30 -30 30 15 0 ∆(α cosδ) -15 -30 30 15 0 -15 -30 ∆(α cosδ) Figure 6. 2D-perspective on Ru 1’s field decontamination. Top: stellar surface density σ(stars arcmin−2 ) computed before (left panel) and after (right) decontamination. Bottom: the respective isopleths. ∆(α cos(δ)) and ∆δ in arcmin. cluster size and geometry can be appreciated. Clearly, the decontamination largely enhanced the cluster/background contrast, revealing a marked central excess in the surface density distribution, together with a well-defined, approximately round and narrow stellar distribution. 4 DERIVATION OF FUNDAMENTAL PARAMETERS The presence of somewhat distant and evolved (in different degrees) OCs is suggested by the J × (J − H) CMDs built with the raw photometry of the sample clusters (top panels of Figs. 3-5). This is clearly confirmed in the decontaminated CMDs (bottom panels), in which conspicuous giant clumps and red giant branches can be seen in some cases (e.g. Ru 10, 23, 60, and 66). We derive the fundamental (reddening, age and distance from the Sun) parameters by means of the decontaminated CMD morphologies together with Padova isochrones (Girardi et al. 2002) computed with the 2MASS J, H, and Ks filters6 . With respect to metallicity, the difference between, e.g. solar and half-solar metallicity isochrones for a given age is small, to within the 2MASS photometric uncertainties. Thus, for simplicity, we adopt the solar metallicity ones. Although several analytical approaches for CMD fitting are available (see a summary in Naylor & Jeffries 2006), we employ a more direct comparison of the isochrones with the 6 http://stev.oapd.inaf.it/cgi-bin/cmd. These isochrones are very similar to the Johnson-Kron-Cousins ones (e.g. Bessel & Brett 1988), with differences of at most 0.01 mag in colour (Bonatto, Bica & Girardi 2004). decontaminated CMD morphology. Specifically, the fits are made by eye, using the combined main sequence (MS) and evolved stellar distributions as constraint. We also take variations due to photometric uncertainties into account (which, because of the restrictions imposed in Sect. 3, are usually small) and the presence of binaries (which tend to produce a redwards bias in the MS). Starting with the isochrones set for zero distance modulus and reddening, we shift them in magnitude and colour until a satisfactory match7 with the CMD is obtained. The best-fits, according to this approach, are shown in Figs. 3-5 (bottom panels), and the respective fundamental parameters are given in Table 1. We derive ages within 400 Myr - 1 Gyr, except for Ru 37, which seems to be somewhat older, with an age of ∼ 3 Gyr. As expected of optical clusters, the reddening values are relatively low, E(B − V ) 6 0.9 (or AV 6 2.8). In general, they are distant from the Sun (1.5 6 d⊙ (kpc) 6 8.0), and located outside the solar circle (0.8 6 ∆RSC (kpc) 6 5.0), except for Ru 174 at ∆RSC ∼ −0.13 kpc. Our sample has 3 clusters in common with Kharchenko et al. (2005). Within the uncertainties, both works agree on the age of Ru 1 (500 - 600 Myr); however, we find values of reddening and distance from the Sun about 60% higher. For Ru 26 and Ru 27 they find ages significantly younger than the present paper, especially for Ru 27 with 30 Myr as compared to 400 Myr. Reddening and distance from the Sun also present significant discrepancies (Table 1). A probable source for such differences is the presence of unaccounted for field stars in the analysis of Kharchenko et al. (2005). As can be seen in the decontaminated CMDs of Ru 1, Ru 26, and Ru 27 (Fig. 3), the age (and consequently the reddening and distance) is quite constrained, to within the quoted errors in Table 1. 5 STRUCTURAL PARAMETERS Based on the decontaminated CMD morphologies and corresponding isochrone solutions (Figs. 3-5), we build a colourmagnitude filter for each cluster. By excluding stars with colours not compatible with those of the cluster8 , noise in the RDPs is minimised, while the contrast with the background is enhanced (e.g. Bonatto & Bica 2007b). To preserve spatial resolution along the full radial range and, at the same time keeping moderate error bars, the RDPs are built in rings of increasing width with distance from the cluster centre. The set of ring widths used is ∆ R = 0.25, 0.5, 1.0, 2.5, and 5′ , respectively for 0′ 6 R < 0.5′ , 0.5′ 6 R < 2′ , 2′ 6 R < 5′ , 5′ 6 R < 20′ , and R > 20′ . Obviously, for any magnitude range, field stars with the same colour as the cluster’s will not be excluded by the above filtering process. This gives rise to a residual background level, which can be measured as the average number density of stars away from the cluster. The R coordinate (and uncertainty) of each ring corresponds to the average position (and standard deviation) of the stars inside the ring. 7 Any isochrone solution that occurs within the photometric error bars is taken as acceptable. 8 Note that the colour-magnitude filters are wide enough to take photometric uncertainties and binaries into account (or other multiple systems). Overlooked Ruprecht clusters 7 Table 2. Structural parameters derived from the RDPs Cluster (1) σ0 Rc RRDP 1′ σ0 Rc RRDP (∗ ′ −2 ) (′ ) (′ ) (pc) (∗ pc−2 ) (pc) (pc) (2) (3) (4) (5) (6) (7) (8) Ru1 16.5 ± 8.4 0.32 ± 0.10 8.0 ± 1.0 0.499 66.1 ± 33.8 0.16 ± 0.05 4.0 ± 1.0 Ru10 13.1 ± 6.4 0.39 ± 0.12 4.0 ± 0.5 0.679 28.4 ± 13.9 0.26 ± 0.08 2.7 ± 0.3 Ru23 8.2 ± 2.9 0.79 ± 0.20 6.0 ± 0.5 0.888 10.3 ± 3.7 0.70 ± 0.18 5.3 ± 0.4 Ru26 12.5 ± 5.4 0.42 ± 0.13 5.5 ± 0.5 0.527 45.0 ± 19.4 0.22 ± 0.07 2.9 ± 0.3 Ru27 3.6 ± 1.6 1.05 ± 0.37 5.5 ± 0.5 0.433 19.0 ± 8.5 0.45 ± 0.16 2.4 ± 0.2 Ru34 15.6 ± 6.4 0.34 ± 0.08 4.5 ± 0.5 0.763 26.8 ± 11.0 0.26 ± 0.06 3.4 ± 0.4 Ru35 55.3 ± 28.8 0.24 ± 0.08 3.0 ± 0.5 1.135 42.9 ± 22.3 0.27 ± 0.09 3.4 ± 0.6 Ru37 34.1 ± 15.0 0.20 ± 0.06 1.4 ± 0.2 1.522 14.7 ± 6.5 0.30 ± 0.09 2.1 ± 0.3 Ru41 6.0 ± 3.5 0.47 ± 0.20 3.5 ± 0.5 0.913 7.2 ± 4.2 0.43 ± 0.18 3.2 ± 0.5 Ru54 45.9 ± 29.9 0.29 ± 0.15 3.0 ± 0.5 1.586 18.3 ± 11.9 0.46 ± 0.24 4.7 ± 0.8 Ru60 45.5 ± 20.4 0.39 ± 0.11 4.0 ± 0.5 1.786 14.3 ± 6.4 0.70 ± 0.20 7.1 ± 0.9 Ru63 13.1 ± 5.2 0.90 ± 0.25 7.0 ± 1.0 1.090 11.0 ± 4.3 0.98 ± 0.27 7.6 ± 1.1 Ru66 15.9 ± 6.5 0.64 ± 0.18 4.0 ± 0.5 1.091 6.2 ± 2.5 0.99 ± 0.29 6.4 ± 0.8 Ru152 47.0 ± 32.0 0.20 ± 0.08 3.5 ± 0.5 2.325 8.7 ± 5.6 0.47 ± 0.19 8.1 ± 1.2 Ru174 5.0 ± 1.7 0.94 ± 0.24 4.8 ± 0.5 0.613 13.4 ± 0.5 0.58 ± 0.15 2.9 ± 0.3 Table Notes. Col. 6: arcmin to parsec scale. For comparison with other clusters, the King-like central stellar density (σ0 ) and core radius (Rc ), together with the cluster radius (RRDP ), are given both in angular and absolute units. Table 3. Integrated magnitude and colours Apparent Absolute/reddening corrected Cluster mJ (J − H) (J − Ks ) (H − Ks ) MJ MV (J − H)0 (J − Ks )0 (1) (2) (3) (4) (5) (6) (7) (8) (9) (H − Ks )0 (V − J)0 (10) (11) Ru 1 8.08 ± 0.03 +0.30 ± 0.06 +0.37 ± 0.06 +0.06 ± 0.08 −3.3 ± 0.2 −1.8 ± 0.3 +0.22 ± 0.06 +0.24 ± 0.06 +0.02 ± 0.08 1.5 ± 0.4 Ru 10 8.67 ± 0.02 −0.17 ± 0.08 −0.64 ± 0.10 −0.47 ± 0.13 −3.7 ± 0.2 −2.2 ± 0.4 −0.37 ± 0.08 −0.95 ± 0.10 −0.58 ± 0.13 1.6 ± 0.4 Ru 23 7.94 ± 0.01 +0.65 ± 0.03 +0.84 ± 0.02 +0.19 ± 0.03 −4.9 ± 0.2 −3.3 ± 0.4 +0.48 ± 0.03 +0.58 ± 0.02 +0.09 ± 0.03 1.6 ± 0.4 Ru 26 9.03 ± 0.06 −0.21 ± 0.26 −1.44 ± 0.62 −1.23 ± 0.67 −2.6 ± 0.2 −1.1 ± 0.3 −0.32 ± 0.26 −1.61 ± 0.62 −1.29 ± 0.67 1.5 ± 0.4 Ru 27 6.42 ± 0.03 +0.49 ± 0.06 +0.67 ± 0.07 +0.17 ± 0.08 −4.5 ± 0.2 −2.9 ± 0.4 +0.49 ± 0.06 +0.65 ± 0.07 +0.17 ± 0.08 1.6 ± 0.4 Ru 34 7.40 ± 0.01 +0.48 ± 0.03 +0.63 ± 0.02 +0.15 ± 0.03 −4.7 ± 0.2 −3.1 ± 0.4 +0.48 ± 0.03 +0.63 ± 0.02 +0.15 ± 0.03 1.6 ± 0.4 Ru 35 9.20 ± 0.02 +0.49 ± 0.03 +0.63 ± 0.03 +0.14 ± 0.03 −4.1 ± 0.3 −2.6 ± 0.4 +0.35 ± 0.03 +0.41 ± 0.03 +0.05 ± 0.03 1.6 ± 0.5 Ru 37 7.04 ± 0.02 +1.18 ± 0.05 +1.86 ± 0.03 +0.68 ± 0.05 −6.6 ± 0.3 −4.9 ± 0.5 +1.18 ± 0.05 +1.86 ± 0.03 +0.68 ± 0.05 1.7 ± 0.5 Ru 41 9.41 ± 0.03 −0.07 ± 0.07 −0.51 ± 0.10 −0.43 ± 0.11 −3.2 ± 0.3 −1.6 ± 0.4 −0.11 ± 0.07 −0.57 ± 0.10 −0.46 ± 0.11 1.5 ± 0.5 Ru 54 8.81 ± 0.02 +0.60 ± 0.02 +0.78 ± 0.02 +0.18 ± 0.02 −5.0 ± 0.3 −3.4 ± 0.4 +0.56 ± 0.02 +0.72 ± 0.02 +0.16 ± 0.02 1.6 ± 0.5 Ru 60 9.29 ± 0.03 +0.50 ± 0.06 +0.63 ± 0.06 +0.14 ± 0.08 −5.2 ± 0.3 −3.6 ± 0.4 +0.30 ± 0.06 +0.32 ± 0.06 +0.02 ± 0.08 1.6 ± 0.5 Ru 63 8.76 ± 0.03 −0.31 ± 0.13 −1.42 ± 0.35 −1.11 ± 0.37 −4.6 ± 0.2 −3.0 ± 0.4 −0.50 ± 0.13 −1.72 ± 0.35 −1.22 ± 0.37 1.6 ± 0.4 Ru 66 9.76 ± 0.02 +0.05 ± 0.05 −0.04 ± 0.07 −0.09 ± 0.08 −3.9 ± 0.3 −2.3 ± 0.4 −0.23 ± 0.05 −0.48 ± 0.07 −0.26 ± 0.08 1.6 ± 0.5 Ru 152 9.69 ± 0.03 +0.41 ± 0.06 +0.39 ± 0.06 −0.01 ± 0.07 −5.4 ± 0.3 −3.8 ± 0.4 +0.20 ± 0.06 +0.06 ± 0.06 −0.13 ± 0.07 1.6 ± 0.5 Ru 174 8.60 ± 0.03 −0.56 ± 0.08 −1.56 ± 0.21 −1.00 ± 0.22 −3.3 ± 0.2 −1.8 ± 0.3 −0.66 ± 0.08 −1.72 ± 0.21 −1.05 ± 0.22 1.5 ± 0.4 Table Notes. Magnitude and colours have been computed with the decontaminated photometry for the region R 6 RRDP (Table 2). Reddening and distance from the Sun (for the absolute magnitude and reddening-corrected colours - cols. 6-9) are derived in Sect. 4. Cols. 7 and 11: estimated MV and (V − J)0 (Sect. 6.4). The resulting RDPs (and residual background) are shown in Fig. 7. Note that Ru 152 is located at ≈ 30′ to the northwest of NGC 2477, which causes a conspicuous bump in the RDP. We also estimate the cluster radius (RRDP ) by mea- suring the distance from the centre where the cluster RDP and residual background are statistically indistinguishable. In this sense, RRDP can be considered as an observational truncation radius, whose value depends both on the radial distribution of member stars and the field density. 8 C. Bonatto and E. Bica Ru10 Ru1 Ru23 Ru26 Ru27 10 1 Ru35 Ru37 Ru41 Ru66 Ru152 Ru54 −2 σ (stars arcmin ) Ru34 10 1 Ru60 Ru63 10 Ru174 a sample of relatively nearby OCs by Piskunov et al. (2007) - their Fig. 3, the present clusters occupy the small-Rc tail. However, we find significant differences, especially in Rc , for the 3 clusters in common with Kharchenko et al. (2005). While they find angular values of RRDP about twice those we derive, their angular values of Rc are ≈ 5 (Ru 27) and ≈ 15 (Ru 1 and Ru 26) times larger. This, in turn, would imply core radii of the order of ∼ 2.5 pc to ∼ 4.0 pc, bigger than most of the Galactic globular clusters (see, e.g. Fig. 8 of Bonatto & Bica 2008b). These discrepancies probably arise from the fact that they do not field-decontaminate their photometry. Because of the low-contrast RDPs that result when field stars are not eliminated, structural radii derived from RDP fits may not be robust. Finally, according to Bonatto & Bica (2008a), the depth-limited 2MASS photometry has only a small effect on the core radius determination (by means of the Kinglike fit), but may be somewhat more important for RRDP , especially in Ru 37, for which stars fainter than the mainsequence turnoff (MSTO) are not detected. NGC2477 6 1 0.1 1 10 0.1 1 10 0.1 1 10 0.1 R (arcmin) 1 10 0.1 1 10 Figure 7. Stellar RDPs (filled circles) together with the bestfit King-like profile (solid line), the 1σ uncertainty (light-shaded region) and the residual background level (shaded polygon). Note the pronounced central cusps in Ru 23, 27, 41, 63 and 174. The excess in the RDP of Ru 152 at R ≈ 20′ − 40′ is due to NGC 2477. The above RDPs are fitted with the function σ(R) = σbg + σ0 /(1 + (R/Rc )2 ), where σ0 and σbg are the central and residual background stellar densities, and Rc is the core radius. When applied to star counts, this function is similar to that used by King (1962) to the surface-brightness profiles in the central parts of globular clusters. Degrees of freedom are minimised by allowing only σ0 and Rc to vary in the fits, while σbg is previously measured in the surrounding field and kept fixed. The best-fit solutions are shown in Fig. 7, and the corresponding structural parameters are given in Table 2. Within uncertainties, the adopted King-like function provides a reasonable description along the full radial range of the RDPs for most of the sample (Fig. 7). The exceptions are Ru 27, Ru 41, and Ru 174, which present a pronounced cusp (density excess over the King-like fit) in the innermost RDP bin. The same appears to apply to Ru 23 and Ru 63, although only at the 1σ level. This feature has been attributed to a post-core collapse structure in some globular clusters (e.g. Trager, King & Djorgovski 1995). However, such a dynamical evolution-related feature has also been detected in the RDP of some Gyr-old OCs, e.g. NGC 3960 (Bonatto & Bica 2006) and LK 10 (Bonatto & Bica 2009a). Alternatively, clusters that form dynamically cool and with significant substructure will probably develop an irregular central region, unless such a region collapses and smoothsout the initial substructure (Allison et al. 2009). Compared to the distribution of core radii derived for DISCUSSION In the previous sections we derived a set of fundamental and structural parameters for a sample of 15 overlooked Ruprecht clusters. Now we use these parameters for comparison with the previously analysed Ruprecht clusters listed in WEBDA, as well as to investigate relations among parameters. 6.1 Comparison with the Ruprecht OCs in WEBDA WEBDA contains 171 such clusters with coordinates, but only 79 have age, reddening and distance from the Sun been determined so far. The ℓ and b distribution of the Ruprecht clusters in WEBDA is shown in Fig. 8. By far, most of them are located in the 3rd and 4th quadrants, and within |b| . 8◦ . Our sample shares the same b distribution but is restricted essentially to the 3rd quadrant. With respect to the age and reddening distributions, our sample basically maps those of the WEBDA clusters. However, our sample is biased towards larger values of the distance from the Sun, which is consistent with the fact that they still haven’t been studied in detail. 6.2 Location in the Galaxy The positions of the sample clusters, projected onto the Galactic plane, are shown in Fig. 9, which contains the spiral arm structure of the Milky Way based on Momany et al. (2006) and Drimmel & Spergel (2001), derived from HII regions and molecular clouds (e.g. Russeil 2003). The Galactic bar is shown with an orientation of 14◦ and 6 kpc of total length (Freudenreich 1998; Vallée 2005). For comparison we also include the OCs with age and distance from the Sun given in WEBDA, separated in two age groups, clusters younger or older than 1 Gyr. The main features that emerge from Fig. 9 are summarised as follows. With respect to the Sun, all directions Overlooked Ruprecht clusters N 30 20 20 12 15 8 10 9 τ < 1.0Gyr τ > 1.0Gyr Present sample Sun 12 N 8 O b( ) 4 10 4 Orion−Cygnus Outer Arm −4 yGC (kpc) 0 5 −8 −12 −16 0 90 180 270 O l( ) 0 5 20 35 N 0 0.3 0.6 0.9 E(B−V) Norma 1.2 −4 Crux−Scutum 30 20 Bar 0 −8 Perseus Sagittarius−Carina 25 15 −12 −16 N N 20 15 10 10 5 5 0 0 1 2 3 4 5 6 7 8 9 dO (kpc) 0 0 1000 2000 3000 4000 Age (Myr) Figure 8. General properties of the present OCs (filled circles and shaded histograms) compared to the Ruprecht clusters (empty circles and histograms) listed in WEBDA. Dashed lines in the ℓ × b diagram show the borders of the Galactic quadrants. show a depletion in the number of detected OCs for distances farther than ∼ 2 kpc. This occurs because completeness effects (due to crowding and high background levels) together with enhanced disruption rates begin to affect critically regions more distant than ∼ 2 kpc, especially towards the bulge (e.g. Bonatto et al. 2006). Given the high dissolution rates in the inner Galaxy associated with dynamical interactions with the disk, the tidal pull of the bulge, and collisions with giant molecular clouds (e.g. Friel 1995; Bergond, Leon & Guilbert 2001; Bonatto & Bica 2007a), old OCs are found preferentially outside the solar circle, a region with relatively low tidal stress. On the other hand, the presence of bright stars in young OCs allows them to be detected farther than the old ones, especially towards the central Galaxy. It should be noted that WEBDA contains essentially optically-selected OCs, and when surveys in the near-infrared are conducted - like the present one, an increasing number of (basically old) OCs at large distances from the Sun are being found. Near-infrared searches, in turn, might minimise the OC incompleteness around the Sun, but the problem for large distances would still remain (e.g. Bonatto et al. 2006). Most of the present sample is located between the Perseus and Sagittarius-Carina arms, except for Ru 37 and especially Ru 152 that are beyond the Perseus arm. Given their age range (400 Myr − 3 Gyr), it is quite possible that some of them may have suffered tidal stress from the arms, by means of encounters with giant molec- −12 −8 −4 xGC (kpc) 0 4 8 Figure 9. Schematic projection of the Galaxy, as seen from the North pole, with 7.2 kpc as the Sun’s distance to the Galactic centre, in which the projected distribution of the present Ruprecht star clusters (triangles) is compared to the WEBDA OCs younger (circles) and older than 1 Gyr (squares). Clusters with the central cusp (Fig. 7) are shown as filled triangles. Main Galactic structures are identified. ular clouds. Collision with such clouds is another potential dissolution mechanism, especially for low-mass clusters (e.g. Wielen 1971; Wielen 1991; Gieles et al. 2006; Gieles, Athanassoula & Portegies Zwart 2007). Such events might have accelerated the dynamical evolution and produced changes in the cluster structure. However, we note that there is no difference in the projected positions of the clusters that display the central cusp in the RDP (Fig. 7) with respect to the King-like ones. In any case, it would be necessary to re-construct their orbits through the Galaxy for a deeper analysis on this issue. 6.3 Cluster size dependencies Despite the considerable scatter, a first-order dependence of cluster size on Galactocentric distance is suggested in Fig. 10 (panel a). Incidentally, the discordant cluster is Ru 37 (RRDP ≈ 2.1 pc), the oldest one (∼ 3 Gyr) of our sample. Given the age and distance from the Sun (d⊙ ∼ 5 kpc) of Ru 37, stars fainter than the MSTO are not detected by 2MASS, which may have underestimated its size. Such a relation has already been observed (e.g. Lyngå 1982; Tadross et al. 2002; van den Bergh, Morbey & Pazder 1991), and may reflect the low dissolution rates associated with large Galactocentric distances. The rather weak correlation may be partly due to the fact that our sample clusters are located essentially outside the solar circle. This point can be further investigated by examining the dependence of cluster size on the vertical distance to the Galactic plane |ZGP |, since our clusters are located within |ZGP | . 1.0 kpc. With the exception of Ru 37, a somewhat tight correlation shows up between RRDP and |ZGP |. In- C. Bonatto and E. Bica RRDP (pc) 10 9 8 7 6 5 (b) (a) 4 3 Ru37 Ru37 2 7 8 9 10 dGC (kpc) 11 12 0.1 |zGC| (kpc) 1 2 (c) (d) (e) (f) (J−KS)O 1 0 −1 MJ (mag) −6 −5 −4 −3 −2 −1 −0.5 0 0.5 (J−H)O 1 300 500 700 1000 20003000 Age (Myr) Figure 10. Top: relation of the cluster radius with Galactocentric distance (left) and distance from the plane (right). Arrows indicate the lower-limit of RRDP for Ru 37. Middle: dependence of the integrated (J − Ks )0 colour on (J − H)0 (left) and cluster age (right). Bottom: same as above for the absolute J magnitude. Clusters with the central cusp (Fig. 7) are shown as filled circles. Dashed-line in (b): RRDP (pc) = (2.4 ± 0.4) + (6.5 ± 2.7) × |ZGP (kpc)|. Dashed-line in (c): (J − Ks )0 = (−0.27 ± 0.04) + (1.78 ± 0.06) × (J − H)0 . Shaded region in (b) and (c): 1σ fit uncertainty. deed, excluding Ru 37, the remaining points are roughly described by the relation RRDP (pc) = (2.4 ± 0.4) + (6.5 ± 2.7) × |ZGP (kpc)|. Again, this relation is consistent with a lower-frequency of encounters with giant molecular clouds and the disk for OCs at high |ZGP | with respect to those orbiting closer to the plane. However, we note that part of this effect may be related to completeness. Given that the average background+foreground contamination decreases with increasing |ZGP |, the external parts of an OC (where the surface brightness is intrinsically low) can be detected at larger distances for high-|ZGP | objects than for those near the plane (Bonatto et al. 2006). On average, clusters at high|ZGP | will tend to seem bigger than near the plane. 6.4 Integrated colours and magnitudes Having decontaminated the photometry (Sect. 3) and derived structural parameters (Sect. 5), we now proceed to compute the integrated (apparent and absolute) magnitudes and reddening-corrected colours for the 2MASS bands. Since the decontamination efficiency is lower than 100% (Sect. 3), we start by applying the colour-magnitude filter to the de- contaminated photometry. Then we sum the flux (for a given band) of all stars within R 6 RRDP (Table P 2) to compute the cluster+residual field stars flux (FJcl+f s = i 10−0.4Ji ). The same is done for all the comparison field stars, to estimate the residual contamination flux (FJf s ). Thus, the integrated
magnitude is given by mJ = −2.5 log FJcl+f s − Ω × FJf s , where Ω is the ratio between the projected areas of the cluster and the comparison field. This procedure is applied to the J, H, and Ks bands, and should minimise decontamination efficiency effects. Since all clusters contain giant and MSTO stars (Figs. 3 - 5) - which by far dominate the luminosity, the integrated magnitudes should not be significantly affected by the non-detection of the lower-MS stars associated with the depth-limited 2MASS photometry. Reddening and distance from the Sun (for the absolute magnitude and reddeningcorrected colours) are those computed in Sect. 4. The results are given in Table 3 and discussed below. The integrated and reddening-corrected (J − Ks )0 and (J − H)0 colours are tightly related by (J − Ks )0 = (−0.27 ± 0.04) + (1.78 ± 0.06) × (J − H)0 (Fig. 10, panel c), and redder clusters also tend to be brighter in J (e). Panels (d) and (f) seem to show a slight tendency of old clusters to be redder and brighter than the young ones. This is consistent with most of the stellar luminosity (especially for the more massive stars) being transferred from the optical to the near-IR, as star clusters become older. As a caveat, the latter relation hinges essentially on a single cluster with ∼ 3 Gyr of age. Thus, with the present data we cannot quantify the role of age in driving the near-infrared colours (panels c and d), since the age for most of the present OCs are restricted to the range 400 Myr ∼ 1 Gyr. As far as we are aware, there is no study of OC integrated colours or magnitudes linking the near-IR to the optical. However, if we assume that OCs and globular clusters follow similar scaling relations - at least with respect to integrated colours and magnitudes, we can use the Galactic globular clusters (MWGCs) both for comparison and to search for such a link. For this purpose, we use the integrated and reddening-corrected (V − Ks )0 , (J − H)0 , and (J − Ks )0 colours computed for a large set of MWGCs on 2MASS images (Cohen et al. 2007), coupled to the respective absolute MV magnitudes from Harris (1996, together with the 2003 revision). The results are summarised in Fig. 11 (top panels). Consistent with their old ages, the MWGCs (J − Ks )0 and (J − H)0 colours (panel a) are restricted to a narrow range (the spread is essentially due to the different metallicities and partly to unaccounted for reddening), when compared to the set of (younger) Ruprecht OCs (Fig. 10, panel c). Besides, the near-IR MWGC colours follow a similar - although somewhat flatter ((J − Ks )0 ∝ 1.2 × (J − H)0 ) - relation than our Ruprecht OCs ((J − Ks )0 ∝ 1.8 × (J − H)0 ). Finally, with respect to the absolute magnitudes MV and MJ (panel b), the MWGCs are tightly related by MV = (1.41 ± 0.27) + (0.96 ± 0.03) × MJ , over the relatively wide ranges −12 . MV . −6.5 and −10 . MJ . −4.5. Note that the few discordant points can be accounted for by a reddening under-correction. The apparent J magnitude distribution of our sample clusters is clearly biased towards fainter objects (panel c of Fig. 11), with about half of the sample having mJ & 8.5, Overlooked Ruprecht clusters −11 (a) 0.8 MWGCs (b) similar to - but still somewhat biased to lower luminosities than - the MWOCs. MWGCs 0.7 MV (J−KS)O −9 0.6 0.5 AV=0 −7 0.4 0.5 0.6 (J−H)O −6 0.7 5 N (OCs) N (OCs) −8 −9 MJ −10 −11 −12 (d) 5 3 2 1 7 10 9 8 mJ 7 3 2 0 6 6 −1 −0.5 0 0.5 (J−H) 1 1.5 0 0.5 (J−H)O 1 1.5 6 (e) 5 (f) 5 N (OCs) 4 3 2 1 4 3 2 1 −2 −3 −4 −5 MJ −6 0 −7 20 N (OCs) −1 −0.5 Ru Sample MWOCs (g) 15 10 5 0 −1 −2 −3 −4 −5 MV −6 −7 −8 −9 Figure 11. Panels (a) and (b): relations derived from MWGCs for the (J − Ks )0 and (J − H)0 colours ((J − Ks )0 = (1.16 ± 0.01) × (J − H)0 ), and the absolute V and J magnitudes (MV = (1.41 ± 0.27) + (0.96 ± 0.03) × MJ ). Arrow in (b): reddening vector for AV = 2. Panels (c) and (d): histograms for the number of OCs within bins of apparent J magnitude and (J − H) colour. Panels (e) and (f): same as above for the absolute J magnitude, and the reddening-corrected (J − H)0 colour. Panel (g): the distribution of the extrapolated MV values of our Ruprecht sample (shaded histogram) compared (empty histogram) to the Galactic OCs of Lata et al. (2002) and Battinelli, Brandimarti & Capuzzo-Dolcetta (1994). while the absolute J magnitude (e) is roughly uniformly distributed around MJ ≈ −4.5, with a ±2.0 mag spread. The observed (d) and reddening-corrected (f) (J − H) colours are roughly distributed around the average value (J − H) ≈ 0.5, with a ±1.0 mag spread. Now, extrapolating the MWGC MV × MJ relation to the MJ values derived for our Ruprecht clusters, we find MV values in the range −5 . MV . −1 (panel g of Fig. 11 and Table 3). Note that the integrated colour (V − J) is similar in all cases, with an average value (V − J)0 = 1.6 ± 0.5. We now compare the Ruprecht MV values with those measured for 140 Galactic OCs (MWOCs) by Lata et al. (2002) together with 106 OCs of Battinelli, Brandimarti & Capuzzo-Dolcetta (1994)9 . Most (≈ 72%) of the MWOCs have MV within −5.5 . MV . −2.5, but the remaining ones can be as luminous as MV ≈ −10. Clearly, our Ruprecht clusters, in general, appear to be intrinsically faint in the optical, with an MV distribution 9 SUMMARY AND CONCLUSIONS 4 1 0 N (OCs) −7 6 (c) 4 0 AV=2 −5 0.4 0.3 11 Both samples have similar MV distributions. For the OCs in common we have used the more recent values of Lata et al. (2002). Given the rather efficient and numerous dissolution mechanisms operating in the Galaxy, the majority of the open clusters do not survive beyond a few 108 yr. In this context, it is important to investigate the structural and photometric properties of OCs that are undergoing this evolved phase. The present paper focuses on 15 overlooked Ruprecht clusters, 12 of them never before studied. With the exception of a single object at ℓ ≈ 78◦ , the remaining clusters are located in the 3rd Galactic quadrant, which minimises the field-star contamination. We work with 2MASS photometry (with errors . 0.15 mag), on which we apply field-star decontamination to enhance CMD evolutionary sequences and stellar RDPs, thus yielding more constrained fundamental and structural parameters. As typical optically discovered clusters, the reddening values are relatively low, within 0.0 . E(B − V ) . 0.9; on the other hand, they are distant from the Sun, within 1.5 . d⊙ (kpc) . 8.0. The integrated apparent J magnitudes are rather faint, within 6.4 . mJ . 9.8, but given the distances, the absolute magnitudes are relatively bright −6.6 . MJ . −2.6. The ages are in the range 400 Myr 1 Gyr, except for the significantly older Ru 37, with ∼ 3 Gyr. The RDPs are well contrasted with respect to the background and follow the King-like profile for most of the radial range. Exceptions are Ru 23, Ru 27, Ru 41, Ru 63, and Ru 174, which present a pronounced stellar density excess in the innermost RDP bin. The core radii of the present sample are small, when compared to those of nearby OCs (e.g. Piskunov et al. 2007). By extrapolating the relation between MV and MJ , derived for globular clusters, we estimate −5 . MV . −1, which suggests that they are lowluminosity optically-selected clusters. The sample clusters are located between (or close to) the Perseus and Sagittarius-Carina arms, and we present evidence that the cluster size increases both with Galactocentric distance and distance to the plane. The latter relation, in particular, is consistent with a low frequency of tidal stress associated with high-|ZGP | regions. It is clear from the above analysis that searches for star clusters in catalogues of candidates - even in the optical are far from complete. Detailed investigations will certainly add more members to the present-day open cluster census. Besides, since young clusters are rather easy to identify even at large distances, the overlooked clusters are expected to be of the evolved/old age range. Thus, works like the present one are important not only because reliable astrophysical parameters are derived for a sample of unstudied clusters. Perhaps the main importance lies in the unambiguous characterisation of open clusters with ages beyond several 108 yr. A better statistics on the population of these - and older clusters can be used to investigate cluster formation rates and to constrain the time scale of cluster dissolution in the Galaxy. 12 C. Bonatto and E. Bica ACKNOWLEDGEMENTS We thank the reviewer, Dr. A.F. Moffat, for interesting comments and suggestions. We acknowledge support from the Brazilian Institution CNPq. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Centre/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This research has made use of the WEBDA database, operated at the Institute for Astronomy of the University of Vienna. REFERENCES Allison R.J., Goodwin S.P., Parker R.J., de Grijs R., Portegies Zwart S.F. & Kouwenhoven M.B.N. 2009, ApJL, 700,99 Alter G., Balázs B., Ruprecht J. & Vanysek J. 1970, in Catalogue of Star Clusters and Associations, Budapest Akademiai Kiado, 2nd Edition, ed. by Alter G., Balázs B. & Ruprecht J. Battinelli P., Brandimarti A. & Capuzzo-Dolcetta R. 1994, A&AS, 104, 379 Baumgardt H. & Makino J. 2003, MNRAS, 340, 227 van den Bergh S., Morbey C. & Pazder J. 1991, ApJ, 375, 594 Bergond G., Leon S. & Guilbert J. 2001, A&A, 377, 462 Bessel M.S. & Brett J.M. 1988, PASP, 100, 1134 Bica E., Bonatto C. & Camargo D. 2008, MNRAS, 385, 349 Bonatto C., Bica E. & Girardi L. 2004, A&A, 415, 571 Bonatto C., Kerber L.O., Bica E. & Santiago B.X. 2006, A&A, 446, 121 Bonatto C. & Bica E. 2006, A&A, 455, 931 Bonatto C. & Bica E. 2007a, A&A, 473, 445 Bonatto C. & Bica E. 2007b, MNRAS, 377, 1301 Bonatto C. & Bica E. 2008a, A&A, 477, 829 Bonatto C. & Bica E. 2008b, A&A, 479, 741 Bonatto C. & Bica E. 2009a, MNRAS, 392, 483 Bonatto C. & Bica E. 2009b, MNRAS, 394, 2127 Bonatto C. & Bica E. 2010, A&A, in press Cardelli J.A., Clayton G.C. & Mathis, J.S. 1989, ApJ, 345, 245 Carraro G., Janes K.A. & Eastman J.D. 2005, MNRAS, 364, 179 Carraro G., Janes K.A., Costa E. & Méndez R.A. 2006, MNRAS, 368, 1078 Carraro G., Subramaniam A. & Janes K.A. 2006, MNRAS, 371, 1301 Cohen J.G., Hsieh S., Metchev S., Djorgovski S.G. & Malkan M. 2007, AJ, 133, 99 Dias W.S., Alessi B.S., Moitinho A. & Lépine J.R.D. 2002, A&A, 389, 871 Drimmel R., & Spergel D.N. 2001, ApJ, 556, 181 Dutra C.M., Santiago B.X. & Bica E. 2002, A&A, 383, 219 Freudenreich H.T. 1998, ApJ, 492, 495 Friel E.D. 1995, ARA&A 1995, 33, 381 Gieles M., Athanassoula E. & Portegies Zwart S.F. 2007, MNRAS, 376, 809 Gieles M., Portegies Zwart S.F., Baumgardt H., Athanassoula E., Lamers H.J.G.L.M. Sipior M. & Leenaarts J. 2006, MNRAS, 371, 793 Girardi L., Bertelli G., Bressan A., Chiosi C., Groenewegen M.A.T., Marigo P., Salasnich B. & Weiss A. 2002, A&A, 391, 195 Goodwin S.P. & Bastian N. 2006, MNRAS, 373, 752 Harris W.E. 1996, AJ, 112, 1487 Khalisi E., Amaro-Seoane P. & Spurzem R. 2007, MNRAS, 374, 703 Kharchenko N.V., Piskunov A.E., Röser S., Schilbach E. & Scholz R.-D. 2005, A&A, 438, 1163 King I. 1962, AJ, 67, 471 Lada C.J. & Lada E.A. 2003, ARA&A, 41, 57 Lamers H.J.G.L.M. & Gieles M. 2006, A&AL, 455, 17 Lamers H.J.G.L.M., Gieles M., Bastian N., Baumgardt H., Kharchenko N.V. & Portegies Zwart S. 2005, A&A, 441, 117 Lata S., Pandey A.K., Sagar R. & Mohan V. 2002, A&A, 388, 158 Lyngå G. 1982, A&A, 109, 213 Momany Y., Zaggia S., Gilmore G., Piotto G., Carraro G., Bedin L.R. & de Angeli F. 2006, A&A, 451, 515 Naylor T. & Jeffries R.D. 2006, MNRAS, 373, 1251 Oort J.H. 1958, in Ricerche Astronomiche, 5, 415, Specola Vaticana, Proc. of a Conference at Vatican Observatory, Castel Gandolfo, May 20-28, 1957, ed. D.J.K. O’Connell Pavani D.N. & Bica E. 2007, MNRAS, 468, 139 Piskunov A.E., Schilbach E., Kharchenko N.V., Röser S. & Scholz R.-D. 2007, A&A, 468, 151 Russeil D. 2003, A&A, 397, 133 Skrutskie M., Schneider S.E., Stiening R., Strom S.E., Weinberg M.D., Beichman C., Chester T., Cutri R .et al. 1997, in The Impact of Large Scale Near-IR Sky Surveys, ed. F. Garzon et al., Kluwer (Netherlands), 210, 187 Spitzer L. 1958, ApJ 127, 17 Tadross A.L., Werner P., Osman A. & Marie M. 2002, NewAst, 7, 553 Trager S.C., King I.R. & Djorgovski S. 1995, AJ, 109, 218 Vallée J.P. 2005, AJ, 130, 56 Wielen R. 1971, A&A, 13, 309 Wielen R. 1991, in “The Formation and Evolution of Star Clusters”, K. Janes (ed.), Astron. Soc. Pac. Conf. Ser. 13, San Francisco, CA, p. 343-349