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