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OPEN CLUSTERS IN THE MILKY WAY OUTER DISK: NEWLY DISCOVERED AND UNSTUDIED CLUSTERS IN THE SPITZER GLIMPSE-360, CYG-X, AND SMOG SURVEYS

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Published 2013 August 12 © 2013. The American Astronomical Society. All rights reserved.
, , Citation G. Zasowski et al 2013 AJ 146 64 DOI 10.1088/0004-6256/146/3/64

1538-3881/146/3/64

ABSTRACT

Open stellar clusters are extremely valuable probes of Galactic structure, star formation, kinematics, and chemical abundance patterns. Near-infrared (NIR) data have enabled the detection of hundreds of clusters hidden from optical surveys, and mid-infrared (MIR) data are poised to offer an even clearer view into the most heavily obscured parts of the Milky Way. We use new MIR images from the Spitzer GLIMPSE-360, Cyg-X, and SMOG surveys to visually identify a large number of open cluster candidates in the outer disk of the Milky Way (65° < l < 265°). Using NIR color–magnitude diagrams, stellar isochrones, and stellar reddening estimates, we derive cluster parameters (metallicity, distance, reddening) for those objects without previous identification and/or parameters in the literature. In total, we present coordinates and sizes of 20 previously unknown open cluster candidates; for 7 of these we also present metallicity, distance, and reddening values. In addition, we provide the first estimates of these values for nine clusters that had been previously cataloged. We compare our cluster sizes and other derived parameters to those in the open cluster catalog of Dias et al. and find strong similarities except for a higher mean reddening for our objects, which signifies our increased detection sensitivity in regions of high extinction. The results of this cluster search and analysis demonstrate the ability of MIR imaging and photometry to augment significantly the current census of open clusters in the Galaxy.

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1. INTRODUCTION

The detection and study of open clusters have proven to be of great benefit for understanding the structure and stellar evolution of our Galaxy. Because the stars of a given cluster are formed within the same giant molecular cloud in the same star-forming episode, the stars will have a common age and chemical composition, which enables much more reliable determinations of age, metallicity, and distance for clusters than are typical with photometry for single field stars. In addition, robust mean radial velocities and proper motions are more easily obtained for multiple stars moving together, which, when combined with the distances, yield full three-dimensional velocity information. Thus, a well-populated census of open clusters is a powerful tracer of not only the Milky Way's (MW) historical and present rate of star formation, but also of the MW's stellar structures and abundance patterns (e.g., Phelps & Janes 1994; Friel 1995; Twarog et al. 1997; Lamers & Gieles 2006; Frinchaboy & Majewski 2008). Currently, ∼2200 open clusters and cluster candidates have been identified in the MW, though some models predict that as many as 100× that number may exist (Bonatto et al. 2006). The majority of these known clusters reside toward the inner parts of the MW disk near the Sun, an effect of both the increased quantity of stars interior to the solar circle and the relative dearth of studies focused on the outer disk, as well as the increased extinction in the MW midplane.

The outer Galactic disk has different structural, dynamical, and abundance properties than the inner Galaxy. For example, though the metallicity gradient beyond the solar circle is relatively poorly constrained, there have been reported indications of discontinuities (e.g., Twarog et al. 1997; Pedicelli et al. 2009; Friel et al. 2010; Cheng et al. 2012), and the overall stellar dynamics of the outer disk warp/flare remain poorly understood (e.g., López-Corredoira 2006; Bellazzini et al. 2006). Furthermore, the gentler dynamics of the outer disk may prolong the lifetime of open clusters, and older clusters are crucial for tracing the Galactic star formation history. To date, many open cluster searches have targeted the inner Galaxy (e.g., Reylé & Robin 2002; Mercer et al. 2005; Magrini et al. 2010; Carraro & Seleznev 2012) or well-known nebulae and star-forming regions in the outer Galaxy (e.g., Bica et al. 2003; Dutra et al. 2003). Some larger-scale automated cluster searches have probed the all-sky Two Micron All Sky Survey (2MASS) photometry (e.g., Ivanov et al. 2002; Froebrich et al. 2007) and identified a large number of apparent stellar overdensities in the outer disk; many of these, however, remain unverified as genuine stellar clusters.

While cluster searches in the near-infrared (NIR) have probed distant and heavily reddened regions, and revealed distant or dust-embedded (i.e., young) objects not visible at optical wavelengths (e.g., Ivanov et al. 2002; Bica et al. 2003; Dutra et al. 2003; Kronberger et al. 2006; Froebrich et al. 2007; Borissova et al. 2012), the Galactic cluster sample remains far from complete. The depth and resolution of the oft-used 2MASS (Skrutskie et al. 2006) are not sufficient to trace clusters of main sequence stars near the edge of the disk, while the UKIDSS Galactic Plane Survey (Lucas et al. 2008), though deeper than 2MASS, only spans a fraction of the outer disk. Enhanced open cluster detection capability is offered by multiple Spitzer surveys—Cyg-X, Vela-Carina, SMOG, and GLIMPSE-360 (Section 2.1; Hora et al. 2007; Majewski et al. 2007; Carey et al. 2008; Whitney et al. 2011)—which together use the Spitzer-IRAC instrument to image the complete outer disk midplane at high angular resolution (∼2'') from 3.6 μm up to 8.0 μm. With these mid-IR (MIR) images and the subsequent source catalogs, we have conducted a visual search for open cluster candidates and performed isochrone fitting on those with sufficient NIR photometry to identify cluster color–magnitude sequences. In this paper, we focus only on the regions covered by Cyg-X, SMOG, and GLIMPSE-360.

In Section 2, we describe the data and methods used in the cluster identification and characterization. A descriptive list of the individual clusters can be found in Sections 3.1 and 3.2 for the newly discovered objects and in Section 3.3 for the previously known objects. In Section 4, we compare our cluster properties to those of the current open cluster census and summarize our findings.

2. DATA AND METHODS

2.1. Data

The primary source of MIR images for this cluster search is the GLIMPSE-360 survey (Whitney et al. 2011, 2008), a "Warm Spitzer" campaign to complete the IRAC coverage of the Galactic midplane started by the earlier Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE; Churchwell et al. 2009). The GLIMPSE-360 program is producing images of the outer Galactic midplane (65° ≲ l ≲ 265°) from Spitzer-IRAC's surviving [3.6μ] and [4.5μ] channels, using exposure sequences of 3 × 0.6 s and 3 × 12 s in High Dynamic Range mode.

Prior to the loss of Spitzer's cryogen, three observing programs compiled comparable images—including the now defunct [5.8μ] and [8.0μ] IRAC channels—for select regions in the outer midplane. The first of these, Cygnus-X (Cyg-X; Hora et al. 2007), was designed to target the rich star-formation regions in Cygnus and spans ∼24 deg2 centered at (l, b) ∼ (78fdg85, 0fdg44). The second survey, Spitzer Mapping of the Outer Galaxy (SMOG; Carey et al. 2008), covers ∼21 deg2 at (l, b) ∼ (105fdg5, 1fdg5). These programs utilized the same exposure scheme as GLIMPSE-360. The Vela-Carina survey (Majewski et al. 2007) imaged a large swath of the midplane in the third and fourth Galactic quadrants (255° ≲ l ≲ 295°), including the Vela molecular ridge, using an exposure sequence matched to the original GLIMPSE survey (2 × 2 s). These Vela-Carina data will be analyzed in a similar manner in an upcoming paper.

All of these MIR images have been processed with the same University of Wisconsin IRAC pipeline developed for the earlier GLIMPSE-I/II/3D surveys.7 This paper uses the highly reliable "Catalog" source lists from that pipeline, along with the merged set of GLIMPSE-360, Cyg-X, and SMOG images.8

The Spitzer MIR data are supplemented with NIR photometry from the 2MASS Point Source Catalog (Skrutskie et al. 2006) merged as part of the GLIMPSE pipeline, with the associations having positional offsets of typically <0farcs3. Because they are significantly more sensitive to stellar temperature than the MIR photometry, these NIR data are necessary for fitting isochrones in IR color–magnitude space. We require total photometric uncertainties of ⩽0.1 mag in the 2MASS and IRAC ([3.6μ] and [4.5μ]) bands in order for a star to be considered, and the vast majority have uncertainties far below this limit.

2.2. Identifying Cluster Candidates

We visually identified the cluster candidates using the IRAC [3.6μ], [4.5μ], and [8.0μ] (where available) image mosaics, inspecting the entire set of images from GLIMPSE-360, Cyg-X, and SMOG for potential clusters based on an overdensity of stars with similar brightness in a given area. For each pair of central coordinates (l, b), we visually estimated an initial cluster angular radius R as the radius at which the cluster candidate stellar density was indistinguishable from the background stellar density (i.e., the "cluster density" approaches zero).

We searched for published cluster identifications at all of our candidate positions using the WEBDA database9 and the updated catalog of Dias et al. (2002).10 For each cluster candidate that matched a known cluster within ∼8 initial R, we reviewed the available literature for the known object to check whether our MIR candidate (including coordinates and any associated NIR photometry) was consistent with the published data or represented a new cluster. Nearly all of the objects that had matches were within 0.75R of the published coordinates. Considering all of our detected candidates, and those entries in the Dias et al. (2002) catalog that have been verified as genuine clusters (via distance, reddening, or metallicity measurements), we estimate our sample completeness to be ∼50%, with the "missed" objects being preferentially larger clusters (R ≳ 7') that appear like random, loose scatterings of bright stars on the angular scales at which we examined the Spitzer images.

In addition, for each cluster candidate, we compared the 2MASS (JKs, H) color–magnitude diagram (CMD) of the identified center (l, b) and size R to that of an equal-area annulus with an inner edge at 2R from the center. The cluster candidates were sorted into quality bins depending on the qualitative difference between the candidate cluster and comparison CMDs and on the clarity of the stellar overdensity in the Spitzer image. Some faint, compact cluster candidates have very weak, poorly populated CMDs that are likely to be limited by the 2MASS catalog's magnitude limit (H ≲ 15.1) and point source separation limit (∼6''), both of which are more restrictive than those of the Spitzer data.

Combining the results of the literature search and the CMD evaluation resulted in multiple categories of cluster candidate, three of which are presented in this paper: (1) previously unidentified clusters with well-populated NIR CMDs (e.g., top row of Figure 1; 7 objects), (2) previously unidentified clusters without a high-quality NIR CMD but with a very distinct MIR stellar overdensity (e.g., bottom row of Figure 1; 13 objects), and (3) clusters with a published identification but without distances or reddening derived from isochrone-fitting (9 objects). These categories shape the organization of our results presented in Section 3.

Figure 1.

Figure 1. Examples of the data used in sorting the initial list of candidates. Top row: for a cluster classified as having both a good image and a good CMD (GLM-CYGX 16), (a) [3.6μ] image of the cluster center, with the initial radius indicated by the solid line, along with the equal-area annulus used as the initial comparison region (dashed lines), (b) CMD within one initial cluster radius, and (c) CMD of the comparison region. Bottom row: (d)–(f) Same as top row, for a cluster classified as having a good image but a NIR CMD too poorly populated for isochrone-fitting (GLM-G360 174).

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2.3. Calculating Stellar Extinction

One of the major difficulties in distinguishing open clusters from their stellar neighborhoods is that the cluster stars are photometrically very similar to their foreground and background neighbors, a problem made even more complex when the observed cluster stars are near the magnitude limit of a photometric catalog and/or belong to a cluster of intrinsically low stellar density. In the absence of kinematical data from spectroscopy to establish cluster membership, the stellar reddening values can be used to isolate candidate cluster stars from the stellar fore- and background, under the assumption that stars in the cluster suffer a similar level of reddening.

We calculate a reddening value for each individual star in the cluster regions using the Rayleigh–Jeans Color Excess (RJCE) method (Majewski et al. 2011). This technique takes advantage of the fact that most normal stars, regardless of spectral type, have a common shape in the Rayleigh–Jeans regime of their spectral energy distributions (SEDs). This similarity results in a common intrinsic color in wavelengths sampling the Rayleigh–Jeans tail of the SED. Then, any observed excess in these colors represents a deviation from the values expected for an extinction-free normal stellar photosphere and can usually be assumed to be caused by interstellar extinction.

To first order, foreground field stars will have lower reddening than the cluster, and background field stars will have higher, though this simple solution is complicated (particularly in the MW midplane) by the presence of patchy interstellar clouds on arcminute scales, similar to the angular sizes of typical clusters. Furthermore, the RJCE method systematically overestimates the extinction toward objects with IR excesses, such as young stellar objects (YSOs), which are common in open clusters and in the gaseous regions containing young clusters. Nevertheless, as we demonstrate in Section 2.4.2 and Figure 2, the RJCE reddening estimates prove to be quite efficient at isolating cluster sequences, particularly in heavily reddened regions of the sky.

Figure 2.

Figure 2. Example of the use of RJCE extinction estimates to isolate the cluster stellar locus (here, GLM-CYGX 16). (a) Distribution of RJCE-derived reddening values for each star within the nominal cluster radius. The color of each bin is scaled to its distance from the adopted mean reddening of this cluster. (b) 2MASS CMD of all stars within the nominal cluster radius. The color of each point indicates the difference between its RJCE reddening and the mean cluster RJCE reddening (same color scale as in panel (a)). The dashed line is a metal-rich, low-reddening isochrone representing the typical "disk" population, and the arrow indicates the reddening vector of a MSTO star at this distance behind 1 mag of H-band extinction (using the NIR extinction law of Indebetouw et al. 2005), which corresponds to ∼6 mag of V-band extinction. (c) 2MASS CMD of stars falling within the reddening range adopted for this cluster (0.98 ⩽ E(JKs)RJCE ⩽ 1.4) and used for identifying the best-fit isochrone. Note that the low- and high-reddening "disk" contaminants have been largely removed.

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2.4. Fitting Isochrones

At the conclusion of our cluster identification process (Section 2.2), we had visually estimated the central coordinates (l, b) and angular radius R of the cluster. We used these initial parameters to generate NIR CMDs to identify color–magnitude features consistent with a young main sequence turnoff (MSTO, hereafter) and/or a red clump (RC, hereafter). Here, we describe the selection of likely cluster member stars and the simple fitting of isochrones in the NIR CMDs. Discussion of any details specific to individual clusters are reserved for their own sections in Section 3.

2.4.1. Selection of Comparison Regions

Because of the high incidence of bright diffuse emission in the vicinity of many clusters, the original annuli used for evaluating the cluster candidates were deemed insufficient to serve as appropriate comparison regions for the steps of filtering the cluster CMDs by extinction (Section 2.4.2) and fitting them with isochrones (Section 2.4.4). To refine the CMD comparison, we chose a new circular region with the same radius as the cluster, situated nearby but placed carefully so that the "MW disk" stellar sequences in the CMD have the same apparent color range (which includes the intrinsic color plus foreground reddening) as the corresponding sequences in the cluster CMD. This allows us to identify the cluster sequence amongst a more reliable representation of the disk stellar population.

2.4.2. CMD Filtering

The 2MASS CMDs for each cluster represent the coaddition of several different stellar populations, including the Galactic disk in both the fore- and background, as well as the cluster itself. In addition to these distinct stellar sequences, these regions often harbor active star-forming sites that contain YSOs and other objects with atypical NIR or MIR colors. Thus to identify and fit the candidate star cluster properly, we take measures to isolate the true CMD signal of the cluster stars.

Typical statistical field star decontamination techniques (such as those applied by, e.g., Kharchenko et al. 2005; Piatti et al. 2003; Bica & Bonatto 2011), are not reliably effective for our sample, because the MSTO overdensities of the majority of the candidate clusters occur near the completeness limit of the 2MASS photometry (H ∼ 15), where the H and (JKs) measurements can be dominated by photometric scatter induced by the uncertainties. This effect is even stronger in the dereddened CMDs, where the uncertainties in the MIR photometry also play a role. Some of the cluster candidates are in regions with highly variable reddening, as evidenced by the presence of small (subarcminute) absorption and emission structures in the MIR or 2MASS images. The quality of the photometry, the potential for source confusion, and the robustness of stellar detection may thus be variable across the cluster field and between the cluster and comparison region.

In lieu of statistical field star decontamination, we adopt a technique that utilizes our additional leverage from the MIR imaging, via star-by-star reddening estimates (Section 2.3). For each pair of cluster and comparison regions (Section 2.4.1), we evaluated the distribution of RJCE reddening values, both spatially and in the CMDs. Since one criterion for including a cluster in the samples presented here is a prominent cluster CMD sequence distinct from the underlying disk population(s), we were able to identify an initial range of reddening that encompassed the greatest number of cluster stars while rejecting the largest number of disk stars, which are defined as those with colors, magnitudes, and reddening values equally well-represented in both the cluster and comparison CMDs. We checked our selected reddening range by inspecting the spatial distribution of reddening in the cluster and comparison regions and confirming both that the cluster stars within the adopted reddening range clump together and that stars beyond the adopted range have similar scatter in both the cluster and comparison maps. The width of the RJCE reddening "filter" is one of the parameters optimized in the isochrone-fitting iterations (Section 2.4.4).

In Figure 2, we illustrate this process for a dusty cluster field with a large range of reddening. Panel 2(a) contains the reddening distribution for stars within the cluster radius, shaded by separation from the adopted mean RJCE reddening for this field, 〈E(JKs)〉RJCE ∼ 1.2. Panel 2(b) contains the CMD for this cluster region, with the points shaded on the same scale as the distribution in panel 2(a). Note how the cluster sequence stands out from the foreground disk stars with low reddening and the background, more heavily reddened disk stars (which may also include some YSOs). Panel 2(c) shows just this isolated cluster sequence with the best-fitting isochrone, as explained in Section 2.4.4. We note that even if YSOs are inappropriately removed from a cluster field because their reddening is overestimated (Section 2.3), the remaining stellar data are better matched to the theoretical isochrones we use to derive the cluster parameters because the isochrones do not include a YSO sequence.

2.4.3. Initial Estimates of Cluster Parameters

After applying the RJCE reddening filter (Section 2.4.2, Figure 2), we make initial estimates of the key parameters for each cluster in our sample using underlying principles of single stellar populations. We emphasize that these are initial estimates only; the final values reported in Section 3 and Tables 1 and 3 are derived from the iterative isochrone-fitting approach outlined in Section 2.4.4.

Table 1. New Clusters: MIR Images and NIR Isochrone Fits

Cluster ID l b R D E(JKs) [Fe/H]
(deg) (deg) (arcmin) (kpc) (mag)
GLM-CYGX 14 78.992 3.674 2.3 1.69 ± 0.3 1.20 ± 0.06 0.2 ± 0.10
GLM-CYGX 16 79.876 −0.927 4.3 1.36 ± 0.2 1.27 ± 0.02 0.2 ± 0.10
GLM-G360 18 86.947 0.630 4.7 3.50 ± 0.7 0.60 ± 0.10 0.2 ± 0.24
GLM-G360 90 112.632 1.240 4.8 2.91 ± 0.7 0.60 ± 0.08 0.2 ± 0.15
GLM-G360 105 116.999 2.391 4.0 3.04 ± 0.7 0.50 ± 0.14 0.2 ± 0.14
GLM-G360 58 224.618 −0.125 3.3 3.11 ± 1.3 0.45 ± 0.19 0.0 ± 0.14
GLM-G360 75 248.131 −1.206 4.0 4.81 ± 1.0 0.40 ± 0.16  ⋅⋅⋅

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The RC is an oft-utilized standard candle for stellar population studies dating back to, e.g., Stanek et al. (1994) and Paczynski & Stanek (1998). Groenewegen (2008) used the revised Hipparcos parallaxes to revisit the calibration of the absolute magnitude of the RC in the I and Ks bands and found MKs = −1.54 ± 0.04, without a significant trend with either (IKs) or metallicity. Though other studies have identified a relationship between the RC absolute magnitude and metallicity (e.g., Girardi & Salaris 2001; Salaris & Girardi 2002), the range reported (σ ≲ 0.28 mag) is sufficiently narrow for our purposes. For our clusters with a RC, we estimate the initial distance from the difference between the intrinsic MKs magnitude and the mean extinction-corrected Ks magnitude of the stars in the RC.

The magnitude difference ΔKs between the RC and the MSTO can also be used to estimate the age of a stellar population, and this approach has been used extensively for clusters with optical CMDs (e.g., Phelps et al. 1994). Beletsky et al. (2009) extended this diagnostic to the NIR by deriving empirical relationships between age and ΔKs for 14 open clusters with metallicities in the range −0.4 < [Fe/H] < +0.4. (Though only a small sample of clusters were used, the study found a negligible trend with metallicity.)

Thus for systems with a clear RC and MSTO, we estimate the age of the cluster using Equation (2) of Beletsky et al.:

For the subset of our cluster candidates with a clear RC, we estimate an age of ∼1 gigayear (Gyr)—i.e., we find ΔKs ∼ 2.1 mag for nearly all of the clusters with a RC.

For those clusters without a clear RC, we have no means of estimating the age and distance independent of each other; some assumption must be made for either age or distance to estimate the other parameter using a comparison to theoretical isochrones. To simplify our task, we constrain the age of our isochrone suite to the typical age of those clusters with reliable age estimates, 1 Gyr. With the age fixed, we use theoretical isochrones (Girardi et al. 2002) to estimate an initial distance using the mean absolute magnitude of the MSTO over a range of metallicities, compared to the observed magnitude, and this estimate is then iteratively refined as described in Section 2.4.4.

We make an initial estimate of the reddening, E(JKs), through a comparison of the mean (JKs) color of the MSTO and RC (if available) and the characteristic color predicted by the isochrones, without any reference to the adopted RJCE reddening range (though we certainly expect them to be consistent). To estimate the intrinsic spread in color for our 1 Gyr isochrones, we evaluate the mean color, (JKs)RC and (JKs)MSTO, and the spread in color (i.e., the difference between minimum and maximum color), Δ(JKs)RC and Δ(JKs)MSTO, for the full range of −2.0 ⩽ [Fe/H] ⩽ +0.2. We find (JKs)RC = 0.76 with a spread of Δ(JKs)RC = 0.06 and (JKs)MSTO = 0.49 with a spread of Δ(JKs)MSTO = 0.17. These ranges are on the order of the average observed scatter at the MSTO magnitudes of our sample, and we iteratively refine the estimates as described in Section 2.4.4.

2.4.4. Iterative Isochrone Fitting

As in the initial parameter estimates (Section 2.4.3), we utilize the isochrones of Girardi et al. (2002) in the 2MASS photometric system for the more advanced determination of cluster parameters. For the approach outlined in this section, we include the isochrone suite's full metallicity range (−2.0 ⩽ [Fe/H] ⩽ +0.2, Δ[Fe/H] = 0.1 dex), at a fixed age of 1 Gyr. Older isochrones (at 2, 5, 8, 10, and 13 Gyr) were available to include if indicated by the ΔH or Δ(JKs) separation between the MSTO and RC for an individual cluster but were not found to be necessary (Section 2.4.3). These isochrones include stage designations for the main phases of stellar evolution, and to eliminate confusion in the fitting process, the scope of the isochrones was limited to include only the main sequence, subgiant branch, red giant branch, and the location of the RC.

The first step of the fitting procedure is to use the initial parameter estimates to shift each isochrone to the apparent H magnitude and (JKs) color of the identified cluster feature(s) in the CMD. For each star within 1.5 initial R of our cluster center, the H magnitude separation, (ΔH)star, is computed as the distance between that star and the point on each reddened isochrone corresponding to the (JKs) color of the star. For each isochrone, (ΔH)star is summed over all stars in the spatial region to find (ΔH)isochrone, or the net H offset of that isochrone from our identified feature. We identify the "isochrone of best fit" for the assumed E(JKs) and (mM) as the isochrone that has the smallest (ΔH)isochrone. The isochrone of best fit is then overlaid on the (JKs, H) CMD, and a series of manual inspections are applied to iterate on the input E(JKs) and (mM), as well as the applied CMD filtering parameters.

Several visual diagnostics of the cluster CMD and fitted isochrone are used to assess and iterate over five input parameters: R, (l, b), (mM), E(JKs), and the range of E(JKs)RJCE. First, we assess how well the fitted isochrone traces the visually identified stellar sequence and adjust E(JKs) and (mM) accordingly. Second, we compare the MSTO and RC features in the CMD to those in the nearby comparison region's CMD. Strong overdensities associated with the cluster sequence confirm that the range of reddening values is reasonable and is not erroneously including or excluding regions of the CMD. Third, we adjust R and (l, b), based on the CMD-filtered spatial map, to produce the strongest MSTO and RC signal in the CMD. Once we are satisfied with our fits in all of these dimensions, we determine uncertainties on our values for E(JKs), (mM), and [Fe/H] (Section 2.4.5).

We explored a variety of approaches to "weighting" the individual stars by their photometric uncertainties in the calculation of (ΔH)isochrone. However, we found that all of these methods tend to produce poorer fits to the stellar CMD sequences, primarily because the fits are then dominated by the brightest stars, which are not necessarily the most likely cluster members. A proper weighting methodology would need to account for our stellar reddening selection, the likely type of each star (e.g., MS versus RC), and the CMD features specific to each of the clusters before it could emulate the multi-parameter visual assessment and iteration process used here.

2.4.5. Uncertainties

Uncertainties on our fitting method are obtained for [Fe/H], E(JKs), and (mM) using Monte-Carlo simulations of the method. These values are "measurement errors" only and do not include systematic errors in our procedure or biases in our cluster detection.

We create simulated datasets by varying the apparent J, H, and Ks magnitudes of each star in our cluster region by a Gaussian deviate, centered on the star's magnitude and color and with a width (σ) of the photometric uncertainty for each dimension. We generate 1000 realizations of each cluster dataset using this process.

The uncertainties in the fitted [Fe/H] are estimated by passing each of the simulated datasets independently through our isochrone fitting algorithm, with E(JKs) and (mM) fixed at the final values from the procedure described in Section 2.4.4. This produces an output distribution of best-fit [Fe/H], from which we measure the standard deviation, add it in quadrature with the [Fe/H] grid spacing, and adopt the result as our best estimate of the measurement error on [Fe/H]. Uncertainties of our iteratively determined values of E(JKs) and (mM) are estimated using a similar procedure—holding two parameters fixed while allowing the one under investigation to vary.

This procedure is performed for each of the clusters in our NIR+MIR sample, resulting in the distribution of uncertainties shown in Figure 3. For [Fe/H], the uncertainties varied from σ[Fe/H] ∼ 0.1, meaning the same [Fe/H] was measured for all of the 1000 realizations, to σ[Fe/H] ∼ 0.28, indicating considerably more degeneracy in the fitting procedure. The mean of the distribution of the uncertainties for all 16 clusters is σ[Fe/H] = 0.17. Given that the isochrone grid has Δ[Fe/H] = 0.1, our method described here appears to reliably identify the best-fitting isochrones to the clusters. The uncertainty in (mM) range from 0.26 to 1.49, with a mean of 0.71. The (mM) grid used in estimating these uncertainties has a spacing of 0.05 mag. Finally, the E(JKs) uncertainties span 0.02–0.28, with a mean of 0.12 and a grid spacing of 0.01.

Figure 3.

Figure 3. Distribution of uncertainties in (a) [Fe/H], (b) (mM), and (c) E(JKs) for the cluster fits (Section 2.4.5).

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2.5. Caveats for Comparison to Other Studies and Crowding

We emphasize that some important differences exist between the methodology described here and that of other studies with similar goals. First, we perform no field star decontamination with the NIR photometry alone, but instead use the robust RJCE reddening estimates to filter foreground and background stars. This method appears to work remarkably well, particularly in highly reddened and sparse regions where NIR statistical decontamination would struggle with low starcounts. Second, we do not use our algorithm to fit for E(JKs) or (mM) directly but instead use careful visual inspection of the match between the isochrone and the cluster CMD sequences. Lastly, unless strongly motivated otherwise by the NIR source counts or by previously published values, the initial R and (l, b) estimates are retained from the initial identification in the MIR image.

In contrast to the high stellar densities and subsequent strong crowding effects that impact studies of globular clusters (particularly those also employing 2MASS; e.g., Ivanov & Borissova 2002), our objects' comparatively low surface densities render crowding much less of a concern. We confirm this for the IRAC photometry by comparing the local surface density of each source in the catalog to the maximum density resolvable by the GLIMPSE pipeline, and we find typical values ∼18× lower than this maximum (with no object less than 5× lower). Follow-up visual inspection of the Spitzer images on finer scales than in Section 2.2 confirms the reliability of the GLIMPSE source catalog, though we note some instances of possible contamination by diffuse emission in the relevant Section 3 subsections.

The larger pixel size of the 2MASS survey decreases the stellar density at which the possibility of neighbors affecting the 2MASS point-spread function fits and resulting photometry becomes a concern. We assess the potential effects (assisted by the fact that all of our sources are merged with the GLIMPSE catalog, which has not only a higher angular resolution but also a fainter magnitude limit), considering the crowding of only those sources meeting our uncertainty requirements in the five 2MASS+IRAC bands (i.e., those sources that are candidates for the isochrone fitting). The candidate contaminants comprise all GLIMPSE sources with [3.6μ] and [4.5μ] detections (which, because of the fainter limit and weaker extinction effects, should include nearly all of the 2MASS sources not meeting our quality requirements). We experimented with magnitude limits on the GLIMPSE catalog—specifically, removing those stars too faint to artificially affect the 2MASS photometry by varying fractions of a magnitude, in the worst-case scenario of a 2MASS blend—in the end adopting a 0.1 mag contamination as the limit for a neighbor to be considered a potential crowded contaminant.

When we consider the IRAC stellar density in the immediate vicinity of each "good" 2MASS+IRAC source, we find that the inclusion of our uncertainty limits preferentially removes stars with more and/or closer neighbors. Typical local surface densities are 30–40 arcmin−2,—and much lower for the brighter RC and RGB stars so important to many of the fits—compared to the 2MASS maximum density for uncrowded sources of ∼64 arcmin−2. In the densest clusters, ≲33% of the fainter "good" sources have stochastic local densities above this value, but examination of the CMDs does not indicate that removing these stars would decrease the scatter of the stellar sequences. Nevertheless, we include caveats for those clusters in their Section 3 subsections.

3. RESULTS

In Tables 1 and 2, we list the position (l, b) and radius R of open clusters for which we could find no prior identification in the literature. We have adopted the naming scheme "GLM-<survey> <ID#>." This reflects the fact that all data have been processed with the GLIMPSE pipeline ("GLM") but may originate from different Spitzer surveys (see Section 2.1; "G360": GLIMPSE-360, "CYGX": Cygnux-X, "SMOG": SMOG11). The ID number comes from our internal database of candidates. We have chosen to sort objects in these subsections and in the tables by Galactic longitude. Table 1 also contains the distance D (as converted from mHMHAH), reddening E(JKs), and metallicity [Fe/H], with associated uncertainties, derived from comparing the cluster CMDs to isochrones (Section 2.4.4); Table 2 contains those clusters that are too small or too faint to have well-populated 2MASS CMDs.

Table 2. New Clusters: MIR Images Only

Cluster ID l b R
(deg) (deg) (arcmin)
GLM-G360 9 74.129 1.512 1.7
GLM-G360 123 133.638 0.139 2.8
GLM-G360 125 134.796 1.311 3.2
GLM-G360 174 136.827 1.065 1.0
GLM-G360 128 137.201 0.899 4.2
GLM-G360 129 137.414 1.281 3.8
GLM-G360 167 190.527 0.870 1.8
GLM-G360 169 194.454 0.035 2.3
GLM-G360 46 209.610 0.077 3.8
GLM-G360 49 212.899 −0.438 2.4
GLM-G360 50 212.932 −0.595 4.3
GLM-G360 60 227.328 −2.029 3.3
GLM-G360 63 227.752 −1.905 2.7

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Table 3 contains the position, size, distance, reddening, and metallicity, with associated uncertainties, for clusters that have prior identifications but that do not have published parameters from isochrone fitting. Finally, Table 4 contains the range of reddening adopted to filter each cluster's candidate members from the Galactic fore- and background (Section 2.4.2).

Table 3. Previously Known Clusters: MIR Images and NIR Isochrone Fits

Cluster ID l b R D E(JKs) [Fe/H]
(deg) (deg) (arcmin) (kpc) (mag)
FSR 0442 114.0001 2.0321 7.0 1.84 ± 0.3 0.70 ± 0.04 −0.1 ± 0.15
BDS 2003_46 114.6042 0.2232 3.0 3.76 ± 2.6 0.95 ± 0.28 −0.4 ± 0.27
FSR 0494 120.067 1.050 5.0 2.80 ± 1.1 0.48 ± 0.15 −0.2 ± 0.15
SAI 24 138.041 1.510 5.0 1.57 ± 0.8 0.95 ± 0.07 −0.2 ± 0.12
FSR 0665 150.661 −0.608 4.0 1.47 ± 0.4 1.20 ± 0.10 −0.1 ± 0.15
Czernik 20 168.292 1.440 2.0 3.10 ± 1.8 0.35 ± 0.20   0.0 ± 0.28
NGC 1857 168.407 1.199 3.5 1.40 ± 0.5 0.07 ± 0.03   0.0 ± 0.10
FSR 0777 173.0461 −0.1181 5.0 3.11 ± 1.1 0.55 ± 0.15   0.0 ± 0.10
FSR 0979 200.7901 0.6301 3.0 2.90 ± 0.7 0.50 ± 0.17   0.2 ± 0.25

References. (1) Froebrich et al. 2007; (2) Bica et al. 2003.

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Table 4. All Fitted Clusters: Reddening Filter

Cluster ID E(JKs)RJCE
GLM-CYGX 14 0.77–1.19
GLM-CYGX 16 0.98–1.40
GLM-G360 18 0.42–0.56
GLM-G360 90 0.45–0.57
GLM-G360 105 0.28–0.45
GLM-G360 58 0.21–0.49
GLM-G360 75 0.35–0.48
FSR 0442 0.56–0.73
BDS 2003_46 0.70–0.98
FSR 0494 0.38–0.50
SAI 24 0.53–0.70
FSR 0665 0.70–0.98
Czernik 20 0.21–0.34
NGC 1857 0.0–0.17
FSR 0777 0.28–0.49
FSR 0979 0.28–0.49

Notes. See Tables 1 and 3 for the reddening calculated via isochrone-fitting for each cluster.

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3.1. New Clusters with NIR CMDs

Each of the clusters described in the following subsections corresponds to a figure in Appendix A.1 (Figures 713). Panel (a) of each figure contains the [3.6μ] IRAC image of the cluster, and panel (b) contains the Catalog source density map of all [3.6μ] and [4.5μ] detections with an uncertainty <0.1 mag. In panel (c), we show the CMD and best-fitting isochrone of stars within 1.5R of the cluster and within the adopted reddening range given in Table 4. For comparison, panel (d) contains stars with the same reddening range from the spatially offset comparison region (Section 2.4.1).

3.1.1. GLM-CYGX 14

As would be expected from its dusty surroundings (clearly visible in Figure 7(a)), this cluster has a heavily reddened main sequence with a few stars that are RGB candidates, though the RGB density is comparable to that of the nearby comparison region. Fitted with a 1 Gyr isochrone, the MSTO corresponds to a reddening of 1.20 mag in (JKs) and a distance of 1.69 kpc. The best-fit isochrone indicates a metal-rich cluster, with [Fe/H] ∼ 0.2, though we note that just under a third of the MS stars have local stellar densities (as determined from the IRAC catalog; Section 2.5) indicative of potential crowding effects on the 2MASS photometry.

3.1.2. GLM-CYGX 16

This cluster also sits in a region of heavy reddening, with diffuse emission visible at MIR wavelengths (Figure 8); however, the contrast between the cluster and comparison regions suggests more localized extinction, with very few stars in the comparison region within the reddening range of the cluster. We note the very clear RC feature here, which tightly constrains the reddening and distance to E(JKs) = 1.27 and D = 1.36 kpc, with the best-fitting 1 Gyr isochrone having [Fe/H] ∼ 0.2.

3.1.3. GLM-G360 18

Both a dense MSTO and RC-like feature characterize this object (Figure 9), even within a narrow reddening range of ΔE(JKs)RJCE = 0.14. The RC is only ∼1 mag brighter than the MSTO, suggesting an age possibly younger than our 1 Gyr nominal isochrone. Our suite of models does not extend to younger ages, however, and using the 1 Gyr isochrone, we derive E(JKs) = 0.60, D = 3.50 kpc, and [Fe/H] ∼ 0.2. The large scatter in the RC cannot be explained by crowding effects, as all of the stars are comfortably isolated (Section 2.5), but we do note that nearly a third of the MS stars are potentially affected.

3.1.4. GLM-G360 90

Though without a particularly strong overdensity in the MIR source map, this cluster has significantly overdense MS and RC features in the NIR CMD, in contrast to the comparison region (Figure 10). We note the presence of diffuse light in the cluster vicinity, which may be impacting the NIR photometry to produce the increased scatter in the RC feature. Despite this, the presence of such a feature constrains the cluster to E(JKs) = 0.60, D = 2.91 kpc, and [Fe/H] ∼ 0.2.

3.1.5. GLM-G360 105

This cluster is visible in the source maps as a clear overdensity (Figure 11), and comparison of our candidate positions to the Dias et al. catalog yielded a potential match in Czernik 45 (Czernik 1966). However, the offset of 5farcm75 is larger than our original or best-fit cluster radii (3farcm4 and 4', respectively), Czernik's original size (1farcm5), and the calculated size from the only identified follow-up study to Czernik 45 (1farcm25; Tadross 2009). Furthermore, the 2MASS CMD presented by Tadross (2009) bears little resemblance to the CMD at our candidate position, including a complete lack of the RC stars we see at H ∼ 11.75. Given the coordinate, size, and CMD discrepancies, there does not appear to be sufficient evidence to identify this stellar overdensity as Czernik 45. Some scatter remains on the red side of the MS even after applying the reddening filter, but the MS and RC of this cluster correspond most closely to a stellar population with E(JKs) = 0.50, D = 3.04 kpc, and [Fe/H] ∼ 0.2.

3.1.6. GLM-G360 58

The overdensity in the MIR images and source maps (Figure 12) is weaker here than in many of the other clusters, but the CMD demonstrates a much stronger MS than the comparison region, along with ∼4 possible RC stars. We note that there is considerable scatter at (JKs) ∼ 1.0, but this is present in both the cluster and comparison CMD. The MS and RC of this cluster correspond to E(JKs) = 0.45, D = 3.11 kpc, and [Fe/H] ∼ 0.0.

3.1.7. GLM-G360 75

This object is included in our sample due to its significant source count overdensity and MSTO (Figure 13). However, this MSTO is located very close to the limits of the 2MASS photometry, and the residual scatter in the RC/RGB part of the CMD prevents us from placing reliable constraints on the metallicity. We are able to derive both a reddening and a distance: E(JKs) = 0.40 and D = 4.81 kpc.

3.2. New Clusters with Images Only

The clusters in Figures 1426 in Appendix A.2 and Table 2 are those showing a clear overdensity of faint stars in the MIR images and a high concentration of source counts in the MIR source catalog (in the figures' panels (a) and (b), respectively). However, the vast majority of the stellar sources in these clusters have no NIR counterpart. We give additional notes on only those clusters bearing special mention:

3.2.1. GLM-G360 9

This object, shown in Figure 14(a), appears to have a significant amount of diffuse emission in the MIR image, which also appears (though much weaker) in the DSS-Red and 2MASS images. It is also coincident with a 6 cm emission radio source (GB6 B2010+3635; Gregory et al. 1996) and an IRAS source (IRAS 20103+3633). Odenwald (1989) noted the presence of several YSOs near the IRAS source, but we could not find any identification of a stellar cluster at this position.

3.2.2. GLM-G360 128

This object (Figure 18) does have a coordinate match in the Dias catalog as "IC 1848," with an offset of 1farcm4, but it is unclear from the rest of the literature that a detection of the same open stellar cluster has been made here. Many papers refer to IC 1848 as an H ii region or star forming region alone (e.g., Chauhan et al. 2011; Koenig et al. 2012). Hillwig et al. (2006) refers to IC 1848 as an open cluster, dominated by the star system HD 17505 at the center, and find a distance of 1.9 kpc. This system is within 0farcm7 of our observed overdensity center, though Hillwig et al. (2006) identify IC 1848 with OCL 364 (Ruprecht et al. 1981), which lies ∼48farcm5 away. The cluster radius given in the Dias catalog, 9', appears better-matched to the rim of diffuse emission surrounding our much smaller (∼4') grouping of stars, and we are not able to identify the source of the catalog's distance (2 kpc) to determine whether this is a photometric stellar distance or a kinematical distance of the nebula. The presence of the bright HD 17505 system in the center makes the stellar cluster nearby very difficult to discern in shorter wavelength images, such as 2MASS and the DSS, but in the Spitzer image (Figure 18(a)), a large number of fainter, densely packed stars are clearly visible.

3.3. New NIR CMDs for Previously Known Clusters

Each of the clusters described in the following subsections corresponds to a figure in Appendix A.3 (Figures 2735). The panels are identical to those described in Section 3.1.

3.3.1. FSR 0442

FSR 0442 (Figure 27) was identified in the same location in the MIR source images but with a larger radius (7') than that published in its discovery (4') in the automated cluster search by Froebrich et al. (2007). Based on the RJCE extinction estimates and the MIR source maps, we isolated a strong MS and fit a 1 Gyr isochrone to the CMD features with D = 1.84 kpc, E(JKs) = 0.70, and [Fe/H] ∼ −0.1.

3.3.2. BDS 2003 46

A cluster of stars was identified at (l, b) = (114fdg617, 0fdg222) in the center of a large region of gaseous emission (Figure 28(a)). We identified this cluster as BDS 2003 46, cataloged by Bica et al. (2003), who used 2MASS images to look for new clusters around the central positions of optical and radio nebulae. They identified an "Infrared Group" at the same position as our star cluster, measured the size and ellipticity of the group, and recorded a kinematical distance using the nebula in which the cluster is embedded (Sh2-165; 1.6 kpc). From our isochrone-fitting procedure, we derive E(JKs) = 0.95, D = 3.76 kpc, and [Fe/H] ∼ −0.1.

The distance is ∼2 kpc greater than that of Bica et al. (2003), though no distance uncertainties were reported in that study. However, the method cited (Downes et al. 1980) reports distance uncertainties on the order of 1–2 kpc, so the difference may not be that highly significant. (This assumes that the cluster is truly coincident with the gaseous nebula.) Kinematic distances in the vicinity of outer disk spiral arms are often offset from photometric distances due to non-circular gas motion associated with the arms. Generally the kinematical distances in this part of the Galaxy, which includes the Perseus spiral arm, exceed the photometric ones by a kpc or more, particularly on the near side of the arm (where a nebula at 1.6 kpc would lie), though exceptions are known where the kinematic distance underestimates that obtained by other means (Humphreys 1976; Moisés et al. 2011).

A properly reddened isochrone at D = 1.6 kpc placed in the CMD in Figure 28(c) has a MSTO ∼0.4 mag brighter than could be attributed to the stellar data (excluding the four bright stars near (JKs) ∼ 1.5), so this kinematical distance appears genuinely inconsistent with the stellar cluster. However, the vertical scatter in Figure 28(c) suggests that the isochrone fit may not be sufficient to determine this object's parameters unambiguously—if the brighter blue stars are genuine cluster members, then perhaps a smaller distance is more appropriate. But treating those stars as cluster members produces a considerably worse overall match to the isochrone, so in Table 3, we report the parameters derived for the fit shown in Figure 28(c). However, we note that the bright diffuse emission in this region may be causing problems with the NIR and MIR photometry, despite our photometric quality restrictions.

3.3.3. FSR 0494

We initially identified a stellar overdensity at (l, b) = (120fdg067, 1fdg037) with R = 4farcm4 in the MIR images but optimized the cluster sequence shown in Figure 29 by adjusting the coordinates to (120fdg067, 1fdg050) with R = 5farcm0. This sequence corresponds to a population with D = 2.80 kpc, E(JKs) = 0.48, and [Fe/H] ∼ −0.2. This position was matched to that of the cluster FSR 0494 (Froebrich et al. 2007), which was originally identified with a much smaller radius (R = 0farcm8).

We note that there is a density peak corresponding to the Froebrich et al. object within our cluster radius (Figure 29(b)).

3.3.4. SAI 24

An embedded cluster was identified in the MIR source maps at (l, b) = (138fdg041, 1fdg515) with a radius of R = 3farcm64 (Figure 30). We matched this detection to SAI 24, discovered by Glushkova et al. (2010), and fit a 1 Gyr isochrone with D = 1.57 kpc, E(JKs) = 0.95, and [Fe/H] ∼ −0.2 to the strong MS feature.

Despite the seemingly very good fit (Figure 30(c)), we find a puzzling discrepancy between the RJCE reddening estimates for the cluster stars and the NIR reddening needed to fit the isochrone. The comparison between these two reddening estimates for the entire set of fitted objects is explored in Section 4 and Figure 6, in which SAI 24 is a clear outlier. However, the explanation invoked for the other minor discrepancies—variations in the MIR extinction law—is insufficient for SAI 24. Assuming a constant NIR extinction law (i.e., AJ/AKs and AH/AKs constant), the discrepancy in SAI 24's reddening values implies a MIR extinction ratio A[4.5μ]/AKs of ∼0.9 ± 0.14, almost a factor of two higher (and beyond the uncertainties) than has been measured in even the most "extreme" cloud cores (Román-Zúñiga et al. 2007; Flaherty et al. 2007). Allowing for the NIR extinction law variations observed in both diffuse and dense regions (e.g., throughout the diffuse interstellar medium and toward the Galactic center; Nishiyama et al. 2009; Zasowski et al. 2009; Stead & Hoare 2009) only worsens the problem.

Reconciling the reddening values within the uncertainties is barely possible if the stellar locus observed at (JKs) ∼ 1–1.2 is a very blue (metal-poor) RGB instead of a MS, but beyond the reddening offset, there is no evidence in support of this theory, and numerous lines of evidence against it (such as the shape of the CMD stellar locus, the location of the cluster within a dust cavity, and the massive size implied by such a well-populated RGB). Spectroscopic follow-up to determine the stellar properties of the cluster members will shed valuable light on this puzzle.

3.3.5. FSR 0665

In the MIR images, a cluster was identified at (l, b) = (150fdg661, −0fdg608) with R = 4farcm1 (Figure 31) and matched to FSR 0665 (Froebrich et al. 2007). We isolate a highly reddened sequence of stars absent from the comparison region and fit a 1 Gyr isochrone with D = 1.47 kpc, E(JKs) = 1.20, and [Fe/H] ∼ −0.1.

Like SAI 24 (Section 3.3.4), FSR 0665 has a discrepancy between its reddening as estimated from the RJCE method and that estimated from the fitted NIR isochrone, which cannot be explained by reasonable variations in the extinction law (nor does it lie in a visibly dusty region likely to have extreme variations). However, the CMD at this position (Figure 31(c)) inspires less confidence in the best-fit reddening, which is reflected in the relatively large reddening uncertainty of 0.10 mag. In fitting this cluster, given the absence of a RC, we were strongly guided by the overdensity of brighter stars not apparent in the comparison CMD (i.e., the stars with (JKs) ∼ 1.4 and H ∼ 12.5) that lie to the red side of the color distribution of cluster candidate members. Emphasis on this brighter overdensity is consistent with the fitting procedure applied to all of the clusters, and we report the best-fitting values as our best estimates for this cluster; however, we acknowledge that the high level of scatter in the CMD makes the fit less secure, and further observations (spectroscopy or deeper photometry) of this cluster may well confirm the membership of some of the bluer stars and thus revise the cluster reddening value downward to be more consistent with the RJCE-derived stellar reddening values.

3.3.6. Czernik 20 and NGC 1857

A cluster was identified in MIR images at (l, b) = 168fdg292, 1fdg440) with an estimated radius of R = 3farcm98 (Figure 32). This detection matches well the published coordinates of Czernik 20 (Czernik 1966).

However, we noticed some differences between our NIR CMD (Figure 32) and those published in the literature. We resolve the differences by both carefully inspecting the literature and exploring the environs of the candidate cluster.

Czernik 20 was first identified by Czernik (1966) in the images of the Palomar Sky Atlas. The later studies by Babu (1989) and Sujatha et al. (2006) determined cluster parameters via isochrone-fitting, but both authors expressed concern that the original cluster identified by Czernik (1966) was actually a redetection of NGC 1857 (Cuffey & Shapley 1937). NGC 1857 is offset from Czernik's original published position by ∼8', and both Babu (1989) and Sujatha et al. (2006) selected the stars at this offset position in their analyses instead of using the published coordinates of Czernik 20. However, our examination of the Spitzer images identified a cluster at Czernik's (1966) original coordinates, prior to any knowledge of the Czernik object. Furthermore, the NIR CMDs at the two positions of Czernik 20 and NGC 1857 are quite different from each other, but both show distinct cluster-like stellar loci (Figures 32(c) and (d)). The independent detection of Czernik 20, combined with the obvious differences in the CMDs at the two positions, indicate that there are in fact two distinct star clusters close together on the sky. See Figure 4 for a comparison of the positions and sizes identified by Czernik (1966), by Sujatha et al. (2006), and independently in this work.

Figure 4.

Figure 4. Positions and sizes of "Czernik 20" as cataloged by Czernik (1966), Sujatha et al. (2006), and this work, along with the position and size of "NGC 1857" from Battinelli & Capuzzo-Dolcetta (1991; smaller circle of lower-left pair).

Standard image High-resolution image

To augment the existing confusion over the location of Czernik 20, an isochrone with Sujatha et al.'s (2006) cluster parameters (which were ostensibly fit to the stars at the location of NGC 1857) is actually significantly better matched to the stars at Czernik's original coordinates for Czernik 20. After applying our reddening filter and isochrone-fitting procedure, we find comparable reddening but a smaller distance (D = 3.10 kpc and E(JKs) = 0.35), with [Fe/H] ∼ 0.0.12

With regard to NGC 1857, we identified a distance and reddening cataloged in Battinelli & Capuzzo-Dolcetta (1991, D = 1.9 kpc and E(JK) = 0.2); however, when comparing isochrones of these parameters with the CMD of NGC 1857's position, we observed a substantial mismatch. The reddening later reported by Colegrove et al. (1994) for this cluster, E(JK) = 0.36, only increases the mismatch. An isochrone with the distance, reddening, and metallicity from Battinelli & Capuzzo-Dolcetta (1991) appears to be closely matched to the Galactic disk stars, not to the clear cluster MS we observe. It is this locus that we fit in Figure 33(c), with D = 1.40 kpc, E(JKs) = 0.07, and [Fe/H] ∼ 0.0. We note that while our distance is somewhat similar to that given in Battinelli & Capuzzo-Dolcetta (1991), the discrepancy in reddening (coupled with the very narrow color spread in the MS in Figure 33(c)) rules out the possibility that we are fitting the same stellar sequence. This apparent disagreement emphasizes the benefit of exploring open clusters with multi-wavelength IR datasets. Namely, the increased sensitivity of the (JKs) color to stellar temperature, and the decreased sensitivity of MIR colors to interstellar dust, can break degeneracies between derived parameters based on intrinsic color and reddening, adding considerable leverage to understanding these low density stellar clusters.

3.3.7. FSR 0777

The visual cluster search identified a stellar grouping at (l, b) = (173fdg046, −0fdg160) with an estimated radius of R = 4farcm4 (Figure 34), spatially coincident with FSR 0777 (Froebrich et al. 2007). We note the presence of bright emission nearby, coincident with a peak in the source counts map (Figure 34(b)), but careful inspection of the image itself does not indicate the presence of a genuine stellar cluster associated with this emission. We find a best-fit 1 Gyr isochrone with [Fe/H] ∼ 0.0 and E(JKs) = 0.55 at a distance D = 3.11 kpc. Despite being removed from the visible emission region, the cluster still has a large E(JKs) and a large ΔE(JKs) of 0.49 mag. We note that there is some (JKs) scatter in the cluster CMD not present in the comparison region (Figures 34(c) and (d)) that cannot be reduced by further restricting the E(JKs) range. Some of these differences could be due to the rather large angular separation of the comparison region, which was specifically chosen to avoid the widespread MIR emission, but we suspect much of the scatter in Figure 34(c) could be image artifacts or spurious detections associated with the nearby nebulosity.

3.3.8. FSR 0979

We identified a stellar overdensity at (l, b) = (200fdg79, 0fdg625) with R = 2farcm7 (Figure 35) and matched it to FSR 0979 (Froebrich et al. 2007). The overdensity highlighted in the NIR CMD is not particularly strong (Figure 35(a)), but the MS is more densely populated, corresponding to a cluster at a distance D = 2.90 kpc, E(JKs) = 0.50, and [Fe/H] ∼ 0.2.

4. DISCUSSION AND SUMMARY

We have visually identified more than two dozen previously unknown or poorly studied open clusters in new Spitzer-IRAC images of the outer Galactic disk (65° ≲ l ≲ 265°) and, where possible, fit isochrones to the NIR CMDs to measure the basic cluster parameters. Our sample with newly derived distances and reddening values increases by ∼6% the number of clusters in the (l, b) coverage of the searched Spitzer surveys with these parameters known (though many have been derived from methods other than analysis of the stellar population).

In Figure 5, we compare our sample to the online catalog of Dias et al. (2002), restricted to the subset of clusters lying within the footprint of the combined GLIMPSE-360, Cyg-X, and SMOG surveys. Figure 5(a) shows the spatial distribution of all of our plausible cluster candidates, including those with less distinct MIR stellar overdensities not analyzed in this paper. In Figure 5(b), we find our sample's typical cluster radius to be ∼2–5' (where, again, our radius typically represents the point at which the visible cluster stellar density becomes indistinguishable from the background density), higher than the Dias catalog's typical radius of ≲2farcm5 and with a sharper count cutoff at larger radii, R ≳ 9'. We note that many of the smaller objects in the Dias catalog are results of the Froebrich et al. (2007) automated search through the 2MASS catalog; for many of these, we do not see an overdensity in the MIR images or source counts where our data overlap theirs, suggesting that at least some of these may not be genuine clusters (e.g., Froebrich et al. 2008). Nevertheless, the near total lack of very small (R ≲ 1') and large (R ≳ 9') objects in our sample suggests that the count peak at R ∼ 2'–5' reflects our visual search's stronger bias toward that angular size.

Figure 5.

Figure 5. Comparison between our MIR-identified clusters and the updated catalog of Dias et al. (2002). In each plot, the Dias et al. clusters have been restricted to only those falling within the GLIMPSE-360, Cyg-X, and SMOG survey footprints and having a value recorded for the plot's parameter. All Dias et al. clusters meeting these requirements are shown; we have not culled the sample based on parameter uncertainty or method. (a) Map of all clusters in the Dias et al.  catalog (gray circles), all of our plausible candidates (black +'s), and our high-quality new clusters (Section 3.1; black circles). The dotted lines mark l = 65° and 265°, the "edges" of the combined Spitzer surveys. (b) Cluster radius distributions for all objects in the Dias et al.  catalog (gray), all of our plausible candidates (black hatching), and our high-quality new clusters (solid black). (c) Cluster metallicity distributions for objects in the Dias et al. catalog (gray) and in our newly fitted sample (black). (d) Spatial distribution of the Dias et al. clusters with recorded distances (gray) and our fitted clusters (black). As in panel (a), the dotted lines indicate the longitude span of the Spitzer data. (e) Distribution of Galactocentric distance RGC for Dias et al. clusters with recorded distances (gray) and for our fitted clusters (black), assuming RGC, ☉ = 7.8 kpc. (f) Reddening distributions for all objects in the Dias et al.  catalog with recorded reddenings (gray; using the relation E(JKs) = 0.53E(BV)) and for the isochrone fits to our sample (black). The inset zooms in on the region enclosed by the dotted line.

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Figure 5(c) compares the distributions of [Fe/H] for our fitted cluster sample and for the few objects in the Dias catalog with a recorded metallicity measurement. We find a slightly lower mean metallicity—e.g., the Dias sample has no clusters with [Fe/H] < 0.0—but both samples are small enough that assessing the statistical significance of the difference is difficult. We do not observe a trend between [Fe/H] and Galactocentric distance RGC in our data.

Panels (d) and (e) in Figure 5 show the distribution of our clusters in the Galactic plane (XGC, YGC) and the distribution of RGC values, respectively. In both comparisons, our fitted objects follow the general distribution of the Dias sample. We note that our sample's lack of objects with RGC > 12 kpc may be attributed to the limited depth of our NIR photometry; even in the absence of extinction, a young (≲1 Gyr old) cluster at RGC = 12 kpc in the direction of the Galactic anti-center would have a MSTO near H ∼ 13, which is ∼1–2 mag above the limit of the 2MASS PSC, and approaching the H range where the NIR colors become significantly impacted by photometric uncertainties. Clusters with nonzero extinction and l ≠ 180° (which describes the majority of our sample), as well as older ages and/or larger RGC, will have MSTOs with increasingly fainter H and would be rejected in our cluster "CMD fittability" assessment (Section 2.2).

In Figure 5(f), we see that our isochrone-fitted reddening distribution is flatter than that of the objects in the Dias catalog. While the Dias sample shows a sharp decrease in number of objects with E(JKs) > 0.4, we have an almost equal number of objects with E(JKs) higher than 0.5 as lower, confirming our MIR-detected sample's much weaker bias toward low-reddening objects.

In Figure 6, we compare the E(JKs) values derived from the isochrone fits to E(JKs) calculated from the mean RJCE reddening identified for each cluster (using the relation E(JKs) = 1.4E(H − 4.5μ); Indebetouw et al. 2005). Though arrived at mostly independently—i.e., the mean RJCE reddening was not considered when iterating through E(JKs) for the isochrones, merely the upper and lower limits used to filter the cluster stars—the two measures obviously should be correlated, and indeed most clusters fall along the dotted 1:1 line within their errorbars. However, the most highly reddened objects deviate systematically from this relationship, in the sense that the RJCE method underestimates the reddening in comparison to the NIR isochrone fitting.

Figure 6.

Figure 6. Comparison between the mean RJCE reddening and the isochrone-fitted reddening for our fitted cluster sample (both new and known clusters). The vertical errorbars indicate the spread in reddening used to isolate the cluster, and the dotted line is the 1:1 correlation line.

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These reddening discrepancies are most likely due to variations in the NIR–MIR extinction law. All of these discrepant clusters lie in visibly dense and dusty regions, which are known to exhibit extinction behavior different from the "standard" law (particularly at MIR wavelengths; e.g., Chapman et al. 2009; McClure 2009). These differences take the form of increased MIR extinction relative to that in the NIR (a "flatter" extinction law, generally attributed to an increase in average dust grain size), meaning that our conversion to E(JKs) using a more typical extinction law leads to an apparent underestimate, by up to ∼6%. This variation is sufficient to bring all of the objects in Figure 6 except two into agreement within the uncertainties, especially given that the vertical "error" bars indicate the range of RJCE reddening adopted only, without any estimate of uncertainty in that range. Furthermore, we note that the increased range in reddening of these clusters is indicative of the variable and spatially differential extinction common in dusty embedded clusters.

Two of the clusters, SAI 24 and FSR 0665, lie too far below the 1:1 line to be explained by variations in the extinction law, and we discuss these in detail in their individual subsections: SAI 24 in Section 3.3.4 and FSR 0665 in Section 3.3.5.

In summary, we find that our new clusters are largely similar to the sample of known objects in terms of angular size and spatial distribution; the largest difference lies in our sample's higher median reddening, which reflects the weaker effects of extinction (and hence greater ability to detect clusters) at longer wavelengths. This study increases by more than a dozen the census of open clusters with constrained distances, reddenings, and metallicities in the outer disk. Further, we provide more than a dozen additional clusters, ideal for follow-up imaging and spectroscopy, which are likely to probe either (1) more distant and/or heavily reddened regions or (2) lower on the mass spectrum than the sample with isochrone fits. All of these clusters are valuable for exploring the structure and star formation history of the relatively poorly studied regions of the MW beyond the solar circle.

The authors would like to thank the anonymous referee for helpful comments that improved the clarity of the paper, and R. Indebetouw for very useful discussions. This work is based in part on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA, and support was provided by NASA through awards issued by JPL/Caltech (1368699 and 1367334). We also acknowledge use of data products from the Two Micron All Sky Survey, a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by NASA and the NSF. G.Z. was supported by a NASA Earth & Space Science Fellowship and an NSF Astronomy & Astrophysics Postdoctoral Fellowship under Award No. AST-1203017, and R.L.B. acknowledges receipt of the Mark C. Pirrung Family Graduate Fellowship from the Jefferson Scholars Foundation. K.K.H. acknowledges support from NSF grant AST-0807945.

APPENDIX: IMAGES, SOURCE DENSITY MAPS, AND COLOR–MAGNITUDE DIAGRAMS

A.1. New Clusters and NIR CMDs

Figure 7.

Figure 7. GLM-CYGX 14. (a) [3.6μ] IRAC image of the cluster; the black circle marks the center and size. (b) Source density map (arcmin−2) of all [3.6μ] and [4.5μ] detections with an uncertainty <0.1 mag. The cluster and the comparison region (Section 2.4.1) are indicated by solid and dashed circles, respectively. (c) Observed color–magnitude diagram (CMD) of stars within 1.5 cluster radii that meet the reddening criteria imposed for this object, along with the best-fit isochrone. (d) CMD of stars within 1.5 cluster radii of the comparison region center that meet the reddening criteria, along with the cluster's best-fit isochrone from panel (c).

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Figure 8.

Figure 8. Same as Figure 7 but for GLM-CYGX 16.

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Figure 9.

Figure 9. Same as Figure 7, but for GLM-G360 18.

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Figure 10.

Figure 10. Same as Figure 7, but for GLM-G360 90.

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Figure 11.

Figure 11. Same as Figure 7, but for GLM-G360 105.

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Figure 12.

Figure 12. Same as Figure 7, but for GLM-G360 58.

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Figure 13.

Figure 13. Same as Figure 7, but for GLM-G360 75.

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A.2. New Clusters with Images Only

Figure 14.

Figure 14. GLM-G360 9—(a) [3.6μ] IRAC image of the cluster; the black circle marks the center and size. (b) Source density map (arcmin−2) of all [3.6μ] and [4.5μ] detections with an uncertainty <0.1 mag. The cluster region is indicated by a solid circle.

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Figure 15.

Figure 15. Same as Figure 14, but for GLM-G360 123.

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Figure 16.

Figure 16. Same as Figure 14, but for GLM-G360 125.

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Figure 17.

Figure 17. Same as Figure 14, but for GLM-G360 174.

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Figure 18.

Figure 18. Same as Figure 14, but for GLM-G360 128.

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Figure 19.

Figure 19. Same as Figure 14, but for GLM-G360 129.

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Figure 20.

Figure 20. Same as Figure 14, but for GLM-G360 167.

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Figure 21.

Figure 21. Same as Figure 14, but for GLM-G360 169.

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Figure 22.

Figure 22. Same as Figure 14, but for GLM-G360 46.

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Figure 23.

Figure 23. Same as Figure 14, but for GLM-G360 49.

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Figure 24.

Figure 24. Same as Figure 14, but for GLM-G360 50.

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Figure 25.

Figure 25. Same as Figure 14, but for GLM-G360 60.

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Figure 26.

Figure 26. Same as Figure 14, but for GLM-G360 63.

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A.3. New NIR CMDs for Previously Known Clusters

Figure 27.

Figure 27. Same as Figure 7, but for FSR 0442.

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Figure 28.

Figure 28. Same as Figure 7, but for BDS 2003_46.

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Figure 29.

Figure 29. Same as Figure 7, but for FSR 0494.

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Figure 30.

Figure 30. Same as Figure 7, but for SAI 24.

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Figure 31.

Figure 31. Same as Figure 7, but for FSR 0665.

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Figure 32.

Figure 32. Same as Figure 7, but for Czernik 20.

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Figure 33.

Figure 33. Same as Figure 7, but for NGC 1857.

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Figure 34.

Figure 34. Same as Figure 7, but for FSR 0777.

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Figure 35.

Figure 35. Same as Figure 7, but for FSR 0979.

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Footnotes

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10.1088/0004-6256/146/3/64