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The MYStIX InfraRed-Excess Source Catalog

The MYStIX project (Massive Young Star-Forming Complex Study in Infrared and X-rays) provides a comparative study of 20 Galactic massive star-forming complexes (d = 0.4 to 3.6 kpc). Probable stellar members in each target complex are identified using X-ray and/or infrared data via two pathways: (1) X-ray detections of young/massive stars with coronal activity/strong winds; or (2) infrared excess (IRE) selection of young stellar objects (YSOs) with circumstellar disks and/or protostellar envelopes. We present the methodology for the second pathway, using Spitzer/IRAC, 2MASS, and UKIRT imaging and photometry. Although IRE selection of YSOs is welltrodden territory, MYStIX presents unique challenges. We combine IR spectral energy distribution (SED) fitting with IR color cuts and spatial clustering analysis to identify IRE sources and isolate probable YSO members in each MYStIX target field from the myriad types of contaminating sources that can resemble YSOs: extragalactic sources, evolved stars, nebular knots, and even unassociated foreground/background YSOs. Applying our methodology consistently across 18 of the target complexes, we produce the MYStIX IRE Source (MIRES) Catalog comprising 20,719 sources, including 8686 probable stellar members of the MYStIX target complexes. We also classify the SEDs of 9365 IR counterparts to MYStIX X-ray sources to assist the first pathway, the identification of X-ray detected stellar members. The MIRES catalog provides a foundation for follow-up studies of diverse phenomena related to massive star cluster formation, including protostellar outflows, circumstellar disks, and sequential star formation triggered by massive star feedback processes.


Introduction
The Massive Young star-forming complex Study in Infrared and X-rays (MYStIX) project, described by Feigelson et al. (2013), provides a comprehensive, parallel study of 20 Galactic massive star-forming regions (MSFRs; d = 0.4 to 3.6 kpc). The core data products of MYStIX are tables of "MYStIX Probable Complex Members" (MPCMs) in each target MSFR, compiled by Broos et al. (2013). MPCMs are identified using a combination of X-ray imaging data from the Chandra X-ray Observatory and infrared (IR) data from the United Kingdom Infrared Telescope (UKIRT), the Two-Micron All-Sky Survey (2MASS), and the Spitzer Space Telescope. Young, pre-main-sequence (pre-MS) stars with convection-driven coronal flaring activity (Feigelson et al. 2002;Flaccomio et al. 2003;Preibisch et al. 2005;Güdel et al. 2007) and massive, OB stars with strong stellar winds (e.g. Harnden et al. 1979;Gagné et al. 2011) produce bright X-ray emission that allows them to be isolated in high-resolution X-ray images from the potentially overwhelming field-star and nebular contamination that plague optical/IR images of young, massive Galactic star-forming regions. Xray observations are thus efficient probes of MPCMs both with and without circumstellar disks, penetrating obscuring absorption columns equivalent to tens of magnitudes of optical extinction A V .
There are, however, some important limitations to basing MPCM identification on X-ray selection alone. X-ray emission from pre-MS stars is generally variable, and there is a wide scatter in the stellar L X /L bol correlation (Preibisch et al. 2005;Telleschi et al. 2007;Güdel & Nazé 2009).
Hence stars that happen to be intrinsically less luminous or in a low state may be missed by the relatively shallow X-ray integrations available to MYStIX. In addition, both classical T Tauri stars with disks and protostars still accreting from infalling envelopes (to which we will refer collectively as young stellar objects, or YSOs) are observed to be somewhat less luminous in X-rays compared to diskless, weak-lined T Tauri stars (Telleschi et al. 2007;Prisinzano et al. 2008), and are usually subject to greater soft X-ray absorption. YSOs are thus underrepresented in X-ray surveys compared to older pre-MS stars. The dusty disks and/or envelopes surrounding YSOs reprocess stellar radiation, producing IR excess (IRE) emission, hence Spitzer observations in particular are highly sensitive to precisely the stellar populations that Chandra may miss . The complementarity between X-ray and IRE detection is a crucial motivation in our search for a more comprehensive survey of young stellar populations in MYStIX. To that end, we present the MYStIX InfraRed Excess Source catalog (MIRES), a compilation of IRE sources identified in wide-field IR survey images of the MYStIX target MSFRs.

Infrared Source Catalogs
The basic input data for MIRES were near-IR (NIR) and mid-IR (MIR) photometric catalogs. We also use NIR and MIR images and mosaics for visualizing the point source populations with respect to various nebular structures. We provide high-level descriptions of each input catalog below. For more detailed information, we refer the reader to the primary sources cited for each catalog.

Spitzer/IRAC
Our selection criteria for circumstellar material rely on IRE emission detected in two or more of the four MIR bands available to the Infrared Array Camera (IRAC; Fazio et al. 2004) on the Spitzer Space Telescope. The IRAC bands (cryogenic mission phase) are centered at 3.6, 4.5, 5.8, and 8.0 µm, and we will henceforth use the notation [3.6], [4.5], [5.8], and [8.0], respectively when referring to a specific IRAC band or photometric magnitudes measured from it.
The Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE; Benjamin et al. 2003), and 3 follow-up survey programs using the GLIMPSE observing strategies and data analysis pipelines (GLIMPSE II, GLIMPSE 3D, and the Vela-Carina Survey) observed 8 of the 18 MYStIX target MSFRs (see Table 1). The GLIMPSE photometry pipeline provides a highly-reliable point source "Catalog" that is a subset of a more complete point source "Archive". For IRE source selection, we use the highly-reliable Catalog exclusively. For analysis of MIR counterparts matched to MYStIX X-ray sources (Naylor et al. 2013) we use the more-complete Archive (see Appendix A for details).
The wide-area sky coverage provided by the GLIMPSE surveys allowed us to define large search fields for MIRES, approaching the full extent of 8.0 µm nebulosity (a qualitative tracer of molecular clouds) associated with these MSFRs. These wider MIRES fields are generally much larger than the MYStIX X-ray fields, which allows us (1) to identify centers of star-forming activity that did not happen to fall within the X-ray observations and (2) to define off-target, "control" regions and establish a baseline density for contaminating field sources that masquerade as MSFR members with IRE (see Section 5.1). Kuhn et al. (2013b, hereafter K13) performed MIR point-source photometry on archival IRAC data for the 10 other MYStIX targets used in MIRES that were not covered by one of the GLIMPSE surveys (see Table 1). K13 modeled their catalog structure on the GLIMPSE pipeline and similarly produced both highly-reliable Catalog (their primary published data product) and more-complete Archive source lists. There are, however, important differences from GLIMPSE in both the data analyzed by K13 and the photometry pipeline itself: 1. Photometric depth. In general, the archival data analyzed by K13 were deeper integrations than the GLIMPSE surveys. Faint, extragalactic sources are rare in the GLIMPSE Catalogs -5but prevalent in the K13 Catalogs.
2. Fields-of-view. The archival IRAC data came from various programs, and the size of the fields-of-view differ greatly among the targets.
3. Source detection and extraction. K13 used a point-source detection algorithm with a less stringent roundness criterion compared to the GLIMPSE pipeline. K13 performed aperture photometry on mosaic images combining all available IRAC data, while the GLIMPSE pipeline performed point-spread-function (PSF) fitting photometry on the individual IRAC frames. K13 note that while their pipeline tends to detect point sources that the GLIMPSE pipeline would miss, it is more susceptible to false-positives, especially in the [5.8] and [8.0] bands where the background nebulosity is brightest.
For two targets, K13 compare the results of their photometry pipeline to those of the GLIMPSE pipeline. A custom run of the GLIMPSE pipeline was performed on archival data for W3 (M. R. Meade and B. L. Babler, private communication). K13 produced sourcelists from the IRAC highdynamic-range GTO observation of the central regions of M17, which was also included (with wider coverage) in the GLIMPSE survey. Both of these targets include luminous H II regions that produce very bright, complex nebular emission on multiple spatial scales. K13 found that in these cases their pipeline produced a significant number of spurious detections (point 3 above) at [5.8] and [8.0]. As these spurious detections produced an unacceptably high fraction of false IRE sources in W3 and M17, for these targets we use the GLIMPSE pipeline Catalogs. We note that the GLIMPSE pipeline was optimized for the (conservative) detection of crowded sources against complicated nebular background emission, and, for the purposes of MIRES, reliability (in the sense of minimizing false-positives) takes priority over completeness (minimizing false negatives).

2MASS
2MASS (Skrutskie et al. 2006) imaging is well-matched to the 2 resolution of Spitzer/IRAC and provides an all-sky, broadband J H K S photometric catalog covering the NIR bands immediately blueward of IRAC [3.6]. Both the GLIMPSE and K13 IRAC photometry pipelines produce 7-band catalogs with 2MASS sources spatially matched to IRAC sources.

The United Kingdom Infrared Telescope (UKIRT)
Although the sensitivity of 2MASS is nominally well-matched to that of the GLIMPSE surveys (K S and [3.6] 15.5 mag), differential extinction (the combination of interstellar and circumstellar reddening) renders many IRE sources significantly fainter at NIR wavelengths. For MYStIX targets with deeper IRAC data, 2MASS is clearly not deep enough. We therefore incorporate J H K S photometry catalogs produced by King et al. (2013) from a combination of UKIRT Infrared Deep -6 -Sky Survey (UKIDSS) imaging and similar observations targeting select MSFRs, where available (see King et al. (2013) and Table 1). UKIRT observations provide sub-arcsec resolution and reach K S 19 mag. For the Lagoon Nebula, NGC 6334, and NGC 6357 the MIRES search field was limited by the area of the corresponding UKIRT catalog.

Cross-Catalog Source Matching
As a preliminary step to our MIRES selection and analysis procedure, for each target MSFR with available UKIRT photometry, we cross-matched the relevant King et al. (2013) source catalog with the appropriate subset of the GLIMPSE or K13 highly-reliable MIR Catalog (Table 1). Because the MIR Catalogs already incorporated 2MASS photometry, for a total of 7 bands, the goal was to replace 2MASS with high-quality UKIRT photometry and populate missing NIR photometry with UKIRT magnitudes wherever possible. The matching was based on astrometric proximity, following the techniques of Broos et al. (2011). The steps in our matching procedure can be summarized as follows: 1. Define the common field-of-view (FOV) of the UKIRT and MIR coverage, and crop both catalogs to this common FOV, which we hereafter call "the MIRES full field." 2. Remove artifacts from the UKIRT catalogs that do not represent astrophysical objects. These include all sources with the following flags (King et al. 2013): W (calibration extractions in any band), E (near edge in K S band), and M (negative flux in K S band).
3. Perform a S/N cut in K S , keeping only sources for which the photometric uncertainty δK S < 0.1 mag. 4. Register the MIR Catalog to bright (K S < 14 mag) sources in the UKIRT catalog, excluding saturated sources (S flag).
5. Match UKIRT sources to MIR Catalog sources using a 1 matching radius. If multiple UKIRT sources fall within the matching radius of a MIR source, then the closest is adopted as the match and the number of secondary matches is recorded.
The results of the matching procedure were evaluated using visual review of the UKIRT and MIR catalog sources on the relevant K S and 3.6 µm images, and by plotting 2MASS K S versus UKIRT K S matched to the same MIR source. In the latter case, we found that the sources correlated tightly with the 1:1 line, with the exception of saturated UKIRT sources that were unsaturated in 2MASS and UKIRT sources with secondary matches present, both of which skew toward larger (fainter) values of K S in UKIRT compared to 2MASS. Generally, secondary UKIRT matches to a MIR source represent close pairs (or triplets) of NIR sources that were unresolvable at the 2 resolution of either 2MASS or Spitzer/IRAC.
-7 -For the nearest MYStIX MSFR with available UKIRT data, NGC 2264, 88% of 22,363 MIR (K13) sources had UKIRT matches, only 0.4% of which were accompanied by secondary matches. This represents a best-case scenario for cross-matching. The worst-case scenarios were more distant MSFRs in the inner Galaxy, with large ( 1 • ) FOVs densely populated by field stars, for example NGC 6357, NGC 6334, and the Trifid Nebula. For each of these targets the above matching procedure found UKIRT matches to 95% of MIR (GLIMPSE II) sources, 15% of which were accompanied by secondary matches.

MIRES Catalog Construction
In this section we describe our methodology for identifying IRE sources among the 1.6 × 10 6 sources (Table 2) in our merged IRAC, 2MASS, and UKIRT catalogs. The general strategy is best described as a series of filters to cull out various populations of contaminating sources that dominate the IR catalogs, including normally-reddened field stars, "marginal" IRE sources that depart from normal photospheric emission only at the longest wavelengths, and "bad data" sources with photometry that is inconsistent with any single astrophysical model. Our technique combines SED model fitting with color-color and color-magnitude criteria to take advantage of all available IR photometric datapoints for each source (see also Povich et al. 2009;Smith et al. 2010;Povich et al. 2011).

Preparation of Photometry Tables for SED Fitting
We use a version of the least-squares, SED fitting tool of Robitaille et al. (2007, hereafter RW07) that batch-processes large numbers of sources using locally-compiled code. This is faster, more efficient, and more flexible compared to the more widely used RW07 web-based fitting tool. 1 To prepare our photometry for SED fitting, we performed the following steps: 1. We chose the provenance of our NIR photometry on a per-band, per-source basis. We preferred a high-quality (00 flag) UKIRT measurement wherever available, replacing the corresponding 2MASS photometry where appropriate. In general, 2MASS photometry was used for targets with no UKIRT observations, and otherwise for bright sources that saturated the UKIRT images or for UKIRT sources affected by artifacts. The filter response functions are applied directly to the SED models by the RW07 software (which does calculations in flux space), hence it was not necessary to shift the 2MASS and UKIRT photometry into a common photometric system.
-8 - b SEDs of all sources in column 4B were visually reviewed. The number of sources in column 4B ultimately "rescued" for inclusion in MIRES can be found by subtracting column 4A from column 5 (this number is 86 total, but zero for certain fields).
-10we set the minimum uncertainty used in SED fitting to 5% in the J H K S , [3.6], and [4.5] bands and 10% for IRAC [5.8] and [8.0]. These floor values were used only where the reported uncertainties in the catalogs were smaller, otherwise the original uncertainties were used. It is important to note that these reset uncertainties are the ones published in MIRES, because they are used in all of our analysis; for original uncertainties we refer the reader to the source catalogs referenced in the previous section.

Filtering Out Non-and Marginal-IR-Excess Sources
As the first step in our filtering process, we fit reddened Castelli & Kurucz (2004) stellar atmosphere models, using the extinction law of Indebetouw et al. (2005), to all sources in our merged photometric catalogs that have N data ≥ 4 detections among the 7 combined NIR-MIR bands. The reddening A V , a free parameter in the RW07 fitting procedure, was allowed to range from 0 to a maximum value A V,max determined independently for targets observed with UKIRT ( Table 1) by inspection of sources plotted on a J − H vs. H − K s color-color diagram. Sources for which the goodness-of-fit parameter χ 2 for the best-fit model satisfied χ 2 /N data ≤ 2 were considered 0 0 well-fit by stellar photospheres and were removed from consideration for MIRES. The tallies of non-IRE versus possible IRE sources are given for each target in columns 2A and 2B of Table 2; note that the difference between the sum of these two columns and the values in column (1) is the number of sources with N data < 4.
Next we filtered out "marginal" IRE sources using the color cuts described by Povich et al. (2011) (see Appendix A for details of the color cuts). Sources classified as marginal IRE (column 3A in Table 2) are not considered for inclusion in MIRES because in general an excess appearing in a single IRAC band is consistent with systematics in the photometry, and is not strong evidence for youth (Smith et al. 2010;Povich et al. 2011 Figure 1 we show example plots of SEDs with the best-fit stellar photosphere models. Most of these sources are relatively faint, falling near or below the detection limit at [5.8] or [8.0], as set by the local nebular background emission. Among the sources plotted in Figure 1, only G006.7218-00.2990 presents a plausible intrinsic IRE, but the non-detection of the source at [8.0] renders the apparent [5.8] excess suspicious. The source populations passing through both of our initial filters (column 3B of Table 2) are dominated by significant IRE sources (but some are strongly variable stars or NIR-MIR catalog mismatches, which we deal with below). Our conclusion that the large majority of marginal IRE sources are not YSOs is supported by comparing the spatial distributions of sources rejected by -13 -0 this filter to those that pass it. In Figure 2 we show this comparison using the prototype MYStIX targets, NGC 2264 and the Trifid Nebula (Feigelson et al. 2013). We note that marginal IRE sources (magenta) are distributed quasi-uniformly throughout the fields while the significant IRE sources (cyan) are strongly clustered in the target MSFRs. In NGC 2264, which has deep IRAC data, the marginal IRE filter may also capture extragalactic sources. In the Trifid field, the distribution of marginal IRE sources is clearly non-uniform, reflecting large-scale spatial variations in interstellar reddening and nebular emission imprinted on the dense population of field stars in the inner Galaxy.

Fitting Significant IR-Excess SEDs with Young Stellar Ob ject Models
After filtering out marginal IRE sources, we fit the SEDs of all remaining sources with star+disk+envelope radiation transfer models of young stellar objects (YSOs) from Robitaille et al. (2006, hereafter RW06). Sources for which χ 2 /N data ≤ 4 were considered well-fit. The relaxation of the goodness-of-fit criterion compared to the previous case of fitting stellar atmospheres is necessary because (1) real YSOs are intrinsically variable sources, and our data come from multiple epochs, and (2) the RW06 model SEDs sparsely sample a very large parameter space. The tallies of sources with successful versus failed RW06 model fits for each target are given in columns 4A and 4B, respectively, of Table 2.
The RW06 models include only radiation from the central star and circumstellar dust, and therefore the model fits may give inaccurate results or fail entirely in the presence of significant emission lines originating in circumstellar gas. In particular, the [4.5] band can be brightened significantly by shocked molecular line emission produced by protostellar outflows (likely related to the "extended green object" phenomenon, see Cyganowski et al. 2008). G09 include a color cut to exclude "shock emission" from their IRE samples. This cut assumes such sources are unresolved knots in otherwise extended structures, an assumption that only works for nearby regions. All of the MYStIX MSFRs are more distant than the regions studied by G09, and the shocked emission is more likely to be confused with the driving YSO itself, as evidenced by the coincidence of point sources satisfying the G09 criteria with bright 24 µm point sources Povich et al. 2011 Table 3, column 5).
-Example plots of SEDs (dots with error bars) that were poorly-fit with RW06 models (curves). Dashed curves show the stellar photospheres of the best-fit RW06 model YSOs as they would appear in the absence of circumstellar reddening from disks and/or envelopes. Top row: Examples of sources that were judged to be legitimate protostellar candidates during visual review and manually entered into MIRES. Center and Bottom rows: Examples of sources that were eliminated from consideration for MIRES after visual review (see text).
For the final step in constructing MIRES, we visually reviewed all SEDs and model fits for sources that were (1) poorly-fit by stellar atmospheres, (2) not classified as marginal IRE, and (3) were poorly-fit by RW06 models (i.e. the 3432 sources in column 4B of Table 2). This check was necessary to prevent our discarding interesting protostellar sources, in particular massive YSOs that can fail to be fit by RW06 models, for example due to excitation of polycyclic aromatic hydrocarbon (PAH) molecules in the disks or uncertainties in the interstellar extinction law. In many cases, we visually reviewed sources in the original MIR images and noted whether they were located in clusters, IR dark clouds, or bright-rimmed clouds, any of which increases the likelihood -16that a source is protostellar. Figure 4 shows example SED plots, drawn from the NGC 6357 field, illustrating various common pathologies for sources poorly fit by either stellar atmospheres or RW06 YSO models. The top row of panels shows examples of "rescues" judged by eye to be legitimate candidates for MIRES: (a) An SED revealing a composite cool dust continuum plus an intrinsic PAH emission spectrum shows monotonic increase in flux density from J to [8.0], with the exception of a dip at [4.5] as this is the only IRAC band that does not contain a PAH emission feature. (b) A potentially variable protostar shows a very red SED, but the K S flux density is elevated above the model while the [3.6] flux density falls below, causing a poor fit. (c) A likely protostar barely missed the χ 2 /N data ≤ 4 cut because of a [8.0] detection due to strong silicate absorption at 9.7 µm. The number of rescued sources for each target (which can be zero) can be found by subtracting column 4A from column 5 in Table 2. The middle and bottom panel rows show common examples MIRES "rejects" that were poorly-fit by RW06 models: (d) Match of a faint star with PAH nebular contamination in IRAC bands and (e) PAH nebular knot both show a characteristic "check-mark" morphology in the IRAC SED, in which the [4.5] band is sharply suppressed compared to the other 3 bands. (f ) A strongly variable star or an NIR-MIR mismatch produces a "broken" SED that otherwise resembles a normally-reddened stellar photosphere. (g, h) Likely asymptotic giant branch (AGB) stars with dust-rich winds (a category that includes carbon stars and OH/IR stars) have SEDs characterized by a precipitous rise with increasing wavelength through the NIR bands followed by a flattening/decline with very bright (λF λ 10 −10 erg cm 2 s −1 ) emission through the IRAC bands. (i) A cool, field giant barely missed the χ 2 cut for well-fit by reddened photosphere and does not show significant IRE above the photosphere of the central star in the best-fit RW06 model. Figure 4 along with all MIRES in the NGC 6357 field (Table 2, column 5) and other sources rejected on the basis of failed RW06 model fits (Table 2, column 4B) are overlaid on an 8.0 µm image in Figure 5. The spatial distributions of these different source populations illustrate both the effectiveness of using the RW06 model fits as a filter and the need for a final visual review. While the MIRES that are well-fit with RW06 YSO models populate several large clusters and a more distributed component to the population, the poorly-fit sources are found exclusively in a distributed mode, biased away from the central clusters. Only seven of the final MIRES originated as SEDs poorly-fit by RW06 models and subsequently "rescued" by the visual review, far too few to impact significantly the global spatial distributions. We note that the three example rescues highlighted in yellow are all found in or near real YSO clusters, IR dark clouds, or bright-rimmed clouds.

SED Fitting Results and Analysis
All IRE sources passing through the filtering process described in the previous section are entered into MIRES, which is available as a single machine-readable table in the online edition of the Journal. Table 3  properties and matching results from the combined MIR and NIR source catalogs (GLIMPSE, K13, and King et al. 2013). In this section we describe columns (9) through (12), which give the basic SED fitting results.

A V from the SED fits
Following Povich et al. (2011) and previous work, for each MIRES SED we define the set i of well-fit RW06 YSO models according to where χ 2 /N data is the data-normalized goodness-of-fit parameter for the best-fit model (Column 10 of Table 3). We then assign a χ 2 -weighted probability to each model using -18 -0 where P n is chosen such that P i = 1. We can use the resulting probability distributions of model parameters to characterize and constrain key physical and observational parameters of each source.
A useful parameter is the interstellar reddening A V , expressed in magnitudes of V-band extinction between the observer and the outer edge of the disk or protostellar envelope in the RW06 models. We compute the weighted-mean interstellar extinction based on the SED fits to each MIRES as i (Column 11 of Table 3). We use A V,SED to help distinguish between faint YSOs and likely extragalactic contaminants (see Section 4.2 below). We caution, however, that in some cases the SED modeling cannot constrain the A V parameter, and A V,SED defaults to A /2 (Table 1). In particular, we expect the A V parameter to be poorly constrained for: 1. Target regions with low obscuration. If the actual interstellar reddening is low (A V 5 mag), the effect on IR SEDs of intrinsically red sources is small and difficult to measure. For example, the NGC 2362 cluster has completely dispersed its natal cloud and therefore has reddening near zero, but its MIRES catalog entries tend toward A V,SED 2.5 mag, as we allowed for up to A V,max = 5 mag of reddening in the SED model fitting.
2. Sources missing J and H photometry measurements. The blue end of our SEDs is most affected by reddening, hence if NIR datapoints are missing we do not expect to achieve good constraints on A V . We recommend that any future investigations of interstellar reddening based on MIRES be restricted to the subset of sources with reported detections at H at minimum, and preferably both J and H detections.
3. YSOs obscured by nearly edge-on disks or deeply embedded in protostellar envelopes. In the cases of the reddest MIRES, the SED (including the NIR datapoints, if present) is likely dominated by emission/absorption from the disk and envelope, which completely veil the central star. In such cases (generally Stage 0/I and Ambiguous YSOs, see below) the A V,SED values should be viewed with suspicion.

Flagging Candidate Starburst Galaxies, AGN, and PAH Nebular Knots
Several types of intrinsically red, contaminating objects in the MIRES catalog can masquerade as YSOs. Unresolved extragalactic sources dominate the faint, red source populations in deep Spitzer observations of nearby star-forming clouds at high Galactic latitude or more distant MSFRs on sightlines toward the outer Galaxy (G09, Beerer et al. 2010). For inner Galaxy MSFRs observed as part of the shallower GLIMPSE or Vela-Carina surveys (see Table 1), extragalactic contaminants are not expected in significant numbers (Kang et al. 2009), but for consistency in building MIRES we apply the same procedure for flagging contaminants to all target regions. H II regions with bright -20nebular PAH emission present a different type of contamination, unresolved nebular knots that can either appear as "spurious," very red point sources in their own right (K13) or contaminate the extraction apertures of stars detected at shorter wavelengths, producing apparent excess emission at longer wavelengths (G09). While some extragalactic sources or PAH nebular contamination may be captured by the marginal IRE filter, sources with strong excess in multiple bands will not be filtered out.
We use the IR color spaces shown in Figure 6 in conjunction with ancillary information from the SED fitting and color-magnitude information to flag candidate extragalactic sources and sources affected by PAH nebular contamination. We flag such sources using SED flg (Column 9 of Table 3) rather than remove them from MIRES because additional photometric or spectroscopic data in the future could confirm that some are indeed young stellar members of the target MSFRs. For candidate YSOs (YSOc), SED flg = 0. Our membership analysis finds a (small) fraction of probable members with SED flg = 0 (see Section 5 below).
Extragalactic contaminants come in two flavors, starburst galaxies (Galc; SED flg = 1) with strong PAH emission enhancing the [8.0] band, and obscured active galactic nuclei (AGNc; SED flg = 2) with intrinsic dust emission (G09). Starburst galaxies are found in the lower-right portions of the color-color diagrams shown in Figures 6a and c;  The G09 color-color and color-magnitude cuts were based on the loci of extragalactic sources detected in deep Spitzer/IRAC observations of fields that contained neither significant numbers of Galactic point sources nor foreground reddening. Thus to avoid mis-classifying legitimate YSO members of Galactic MSFRs, we first deredden each source using the extinction law of Indebetouw et al. (2005) scaled to its A V,SED (Table 3, Column 11), and then apply the G09 cuts (we note that the cut shown in Fig. 6a is essentially reddening-free). The MIRES catalog also includes faint sources that were not detected in the [8.0] band and hence cannot be evaluated against the G09 cuts, so we flag all such sources with dereddened [3.6] 0 > 14.5 mag as Galc (SED flg = 1).
Because the magnitude distribution of the extragalactic background is a function of reddening only, while that of the YSO population in a given Galactic MSFR is a function of both reddening and distance, the degree to which the low-luminosity tail of a YSO population overlaps with the extragalactic contaminating population (particularly AGNc) increases with increasing distance, and is worse for regions with no significant intervening reddening column behind the YSOs but in front of the extragalactic background. For these reasons, it can be easy to mis-classify a legitimate YSO as an extragalactic contaminant, so the Galc and AGNc flags do not automatically disqualify MIRES for membership in a MYStIX MSFR (see Section 5.1). We discuss the impact of extragalactic contaminants on individual MSFRs in Appendix B; here we note that, as expected, we find significant numbers of extragalactic contaminants in the MYStIX targets with deeper Spitzer/IRAC observa--21tions (K13; see Table 1), and negligible numbers in targets with shallower, GLIMPSE observations. Sources were flagged as PAH nebular knots (SED flg = 3; Table 3, Column 11) and rejected for further consideration for membership if they satisfied both of the following criteria (Fig. 6a) low-mass star-forming clouds that included few massive YSOs, while the more distance MYStIX target regions include many more luminous YSOs with the potential for intrinsic PAH excitation in their disks/envelopes.
The large majority of PAH nebular knots and potential extragalactic sources in MIRES came from Spitzer data processed by K13 rather than from GLIMPSE, in part because the observations went deeper, but also because, compared to the GLIMPSE pipeline, their point-source detection and aperture photometry extraction were less conservative in rejecting marginally resolved sources. The majority of Galc, AGNc, and PAH knots have relatively high MIR photometric uncertainty (K13), which is consistent with their faintness but also supports the idea that many are marginally resolved. In Figure 6 we show all MIRES with photometric uncertainties ≤0.2 mag in the relevant bands, including 1761 Galc, 1920 AGNc, and 168 PAH knots. If instead we plotted (in panels a and c) only sources with uncertainties ≤0.1 mag (as in the other color-color diagrams presented in this work), 261 Galc, 360 AGNc, and 35 PAH knots would remain.

Evolutionary Stage from the SED fits
The RW06 YSO models can be divided into evolutionary stages that parallel the well-known empirical T Tauri classification scheme: MIR emission from Stage 0/I YSOs is dominated by infalling, dusty envelopes; Stage II and III YSOs are dominated by optically thick and optically thin circumstellar disks, respectively. Following previous work   Table 3).
While MIRES incorporates only photometric data from 1-8 µm, the intrinsic SED emission from a cool, infalling envelope peaks from 50-100 µm (RW06, and see also the left and right panel columns of Figure 7). We therefore have no constraints from our data in the thermal IR, where the difference between a disk-dominated and envelope-dominated SED is easiest to measure ). Our stage classifications from SED fitting are therefore based on extrapolating redward from the available data. As a consequence, Stage II objects with high interstellar reddening may be misclassified as Stage 0/I, and the fraction of MIRES with Ambiguous stage classifications is relatively high, 28%. Other approaches for classifying YSOs based on spectral indices or colors (e.g. G09) can be applied to MIRES using the photometry values given in Column 5 of Table 3, but we emphasize that all classification schemes based solely on some combination of J H K S and Spitzer/IRAC photometric data are vulnerable to the same extrapolation uncertainties. For future studies based on the analysis of evolutionary stage or class, we recommend that longer-wavelength photometry from available Spitzer/MIPS, Herschel, and/or WISE observations be used in conjunction with MIRES.

Identification of Probable Complex Members
The MIRES catalog includes both young stellar members of the MSFRs and a variety of unassociated contaminants. In addition to extragalactic sources and PAH nebular knots (see Section 4.2 and Table 3), dusty AGB stars, field giants with high interstellar reddening, and even unassociated YSOs may all be mistaken for YSO members. The last three categories of stellar contaminants, most prevalent in the inner Galactic plane fields covered by the various GLIMPSE Catalogs, cannot be readily distinguished from members using 1-8 µm photometry alone ). Reddened giants and dusty AGB stars could be distinguished by matching MIRES with longerwavelength photometry data from MIPS, Herschel, and/or WISE observations, as evolved stars have bluer [8.0] − [24] colors compared to YSOs (see Povich et al. 2011, and references therein); this is beyond the scope of the present work.
In this section we describe the remaining four columns in the MIRES catalog (Table 3), which report the results of our membership analysis. Column 13 (Prob dens) is a parameter related to the probability that a source at a given coordinate is a complex member, based on spatial clustering analysis, column 14 (MEM flg) is a binary flag set if a MIRES is a probable member of the parent MSFR identified in column 16 (MYStIX SFR). Column 15 (XFOV) is another binary flag set if the source is found within the field-of-view of the Chandra/ACIS observations used for MYStIX, which is a subset of the MIRES extended membership field. MIRES with both the MEM flg and XFOV bits set are adopted as MPCMs (Broos et al. 2013).

Estimating Membership Probabilities from Spatial Distribution
We can leverage information about the spatial distribution of MIRES in and around each target MSFR to aid in the identification of YSO members. Members are expected to be spatially concentrated or "clustered" toward their parent MSFR, while contaminants, with the exception of PAH nebular knots and unassociated YSOs, should be uniformly distributed. We can therefore consider the spatial distribution of MIRES in a given target field to be a statistical mixture of clustered and distributed components. Each MIRES has a probability of association with either component, depending on its position (coordinates; Columns 2 and 3 of Table 3).
To establish a baseline for the surface density Σ con of contaminants (the distributed component), where possible we define "control fields" within the larger MIRES field around each target MSFR, selected to avoid both bright PAH nebulosity in the [8.0] images and evident clusters of MIRES. In the process we also defined a "primary target field" for each MSFR, which included the Chandra field-of-view (the "MYStIX field") plus any spatially contiguous regions containing clustered MIRES and/or molecular clouds as evidenced by bright or dark 8 µm diffuse emission (the "MIRES extended membership field"). The selection of target and control fields as applied to the Trifid Nebula and NGC 6357 is illustrated in Figure 8. Some MIRES fields contain other, unassociated young star clusters or star-forming clouds (for example, the NGC 3576 field also contains the famous massive young cluster NGC 3603 in the background), and in these cases we defined secondary target fields that were excluded from both the control and MIRES extended membership fields. For some MSFRs there was insufficient NIR/MIR coverage to establish a control field, so the spatial distribution analysis was omitted, as noted in Section 5 below.
While Σ con can be measured directly in the control fields, it may vary by a factor of a few within the target fields due to variations in sensitivity that can arise from background nebulosity, extinction, or source crowding. To estimate surface density of contaminants in the target fields, we assume that the sensitivity variations affect both MIRES contaminants and the far more numerous, non-IRE field stars (Column 2A of Table 2) similarly within a given MIRES field. We then use the surface density of field stars as a proxy for the spatial distribution of the unclustered (contaminant) component. Surface densities for all MIRES (Σ) and for non-IRE field stars (Σ field ) are calculated independently using kernel density estimation with a σ = 1 Gaussian kernel. The surface density of MIRES members as a function of position is then calculated as where Σ con and Σ field apply to the full MIRES field, and the scale factor between them is the ratio of MIRES to non-IRE field stars in the control field. The probability that any specific MIRES belongs to the clustered spatial component is then calculated as and reported in Column 13 of Table 3. The "contamination fraction," f con , is the fraction of MIRES -26that are expected to belong to the distributed component, as a function of position. The positional variation of f con in the Trifid and NGC 6357 fields is illustrated in Figure 8. The contamination fraction is indeed lowest in the dense, central clusters, increases toward the outer regions of each MSFR, and is undefined in the control fields. The results of the above membership probability calculations were visually reviewed for each MIRES field, and if evident clusters were found to have high f con , or conversely if regions of low f con were found to extend to the boundary of the target field, the spatial boundaries of the target and control field were adjusted and the procedure was repeated iteratively.
For the purposes of identifying probable members, the various types of MIRES (as denoted by SED flg, column 9 of Table 3) must be handled differently:

Candidate YSOs (YSOc Flags)
The large majority of MIRES members in any target MSFR are classified YSOc (SED flg = 0), but the converse, that the majority of YSOc are members, need not be true in a given field. Figure  9 shows mid-IR images of the prototype MYStIX regions NGC 2264 and the Trifid Nebula. (Fig. 9 In the NGC 2264 field, YSOc are found almost exclusively in the clustered component, while the distributed component is dominated by extragalactic sources (Fig. 9d). NGC 2264 is located along a sightline toward the outer Galaxy, with relatively few field stars apparent in the [3.6] image. We therefore classify all MIRES flagged YSOc as probable members of NGC 2264.
In the Trifid field, by contrast, both the clustered and distributed components are dominated by YSOc (Fig. 9p). It is not immediately clear which component contains the greater number of sources, and it would definitely not be prudent to assume that all YSOc in this field are associated with the Trifid complex. Trifid is located in the inner Galaxy, and consequently the [3.6] image is dominated by field stars that contribute a significant fraction of contaminating, stellar sources to MIRES. For the case of Trifid, we therefore use 1 − f con (column 13 of Table 3, see Section 5.1 above) as the probability that a given MIRES is part of the spatially clustered component, and define a threshold value max(f con ) below which MIRES with YSOc flags are classified as probable members (MEM flg = 1). To find a reasonable threshold, we first specify a global contamination fraction that we are willing to accept for the membership sample, F con = 0.15 in the case of Trifid. We then compute max(f con ) as follows: 1. Define the initial value max(f con ) = F con .
2. Define the subset F = {f con : f con ≤ max (f con )} of MIRES spatially restricted to the primary -27target field (delineated by green and blue boundary lines in Fig. 9p, top panel). F thus represents MIRES nominated for probable membership.
3. Add sources iteratively to F by increasing max(f con ). Stop at the final, cutoff value of max(f con ) when the (increasing) moving average of F reaches or exceeds F con .
The 18 MIRES target MSFRs are divided evenly between those resembling NGC 2264, with negligible contamination from unassociated stellar sources, and those resembling Trifid, with significant contamination among YSOc. The F con column under "YSOc Flags" in Table 4 identifies which MIRES fields, including Trifid, required spatial clustering analysis to establish YSOc membership; for the remaining fields, including NGC 2264, all MIRES flagged as YSOc (SED flg = 0) were also flagged as members, so F con = 0 by construction. Trifid represents a "worst-case" for YSOc contamination (joined by the Lagoon Nebula, M17, and NGC 3576), and for other MSFRs we were able to reduce F con .

Candidate Extragalactic Point Sources (Galc/AGNc Flags)
MIRES flagged as extragalactic (Galc or AGNc with SED flg = 1 or 2) are dominated by contaminants, but our inability to cleanly separate extragalactic sources from low-luminosity YSOs becomes evident in several MIRES fields, notably NGC 2264 and NGC 1893. NGC 1893 is the most distant target MSFR (Table 1), and it also was observed with a deep Spitzer/IRAC integration (K13). MIRES with extragalactic flags clearly cluster together with YSOc in the central regions of this field (Fig. 9r), meaning that they are most probably YSO members with apparent magnitudes falling in the range occupied by extragalactic background sources. In NGC 2264 we observe a weak tendency for extragalactic-flagged MIRES to cluster with the two dense YSOc clusters (Fig. 9d), some of these are also likely members.
For NGC 2264 and NGC 1893, in addition to the 9 other MIRES target fields for which we applied spatial clustering analysis to determine YSOc probable members, we define a new (more stringent) threshold The second term is the fraction N exgal /N of MIRES in the subset F of the primary target field that have both extragalactic flags (Galc or AGNc) and f con ≤ max (f con ). MIRES with extragalactic flags and f con < max (f con ) are also classified as probable members (MEM flg = 1). The columns under "Galc/AGNc Flags" in Table 4 give the fraction F exgal of probable members flagged as extragalactic (identically zero in the fields where no Galc/AGNc sources were considered for membership), and the threshold max (f con ). With the exception of NGC 1893, F exgal is very small, 1%. The membership flag should be given priority over the extragalactic flags for subsequent population studies based on MIRES.

PAH Nebular Knots
Among all the possible contaminating source populations, PAH nebular knots (SED flg = 3) are the most pernicious. Because they appear in regions of bright nebular emission, their spatial distribution is highly non-uniform, with a tendency to cluster in the same locations as the young stellar populations responsible for producing the numerous bright H II regions targeted by MYStIX (see the Flame Nebula and W40, Fig. 9a and b, for two of the worst cases). We therefore reject any MIRES flagged as PAH nebular knots from consideration as probable MIRES complex members.

Discussion and Summary
Final tallies of MIRES, broken down by target MPCM and source classifications, are presented in Table 5. Probable members are drawn from the combined MYStIX X-ray fields and the MIRES extended membership fields and comprise 8686/20,719 = 41.9% of the IRAC Catalog. Anticipating that much future MYStIX-based science will concentrate on the combined X-ray and MIRES MPCM samples (Broos et al. 2013) that are spatially restricted to the MYStIX X-ray fields, in Table 6 we give final tallies for the subset of 8127/20,719 = 39.2% of MIRES located within the boundaries of the MYStIX fields. Within the MYStIX fields, the fraction of MIRES members is 5103/8127 = 62.8%, significantly higher than for MIRES as a whole. This implies that any residual contamination among the MIRES classified as members in the MYStIX fields is low (compared to the global contamination fractions F con reported in Table 4), as expected given that the archival Chandra/ACIS observations used for MYStIX typically targeted dense, young stellar clusters.
A majority of MIRES probable members, 5103/8686 = 58.7%, are found within the MYStIX fields. This fraction is a lower limit to the true spatially-limited fraction of star formation activity in each MYStIX target sampled by the Chandra data, because the MYStIX fields generally contain the densest stellar clusters and brightest diffuse nebular emission (see Figs. 9) within the larger MIRES fields. Crowding and nebulosity conspire to reduce IR point-source sensitivity, while the contamination fraction among MIRES members is generally higher in the extended fields. Conversely, a significant minority of MIRES are located within the extended membership fields, and these often reveal regions of active star-formation associated with the MYStIX MSFRs that fall outside the Chandra FOV and hence were excluded from the MPCM tables provided by Broos et al. (2013).
-32photometry available from UKIRT (King et al. 2013), while others have only 2MASS photometry. These competing photometric sensitivity limits create large variations in completeness as a function of bolometric luminosity (a proxy for stellar mass) both between different target MSFRs and even across a given MIRES field. MIRES should provide a near-complete sample of the YSO population to sub-solar masses for targets resembling the relatively nearby NGC 2264 complex, with its deep UKIRT and IRAC photometric catalogs. By contrast, MIRES samples primarily the intermediatemass (2-8 M ) YSO population but is substantially incomplete even at solar masses in more distant targets resembling the Trifid Nebula, with only the shallower GLIMPSE Catalog available, limited further by brighter nebulosity and confusion from the dense field star population (see also Povich et al. 2011). In addition, the following important types of IRE sources will generally be missing from MIRES, given our selection criteria: 1. Dense clusters in bright, compact H II regions. Any areas where the [8.0] mosaics in Figure 9 saturate to white show MIR nebular background emission so extreme as to preclude the detection of the large majority of point sources over the entire luminosity range. M17 is among the worst offenders  The literature for identifying and classifying IRE sources based on Spitzer/IRAC photometry now spans a decade. As MIRES represents the most recent, and arguably most complicated, such methodology, it is worth comparing our classification results to the early, more straightforward approaches. Allen et al. (2004) showed that YSOs separate most cleanly from field stars on the  We do not, however, find any clean separation between Stage 0/I and Stage II/III sources in the color space of Figure 10 (or in any other color space, see Figs. 3 and 6), and the region of overlap is heavily populated by sources with ambiguous stage classifications. This is the largest difference between our SED-model-based classifications and the work of Allen et al. (2004), G09, and other authors using color-color diagrams (see also the discussion in Povich et al. 2011). Geometry and viewing angle often conspire to make protostars appear bluer than disk-dominated YSOs (1) in [5.8] − [8.0] where the envelope produces a deep 9.7 µm silicate absorption feature, or (2) in [3.6] − [4.5] where light from the central star scatters off of the envelope cavity walls (Whitney et al. 2003). The definition of Stage 0/I from RW06 includes both deeply-embedded protostars with red spectral indices at all IR wavelengths and more evolved objects retaining significant longerwavelength (λ 8 µm) emission from infalling envelopes. Classifications based solely on 1-8 µm colors or SEDs cannot reliably distinguish the latter case from disk-dominated YSOs. Figure 10 illustrates a clear disadvantage of relying solely on MIR colors for IRE source selection: YSOs do not separate cleanly from the various contaminating populations, especially obscured -34 -AGN and reddened field giants. The work of the IRAC GTO team (including G09) and the Cores to Disks (c2d) survey team (notably Harvey et al. 2006) in cleaning extragalactic contaminants from IRE samples greatly ameliorates this fundamentally intractable problem. The MIRES targets include MSFRs at significantly greater distances and with far more variation in background reddening through the Galaxy compared to the regions commonly studied by these groups, requiring us to incorporate our SED-based dereddening into the G09 color cuts and to apply spatial clustering analysis to establish membership of faint MIRES in the more distant MSFRs.
Requiring detections in all 4 IRAC bands with high-precision photometry significantly reduces the number of IRE sources that can be identified and classified. Only 26.5% of all MIRES, including 40.2% of probable members, are plotted in Figure 10. To get around this limitation, G09 provide a "Phase 2" analysis using only J H K S plus [3.6] and [4.5] photometry to identify YSOs lacking detections at [5.8] and [8.0]. This analysis is more vulnerable to confusion between reddened field stars and YSOs than the G09 "Phase 1" analysis using all IRAC bands, and Povich et al. (2009) showed that even the Phase 1 color-color analysis would mis-classify large numbers of highlyreddened field stars (most likely giants that already have intrinsically redder IR colors) as YSOs in the inner-Galaxy M17 field. We find that an initial filtering based on fitting reddened stellar photospheres to SEDs, as employed in this work, its direct antecedents Kang et al. 2009;Povich et al. 2011), or the parallel strategy employed by the c2d team (Harvey et al. 2006), is a critical step to mitigate otherwise overwhelming field-star contamination in dense, inner Galaxy fields.
With MIRES, we have analyzed a broad range of Galactic MSFRs in terms of distance, Galactic location, and depth of photometric data. MIRES provides both a unified strategy for identifying young stellar members of diverse MSFRs based on IRE emission and the basic lesson that there is no one ideal strategy. The central compromise for MIRES is the aggressive rejection of likely contaminants in favor of a more reliable sample of stellar members. Broos et al. (2013) combine MIRES members with the X-ray-selected MPCM samples, providing the basis for MYStIX followup studies, and future research should also return to the larger MIRES sample to find additional YSO members of the MYStIX MSFRs. Other follow-up studies could incorporate longer-wavelength survey data from Spitzer/MIPS or Herschel or use MIRES as a finding chart for observations with the Atacama Large Millimeter Array or the KMOS multiobject spectrograph on the Very Large Telescope. The MIRES catalog should provide a foundation, a starting point for follow-up studies of diverse phenomena related to massive star cluster formation, including protostellar outflows, circumstellar disks, and star formation triggered by massive star feedback.
S. R. Majewski and R. Indebetouw generously provided data from the Spitzer Vela-Carina Survey for this work. We thank M. R. Meade and B. L. Babler for providing point-source photometry for W3 via the GLIMPSE pipeline. We thank the referee, M. Gagné, for constructive comments that helped improve this work. M.S.P. was supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-0901646 during the main analysis phase of -35this project. The MIRES catalog is based on observations from the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory (California Institute of Technology) under contract with NASA. 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 Center/California Institute of Technology, funded by NASA and the NSF. This work is based in part on data obtained as part of the United Kingdom Infrared Telescope (UKIRT) Infrared Deep Sky Survey and in part data obtained in UKIRT director's discretionary time. UKIRT is operated by the Joint Astronomy Centre on behalf of the Science and Technology Facilities Council of the U.K. The MYStIX project is supported at Penn State by NASA grant NNX09AC74G, NSF grant AST-0908038, and the Chandra ACIS Team contract SV4-74018 (G. Garmire & L. Townsley, Principal Investigators), issued by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060.

A. SED Classification Applied to IR Counterparts of MYStIX X-ray Sources
Identifying probable members of the target MSFRs is a fundamental goal of MYStIX. Analysis of IR counterparts matched to X-ray sources has proven to be a critical component of classifying Xsources and evaluating their probability of membership in MSFRs (Broos et al. , 2013. Naylor et al. (2013) matched the various MYStIX Chandra catalogs to the more complete Spitzer Archive source lists (Benjamin et al. 2003, K13), presenting an opportunity to find new IRE counterparts to X-ray sources that were omitted from the MIRES analysis, which was based on the highly-reliable Catalogs to reduce contamination in our "blind," IRE-only search.
In this appendix we present results from our MIRES SED classification methodology as applied to all MYStIX X-ray sources with sufficient IR counterpart photometry available to support our analysis. The product of this analysis is the SED Classification of IR Counterparts to MYStIX Xray sources (SCIM-X) online table, described in Table A1. 2 The following points were implemented in producing SCIM-X: • The combination of X-ray emission and IRE is a powerful indicator of youth. We therefore used the more-complete IRAC Archive lists in lieu of the highly-reliable Catalog lists used for MIRES.
• Cross-matching was done by Naylor et al. (2013) in an X-ray centric fashion. It is possible to get a different NIR match to a given MIR source that appears in MIRES. We have not -36attempted to quantify how often this occurs, but we note that erroneous NIR-MIR crossmatches most likely will result in no valid SED fits (column 5 of Table A2).
• X-ray selection allows us to be more strict in our stellar atmosphere fits: χ 2 /N data ≤ 1 is required for good fits. The goodness-of-fit criteria for RW06 model fits to IRE SEDs are unchanged. This allows for the identification of weaker IRE sources, or more evolved circumstellar disks, compared to MIRES.
• SCIM-X incorporates non-IRE (SED flg = −2) and marginal-IRE (SED flg = −1) source classifications (column 10 of Table A1). The former are more robust indicators that a star has an evolved/dispersed disk than in the case of J H K s color analysis alone (see Fig. A1), and the latter are far more likely to represent transitional disks or optically thin disks than the vast numbers of sources rejected for consideration from MIRES.
We identified sources with marginal IR excess emission (see also Section 3.2), where the excess appears in only the single IRAC [5.8] where the κ λ are opacities given by the extinction law (Indebetouw et al. 2005) and A V is the maximum interstellar reddening observed to field stars in each MIRES field (Table 1) (Table A2). MIRES contains 13,695 YSO candidates (sum of Columns 1+2 in Table 2), implying an upper limit of 0.19 × 13, 695 = 2602 sources excluded from MIRES that were legitimate YSO candidates. This is an upper limit because marginal-IRE objects that are legitimate YSOs -37should be over-represented in an X-ray-selected sample compared to an IRE-selected sample, which includes a higher fraction of more embedded objects. Even this upper limit represents only 2% of the 101,814 marginal-IRE sources originally found Table 2), implying that >98% of objects excluded globally by the marginal IRE filter were not YSOs.
The results of the SCIM-X classifications are summarized in Table A2. The first two (unnumbered) columns give the total number of of MYStIX X-ray sources and the number with sufficient IR counterpart photometry for SED classification in each target MSFR; across all targets an average of 37% of X-ray sources have counterparts in SCIM-X. The last column in Table A2 gives tallies of SCIM-X significant IRE sources that have no counterpart in MIRES; these 1504 sources increase the tally of IRE sources in the MYStIX X-ray fields by 18%, particularly in regions with high MIR nebulosity or dense clusters with MIR sources suffer crowding (for example in NGC 6334, M17, and W3), as either high backgrounds or crowding can cause an MIR source to be excluded from the highly-reliable Catalog lists. In some targets with both deep Chandra and deep Spitzer data (in particular NGC 1893, which has the deepest Chandra integration among the 18 MYStIX targets analyzed for MIRES; Feigelson et al. 2013) the increase is driven by sources classified AGNc (column 4). Note that for source-by-source cross-indexing of SCIM-X to MIRES, the MIR NAME must be used, as the MIRES coordinates are based on the MIR source positions while the SCIM-X coordinates are based on the X-ray source positions.
SCIM-X sources are plotted on the J − H versus H − K s color-color diagram in the top panel of Figure A1. This color-color diagram enjoys great popularity because it is based on NIR photometry accessible from the ground. It is especially useful for MYStIX because the UKIRT data have higher resolution and are less compromised by nebular background emission compared to Spitzer (King et al. 2013), hence for many X-ray sources UKIRT photometry is the only available counterpart photometry (Naylor et al. 2013). This color space presents an extended, diagonal locus of normallyreddened stars (between the parallel reddening vectors in the top panel of Fig. A1), and K S -excess sources are located to the lower-right of this region. By color-coding the NIR sources based on SCIM-X classification, we confirm the earlier conclusions of Whitney et al. (2003), RW06, and others that while K S excess is a reasonably robust indicator of the presence of circumstellar dust, the lack of K S excess emission provides no useful constraints on circumstellar dust disks. Marginal IRE sources are found throughout the locus of normally-reddened stars, with a few showing modest K S excess emission.
The bottom panel of Figure A1 presents SCIM-X sources plotted on the same IRAC color space shown in Figure 10 for MIRES, but here the color coding distinguishes IRE from non-IRE, AGNc/Galc, and sources with failed SED fits. The evolutionary stage of YSOs is omitted for clarity. No marginal IRE sources satisfied the photometric uncertainty ≤0.1 mag criterion at both [5.8] and [8.0] for inclusion in this plot. We find that the simple application of the Allen et al. (2004) color cuts does a reliable job of separating YSOs from stellar photospheres when X-ray selection is employed as a pre-filter against contamination, although there is some overlap between the IRE and non-IRE populations. As was the case for MIRES, only a minority of SCIM-X sources can be -38 - Table A1. SCIM-X Online Table Format Column Label

−1=none
Type of SED model fit to source: 0=reddened stellar atmospheres, 1=RW06 YSO models (10) (11) SED flg SED chisq norm Source classification flag: −2=stellar photosphere, −1=marginal IRE, 0=likely YSO, 1=starburst galaxy, 2=AGN, −99=no acceptable SED fits χ 2 /N data of best-fit SED model, number of data points fit is 3 ≤ N data ≤ 7 (12) SED AV Visual extinction A V determined from χ 2 -weighted mean of all acceptable SED fits (13) SED stage Evolutionary Stage classification, RW06 YSO models: 1=Stage 0/I, 2=Stage MYStIX SFR II/III, −1=ambiguous, −99=unclassified e Name of MYStIX target MSFR a Xray Name should be used for cross-indexing SCIM-X with the X-ray classification and MPCM tables in Broos et al. (2013). b MIR Name should be used for cross-indexing SCIM-X with MIRES (Table 3), as there are many sources in common. c Value of −99.99 means that flux was used as an upper limit for SED fitting. d As described in Section 3.1, minimum uncertainty used for SED fitting was set in flux density space using δF i ≥ 0.05F i for J H K S , [3.6], and [4.5] and δF i ≥ 0.10F i for [5.8] and [8.0]. For original photometric error bars we refer the reader to the appropriate original source catalogs (King et al. 2013, K13 or GLIMPSE). e Sources with SED flg < 0 were not fit with RW06 models and hence cannot be classified according to YSO evolutionary stage.