HUBBLE SPACE TELESCOPE MORPHOLOGIES OF z ∼ 2 DUST OBSCURED GALAXIES. I. POWER-LAW SOURCES

As outlined in Section 1, a sample of ≈2600 DOGs from Dey et al. (2008) was originally identified using the 9.3 deg² Boötes field of the NDWFS. For details of the selection criteria and photometric analysis, we refer the reader to Dey et al. (2008). In this paper, we analyze HST imaging from program HST-GO10890 of 31 of the brightest DOGs at 24 μm (all have F_24 μm > 0.8 mJy). The bolometric luminosity of DOGs with bright 24 μm flux densities is typically dominated by AGN emission, while the opposite is true for 24 μm faint DOGs (0.1 mJy < F_24 μm < 0.3 mJy), which are dominated by star formation (Pope et al. 2008). Additionally, IRAC photometry shows that the objects in this paper are dominated by a power-law component in the mid-IR. The most likely cause of this emission is the presence of warm dust heated by an AGN (Donley et al. 2007).

Shallow X-ray coverage of the Boötes field exists and has yielded a full catalog of X-ray sources (Murray et al. 2005; Kenter et al. 2005; Brand et al. 2006). Within a 2'' search radius, two of the DOGs studied in this paper (SST24 J143102.2+325152 and SST24 J143644.2+350627) have a single X-ray counterpart, and one DOG has two counterparts (SST24 J142644.3+333051). A full analysis of the X-ray data is beyond the scope of this paper, but these basic results suggest that most DOGs are either not strong X-ray emitters or are heavily obscured. The latter view is supported both by mid-IR spectral features and the fact that this subset of 24 μm bright DOGs shows some of the reddest R − [24] colors of the entire DOG population. Figure 1 shows the color–magnitude diagram in R − [24] versus [24] space for the full DOG population in Boötes and highlights the subsample of objects studied in this paper.

Zoom In Zoom Out Reset image size

Previous work has shown that objects dominated by a power-law signature in the mid-IR tend to have AGN indicators in their mid-IR spectra, usually silicate absorption but no polycyclic aromatic hydrocarbon (PAH) emission (Weedman et al. 2006a; Polletta et al. 2008; Brand et al. 2008). Indeed, IRS spectra of these sources have revealed redshifts based on the 9.7 μm silicate absorption feature, and all are located at z ∼ 2. Of the 31 objects in this sample, 17 have spectra from Houck et al. (2005), two have spectra from Weedman et al. (2006b), and the remaining spectra will be presented in a future work (Higdon et al. 2009, in preparation). Subsequent Keck/NIRSPEC (Brand et al. 2007), Keck/LRIS, and Keck/DEIMOS spectroscopy has yielded more precise redshifts for four of the DOGs. The redshift distribution of the sample studied in this paper compared to the overall distribution of spectroscopic redshifts for the DOGs from the Boötes field is shown in Figure 2.

Zoom In Zoom Out Reset image size

Thirty one DOGs we study here were observed with HST from 2006 November to 2008 February. Nine were imaged in the Wide Field Channel (WFC) mode of ACS (Ford et al. 1998) before the failure of the instrument. We have observed the remaining 22 DOGs with WFPC2 (Trauger et al. 1994). All 31 DOGs were observed with the NICMOS NIC2 camera. Table 1 summarizes the details of the observations. All data were processed using IRAF.¹³ In the following sections, we provide more details about the processing of the ACS, WFPC2, and NICMOS images used in this paper.

2.2.1. ACS

2.2.2. WFPC2

2.2.3. NICMOS

Each ACS/WFPC2 and NICMOS image is aligned to the reference frame of the NDWFS, which itself is tied to the USNO A-2 catalog. We first run Source Extractor (SExtractor, Bertin & Arnouts 1996) on a cutout of the I-band NDWFS corresponding to the appropriate ACS/WFPC2 field of view (FOV) to generate a list of comparison objects. The IRAF task wcsctran is used to convert this list into pixel coordinates on the ACS/WFPC2 image. Another IRAF task, imcentroid, is used to improve the accuracy of the pixel coordinates. Finally, the IRAF task ccmap applies a first-order fit to correct the zero point of the astrometry and update the appropriate WCS information in the header of the ACS/WFPC2 image. This aligned ACS/WFPC2 image is then used as the reference frame for correcting the astrometry of the NICMOS image and the IRAC images (since the IRAC images of the Boötes Field are not tied to the USNO A-2 catalog, but instead to the 2 μm All-Sky Survey frames, see Eisenhardt et al. 2004). Using the properly aligned, multi-wavelength data set, identifying the proper counterpart to the MIPS source is relatively straightforward, since inspection of the four IRAC channels reveals a single source associated with the 24 μm emission for all but one source (this source is undetected in all four IRAC channels). The absolute uncertainty in the centroid of the IRAC 3.6 μm emission ranges from 03 to 05.

We perform 2'' diameter aperture photometry on each DOG in both the rest-optical and rest-UV, choosing the center of the aperture to be located at the peak flux pixel in the NICMOS images. We remove foreground and background objects using SExtractor (see Section 4.2.2) and calculate the sky level using an annulus with an inner diameter of 2'' and a width of 1''. We found that in some cases (particularly those NICMOS images where significant residual nonlinearities remained), the flux density radial profile did not flatten at large radii. When this occurred, we determined the appropriate sky value by the trial-and-error method. We computed the background level and photometric uncertainty by measuring the sigma-clipped mean and rms of fluxes measured in N 2'' diameter apertures, where N ≈ 10 and N ≈ 50 for the NICMOS and ACS/WFPC2 images, respectively.

We compute 4'' diameter aperture photometry in the NDWFS B_W, R, and I images centered on the IRAC 3.6 μm centroid of emission. Sky background levels were computed in a 3'' wide annulus with an inner diameter of 4''. Limiting magnitudes were determined by measuring the flux within a 4'' aperture at several sourceless locations near the DOG and computing the rms variation of the flux values.

We verified the accuracy of our ACS and WFPC2 photometric zero points by comparing well-detected sources common to both our HST and NDWFS imaging. For our ACS/F814W observations, we compared to the NDWFS I-band imaging and found negligible offsets (−0.03 ± 0.10 magnitudes). For our WFPC2/F606W observations, we compared to the NDWFS R-band (after correcting for color terms due to the dissimilarity of the R and F606W filter bandpasses) and again found negligible offsets (0.05 ± 0.15 magnitudes).

Figure 3 shows 2'' × 2'' cutout images of the DOGs in order of increasing redshift. Each cutout is centered roughly on the centroid of emission as seen in the NICMOS image. A red plus sign shows the centroid of IRAC 3.6 μm emission and is sized to represent the 1σ uncertainty in the position, which includes independent contributions from the centroiding error on the 3.6 μm emission (≈02–04, depending on the signal-to-noise ratio (S/N)), the relative astrometric calibration uncertainty within the 3.6 μm map (≈02), and the uncertainty in tying the 3.6 μm map to the HST images (≈01). The 1σ rms offset between IRAC and NICMOS centroids of the sample is 02. In most cases, the offset in centroids is negligible, but those cases where it is not are associated with faint 3.6 μm emission (when the absolute astrometric uncertainty may be as large as 05). This suggests there is no significant offset between the near-IR and mid-IR centroids, although we note that we cannot rule out offsets at the <1 kpc scale.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

The DOGs exhibit a wide range of morphologies, with most being well resolved. Only one object (SST24 J142644.3+333051) shows strong Airy rings and is clearly an unresolved point source. Here we give a brief qualitative description of the morphology of each object.

• 1.  
  SST24 J143135.2+325456: F606W: weak detection. F160W: large-scale emission with a faint tail extending northeast.
• 2.  
  SST24 J142645.7+351901: F606W: no significant detection. F160W: two compact, resolved components separated by ≈05.
• 3.  
  SST24 J143251.8+333536: F606W: faint emission slightly northeast (NE) of NICMOS centroid; possible second source ∼05 northwest (NW) of NICMOS centroid. F160W: extended object; possible point-source contamination.
• 4.  
  SST24 J143447.7+330230: F606W: no significant detection. F160W: irregular, diffuse object.
• 5.  
  SST24 J143520.7+340418: F606W: compact, resolved object. F160W: very compact object, but no evidence for Airy rings.
• 6.  
  SST24 J142653.2+330220: F814W: large-scale, irregular, and diffuse emission. F160W: large-scale, irregular, and diffuse, but with bright compact nuclear component.
• 7.  
  SST24 J143325.8+333736: F606W: compact, resolved object. F160W: bright compact and extended components.
• 8.  
  SST24 J143644.2+350627: F606W: compact, resolved object. F160W: extended object; possible point-source contamination. This object has a counterpart in the XBoötes catalog (Brand et al. 2006).
• 9.  
  SST24 J142622.0+345249: F814W: four compact, resolved clumps spread in a `T' shape with no visible central component. F160W: similar irregular `T' shape, but components are not as distinct. NE component is bluer than other components.
• 10.  
  SST24 J142648.9+332927: F814W: compact, resolved object. Chain of sources extends toward southwest. One of these sources is within 1'' of the DOG and is included in the photometric and morphological measurements, since there is no clear evidence to suggest it is not associated with the system. F160W: similar compact, resolved object; possible point-source contamination.
• 11.  
  SST24 J143102.2+325152: F606W: no significant detection. F160W: no significant detection. This object is also not detected in any of the IRAC images, but does have a counterpart in the XBoötes catalog (Brand et al. 2006).
• 12.  
  SST24 J143225.3+334716: F814W: compact, irregular object. F160W: compact, resolved object; possible point-source contamination.
• 13.  
  SST24 J143109.7+342802: F606W: no significant detection. F160W: irregular, diffuse object.
• 14.  
  SST24 J143508.4+334739: F606W: compact, resolved, and irregular central component with tail of emission to southeast (SE). F160W: very similar, but central component is stronger relative to tail.
• 15.  
  SST24 J143312.7+342011: F606W: four compact components in a semi-circle offset from the centroid of NICMOS emission. F160W: extended object; possible point-source contamination.
• 16.  
  SST24 J142626.4+344731: F606W: no significant detection. F160W: irregular, diffuse object.
• 17.  
  SST24 J143504.1+354743: F606W: faint source barely detected. F160W: irregular, extended object; possible point-source contamination.
• 18.  
  SST24 J143242.5+342232: F606W: no significant detection. F160W: faint, compact component near 3.6 μm centroid with emission leading to second, brighter peak ∼05 to southwest (SW). Possible multiple-component system.
• 19.  
  SST24 J142538.0+332607: F606W: no significant detection. F160W: irregular objected elongated in the NW–SE direction.
• 20.  
  SST24 J142804.1+332135: F606W: no significant detection. F160W: faint, irregular object.
• 21.  
  SST24 J143358.0+332607: F606W: faint, irregular object. F160W: extended object with possible point-source contamination.
• 22.  
  SST24 J143001.9+334538: F606W: no significant detection. F160W: faint, irregular object.
• 23.  
  SST24 J143545.1+342831: F814W: faint, compact irregular objects; possibly two component system. F160W: extended emission; possible point-source contamination.
• 24.  
  SST24 J143725.1+341502: F814W: very faint, low-surface brightness feature extending to east. F160W: diffuse emission with compact object; faint Airy ring present.
• 25.  
  SST24 J143808.3+341016: F814W: faint, compact, resolved components offset from centroid of NIC2 emission. F160W: compact, central component with extension to SE overlapping ACS emission centroid.
• 26.  
  SST24 J143025.7+342957: F606W: compact, resolved object. F160W: compact, resolved object; possible point-source contamination.
• 27.  
  SST24 J143523.9+330706: F814W: compact, resolved object with tail of emission to SE; possible point-source contamination. F160W: compact, resolved object; possible point-source contamination.
• 28.  
  SST24 J143539.3+334159: F606W: possible faint diffuse emission north of NIC2 centroid. F160W: compact, resolved object; possible point-source contamination; possible tail of emission toward N.
• 29.  
  SST24 J142958.3+322615: F606W: compact resolved object; possible point-source contamination. F160W: extended object with a bright nuclear source; possible point-source contamination.
• 30.  
  SST24 J142924.8+353320: F606W: no significant detection. F160W: very compact, irregular, faint object near IRAC 3.6 μm centroid. Larger, brighter object ∼08 to north.
• 31.  
  SST24 J142644.3+333051: F606W: weak detection. F160W: dominated by point-source emission; clear Airy ring. This source has two X-ray counterparts in the XBoötes catalog (Brand et al. 2006).

We first undertook a visual classification of the DOGs by conducting the following experiment: for each ACS/WFPC2 image, we generate a 5 arcsec × 5 arcsec cutout image of both the DOG and 14 other randomly selected galaxies in the same FOV with the same magnitude range as our DOG sample. Eight of the coauthors then classified all 15 galaxies in each FOV (the DOG was not identified), placing them into one of the following bins: elliptical/compact (E/C), disk, irregular/multi-component, irregular/diffuse, or too faint to tell. In practice, since these galaxies are selected to be faint in the optical and generally have low S/N, we group together the E/C and disk categories into a "Regular" bin and the two irregular categories into an "Irregular" bin. This results in a total of 3600 independent classifications, of which 240 pertain to the DOGs. In an effort to explore the robustness of our results, we flag and remove from the sample all objects where fewer than six classifiers were in agreement. This has the effect of reducing the fraction of "Too Faint To Tell" responses, but the ratio of the regular to irregular classifications changes by less than 15%. A similar experiment was done on the NICMOS images, without the control sample, since the NIC2 FOV is so small.

Interpretation of the results of our visual classification analysis is hampered by low S/N (in the case of the ACS/WFPC2 images) or the lack of a control sample (in the case of the NICMOS images), so we forego a detailed analysis and instead present the mode of the classifications for each DOG along with an indication of whether the eight coauthors were in general agreement in our morpholical results table in Section 4.2.2. This is useful as a qualitative assessment of the morphology for comparison with the more quantitative methods discussed below.

In many of the NICMOS images, there is a compact component that is not seen in the corresponding ACS/WFPC2 image, implying there is significant obscuration in the central region of many of the DOGs. In this section, we describe the method we use to explore the degree to which each DOG is dominated by a central, unresolved component. Our tool in this effort is GALFIT (Peng et al. 2002), which uses a two-dimensional χ² minimization to search the parameter space of a set of predefined functions and identify the parameters that best describe the observed two-dimensional profile.

Because the DOGs are small and have low S/N compared to more typical applications of GALFIT, we restrict the size of the fitting region to be 41 × 41 pixels (corresponding to an angular and physical size of 3'' and ≈24 kpc, respectively) and include the minimum necessary components in our model. For a variety of reasons, we expect AGN to be important contributors to the emitted radiation from these sources. Therefore, we model the observed emission with three components which are described by a total of 10 free parameters. The number of degrees of freedom (DOF), N_DOF, is calculated as the number of pixels in the image being modeled minus the number of free parameters. This implies that the maximum N_DOF is 1671. Those cases where N_DOF < 1671 are associated with images where pixels were masked out because they were associated with residual instrumental noise and prevented convergence with GALFIT. We note that because NIC2 is a Nyquist-sampled array (0075 pix⁻¹ compared to 016 FWHM beam), the pixels in our image may not be completely independent. As a result, the χ²_ν values should be interpreted in a relative sense rather than an absolute one.

The first element in our GALFIT model is a sky component whose amplitude is chosen to obtain flat radial profiles at large radii and is not allowed to vary. The second is an instrumental PSF generated from the TinyTim software (Krist & Hook 1997), which can simulate a PSF for NICMOS, WFPC2, and ACS. For the NICMOS and WFPC2 images, the DOG is positioned in nearly the same spot on the camera. In the case of WFPC2, this is pixel (400, 400) of chip 3 and pixel (155, 164) for NICMOS. Meanwhile, a different region of the ACS camera is used for each DOG. Therefore, we generate a unique PSF at each position on the appropriate chip in which a DOG is observed. We use a red power-law spectrum (F_ν ∝ ν⁻²) as the object spectrum. The PSF is computed out to a size of 30, and for the WFPC2 PSF, we oversample by a factor of 2 to match the pixel scale of the drizzled WFPC2 images.

The final component is a Sérsic profile (Sersic 1968) where the surface brightness scales with radius as exp[−κ((r/R_eff)^1/n − 1)], where κ is chosen such that half of the flux falls within R_eff. We attempted to place as few constraints as possible so as to optimize the measurement of the extended flux (i.e., the nonpoint-source component). However, in certain cases, the Sérsic index had to be constrained to be positive to ensure convergence on a realistic solution. For the NICMOS images, we used the uncertainty image output by calnicb as the error image required by GALFIT to perform a proper χ² minimization. The TinyTim NIC2 PSF is convolved with the Sérsic profile prior to performing the χ² minimization. The initial guesses of the magnitude, half-light radius, position angle, and ellipticity were determined from the output values from SExtractor. Varying the initial guesses within reasonable values (e.g., plus or minus two pixels for the half-light radius) yielded no significant change in the best-fit model parameters. We used the NICMOS centroid as the initial guess for the (x, y) position of both the PSF and extended components, but in a few cases these guesses had to be modified by 1–2 pixels in order to result in convergence.

We note that we tested two-component models as well (single-component Sérsic profile plus sky background) and found larger reduced χ² values, especially when the point-source fraction in our three-component model was large (see further discussion in Section 4.2.1). In cases where the point-source fraction was small, the two-component model had similar parameter values as the three-component model, as we would expect.

It is important to note here that NIC2 cannot spatially resolve objects smaller than 1.3 kpc at z ≈ 2. This limit is large enough to encompass a compact stellar bulge as well as an active galactic nucleus, implying that we cannot, from these data alone, distinguish between these two possibilities as to the nature of the central, unresolved component.

After the best-fit parameters are found in the NICMOS image, we run GALFIT with a simplified model on the DOGs in the ACS/WFPC2 images. The primary simplification is to fix the position of the PSF based on the best-fit NICMOS PSF location (allowing up to two pixel wiggle room to account for astrometric uncertainties, which can be as large as 01). In many cases, GALFIT required an upper limit to be placed on the magnitude of the PSF component in order to reach convergence. We choose to use the magnitude of a point source detected at the 2σ level for this upper limit. We note that our Sérsic profile model for the extended DOG flux is not representative of the rest-UV morphology of many of the DOGs (i.e., the reduced χ² values are large), but it does adequately recover their total flux.

The Gini coefficient (G) and M₂₀ parameter are known to be reliable tools for the characterization of faint-object morphologies (Lotz et al. 2004). G was originally created to measure how evenly the wealth in a society is distributed (Glasser 1962). Recently, Abraham et al. (2003) and Lotz et al. (2004) applied this method to aid in the classification of galaxies, with G defined such that low (high) values imply an equal (unequal) distribution of a flux. M₂₀ is the logarithm of the second-order moment of the brightest 20% of the galaxy's flux, normalized by the total second-order moment (Lotz et al. 2004). This means that higher values of M₂₀ imply multiple bright clumps offset from the second-order moment center. Lower values, on the other hand, suggest a system dominated by a central component.

Prior to computing G or M₂₀, we first generate a catalog of objects using SExtractor. We use a detection threshold of 1.5σ (corresponding to 24.5 mag arcsec⁻²) and a minimum detection area of 15 pixels. The center of the image as well as the ellipticity and position angle computed by SExtractor are used as inputs for computing morphological measures. In addition, we use catalog sources selected to have magnitudes within the range of all 24 DOGs analyzed in this paper as a "field" galaxy sample for comparison to DOGs.

Much of the methodology in this section relies on the morphology code written by J. Lotz and described in detail in Lotz et al. (2004). Here, we summarize the relevant information. Postage stamps of each object in the SExtractor catalog (and the associated segmentation map) are created with foreground/background objects masked out. Using a small region of the cutout devoid of sources, a sky value is computed and subtracted from the postage stamp. Next, we determine which pixels in each postage stamp belong to the galaxy and which do not. Since the isophotal-based segmentation map produced by SExtractor is subject to the effects of surface brightness dimming at high redshift, we use a segmentation map based on the mean surface brightness at the Petrosian radius μ(R_p). Pixels with surface brightness above μ(R_p) are assigned to the galaxy, while those below it are not. We define R_p as the radius at which the ratio of the surface brightness at R_p to the mean surface brightness within R_p is equal to 0.2.

Using the new segmentation map, we recompute the galaxy's center by minimizing the total second-order moment of the flux. A new value of R_p is then computed and a revised segmentation map is used to calculate G and M₂₀. Finally, the morphology code produces an average S/N per pixel value using the pixels in the revised segmentation map (Equations (1)–(5) in Lotz et al. 2004).

One of the most common methods of characterizing galaxy morphologies in the literature is to measure the concentration index C (Abraham et al. 1994), the rotational asymmetry A (Schade et al. 1995), and the residual clumpiness, S (Conselice 2003). Given sufficiently high S/N and spatial resolution, the CAS system has had demonstrated success in measuring morphological parameters and identifying mergers at low (Conselice 2003) and high redshift (Conselice et al. 2008). Unfortunately, the objects in our sample do not meet simultaneously the S/N and spatial-resolution requirements to be reliably placed in CAS space. Because computation of A and S involves differencing two images, the necessary per pixel S/N to measure these parameters reliably is twice as high as those that do not involve subtracting images. We find per pixel S/N values ranging from ∼ 2–5 for the DOGs, whereas reliable measurements of A and S require S/N⩾5 (Lotz et al. 2004). In principle, the data are of sufficient quality to measure C (see Table 5), but in practice we find that the inherent assumption of circular symmetry does not apply well to the DOGs, making the interpretation of C values difficult.

In Figure 4, we show the color–magnitude diagram for DOGs and a sample of galaxies in the HDF whose photometric redshifts are comparable to DOGs (1.5 < z_phot < 2.5). For DOGs, where the measured flux is below the 2σ detection limit, we use an open-plotting symbol and an upward-pointing arrow. DOGs range in H-band magnitude from 21.93 to 25.1 AB mags. In both V − H and I − H, DOGs are redder than a typical high-z galaxy by 0.2–3 AB mags. In particular, the LBGs from the HDF-N (Papovich et al. 2001) are comparably bright in H, but fainter in V by ≈2 AB mags than DOGs. There is a substantial overlap between the colors of DOGs and DRGs, suggesting that we might expect to see similarities in the morphologies between these two populations. Table 2 summarizes the photometric information derived from the NDWFS and the HST imaging.

Zoom In Zoom Out Reset image size

4.2.1. GALFIT Results

The results of our GALFIT analysis for the extended component Sérsic profile fit to the NICMOS images are shown in Table 3, along with 1σ uncertainties in the best-fit parameters. The Sérsic indices (n) range from 0.1 to 2.2 (median n = 0.9). For those objects where n < 1, we note that constraining n to be equal to 1 does not significantly alter the remaining fit parameters. As the Sérsic index decreases, the radial profile flattens more rapidly within r < R_eff, and the intensity drops more steeply beyond r > R_eff. For reference, n = 0.5 corresponds to a Gaussian profile, n = 1 corresponds to an exponential profile, and n = 4 corresponds to a de Vaucouleurs profile (Peng et al. 2002). The ratio of the minor-to-major axis ranges from 0.20 to 0.88 with a median value of 0.53. In comparison, simulated merger remnants tend to have a luminous component in the shape of an oblate spheroid, with axis ratios of 1:1:0.5 (Novak et al. 2006). The projected axial ratio should thus vary between 0.5 and 1.0. Our observed median value of ≈0.5 suggests that DOGs have more disk-like profiles than the simulated merger remnants. This may be due to a nonmerger origin for DOGs, or it may be an indication that DOGs have not progressed to the merger remnant stage.

Table 3. GALFIT Results

Source Name	n	Axial Ratio	Reff	χ2ν a	χ2ν b	Ndof
			(kpc)
SST24 J142538.2+351855	0.7 ± 0.2	0.64 ± 0.09	2.5 ± 0.4	0.35	0.36	1653
SST24 J142622.0+345249	0.1 ± 0.1	0.55 ± 0.04	2.5 ± 1.0	0.92	0.92	1671
SST24 J142626.4+344731	0.8 ± 0.2	0.59 ± 0.07	3.0 ± 0.4	1.35	1.35	1671
SST24 J142644.3+333051	5.6 ± 3.4	0.71 ± 0.07	1.1 ± 0.3	1.16	2.58	1671
SST24 J142645.7+351901	0.1 ± 0.1	0.41 ± 0.03	4.6 ± 0.2	1.08	1.08	1671
SST24 J142648.9+332927	0.7 ± 0.3	0.70 ± 0.05	1.8 ± 0.1	1.08	1.08	1561
SST24 J142653.2+330220	0.4 ± 0.1	0.85 ± 0.03	2.9 ± 0.1	0.95	0.96	1671
SST24 J142804.1+332135	1.0 ± 0.6	0.19 ± 0.06	6.4 ± 2.6	0.95	0.96	1671
SST24 J142924.8+353320	0.8 ± 0.3	0.35 ± 0.06	2.8 ± 0.4	1.04	1.07	1671
SST24 J142958.3+322615	0.4 ± 0.1	0.78 ± 0.03	2.1 ± 0.1	0.36	0.39	1671
SST24 J143001.9+334538	1.0 ± 1.3	0.6 ± 0.1	1.2 ± 0.3	0.49	0.49	1671
SST24 J143025.7+342957	1.0 ± 0.1	0.52 ± 0.02	1.8 ± 0.1	0.90	0.96	1671
SST24 J143102.2+325152	...	...	...	...	...	...
SST24 J143109.7+342802	1.2 ± 0.4	0.36 ± 0.05	7.0 ± 1.7	1.15	1.15	1671
SST24 J143135.2+325456	0.5 ± 0.1	0.53 ± 0.01	3.8 ± 0.1	1.54	1.56	1671
SST24 J143225.3+334716	0.9 ± 0.2	0.55 ± 0.03	1.9 ± 0.1	0.93	0.94	1671
SST24 J143242.5+342232	2.0 ± 0.4	0.50 ± 0.06	4.0 ± 0.8	0.57	0.58	1601
SST24 J143251.8+333536	0.8 ± 0.1	0.50 ± 0.02	3.3 ± 0.1	0.50	0.52	1671
SST24 J143312.7+342011	0.7 ± 0.1	0.51 ± 0.01	4.0 ± 0.1	0.63	0.66	1671
SST24 J143325.8+333736	1.3 ± 0.1	0.70 ± 0.01	3.1 ± 0.1	0.52	0.60	1671
SST24 J143358.0+332607	2.1 ± 0.5	0.84 ± 0.07	1.4 ± 0.1	0.49	0.48	1671
SST24 J143447.7+330230	0.4 ± 0.1	0.88 ± 0.04	1.9 ± 0.1	0.88	0.89	1671
SST24 J143504.1+354743	0.5 ± 0.1	0.43 ± 0.03	4.6 ± 0.3	0.91	0.93	1671
SST24 J143508.4+334739	2.6 ± 0.4	0.40 ± 0.03	2.2 ± 0.2	1.06	1.10	1671
SST24 J143520.7+340418	0.6 ± 0.4	0.5 ± 0.1	3.4 ± 0.7	1.08	1.10	1671
SST24 J143523.9+330706	0.5 ± 0.1	0.46 ± 0.02	1.5 ± 0.1	1.00	1.05	1671
SST24 J143539.3+334159	1.8 ± 0.5	0.82 ± 0.09	3.7 ± 0.7	0.91	0.92	1671
SST24 J143545.1+342831	1.1 ± 0.2	0.49 ± 0.03	2.2 ± 0.1	1.04	1.06	1671
SST24 J143644.2+350627	0.9 ± 0.2	0.70 ± 0.05	1.9 ± 0.1	1.22	1.23	1670
SST24 J143725.1+341502	0.3 ± 0.1	0.50 ± 0.03	3.4 ± 0.2	1.09	1.14	1424
SST24 J143808.3+341016	0.9 ± 0.1	0.81 ± 0.04	3.0 ± 0.2	1.37	1.38	1671

Notes. ^aAsssuming finite PSF contribution ^bAsssuming zero PSF contribution

Download table as:  ASCIITypeset image

It is possible for a degeneracy to arise in the fitting parameters, in the sense that a high-n, low-point-source fraction model may be comparable to a low-n, high-point-source fraction model. We have tested this by running GALFIT with the point-source fraction set to zero (i.e., removing the PSF component). The resulting n values range from 0.1 to 5.2 with a median of 2.0, which is still below the value of 4 that is typical of early-type galaxies. A total of seven DOGs have n > 3 using this zero-point-source model. The best-fit R_eff values change by less than one pixel, with an offset of −0.2 ± 0.8 pixels. In general, as mentioned in Section 3.2, the removal of the PSF component leads to larger reduced-χ² values (see Columns 5 and 6 in Table 3). However, we note that only one case (SST24 J142644.3+333051) is associated with a  > 0.08 decrease in χ²_ν after adding a nonzero PSF component. This suggests that the PSF component in most of the DOGs in this sample is not dominant at rest-frame optical wavelengths.

We find the effective radius, R_eff, ranges from 1.1 to 5.9 kpc with a median value of 2.5 kpc. In the left panel of Figure 5, we show the distribution of R_eff values for DOGs (dark-shaded histogram), Distant Blue Galaxies (diagonal blue hatched; DBGs, i.e., galaxies with z_phot > 2 that satisfy J − Ks < 2.3; Toft et al. 2007), and DRGs (opposite diagonal red hatched; Zirm et al. 2007; Toft et al. 2007). Two-sided K-S tests show that DOGs are dissimilar from both populations, with a < 7% and < 4% chance of being drawn from the same parent distribution, respectively. Based on the nature of their UV-NIR SED, DRGs may be separated into those that are actively forming stars (active DRGs or sDRGs) and those that are not (quiescent DRGs or qDRGs, see Zirm et al. 2007; Toft et al. 2007). The right panel of Figure 5 shows the DOG R_eff distribution in comparison to active DRGs (diagonal blue hatched) and quiescent DRGs (opposite diagonal red hatched). Quiescent DRGs have much smaller effective radii, while active DRGs are much closer to DOGs. Here, the two-sided K-S test gives a 99.9994% and 34% chance of being drawn from different parent distributions, respectively, suggesting that the DOG and active DRG populations may overlap.

Zoom In Zoom Out Reset image size

In Table 4, we give the V, I, and H magnitudes of the nuclear (PSF) component and the extended (galaxy) component, as well as the fraction of light contributed by a point source (including 1σ uncertainties). When the nuclear component is not detected, we quote the 3σ limit on the point-source fraction. The magnitude of the PSF component is measured using the same aperture photometry method described in Section 2.4, with the exception that the sky background is assumed to be zero. For the extended component, we subtract the PSF component from the science image and compute the photometry in the usual way on the residual image. The fraction of light due to an unresolved component in the rest-optical ranges from 0.04 to 0.78, and the median is 0.12. In the rest-UV, however, this fraction is significantly smaller, with only one object having a detected fraction. This object, SST24 J143523.9+330706, stands out as unique by virtue of having a greater point-source fraction in the rest UV than in the rest optical. This behavior is unique within our sample (but is expected when the AGN is viewed without obscuration) and is also reflected in the nonparametric measures of its morphology (see Section 4.2.2 for more detail).

Table 4. PSF Subtraction Analysis

Source Name	Vnuc	Inuc	Hnuc	Vgal	Igal	Hgal	foptPSF	firPSF
SST24 J142538.2+351855	>28.3	...	27 ± 2	>26.0	...	24.1 ± 0.3	...	<0.27
SST24 J142622.0+345249	...	>27.9	27 ± 1	...	24.2 ± 0.1	23.6 ± 0.2	<0.01	<0.15
SST24 J142626.4+344731	>27.6	...	26.8 ± 0.3	>26.4	...	23.7 ± 0.2	...	<0.07
SST24 J142644.3+333051	>28.1	...	22.3 ± 0.1	26.1 ± 0.6	...	23.4 ± 0.1	<0.06	0.73 ± 0.07
SST24 J142645.7+351901	>27.7	...	27 ± 1	>26.2	...	22.9 ± 0.1	...	<0.08
SST24 J142648.9+332927	...	>28.1	25.2 ± 0.3	...	24.9 ± 0.4	23.3 ± 0.2	<0.03	0.15 ± 0.06
SST24 J142653.2+330220	...	>28.3	25.8 ± 0.2	...	25.0 ± 0.4	22.8 ± 0.2	<0.01	0.06 ± 0.03
SST24 J142804.1+332135	>27.7	...	26.1 ± 0.5	>26.6	...	>25.2	...	...
SST24 J142924.8+353320	>27.9	...	25.9 ± 0.5	>26.1	...	>25.3	...	...
SST24 J142958.3+322615	>28.2	...	25.0 ± 0.1	25.6 ± 0.6	...	23.5 ± 0.2	<0.01	0.20 ± 0.03
SST24 J143001.9+334538	>27.9	...	26.6 ± 0.9	>26.5	...	>25.5	...	<0.53
SST24 J143025.7+342957	>28.4	...	23.9 ± 0.1	24.2 ± 0.2	...	22.58 ± 0.07	<0.01	0.24 ± 0.03
SST24 J143102.2+325152	>27.8	...	>27.0	>26.0	...	>25.1	...	...
SST24 J143109.7+342802	>27.9	...	27 ± 1	>26.3	...	23.78 ± 0.3	...	<0.18
SST24 J143135.2+325456	>27.8	...	26.1 ± 0.3	25.2 ± 0.5	...	22.1 ± 0.1	<0.06	<0.02
SST24 J143225.3+334716	...	>28.3	24.8 ± 0.1	...	26 ± 1	23.0 ± 0.2	<0.02	0.17 ± 0.04
SST24 J143242.5+342232	>28.5	...	25.4 ± 0.2	>26.7	...	22.9 ± 0.1	...	0.09 ± 0.03
SST24 J143251.8+333536	>28.7	...	24.9 ± 0.1	>26.5	...	22.4 ± 0.1	...	0.09 ± 0.01
SST24 J143312.7+342011	>27.9	...	24.6 ± 0.1	24.7 ± 0.3	...	22.4 ± 0.1	<0.04	0.12 ± 0.02
SST24 J143325.8+333736	>27.6	...	23.6 ± 0.1	25.8 ± 0.7	...	21.6 ± 0.1	...	0.13 ± 0.02
SST24 J143358.0+332607	...	27.5 ± 0.5	25.8 ± 0.3	...	>25.9	23.5 ± 0.2	...	0.10 ± 0.05
SST24 J143447.7+330230	>27.9	...	25.8 ± 0.6	>26.0	...	23.2 ± 0.2	...	<0.12
SST24 J143504.1+354743	>27.7	...	24.9 ± 0.2	>26.4	...	23.3 ± 0.2	...	0.18 ± 0.05
SST24 J143508.4+334739	27 ± 2	...	24.9 ± 0.3	23.9 ± 0.1	...	22.6 ± 0.1	<0.14	0.11 ± 0.04
SST24 J143520.7+340418	>28.1	...	24.9 ± 0.1	>26.2	...	25.0 ± 0.5	...	0.5 ± 0.1
SST24 J143523.9+330706	...	26.2 ± 0.2	24.9 ± 0.2	...	25.0 ± 0.5	23.1 ± 0.1	0.24 ± 0.04	0.17 ± 0.03
SST24 J143539.3+334159	>28.4	...	25.2 ± 0.2	25.2 ± 0.5	...	23.3 ± 0.3	<0.01	0.15 ± 0.06
SST24 J143545.1+342831	...	>28.0	24.2 ± 0.1	...	>26.7	22.9 ± 0.1	...	0.22 ± 0.03
SST24 J143644.2+350627	28 ± 1	...	24.9 ± 0.3	25.7 ± 0.4	...	22.9 ± 0.1	<0.11	0.13 ± 0.04
SST24 J143725.1+341502	...	>28.1	23.6 ± 0.1	...	>26.2	23.3 ± 0.2	...	0.43 ± 0.05
SST24 J143808.3+341016	...	>28.3	25.9 ± 0.4	...	24.7 ± 0.4	22.4 ± 0.2	<0.01	<0.06

Download table as:  ASCIITypeset image

Figure 6 shows the V–H and I–H colors of the nuclear, extended, and full galaxy components as a function of H, in AB magnitudes. High-z galaxies and DRGs in the HDF-N and HDF-S are also shown. The full galaxy and extended components have similar colors and H magnitudes, consistent with the nuclear component not dominating the flux. This is why even the extended components of DOGs are redder in both V − H and I − H compared to Lyman break galaxies (LBGs) in the HDF, and suggests that one cannot create a DOG simply by adding an obscured AGN to a star-forming galaxy like an LBG. DRGs show greater overlap with the colors of DOGs, but few are as bright in H as the DOGs in our sample.

Zoom In Zoom Out Reset image size

4.2.2. Non-parametric Classification Results

Nonparametric methods of characterizing galaxy morphology are known to require high S/N imaging to yield reliable results (Lotz et al. 2004). In the rest UV, where the DOGs are very faint, none of the 22 WFPC2 images and only six out of nine ACS images have the per pixel S/N necessary to compute R_p, G, M₂₀, and C. In the rest optical, however, DOGs are much brighter and 23 out of 31 NICMOS images have sufficient S/N. Table 5 presents the visual and nonparametric measures of DOG morphologies, including the per pixel S/N, R_p, G, M₂₀, and C values for the ACS/WFPC2 and NICMOS images.

Table 5. Nonparametric Morphological Classifications

	ACS/WFPC2						NICMOS
Source Name	Visuala	S/N	Rp ('')	G	M20	C	Visuala	S/N	Rp ('')	G	M20	C
SST24 J142538.2+351855	TFTT	...	...	...	...	...	Reg	...	...	...	...	...
SST24 J142622.0+345249	Irr	5.2	0.6	0.45	−0.8	3.6	Irr	3.0	0.5	0.44	−1.0	2.1
SST24 J142626.4+344731	Irr	...	...	...	...	...	Reg	...	...	...	...	...
SST24 J142644.3+333051	TFTT	...	...	...	...	...	Reg	10.7	0.3	0.56	−1.8	3.3
SST24 J142645.7+351901	TFTT	...	...	...	...	...	Irr	2.7	0.8	0.42	−0.7	4.3
SST24 J142648.9+332927	Irr	2.7	0.6	0.46	−0.8	4.9	Reg	2.6	0.6	0.50	−1.7	2.9
SST24 J142653.2+330220	Irr	2.2	0.8	0.42	−0.7	3.6	Reg	3.9	0.6	0.43	−1.2	2.2
SST24 J142804.1+332135	TFTT	...	...	...	...	...	TFTT	...	...	...	...	...
SST24 J142924.8+353320	TFTT	...	...	...	...	...	Irr	...	...	...	...	...
SST24 J142958.3+322615	Reg	...	...	...	...	...	Reg	3.8	0.5	0.46	−1.4	2.3
SST24 J143001.9+334538	TFTT	...	...	...	...	...	TFTT	...	...	...	...	...
SST24 J143025.7+342957	Reg	...	...	...	...	...	Reg	6.1	0.6	0.54	−1.7	2.9
SST24 J143102.2+325152	TFTT	...	...	...	...	...	TFTT	...	...	...	...	...
SST24 J143109.7+342802	TFTT	...	...	...	...	...	Irr	...	...	...	...	...
SST24 J143135.2+325456	TFTT	...	...	...	...	...	Irr	2.8	1.3	0.52	−2.5	4.7
SST24 J143225.3+334716	Irr	3.9	0.4	0.37	−1.6	2.4	Reg	5.1	0.5	0.50	−1.4	2.8
SST24 J143242.5+342232	TFTT	...	...	...	...	...	Irr	...	...	...	...	...
SST24 J143251.8+333536	TFTT	...	...	...	...	...	Reg	4.7	0.9	0.47	−1.7	2.7
SST24 J143312.7+342011	Irr	...	...	...	...	...	Reg	3.8	1.1	0.51	−1.4	3.3
SST24 J143325.8+333736	Reg	...	...	...	...	...	Reg	5.1	1.0	0.54	−1.9	−2.1b
SST24 J143358.0+332607	Reg	...	...	...	...	...	Reg	4.1	0.5	0.50	−1.4	3.1
SST24 J143447.7+330230	TFTT	...	...	...	...	...	Reg	4.3	0.5	0.46	−1.2	2.0
SST24 J143504.1+354743	TFTT	...	...	...	...	...	Reg	2.2	0.9	0.49	−0.9	−2.1b
SST24 J143508.4+334739	Irr	...	...	...	...	...	Reg	4.1	0.8	0.53	−1.2	2.9
SST24 J143520.7+340418	Reg	...	...	...	...	...	Reg	3.3	0.4	0.47	−0.9	3.3
SST24 J143523.9+330706	Reg	5.2	0.5	0.56	−1.2	2.8	Irr	6.3	0.4	0.47	−1.2	2.3
SST24 J143539.3+334159	TFTT	...	...	...	...	...	Reg	2.7	0.7	0.50	−1.7	3.4
SST24 J143545.1+342831	TFTT	...	...	...	...	...	Reg	4.6	0.6	0.55	−1.6	3.2
SST24 J143644.2+350627	TFTT	...	...	...	...	...	Reg	3.1	0.6	0.52	−1.7	2.7
SST24 J143725.1+341502	TFTT	...	...	...	...	...	Reg	2.5	0.9	0.52	−2.1	3.7
SST24 J143808.3+341016	Irr	2.3	1.3	0.44	−0.9	3.6	Irr	2.3	1.0	0.48	−1.6	3.2

Notes. ^aMode of visual classification. Italics indicate multiple users disagreed with the mode. ^bNegative C value indicates r₂₀ was too small to be measured accurately.

Download table as:  ASCIITypeset image

In the left panel of Figure 7, we plot G as a function of M₂₀ as measured in the rest UV for DOGs, a field galaxy sample, and simulated r^1/4 bulges and pure exponential disks (Lotz et al. 2006). None of the DOGs fall within the pure exponential disk- or r^1/4 bulge-dominated regime. The field galaxy population is composed of sources identified within the ACS FOVs and is selected to span the same magnitude range as the DOGs in our sample. We use our NDWFS data to apply color cuts in B_W − R and R–I space in order to remove objects with colors typical of z < 0.7 sources. The morphologies of this field galaxy sample are represented with gray contours. Four out of six DOGs lie in the lower left corner of the plot, with low G and high M₂₀ values indicating irregular, diffuse morphologies. In general, low G and high M₂₀ values are indicative of dust-enshrouded stellar populations, where obscuration by dust causes a galaxy to appear very clumpy with flux distributed among many pixels (Lotz et al. 2008).

Zoom In Zoom Out Reset image size

One object (SST24 J143523.9+330706, panel 27 in Figure 3) has a higher G and lower M₂₀ value than nearly all of the field galaxies. This is the same object that shows a stronger point-source contribution in the rest UV than the rest optical. Visual inspection of this object's cutout image reveals an extended feature fading toward the southeast that is present in both the rest UV and rest optical. It appears that the central activity in this source is not quite as obscured as in other DOGs, but it is not yet clear why this is the case.

The right panel in Figure 7 shows G and M₂₀ values as measured in the rest optical for DOGs as well as LBGs in the HDF-N and a sample of local (z < 0.1) ULIRGs (Lotz et al. 2004). DOGs shift to more typical morphological parameters in the rest optical compared to the rest UV, but they are offset from the parameter space occupied by LBGs and local ULIRGs. The median G and M₂₀ values for DOGs are 0.49 and −1.24, respectively, while for LBGs they are 0.63 and −1.6, and for local ULIRGs they are 0.59 and −1.5. Part of the difference in G and M₂₀ compared to LBGs may be that LBGs are more compact, and hence less resolved. The offset to lower G values in DOGs compared to local ULIRGs is remarkable and indicates that either different mechanisms are involved in creating these two populations, or they represent different stages in the evolution of massive galaxies. We note that the ULIRG sample has comparable S/N as the DOGs studied here, and that the rest-frame wavelength of both samples is similar (∼7000 Å versus ∼5300 Å, respectively). While there is a greater relative difference in the spatial resolution of the two samples (≈0.2 kpc pix⁻¹ versus (≈0.6 kpc pix⁻¹, respectively), Lotz et al. (2004) found that systematic offsets at these resolutions should be on the order of 20% or less for C and M₂₀ and less than 10% for G. Therefore, the difference in G cannot be explained by spatial-resolution effects alone.

As a qualitative consistency check, we examined R-band images of a sample of 56 ULIRGs from Murphy et al. (1996) and determined that 20 (35%) have double nuclei with nuclear separations larger than 2.3 kpc, approximately the resolution limit of our NIC2 images. In comparison, only one DOG has two well-detected, distinct nuclei and three or four have low S/N components separated by 05 (≈4 kpc), implying that at most 16% of the DOGs in our sample have multiple nuclei with separations larger than 2.3 kpc. This result is qualitatively consistent with the differences seen in G between local ULIRGs and DOGs. An important caveat with this analysis is that our sample of DOGs is dominated by power-law sources, while the ULIRG sample has a variety of rest-frame NIR SED shapes. For reference, we measured the G and M₂₀ values of a well-detected, non-DOG point source (S/N per pixel of 18) in one of our NIC2 images, and found values of 0.62 and −1.7, respectively. The DOG whose morphology is dominated by a point source (see panel 31 in Figure 3) has a lower G value (0.56), but almost the same M₂₀ (−1.8). This may be an indication that this DOG contains an underlying extended component, but the data are not conclusive.

Here we estimate some of the intrinsic properties of DOGs including lower limits on their reddening (A_V), dust and gas masses, and stellar masses. To do this, we use Simple Stellar Population (SSP) template SEDs from the Bruzual & Charlot (2003) population synthesis library with ages spaced logarithmically from 10 Myr up to 1 Gyr, as well as the median QSO template from Elvis et al. (1994). All models used here have solar metallicity, a Chabrier IMF over the mass range 0.1–100 M_☉ (Chabrier 2003), and use the Padova 1994 evolutionary tracks (Girardi et al. 1996). The reddening law used is a combination of that from Calzetti et al. (2000) and longer wavelength estimates from Draine (2003), and assumes the case of a dust screen in front of the emitting source in order to derive a firm lower limit on A_V.

For each DOG, we estimate A_V needed as a function of age by determining the amount of extinction necessary to redden the given SSP template such that it reproduces the observed V–H or I–H color. The process is illustrated in Figure 8. Each panel shows the colors of DOGs in our sample as a function of redshift. Blue circles represent the extended component and red stars show the point source component of each DOG, as described in Section 4.2.1. Dotted lines show the expected colors of the SSP templates for varying amounts of extinction. Even with no extinction (A_V = 0), the oldest SSP templates are too red to reproduce the colors exhibited by DOGs. The quasi-stellar object (QSO) templates, on the other hand, require large A_V values in order to match the DOG nuclear colors.

Zoom In Zoom Out Reset image size

We use the relation from Bohlin et al. (1978) to convert A_V to the total column density of hydrogen atoms and molecules, N_H. For the 100 Myr SSP, the column densities range from 3 × 10²⁰–6 × 10²¹ cm⁻², with a median N_H of 3 × 10²¹ cm⁻². If we assume the dust is distributed in a spherical shell around the source with radius equal to the effective radius, then we can place a lower limit on the dust mass:

$$\begin{equation} M_{\rm dust} \ge \frac{1}{f_{\rm gd}} \mu_{\rm p} N_{\rm H} \times 4\pi R_{\rm eff}^2. \end{equation} \tag{ 1 }$$

Here, f_gd is the gas-to-dust mass ratio, and μ_p is the mean molecular weight of the gas, which we take to be 1.6m_p, where m_p is the mass of a proton. We adopt the average gas-to-dust mass ratio of 120 measured for the nuclear regions of local ULIRGs by Wilson et al. (2008). We find dust mass lower limits ranging from 2 × 10⁵–6 ×  10⁷M_☉, with a median of 9 × 10⁶ M_☉ for a 100 Myr SSP.

A complementary method of estimating the dust mass is based on measurements of optically thin sub-mm emission. Because sub-mm photometry for the DOGs in our sample is currently unavailable, we extrapolate from the 24 μm flux density measurement. We used the Mrk231 template to determine the extrapolated 850 μm flux density, F₈₅₀. Using a template SED of a galaxy with colder dust such as Arp220 would increase the inferred 850 μm flux. We follow Hughes et al. (1997) and estimate the dust mass using

$$\begin{equation} M_{\rm dust} = \frac{1}{1+z} \frac{F_{850} d_{\rm L}^2}{ \kappa _{\rm d} B(\nu,T_{\rm d}) }, \end{equation} \tag{ 2 }$$

where d_L is the luminosity distance, κ_d is the rest-frequency mass absorption coefficient, and B(ν, T) is the value of the modified blackbody function (β = 1.5) at the rest frequency ν and a temperature T. The appropriate κ_d value is interpolated from Draine (2003), with typical values being 5 cm² g⁻¹. There is at least a factor of 2 uncertainty in this quantity. We have assumed relatively hot dust (T_d = 75 K), since we expect AGN heating to play an important role in this sample of DOGs (a dust temperature of 50 K would increase the inferred dust mass by an additional factor of ≈1.5). Using this method, we find dust masses of 8 × 10⁷–6 × 10⁸ M_☉, with the median dust mass being 1.6 × 10⁸ M_☉. This is a factor of nearly 20 larger than the median dust mass inferred from the measurements of A_V. This might be expected, given that many of the dust masses based on A_V are lower limits, while the dust masses based on theb 24 μm emission may be overestimates if T_d > 75 K. On the other hand, this difference may be suggesting that the dust causing the average UV extinction of the extended galaxy component is not the same dust that is causing the thermal emission.

We use the SSP templates to estimate the stellar mass in each DOG. This is computed by reddening each SSP template to match the observed color of the DOG at the appropriate redshift. We then scale the redshifted, reddened template to match the observed H-band photometry. Since the Bruzual & Charlot (2003) models are normalized to a stellar mass of 1 M_☉, this scaling factor represents the stellar mass of the DOG.

In Figure 9, we show the stellar mass of each DOG as a function of age as well as the distribution of stellar masses assuming a 100 Myr SSP model. As stellar populations age, their colors naturally redden, and so less extinction is needed to reproduce the observed colors of the DOGs. For most DOGs, ages greater than ∼300 Myr require A_V values less than zero and are unphysical. Meanwhile, at younger ages, lower mass-to-light ratios are balanced by the need for greater extinction to match the observed colors. As a result, the inferred stellar masses are relatively constant to within a factor of a few for ages less than 300 Myr. We note that these mass estimates are lower limits because (1) the amount of extinction is a lower limit, especially when there is no detection in the V- or I-band image, and (2) our extinction estimate does not take into account gray extinction. For an age of 100 Myr, the stellar masses range from 2 ×  10⁸–1 ×  10¹² M_☉, with the median mass being 3.3 × 10¹¹ M_☉.

Zoom In Zoom Out Reset image size

We use our dust mass estimates inferred from the 24 μm flux densities and a gas-to-dust mass ratio of 120 (Wilson et al. 2008) to obtain an upper limit on the gas masses. This leads to gas masses of 1–7 × 10¹⁰ M_☉, with a median gas mass of 2 × 10¹⁰. If we assume a closed-box model and an exponential star-formation history, then we can write M_gas + M_dust = M_totexp(−t/t₀), where M_tot is the sum of the gas, dust, and stellar masses. The stellar mass is then given by M_star = M_tot(1 − exp(−t/t₀)), which implies

$$\begin{equation} \frac{t}{t_0} = {\rm ln}\frac{M_{\rm tot}}{M_{\rm gas} + M_{\rm dust}}. \end{equation} \tag{ 3 }$$

This quantity represents the fractional lifetime (in units of the scale time for our exponential star-formation rate assumption) of each DOG. Larger values of t/t₀ indicate more evolved systems, as more of the gas has been converted to stars. Our values of t/t₀ represent lower limits on the actual values, because our stellar masses are underestimated and our gas masses are based on our 24 μm flux densities, which likely overestimates the true mass of gas. We find t/t₀ lower limits ranging from 0.02 to 3.3, with a median lower limit of 0.9. This result implies that in half of the DOGs in our sample, at least 90% of one exponential timescale's worth of star formation has occurred. The "oldest" DOG in our sample has gone through more than three exponential timescales of evolution. However, we caution that the "youngest" DOGs from this line of analysis are uniformly associated with sources where the dust extinction is most likely underestimated, thereby causing an additional underestimate in the stellar mass and the associated t/t₀ value. In Table 6, we present the dust and stellar masses derived in this section, as well as our measure of the lower limit on the fractional lifetime, t/t₀.

It is important to understand how DOGs are related to other populations of high-z galaxies that have been studied in the literature. Here, we compare the morphological properties of the DOGs with some of these high-redshift galaxy populations and find that DOG morphologies are distinct from the bulk of LBGs and quiescent high-z galaxies, but are similar to SMGs as well as active DRGs and the extreme subset of faint, diffuse LBGs.

5.2.1. Sub-mm Galaxies

5.2.2. Star-forming Galaxies

5.2.3. Passively Evolving Galaxies

5.2.4. Distant Red Galaxies

In the local universe, there has been evidence for some time that warm dust-dominated ULIRGs may represent a transition stage between cold ULIRGs and optically luminous quasars (Sanders et al. 1988b). If this scenario holds at high redshift, then there is a natural explanation for the observations based on the selection criteria alone: objects selected at long wavelengths (i.e., SMGs) are preferentially cold-dust-dominated systems and represent the "cold ULIRG" phase, whereas objects selected at 24 μm (i.e., DOGs) are dominated by warmer dust and represent the transition phase en route to the optically luminous quasar. As time progresses and the quasar fades in luminosity, the compact, quiescent, elliptical galaxy remnant becomes visible (i.e., quiescent BzKs and DRGs).

Again referring to the local universe for guidance, if the triggering mechanism for this activity is a major merger (Sanders et al. 1988a), then we should expect to see a trend in relaxation and size, where the initial stage shows the largest sizes and least relaxation, and the end product is a relaxed, compact system. This picture is apparently consistent with our data, as DOGs tend to be smaller than SMGs, but larger than quiescent DRGs or BzK galaxies. Furthermore, SMGs frequently exhibit signs of major merger activity, whereas passively evolving systems at high z are very compact with large Sérsic indices. DOGs appear to be intermediate stage objects that typically do not show signs of major mergers, but nonetheless have morphologies indicating they are more dynamically relaxed than SMGs but less than the quiescent systems.

It is important to emphasize that while our morphological results are consistent with the hypothesis that DOGs act as a transition phase in the process of creating a massive galaxy via a major merger, the morphological information currently available is not sufficient to exclude the possibility that DOGs are created by some other process such as minor merging (for example, minor mergers have the potential to increase size temporarily), or are simply dusty galaxies hosting a powerful, obscured AGN.

Our analysis of the stellar, dust, and gas masses of DOGs currently does not provide compelling evidence to place them within an evolutionary scheme with respect to other massive proto-galaxy candidates such as SMGs. Additional data are needed before conclusive statements can be made based on mass estimates such as these.