THE QUaD GALACTIC PLANE SURVEY. II. A COMPACT SOURCE CATALOG

Millimeter (mm), submillimeter (sub-mm), and far-infrared (FIR) observations are ideal for studying the properties of star-forming regions in the galaxy, in particular the cool envelopes of dust and gas that host sites of potential and active star formation. By spanning the peak in the spectra of these objects, measurements between the mm and FIR can tightly constrain the parameters of the thermal radiation produced by the dust. In particular, the mass of a star-forming core and its surrounding envelope is well traced by its measured flux in these bands, since this radiation is optically thin at sub-mm and longer wavelengths.

Surveys covering large sections of the galaxy have the potential to collect statistical samples of cores in a range of evolutionary states comparatively free of bias introduced by targeting particular regions. These surveys are ideal for studying processes related to star-forming regions, such as measuring the core mass function (from which the stellar initial mass function (IMF) may be derived), particularly at the high-mass end, which, on account of the short-lived high mass cores, is understudied relative to lower masses (e.g., Enoch et al. 2006, 2008; Young et al. 2006). Combination with infrared (IR) data yields insight into the ages of cores, permitting differentiation between prestellar sub-mm cores, which lack an IR counterpart, and protostellar cores, in which the ultraviolet radiation produced by protostars is re-radiated into the mm, sub-mm, and IR by the surrounding envelope. Phenomena associated with later evolutionary phases, such as mass ejection, dissipation of the envelope, and dynamical interactions are not significant in the prestellar or protostellar stage—the mass and spatial distribution of such cores therefore capture information regarding the fragmentation process (Enoch et al. 2006).

Observations of polarized radiation permit a window through which to study the role of magnetic fields (e.g., Greaves et al. 1995; Novak et al. 1997) and their role in providing support against collapse. In the mm and sub-mm, polarization is due to emission along the long axis of dust grains partially aligned by the magnetic field, and thus measurements of the dust polarization directly probe local magnetic fields (e.g., Hildebrand 1988). These fields are thought to strongly influence the evolution of molecular clouds, since they provide support preventing the collapse of the gas and subsequent triggering of star formation.

Several large-scale surveys are already underway or completed to help address these questions. Herschel (Pilbratt et al. 2010) and Planck (Villa et al. 2002) will provide extensive spectral coverage from the radio to the FIR, fully characterizing the spectral energy distribution (SED) of star-forming cores over the full sky; selected existing results in targeted regions include, e.g., Hennemann et al. (2010), Juvela et al. (2010), and André et al. (2010), but are limited to total intensity observations. Ground and balloon instruments also contribute substantially to the literature: Schuller et al. (2009) present an APEX LABOCA 95 deg² survey in total intensity with resolution of 192 at 353 GHz, with the final survey coverage expected to reach 350 deg²; Bolocam has mapped 150 deg² of the first Galactic quadrant at 1.1 mm (268 GHz) with resolution 33'', with a source catalog presented in Rosolowsky et al. (2010); BLAST (Olmi et al. 2009; Netterfield et al. 2009) provides a 50 deg² survey of the Vela molecular cloud at 250, 350, and 500 μm (36, 42, and 60 arcsec resolution, respectively).

Observations at comparable resolution are currently scarce at ∼100 GHz, and yet provide additional constraining power to the Rayleigh–Jeans tail of the thermal dust spectrum, and probe for contributions due to other emission mechanisms which contribute increasingly at lower frequencies (e.g., free–free). Furthermore, there is little high angular resolution polarization data at these frequencies, despite their utility in understanding star-forming regions.

In this paper, we present a catalog of compact sources found in the QUaD Galactic Plane Survey (Culverhouse et al. 2010), which covers over ∼800 deg² of the low-latitude Galactic plane at 100 and 150 GHz with beam FWHM of 5' and 35, respectively, in Stokes I, Q, and U parameters.¹⁷ A survey of this size, frequency, and angular resolution can be used to investigate the polarized and unpolarized properties of both diffuse emission and discrete sources. The QUaD survey was conducted blind, in that no region was specifically targeted. In principle, this allows the construction of statistical samples of cores, representative of the distribution of core masses and ages in the Galaxy as a whole. However, we note that at the ∼few arcminute resolution of the survey, the maps do not generally resolve individual cores. Dense cores typically have a size of ∼0.1 pc (e.g., Williams et al. 2000), hence for nominal distances of a few hundred parsecs, the sources presented here should be considered "clumps" hosting cores rather than individual cores themselves. In addition to the lack of resolution and accurate clump distances, the contribution of free–free emission at 100 GHz biases measurements of the flux from the dust component; these caveats prevent reliable mass calculation. Our goals here are therefore to analyze the observed quantities of the sources in the survey, rather than infer their physical properties.

Basic information on the instrument, observations, and maps is presented in Section 2. In Section 3, we describe our algorithm for extracting sources in the presence of a diffuse background. The global properties of the catalog are discussed in Section 4, with the full catalogs presented in Table 2 (total intensity) and Table 3 (polarized intensity). Discussion and Conclusions are found in Section 5. Extensive simulations, presented in the Appendix, are used to quantify the effects of mapmaking and the source extraction algorithm on the recovered source properties.

Here, we summarize the features of the QUaD Galactic Plane Survey. A detailed description of the instrument can be found in Hinderks et al. (2009), hereafter referred to as the "Instrument Paper." The field selection, survey strategy, data processing, and construction of the Stokes I, Q, and U maps are presented in Culverhouse et al. (2010), hereafter the "Map Paper."

QUaD was a 2.6 m Cassegrain radio telescope on the mount originally constructed for the DASI experiment (Leitch et al. 2002). This is an az/el mount, with a third axis allowing the entire optics and receiver to be rotated around the line of sight. The mount is enclosed in a reflective ground shield, extended from DASI, on top of a tower at the MAPO observatory approximately 1 km from the geographic South Pole.

The QUaD receiver consisted of 31 pairs of polarization sensitive bolometers (PSBs; Jones et al. 2003), 12 at 100 GHz and 19 at 150 GHz. The bolometers were read out using AC bias electronics and digitized by a 100 Hz, 16 bit ADC; the raw data were staged on disk at Pole and transferred out daily via satellite.

The observations reported in this paper were made between 2007 July and October, with the telescope decommissioned in late 2007. In total QUaD surveyed the Galaxy for 40 days, covering a total of ∼800 deg². The survey is divided into two regions, approximately covering 245°–295° and 315°–5° in Galactic longitude l, and −4° to +4° in Galactic latitude b. These regions are loosely called the "third quadrant" and "fourth quadrant" throughout.

Maps are made by co-adding the timestream from each detector into flat-sky (R.A., decl.) pixels of size 002 × 002. The absolute pointing accuracy was determined to be ∼05 rms, using pointing checks on RCW 38 and other Galactic sources over two seasons of cosmic microwave background (CMB) observations (see the Instrument Paper for further details). A field-differencing scheme was used to remove spurious ground contamination. Data acquisition was divided into 2 hr blocks. In the first, the telescope scanned over a "lead" field centered on the plane of the Galaxy. The next hour of data covered a "trail" field offset 1 hr later in R.A., such that the azimuth and elevation range scanned by the telescope with respect to the ground was identical for both the lead and trail fields. By differencing the lead and trail field timestream, any spurious ground pickup is removed. The results presented here are derived using field-differenced maps; the consequences of field-differencing in the context of the source catalog are discussed further in Section 3.1, while we refer the reader to the Map Paper for a more detailed discussion of field-differencing. Absolute calibration is applied using a scaling factor at each frequency, derived in the QUaD CMB analysis presented in Brown et al. (2009). These factors were calculated by cross-calibrating QUaD CMB maps to those from the Boomerang experiment (Masi et al. 2006) and have an estimated uncertainty of 3.5%. The 100 GHz I map for both survey regions is shown in Figure 1; the reader is referred to the Map Paper for similar maps at both frequencies and in I, Q, and U. In addition to the sky maps, variance maps for each Stokes parameter are also constructed, which give a measure of the noise in each map pixel. The typical survey sensitivity in each survey area is 74 (107) kJy sr⁻¹ at 100 (150) GHz in I, and 98 (120) kJy sr⁻¹ in Q/U, at a spatial resolution of 5 (3.5) arcmin at 100 (150) GHz. The orientation of Q and U in the QUaD polarization maps follows the IAU convention (Hamaker & Bregman 1996), in which +Q is parallel to N–S and +U parallel to NE–SW.

Zoom In Zoom Out Reset image size

As is readily apparent from Figure 1, a substantial contributor to the sky signal is diffuse emission. This "background" increases the uncertainty in measured properties of compact sources above that due to detector and atmospheric noise. However, the systematic effect of diffuse emission can be reduced using spatial filtering.

The source extraction method implemented here is an adaptation of the algorithm described in Désert et al. (2008), a Mexican-hat linear filter in image space, which was designed to separate compact sources from the diffuse Galactic emission for the Archeops experiment. Maps of each stage of the source extraction algorithm, described below, are shown in Figure 2 in a representative section of the fourth quadrant 100 GHz I data.

Zoom In Zoom Out Reset image size

In our algorithm, two sets of smoothed I and $P=\sqrt{Q^{2}+U^{2}}$ maps are made at each frequency; both are derived from the raw maps m_r. The first set, m_b, consists of m_r smoothed to the beam scale σ_beam. In the second, m_r is smoothed to an angular scale σ_bck = 2.5 × σ_beam to form a template map of the diffuse background, m_bck. In both cases, a circularly symmetric Gaussian function is the smoothing kernel. The choice of σ_bck is designed to minimize the background contribution to source fluxes without introducing large biases in the measured flux. In Appendix A.5, simulations demonstrate the consequences of other choices of σ_bck on recovered source fluxes. The background maps are then subtracted from beam-smoothed maps to yield the "source extraction" map m_s:

$$\begin{equation} m_{I,s}=m_{I,b}-m_{I,{\rm bck}} \end{equation} \tag{ 1 }$$

and likewise for P. Note that since σ_bck > σ_beam, Equation (1) is equivalent to convolving m_r with filter constructed from the difference of the two smoothing kernels, commonly referred to as a "Mexican hat" filter.

Negative pixels due to ringing are masked, and the remaining pixels are subjected to signal-to-noise thresholding. Pixels above a signal-to-noise (S/N) threshold of 5 (3) for total (polarized) intensity are flagged as belonging to source candidates. The polarization data have a lower extraction threshold because the noise properties are closer to white on account of the unpolarized atmosphere, and also because the diffuse component amplitude (fractional polarization <2%; see Map Paper) is close to the instrumental noise level and therefore its effect on source fluxes is small. High signal-to-noise regions in the P map define a set of pixels to which we separately fit polarized sources in the Q and U maps. Candidate pixels in all Stokes maps are subject to suitability checks; isolated pixels or groups of pixels smaller than the beam width are removed.

Sources in close proximity tend to be members of the same thresholded region, so an internally developed segmentation algorithm based on the SExtractor code (Bertin & Arnouts 1996) is used to split such regions into separate sources. Source segmentation is applied to the I, Q, and U maps separately at each frequency, resulting in a set of six source position lists, along with the map pixels assigned to each source.

Having determined source positions, the background maps m_bck are regenerated by again smoothing m_r, but with the pixels corresponding to discrete sources replaced by the local median—this "source-corrected" background map is denoted m_{bck, corr}, with m_{s, corr} = m_b − m_{bck, corr} following from Equation (1). The median-replacement step reduces the amount of ringing due to the background filtering implemented in Equation (1) (see Figure 2). The resulting background map contains less leaked flux due to smoothing discrete sources with a kernel larger than the beam size. The background subtraction, source detection, and segmentation stages are then repeated.

All ingredients for measuring source properties are present at this point: the background map m_{bck, corr}, a list of pixels belonging to each source, and the input map itself m_r, with its variance map σ²_r. The background map m_{bck, corr} is subtracted from the input map m_r yielding the map to which source models are fit,

$$\begin{equation} m_{I,f}=m_{I,r}-m_{I,{\rm bck,corr}}, \end{equation} \tag{ 2 }$$

and likewise for P. An elliptical Gaussian is fit to the resulting pixels for each source; an example of the model reconstructed from these fits is shown in Figure 2. Residuals of this model against m_r, also shown in Figure 2, indicate that the source-fitting works well, except for two cases: (1) particularly bright sources, which can leave residuals at the ∼few percent level, and (2) sources in close proximity, for which the source segmentation fails and the sources are classed as a single object.

Fits are performed independently at each frequency in I, Q, and U, with pixel noise taken from the corresponding variance map σ²_r; errors on source properties follow directly from the parameter errors returned by the fit minimizer. The elliptical Gaussian fit parameters are used to calculate source properties such as flux and position; in a small number of cases, the uncertainty on a fit parameter diverges, in which case we do not quote the uncertainty on any physical quantity derived from this parameter. Derived quantities such as spectral index α = log(I₂/I₁)/log(ν₂/ν₁), polarization angle ϕ = 0.5tan⁻¹(U/Q), polarization fraction P/I, and their associated errors are calculated from I, Q, and U fluxes. In general, a source detected in I will not have the same set of pixels as in Q or U as each map is treated independently; sources are spatially matched across catalogs later to determine, e.g., polarization fraction. Given two catalogs A and B (such as total intensity at two frequencies), each source in A is matched to a source in B if their angular separation is less than three map pixels (36), conservatively larger than the rms day-to-day telescope pointing wander of ∼05. If more than one source in B matches a source in A, as can happen when matching sources between 100 and 150 GHz due to the higher resolution in the latter band, the closer of the two is selected. Having matched sources, the corresponding physical quantities are combined to yield the derived quantity such as the spectral index.

3.1. Consequences of Field Differencing

The field-differencing operation performed on the timestream to remove ground contamination can result in spurious sources in the data. If a source lies in the trail field of the observations (at larger R.A.), when the trail field is differenced against the lead field the source will appear negative in the lead field, resulting in a negative measured flux. Such sources are removed in I by rejecting candidates with fluxes below zero at a signal-to-noise of 5 or greater. This rejection is not possible in Q or U because the polarized flux can take positive or negative values. Instead, detected polarized sources are matched to the total intensity source catalog; if the polarized source is matched to a source of negative total intensity with |S/N| > 5, the polarized source is removed from the catalog. This method may allow small numbers of field differenced polarized sources to leak into the catalog, since sources in I are extracted at a higher significance threshold (5σ) than polarization—a field differenced source in P may not be matched to a total intensity candidate and therefore cannot be rejected.

Field-differenced sources are also increasingly expected at low declinations. The central PSB pair are aligned on the plane of the Galaxy, with the low R.A. edge of the trail field aligned with the high R.A. edge of the lead field; the width of the QUaD focal plane allows for overlapping coverage of the lead and trail fields. At higher elevation (lower declination) the scan throw of δAz = 15° translates into a smaller R.A. range as δR.A. = δAz × cos (decl.). Due to the alignment of lead and trail field edges and the decreasing scan throw in R.A. at lower decl., the trail field lies closer to the galactic plane at low decl.—see Figure 3 (we further refer the reader to Figure 2 of the Map Paper for a graphical representation of the lead/trail field geometry over the full survey). At lower decl. the trail field is therefore more likely to contain a bright source (Figure 3). However, the QUaD catalog indicates that most detected sources lie within 3° of the Galactic plane (Section 4.2), and thus the contribution of field differenced sources is small over most of the survey, since the trail fields never get closer than ∼(15°/2) × cos (60) = 375 to b = 0.

Zoom In Zoom Out Reset image size

Source catalogs from both the third and fourth quadrant maps are extracted and combined for the purposes of calculating statistical properties. Spurious sources are rejected if the flux is negative at one frequency and undetected at the other frequency. Statistics for the survey are shown in Table 1.

In total, 292 (473) sources are detected in I at 100 (150) GHz, of which 239 are spatially matched between frequency bands, resulting in 526 unique sources in total intensity. Position, major/minor axes, flux, and spectral index for each source in I are given in Table 2. Four sources are detected in P, of which two are matched spatially across bands; three of these polarized sources have matching counterparts in at least one frequency band in I. Properties of these sources are presented in Table 3.