GLEAM: The GaLactic and Extragalactic All-sky MWA survey
R. B. Wayth, E. Lenc, M. E. Bell, J. R. Callingham, K. S. Dwarakanath, T. M. O. Franzen, B.-Q. For, B. Gaensler, P. Hancock, L. Hindson, N. Hurley-Walker, C. A. Jackson, M. Johnston-Hollitt, A. D. Kapinska, B. McKinley, J. Morgan, A. R. Offringa, P. Procopio, L. Staveley-Smith, C. Wu, Q. Zheng, C. M. Trott, G. Bernardi, J. D. Bowman, F. Briggs, R. J. Cappallo, B. E. Corey, A. A. Deshpande, D. Emrich, R. Goeke, L. J. Greenhill, B. J. Hazelton, D. L. Kaplan, J. C. Kasper, E. Kratzenberg, C. J. Lonsdale, M. J. Lynch, S. R. McWhirter, D. A. Mitchell, M. F. Morales, E. Morgan, D. Oberoi, S. M. Ord, T. Prabu, A. E. E. Rogers, A. Roshi, N. Udaya Shankar, K. S. Srivani, R. Subrahmanyan, S. J. Tingay, M. Waterson, R. L. Webster, A. R. Whitney, A. Williams, C. L. Williams
PPublications of the Astronomical Society of Australia (PASA)c (cid:13)
Astronomical Society of Australia 2015; published by Cambridge University Press.doi: 10.1017/pas.2015.xxx.
GLEAM: The GaLactic and Extragalactic All-sky MWAsurvey.
R. B. Wayth , , E. Lenc , , M. E. Bell , , J. R. Callingham , , , K. S. Dwarakanath , T. M. O. Franzen ,B.-Q. For , B. Gaensler , , , P. Hancock , , L. Hindson , N. Hurley-Walker , C. A. Jackson , ,M. Johnston-Hollitt , A. D. Kapi´nska , , B. McKinley , , J. Morgan , A. R. Offringa , P. Procopio , ,L. Staveley-Smith , , C. Wu , Q. Zheng , C. M. Trott, , G. Bernardi , , , J. D. Bowman , F. Briggs ,R. J. Cappallo , B. E. Corey , A. A. Deshpande , D. Emrich , R. Goeke , L. J. Greenhill , B. J. Hazelton ,D. L. Kaplan , J. C. Kasper , , E. Kratzenberg , C. J. Lonsdale , M. J. Lynch , S. R. McWhirter ,D. A. Mitchell , , M. F. Morales , E. Morgan , D. Oberoi , S. M. Ord , , T. Prabu , A. E. E. Rogers ,A. Roshi , N. Udaya Shankar , K. S. Srivani , R. Subrahmanyan , , S. J. Tingay , , M. Waterson ,R. L. Webster , , A. R. Whitney , A. Williams , C. L. Williams International Centre for Radio Astronomy Research (ICRAR), Curtin University, Bentley, WA 6102, Australia ARC Centre of Excellence for All-Sky Astrophysics (CAASTRO) Sydney Institute for Astronomy (SIfA), School of Physics, The University of Sydney, NSW 2006, Australia CSIRO Astronomy and Space Science (CASS), Marsfield, NSW 2122, Australia Raman Research Institute, Bangalore 560080, India International Centre for Radio Astronomy Research (ICRAR), University of Western Australia, Crawley, WA 6009, Australia Dunlap Institute for Astronomy & Astrophysics, University of Toronto, 50 St George St, Toronto, ON, M5S 3H4, Canada School of Chemical & Physical Sciences, Victoria University of Wellington, Wellington 6140, New Zealand School of Physics, The University of Melbourne, Parkville, VIC 3010, Australia Netherlands Institute for Radio Astronomy (ASTRON), PO Box 2, 7990 AA Dwingeloo, The Netherlands Square Kilometre Array South Africa (SKA SA), 3rd Floor, The Park, Park Road, Pinelands, 7405, South Africa Department of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown, 6140, South Africa Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia MIT Haystack Observatory, Westford, MA 01886, USA Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Department of Physics, University of Washington, Seattle, WA 98195, USA Department of Physics, University of Wisconsin–Milwaukee, Milwaukee, WI 53201, USA Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI, USA National Centre for Radio Astrophysics, Tata Institute for Fundamental Research, Pune 411007, India National Radio Astronomy Observatory, Green Bank, WV, USA
Abstract
GLEAM, the GaLactic and Extragalactic All-sky MWA survey, is a survey of the entire radio sky southof declination +25 ◦ at frequencies between 72 and 231 MHz, made with the Murchison Widefield Array(MWA) using a drift scan method that makes efficient use of the MWA’s very large field-of-view. Wepresent the observation details, imaging strategies and theoretical sensitivity for GLEAM. The survey ranfor two years, the first year using 40 kHz frequency resolution and 0.5 s time resolution; the second year using10 kHz frequency resolution and 2 s time resolution. The resulting image resolution and sensitivity dependson observing frequency, sky pointing and image weighting scheme. At 154 MHz the image resolution isapproximately 2 . × . / cos( δ + 26 . ◦ ) arcmin with sensitivity to structures up to ∼ ◦ in angular size.We provide tables to calculate the expected thermal noise for GLEAM mosaics depending on pointing andfrequency and discuss limitations to achieving theoretical noise in Stokes I images. We discuss challenges,and their solutions, that arise for GLEAM including ionospheric effects on source positions and linearlypolarised emission, and the instrumental polarisation effects inherent to the MWA’s primary beam. Keywords: surveys – Galaxy: general – radio continuum: general – radio lines: general a r X i v : . [ a s t r o - ph . I M ] M a y Wayth et al.
Low-frequency radio astronomy is once again on thescientific frontier, driven in large part by the goal ofmeasuring the radio emission from high-redshift neu-tral hydrogen during the Epoch of Reionisation (EoR),predicted to lie in the 50 −
200 MHz part of the radiospectrum (e.g. Furlanetto et al. 2006; Morales & Wyithe2010). In addition to established telescopes working atthese frequencies, such as the Giant Metrewave RadioTelescope (‘GMRT’, Swarup et al. 1991), the Mauri-tius Radio Telescope (Golap et al. 1998) and the Jan-sky Very Large Array (‘JVLA’, Clarke et al. 2015), sev-eral new telescopes are now operating in this frequencyrange including the Low Frequency Array (‘LOFAR’,van Haarlem et al. 2013), the Precision Array for Prob-ing the Epoch of Reionization (‘PAPER’, Parsons et al.2010), the Long Wavelength Array (‘LWA’, Elling-son et al. 2013), and the Murchison Widefield Array(‘MWA’, Lonsdale et al. 2009; Tingay et al. 2013). All ofthese instruments have performed, or are undertaking,large-area sky surveys (Cohen et al. 2007; Heald et al.2015; Lane et al. 2014) . The survey properties, includ-ing limiting flux density, resolution, surface brightnesssensitivity and sky coverage vary considerably betweeninstruments and survey programs.We present the details of the GaLactic ExtragalacticAll-sky MWA (GLEAM) survey, which is surveying thesky south of declination +25 ◦ with the MWA. GLEAMwas conceived to provide data for many science goalsincluding studies of: radio galaxies and active galacticnucleii; galaxy clusters; the Magellanic clouds; diffusegalactic emission and the Galactic magnetic field; galac-tic and extragalactic spectral lines; supernova remnants;Galactic Hii regions; pulsars and pulsar wind nebulae;and cosmic rays. GLEAM is intended to leave a signifi-cant legacy dataset from the MWA that can be utilisedfor its capabilities in the time, frequency, polarisationand field-of-view domains. GLEAM’s two year observ-ing program began in August 2013.The myriad MWA science opportunities enabled bylarge sky area surveys, including in the time domain,are detailed in Bowman et al. (2013).In § § § § Also: http://tgss.ncra.tifr.res.in
An advantage for the survey speed of low-frequency ra-dio telescopes is a large field-of-view. For the MWA,whose main antenna ‘tiles’ have an effective width ofapproximately 4 metres, this is especially true. In ad-dition, the 128 tiles of the MWA provide excellentsnapshot u, v -coverage, which is essential for both theimaging and calibration fidelity of such wide-field data.The combination of huge instantaneous field-of-viewand excellent snapshot u, v -coverage makes the MWAwell suited to surveying large volumes of the universein a short time. As has been previously demonstrated(Bernardi et al. 2013; Hurley-Walker et al. 2014), merid-ian drift scans are an effective surveying techniquefor the MWA and we re-used the basic strategy forGLEAM.The sky was divided into seven strips in declinationand five frequency ranges, as summarised in Table 1.The declinations were chosen such that the peak in theprimary beam response for a given setting correspondsapproximately to the half power point of the neighbour-ing beam along the meridian at 150 MHz, which alsomakes the beams overlap at the half power points at216 MHz. Examples of the primary beam patterns forthe various frequencies and declinations are shown inFigure 1.The instantaneous frequency coverage of the MWAis 30.72 MHz, so the frequency range between 72 and231 MHz was divided into five bands that providenear contiguous coverage but avoid the band around137 MHz that is contaminated by satellite interference.The central frequencies of the bands are listed in Ta-ble 1.While GLEAM is designed to cover the entire skysouth of δ +25 ◦ , some sky north of δ +25 ◦ will be ac-cessible with reduced sensitivity in the mid and lowerparts of the GLEAM frequency range due to the largerprimary beam size at those frequencies.The region around the south celestial pole (SCP) isa special case for GLEAM due to its low elevation fromthe MWA site. At the lower frequencies, the SCP re-gion is included in the − ◦ declination observations.For the two highest frequency ranges, extra observa-tions pointed at the SCP are used to cover this region.GLEAM observing was executed as a series of week-long campaigns where a single declination setting wasobserved in a night, covering a strip between approxi-mately 8 and 10 hours in length, depending on the timeof year. Radio emission from the Sun can overwhelmother radio sources at MWA frequencies, so observa-tions were only performed at night. Within a night, theobserving was broken into a series of 120 s scans foreach frequency, cycling through all five frequency set-tings over 10 minutes. Within a scan, typically 108 s ofusable data were collected. Every two hours throughout PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey − . ◦ , − . ◦ and − ◦ ) on timescales of seconds, hours andmonths using data centred at 154 MHz only. The mo-tivations for this survey are as follows: (i) To obtaintemporal data on an extremely large and robust sampleof low-frequency sources to explore and quantify bothintrinsic and extrinsic variability; (ii) To search and findnew classes of low-frequency radio transients that pre-viously remained undetected and obscured from multi-wavelength discovery; (iii) To place rigorous limits onthe occurrence of both transients and variables prior tothe SKA era. Here we briefly review the main features of the MWAand refer the reader to Tingay et al. (2013) for details.The MWA’s 128 antenna tiles are distributed over anarea approximately 2.5 km in diameter. The array hasa central core of approximately 40% of the tiles withthe remainder distributed for u, v -coverage. An exam-ple of u, v -coverage for a 154 MHz zenith pointed snap-shot is shown in Figure 2. The excellent instantaneous u, v -coverage of the MWA is advantageous for both cal-ibration and imaging. As discussed in Ord et al. (2010), MWA snapshotimages follow the well-defined slant orthographic pro-jection which is supported by most current astronomysoftware. The simplest approach for mosaicing GLEAMimages is image-based weighted addition, after regrid-ding to a common coordinate frame. This approach wasused in Hurley-Walker et al. (2014) and we adopt thesame approach here to calculate sensitivity (see § Cot-ter pipeline (Offringa et al. 2015) which flags radio-frequency interference (RFI) and optionally reformatsthe data into standard radio astronomy data formats.Fig 3 shows example snapshot images from GLEAMat high Galactic latitude. Images containing almost theentire main lobe of the primary beam can be generatedwith standard ( ∼ ×
3) oversampling of the synthesisedbeam in image space and 4096 × . × .
24 arcmin and the pixelsare 34 arcsec across at the image centre. In this example,the giant radio galaxy Fornax A can be seen in thelower left of the image, however the vast majority ofextragalactic radio sources are unresolved in GLEAM.Figure 4 shows example snapshot images fromGLEAM on the Galactic plane region containing theGum Nebula from the declination − ◦ drift scan.The left image is the restored image just using MWAdata and shows a negative bowl on the largest scalesaround the region due to missing zero-spacing flux. Theright image shows the same region with the additionof zero-spacing information using Miriad ’s ‘immerge’task (Sault et al. 1995) using a scaled, regridded and pri-mary beam weighted image from 408 MHz data Haslamet al. (1982). The 408 MHz data were scaled by a con-stant spectral index of -0.6, however since Figure 4 isonly meant for illustrative purposes we allowed ‘im-merge’ to adjust the flux scales of the datasets in anoverlap region for baseline lengths between 10 and 45meters, hence the overall flux scale is only approximate.These images demonstrate the MWA’s excellent surfacebrightness sensitivity.
The GLEAM observation strategy includes a calibra-tion scan on a bright compact source every two hours.The MWA is phase stable over many hours and phasecalibration solutions are readily transferred between
PASA (2015)doi:10.1017/pas.2015.xxx
Wayth et al. : : . : : . : : . : : . - : : . - : : . - : : . (a) 88 MHz : : . : : . : : . : : . - : : . - : : . - : : . (b) 118 MHz : : . : : . : : . : : . - : : . - : : . - : : . (c) 154 MHz : : . : : . : : . : : . - : : . - : : . - : : . (d) 185 MHz : : . : : . : : . : : . - : : . - : : . - : : . (e) 216 MHz : : . : : . : : . : : . - : : . - : : . - : : . (f) Example sky Figure 1.: Examples of the MWA’s primary beams used in the survey overlaid on the sky at LST 18 h as seen fromthe MWA site. The contours show the half power levels relative to the peak in the beam for that declination wherethe solid (red) lines are for the ‘X’ (east-west oriented) dipoles and the dashed black lines are for the ‘Y’ (north-south oriented) dipoles. The additional smaller ellipses at the extreme north and south for the higher frequencyimages are due to the chromatic grating lobes of the MWA primary beam exceeding the half power level of themain lobe.Figure 2.: MWA monochromatic (left) and 30 MHz multi-frequency synthesis (right) u, v -coverage for a 2 minutezenith pointed snapshot centred on 154 MHz.
PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey −
1. The left panelshows the full 4096 × . × .
24 arcmin.pointings, after which self-calibration can reduce resid-ual phase and amplitude calibration errors. Calibrationsources used for GLEAM include 3C444, Pictor A, Tau-rus A, Hydra A, Virgo A and Hercules A, most of whichhave well determined flux densities over the GLEAMfrequency range. These scans are useful for diagnosticpurposes and are used to apply an initial amplitude andphase calibration solution onto the survey data.Since the absolute response of the MWA’s primarybeam changes depending on pointing, the flux scale ofsnapshots made via calibration transfer must be scaledby the ratio of the absolute primary beam response onthe target field to the absolute primary beam responseon the calibration field. This procedure was used to setthe flux scale of the example snapshot images used inthis paper but is limited by how accurately the modelprimary beam represents the true primary beam.The full survey, however, has the advantage thatmany thousands of sources sample the primary beamresponse as they drift through it during the night andthat the primary beam response is constant through-out the night. This provides a mechanism to build anaccurate empirical model of the primary beam and si-multaneously bootstrap the absolute flux scale usinga large sample of sources. The overlapping declinationranges of GLEAM also provide a way to ensure boththe primary beam correction and overall flux scale isconsistent over the entire sky.Some complications do arise in processing GLEAMsnapshots into mosaics, in particular: effects of the iono- sphere; strong sources in the primary beam sidelobes;and instrumental polarisation.Concerning the ionosphere, the MWA is located atthe Murchison Radio-astronomy Observatory (MRO),the location of which was chosen in part due toits favourable ionospheric characteristics in the mid-latitude southern hemisphere. For GLEAM purposes,the ionosphere over the MRO is typically stable (Herneet al. 2014) with slowly varying changes in TotalElectron Content (TEC) causing arcmin-scale shiftsin source positions over timescales of hours (Hurley-Walker et al. 2014; Arora et al. 2015), which is of orderthe size of the MWA synthesised beam. Under typicalconditions these shifts can be described as a single bulkposition offset for all sources in the field, an effect whichcan be corrected for in an image simply by adjusting thereference coordinates in the image metadata. Unusualionospheric, tropospheric, and solar wind conditions dooccasionally occur and are the subject of specific de-tailed studies (Loi et al. 2015). Nights that showed detri-mental ionospheric behaviour were re-observed.Powerful radio sources (Cygnus A, Centaurus A,Virgo A, Taurus A etc) in the MWA’s sidelobes cancause artifacts in multi-frequency synthesis images thatcannot be deconvolved. These artifacts are due to chro-matic effects and the nature of the MWA’s primarybeams where, after calibration of the main lobe of thebeam, differences between antenna tiles manifest them-selves as differences in the sidelobes of the primary PASA (2015)doi:10.1017/pas.2015.xxx
Wayth et al.
Figure 4.: An example of the Gum Nebula region of the Galactic plane including the Vela and Puppis A supernovaremnants from a 2 minute snapshot in the declination − ◦ drift scan centred on 154 MHz. Images were made withfull bandwidth synthesis over 30.72 MHz and robust = 0 . Miriad ’s‘immerge’ task to include zero-spacing information based on 408 MHz data (Haslam et al. 1982). The beam sizein these images is 4 . × .
97 arcmin. The colour bar has been omitted because the absolute flux scale is not yetcorrect, but the two images have the same intensity scaling.beam. These bright sources can be modelled and sub-tracted, in principle, via advanced interferometric tech-niques such as ‘peeling’ and ‘A-projection’ (van der Tolet al. 2007; Mitchell et al. 2008; Bhatnagar et al. 2008;Tasse et al. 2013), but are a problem for conventionaldeconvolution where all primary beams are assumed tobe identical. For GLEAM, such sources are a problemin a fraction of data ( ∼ Since the MWA’s antenna tiles are fixed on the ground,the MWA’s primary beam is subject to many signifi-cant instrumental polarisation effects. Full polarisationdata products in instrumental coordinates (XX,YY,XYand YX) are stored by default from the MWA correla-tor (Ord et al. 2015). The two main issues for polarisa-tion are instrumental cross polarisation, due mostly togeometric effects, and a difference in the magnitude ofthe co-polarisation (XX and YY) response within a tile.The cross polarisation is an inevitable projection effectwhich causes an unpolarised source to generate corre-lated signal in the cross-polarisation correlator outputs(XY and YX) independent of any electronic leakage.The difference in co-polar response (XX and YY) isexpected partly due to simple geometric effects (i.e.a dipole’s effective length shortens as a source moves closer to its long axis) and array mutual coupling ef-fects. Both of these effects are considered in the tilemodel detailed in Sutinjo et al. (2015), and this modelhas been adopted as the standard for all MWA dataprocessing.Processing with appropriate calibration and imagingtechniques (e.g. Mitchell et al. 2008; Offringa et al.2014), to account for direction-dependent and time-dependent effects, allows both linear (Stokes Q, U) andcircular polarisation (Stokes V) images to be produced.As the polarised source counts are significantly lowerthan in total intensity (Stokes I), linear and circularpolarisation images are in principle far less affected bysource confusion and can achieve sensitivity levels thatapproach thermal noise.Circular polarisation can easily be processed in a sim-ilar manner to that used for total intensity (Stokes I)imaging, that is, by treating the entire frequency bandin a continuum-like mode. However, care must be takenwhen imaging the two linear polarisation (Stokes Q andU) as even small degrees of Faraday rotation can sig-nificantly rotate the polarisation angle of the radiationacross the observing bandwidth, resulting in significantbandwidth depolarisation. To reduce the effect of band-width depolarisation it is necessary to image Q and U ina spectral-like mode using the fine (10 or 40 kHz) chan-nels available in the GLEAM data. Rotation measure
PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey φ ), aswas previously demonstrated by Bernardi et al. (2013).Figure 5 presents an example polarised source,PMN J0636-2041, detected with early GLEAM data.The total intensity image was processed usingcontinuum-mode imaging and shows a source with anextended morphology. The linear polarisations wereprocessed using spectral mode imaging at 40 kHz spec-tral resolution and RM synthesis. The polarised in-tensity images, selected from the resulting RM cube,show that the northern and southern componentsof this source exhibit peaks at two different Fara-day depths ( φ = 34 . ± . − and φ = 48 . ± .
05 rad m − respectively.) These are both consistentwith VLA observations of this source at 1.4 GHz (Tayloret al. 2009).The resolution ( δφ ), maximum scale size sensitivity(max. scale) and Faraday depth range ( (cid:107) φ max (cid:107) ) avail-able when using the RM synthesis technique is a func-tion of the channel width, the bandwidth and the high-est frequency channel available (Brentjens & de Bruyn2005). This has been summarised in Table 2 for each ofthe GLEAM observing bands. Note that maximum scalesize is always smaller than the resolution in φ space. Es-sentially, this means that the MWA cannot resolve Fara-day thick clouds in φ space in any single band. Wheresensitivity to wider structures in Faraday space is re-quired, lower frequency bands can be combined withthe upper frequency band. In this instance, the maxi-mum scale size is set by the upper band (1.9 rad m − )but the resolution is increased by the separation of thebands.While high precision is achievable in Faraday space itshould be noted that the true Faraday depth measuredwill be affected by the ionosphere. The magnitude of theionospheric degradation can be reduced by observing atnight and at zenith. However, applications that requirehigh-accuracy measurements of Faraday depth will needto correct for the ionospheric component. Observationswith the 32-tile commissioning array confirmed thatcodes that predict the ionospheric Faraday rotation, e.g.ionFR (Sotomayor-Beltran et al. 2013) and ALBUS ,are consistent with the observed effect on linearly po-larised sources. During the course of a GLEAM obser-vation, the ionospheric component of the Faraday ro-tation does not vary significantly; typical variations areof order ∼ . − . However, the overall ionosphericFaraday rotation component can vary significantly fromepoch to epoch, often by several rad m − , and shouldbe corrected for.All polarisation observations are affected by somelevel of polarisation leakage from one Stokes param- https://github.com/twillis449/ALBUS_ionosphere Table 2: Polarisation parameters for GLEAM observingbands with 40 kHz frequency resolution.GLEAM Band δφ max. scale (cid:107) φ max (cid:107) (MHz) (rad m − ) (rad m − ) (rad m − )72 . − .
04 0.40 0.37 91.1103 . − .
76 1.0 0.63 263.7138 . − .
60 2.3 1.0 645.6169 . − .
32 3.9 1.4 1175.6200 . − .
04 6.2 1.9 1937.0eter to another. For dipole instruments such as theMWA, polarisation leakage is a frequency-dependentand position-dependent effect resulting from errors inthe primary beam model used for calibration. The effectresults in a proportion of the Stokes I signal “leaking”into Stokes, Q, U and V. In Faraday space this resultsin an increased flux density at φ = 0 rad m − . The mag-nitude of leakage increases with frequency and with an-gular distance from zenith. In the 139 −
170 MHz band,the leakage is of order 1 −
2% within 10 ◦ of zenith butcan increase to ∼
5% at the survey extremities (Sutinjoet al. 2015).The GLEAM observations provide an outstandingdata set for exploring diffuse polarised emission fromthe Milky Way. Even on a per-snapshot basis, thedensely sampled core of the full 128-tile MWA arrayhas excellent sensitivity to large-scale structures thatmay be expected from diffuse galactic polarised emis-sion. Bernardi et al. (2013) observed such emission withthe 32-tile MWA prototype and found the total polari-sation surface brightness peaking at ∼
200 mJy beam − .By employing a natural weighting scheme to improvesensitivity to large-scale structures, the MWA array canimage such features with a signal to noise ratio of ∼ The third data release from the Australia TelescopeLarge Area Survey (ATLAS DR3; Franzen et al.2015) covers an area of 3.6 deg coincident with theChandra Deep Field South (CDFS; α = 03 h m . s ; δ = − o (cid:48) . (cid:48)(cid:48) J2000) to a typical sensitivity of14 µ Jy beam − at 1.4 GHz. We have compared the AT-LAS image of the CDFS with the declination − ◦ GLEAM mosaic at 147 −
154 MHz, which is closelymatched in declination to the CDFS. Given the muchhigher sensitivity of ATLAS, we expect all GLEAM
PASA (2015)doi:10.1017/pas.2015.xxx
Wayth et al. D e c ( J ) Total Intensity φ =34.5 rad m − φ =48.5 rad m − Figure 5.: Total intensity map of PMN J0636-2041 and the associated polarised intensity maps of the source taken attwo different Faraday depths ( φ =34.5 rad m − and 48.5 rad m − ). All images were processed using uniform visibilityweighting in the 138 . − .
60 MHz band. Units are Jy beam − for total intensity and Jy beam − RMSF − forpolarised intensity.sources to be detected in ATLAS. We compared sourcepositions in the two images but not source flux densitiessince the absolute flux density scale for GLEAM is onlyapproximately correct.The resolution of the GLEAM mosaic is 130 arcsecand that of the ATLAS image is 16.3 by 6.8 arcsec.We convolved the ATLAS image to the same resolutionas the GLEAM mosaic. We then ran the source finder Aegean (Hancock et al. 2012) on both images using a5 σ detection threshold; 133 sources were detected in theATLAS image and 36 in the corresponding region of theGLEAM image. Figure 6 shows the GLEAM mosaic ofthe CDFS, overlayed with the positions of the ATLASand GLEAM sources.All 36 GLEAM sources have a counterpart in AT-LAS within 90 arcsec. While the largest offset betweenATLAS and GLEAM positions is 90 arcsec, the sec-ond largest offset is only 31 arcsec; the median offsetis 9 arcsec. Examination of the original ATLAS imageshows that the largest offset is caused by two sources be-ing blended in the low-resolution ATLAS and GLEAMimages: the ATLAS position lies closer to the westernsource because it is brighter at 1.4 GHz and the GLEAMposition lies closer to the eastern source because it isbrighter at 150 MHz.For many of the ATLAS sources with no counter-part in GLEAM, examination of the GLEAM image shows a weak source at the ATLAS position detectedat the ∼ σ level. Since all GLEAM sources above 5 σ are detected in ATLAS, we conclude that away fromthe Galaxy and other extremely bright sources, sourcescan be reliably detected close to a 5 σ detection limit inour GLEAM mosaics. The MWA is designed for its system temperature to besky noise dominated over the frequency ranges coveredby GLEAM (Tingay et al. 2013). As such, the expectedthermal noise in a snapshot image depends on the regionof sky being observed and, to a lesser extent, the beampointing used during the observation.Using image-based linear mosaicing, the thermalnoise in the final mosaic is reduced by the weightedcontribution of images contributing to the final mosaic.In the ideal case, the noise is reduced as √ N for N images contributing to a given region of the mosaic. Ingeneral, the images contributing to the mosaic are vari-ance weighted by the primary beam (Holdaway 1999).For GLEAM, this means that the contribution to thefinal mosaic from a particular region of sky varies as itdrifts through the primary beam.We calculated the expected thermal noise propertiesof GLEAM mosaics based on noise-only simulations PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey −
154 MHz declination − ◦ XX mosaic coincident with the CDFS. The greyscale islinear and runs from −
20 to +50 mJy (the overall flux scale is only approximately correct). GLEAM detectionsabove 5 σ are shown as red crosses of the same shapes as their fitted Gaussian parameters. Detections above 5 σ inthe 1.4 GHz ATLAS image of the field, convolved to the same resolution as the GLEAM image, are shown as blueellipses of the same shapes as their fitted Gaussian parameters. The solid black contour indicates the boundary ofthe ATLAS CDFS mosaic.that match the GLEAM observing strategy. We useda single fiducial system temperature ( T f = 200 K) fortwo image weighting scenarios, as parametrised by the‘robust’ parameter. More naturally weighted snapshots(robust=1), which are likely to be used for imaging dif-fuse emission, have better theoretical sensitivity thanmore uniformly weighted ones (robust= − Miriad ’s ‘uvgen’ task us-ing T f as the system temperature and matching the du-ration, duty cycle, bandwidth (including the reductionin usable bandwidth due to commonly flagged chan-nels) and frequency setup of GLEAM. Each 2 minutesnapshot is imaged with full bandwidth synthesis andweighted according to the primary beam model (Sutinjoet al. 2015) for the frequency and declination and ac-cumulated into the mosaic using the ‘regrid’ task. Like- wise, the primary beam ‘weights’ are accumulated intoa weight mosaic for each snapshot. After accumulatingall snapshots, the mosaic image is divided by the accu-mulated weight image.The noise in the mosaic was measured in approxi-mately 5 × T f is not ap-plicable for most GLEAM frequencies and pointings,hence the values in Table 3 must be scaled by the ap-propriate system temperature for region of sky and fre-quency.To enable this scaling, we calculated the expectedbeam-weighted average sky temperature over the rangeof frequencies, pointings and LSTs relevant to GLEAM(Figure 7). The correct theoretical thermal noise inan image can then be derived by calculating thecorrect T sys for that image by scaling by the ratio PASA (2015)doi:10.1017/pas.2015.xxx Wayth et al. of the average sky temperature ( T true ) for that fre-quency/LST/pointing, plus receiver noise ( T R ≈
50 K),to the fiducial value, i.e. by ( T true + T R ) /T f . For exam-ple, at 154 MHz the ‘cold’ extragalactic sky will gen-erate a system temperature of approximately 300 K(Figure 7) hence the theoretical thermal noise for auniformly weighted mosaic of that region of the skywill be (300 / × . . − (nearthe zenith). The MWA’s synthesised beam is large enough that clas-sical confusion should become a limiting factor in widebandwidth mosaics or long duration synthesis images,compared to thermal noise. It is difficult to preciselyestimate the classical confusion because the differentialsource counts at low frequencies between 1 and 100 mJyare currently not well known. To estimate the classicalconfusion we model the differential source counts in thisflux density range as n ( S ) = kS γ . Based on Wieringa(1991), who measured the 327 MHz counts down to ∼ k = 4000 and γ = − . − . k can be scaled to frequency ν MHzby the factor ( ν/ − . γ ) . Using this differentialsource count model scaled to 154 MHz and followingCondon (1974) using a signal-to-noise threshold of 6,the 1 σ classical confusion for an image with synthe-sised beam size 2.4 arcmin (i.e. a uniformly weightedimage made at 154 MHz) is approximately 2 mJy. Thereis substantial uncertainty in this estimate because theoverall scaling is uncertain at the ∼
25% level and be-cause the slope of the source count function is known tochange at mJy flux densities at higher frequencies (e.g.Windhorst et al. 1990). For example, a small changein γ from -1.6 to -1.8 around mJy flux densities willtriple the estimated classical confusion. GLEAM andother contemporary low-frequency surveys will make asubstantial contribution to better understand the low-frequency source counts.Full synthesis 2 minute Stokes I snapshot images havea theoretical thermal noise of 5 mJy for T sys = 200 Kusing robust −
1. Despite this, such images typicallycontain ∼ −
30 mJy background noise and the back-ground between instrumental polarisation (XX and YY)images tends to be correlated. The reason for the ex-cess background is still under investigation, but is mostlikely due to a combination of classical and sidelobe con-fusion (sidelobe confusion is the extra background vari-ance due to the combined sidelobes of all the faint un-subtracted sources within the primary beam). Sidelobeconfusion is more pronounced for the MWA than for ra-dio telescopes with larger antennas due to the MWA’shuge field-of-view. A detailed analysis of the impact of sidelobe confusion to MWA snapshot and long durationsynthesis images is underway (Wayth et al., in prep).For the time being the excess background, which is onlyfound in Stokes I, is treated simply as excess noise whichintegrates down with time and bandwidth.
We plan to process GLEAM data and release dataproducts in stages. The expected data products fromGLEAM include: an extragalactic Stokes I compactsource catalogue; a full polarisation compact sourcecatalogue; maps of diffuse extragalactic polarised fore-ground; and maps of the diffuse emission (both Stokes Iand polarised) in the Galactic plane. Most sources willhave at least 5 independent continuum flux density mea-surements made over GLEAM’s frequency range andfurther subdivision of the frequency range is possible.
GLEAM covers 7.5 sr of extragalactic ( | b | >
10) sky. As-suming a 6 σ source detection threshold of 120 mJy inthe 180 MHz frequency band, we again model the dif-ferential source counts, n ( S ), between 0.1 and 1.0 Jyas a power-law based on the general properties ofsource counts at similar frequencies (e.g. Wieringa 1991;Williams et al. 2013). Using n ( S ) = 3600 S − . and adetection threshold of 120 mJy, we estimate GLEAMwill detect approximately 19,500 sources sr − or 150,000sources in the extragalactic sky visible to the MWA.Bright residual structure extending far from the Galac-tic plane and regions around bright compact sourcesmay have higher than typical background noise, whichwill affect source detection locally. By comparison,the MWA Commissioning Survey (‘MWACS’, Hurley-Walker et al. 2014) found 7,540 sources sr − with a de-tection threshold of 200 mJy or greater, depending onthe local noise properties of the mosaic. There have been relatively few sky surveys in the south-ern hemisphere compared to the northern, especially atlow frequencies. Surveys below 1 GHz that cover a sub-stantial fraction of the southern hemisphere are listedin Table 4. We also note the Culgoora array observedselected sources at 80 and 160 MHz (Slee 1995), but didnot perform a blind survey.Table 4 shows that GLEAM is comparable in angularresolution and sky coverage to the all extragalactic sky The normalisation and slope of the model for n ( S ) here differsfrom § he GLEAM survey B e a m - w e i g h t e d s k y t e m p e r a t u r e ( K ) Local sidereal time (hours)dec -26.7dec -13dec +1.6dec +13.8dec -40dec -55dec -72 (a) 88 MHz B e a m - w e i g h t e d s k y t e m p e r a t u r e ( K ) Local sidereal time (hours)dec -26.7dec -13dec +1.6dec +13.8dec -40dec -55dec -72 (b) 118 MHz B e a m - w e i g h t e d s k y t e m p e r a t u r e ( K ) Local sidereal time (hours)dec -26.7dec -13dec +1.6dec +13.8dec -40dec -55dec -72 (c) 154 MHz B e a m - w e i g h t e d s k y t e m p e r a t u r e ( K ) Local sidereal time (hours)dec -26.7dec -13dec +1.6dec +13.8dec -40dec -55dec -72 (d) 185 MHz B e a m - w e i g h t e d s k y t e m p e r a t u r e ( K ) Local sidereal time (hours)dec -26.7dec -13dec +1.6dec +13.8dec -40dec -55dec -72 (e) 216 MHz
Figure 7.: Beam-weighted sky average temperature for the seven declinations used by GLEAM depending on LST.Panels show the five central frequencies used by GLEAM: 88, 118, 154, 185 and 216 MHz.Molonglo Reference Catalogue (MRC), but will be anorder of magnitude more sensitive with full polarisationand sensitivity to very large structures. GLEAM willcomplement the TGSS and VLSS surveys with similarsensitivity, but slightly poorer resolution, filling in theentire sky south of δ = +25. GLEAM will also form anexcellent complementary dataset to the LOFAR MSSS(Heald et al. 2015), which will have similar sensitiv-ity and angular resolution in the northern hemisphere. GLEAM will be unparalleled in its ability to imagelarge, low surface brightness structures, both Galacticand extragalactic, in full polarisation. The strengths ofMWA’s surface brightness sensitivity have already beenmade evident by the serendipitous discovery of a relicradio galaxy in early MWA data (Hurley-Walker et al.2015). PASA (2015)doi:10.1017/pas.2015.xxx Wayth et al.
Table 3: GLEAM expected thermal noise sensitivity (mJy beam − ) from a 2 hour mosaic, assuming fiducial systemtemperature T f = 200 K. Columns are the frequency in MHz, rows are the declination in degrees.88 118 154 185 216 −
72 3.2 3.0 2.3 3.8 5.1 −
55 2.1 2.1 1.9 2.3 4.3 − . − . −
13 1.8 1.9 2.1 2.3 3.4+1 . . (a) Robust -1
88 118 154 185 216 −
72 1.5 1.4 1.1 1.8 2.4 −
55 1.0 1.0 0.9 1.1 2.1 − . − . −
13 0.9 1.0 1.1 1.1 1.6+1 . . (b) Robust +1 Table 4: Summary of radio surveys below 1 GHz substantially covering the southern hemisphereFreq Resolution Max size Stokes ISurvey (MHz) (arcmin) (arcmin) Coverage cutoff (Jy)MRC a
408 2 . × . δ + 35 . ◦ ) ∼
30 +18 . > δ > − | b | > b
843 0 . × .
75 cosec | δ | δ < −
30 0.006 - 0.01VLSS(r) c
74 1.25 ∼ * δ > − ∼ . d
150 0.33 δ > − ∼ . e
145 26 ∼ δ <
10 10MSH f
86 50 n/a δ <
10 20GLEAM 72-231 2 . × . δ + 26 . ◦ ) † ∼ δ < +25 ∼ . † * Assuming 150 λ is the shortest effective baseline for the VLA B array at 74 MHz. † At 154 MHz. a Large et al. (1981). b Bock et al. (1999); Mauch et al. (2003). See also MGPS-2 (Murphy et al. 2007) for sources with | b | < c Cohen et al. (2007); Lane et al. (2014). d http://tgss.ncra.tifr.res.in . e Jacobs et al. (2011). f Mills et al. (1958, 1960, 1961).
We have presented the observing strategy, data pro-cessing strategy and theoretical sensitivity of the MWAGLEAM survey. GLEAM covers the entire radio skysouth of declination +25 ◦ between 72 and 231 MHz.GLEAM aims to leave a significant legacy dataset forthe MWA and GLEAM data are being used for manyGalactic, extragalactic and time domain science pro-grams. Data products will include a compact sourcecatalogue and maps of the diffuse Galactic and extra-galactic sky, both in Stokes I and in polarisation. TheStokes I compact source catalogue, in particular, willhave an order of magnitude improvement in sensitivitycompared to the MRC. Looking towards the SKA era,GLEAM will provide a foundation sky model that canbe used in preparation for SKA-low key science pro-grams. GLEAM data are unparalleled in areas where theMWA’s strengths lie, including very wide field-of-view,full polarisation, high surface brightness sensitivity atlarge angular scales and broad frequency coverage. Thebroad frequency coverage and fine frequency resolutionof GLEAM provide a large lever arm for both polarisa-tion studies using RM synthesis and to measure spectralindices.We showed example snapshot images from GLEAMand discussed practical issues associated with form-ing mosaics from GLEAM including calibration, iono-spheric and primary beam polarisation effects, as well asthe effect of strong sources in the primary beam side-lobes. We discussed how confusion impacts the back-ground noise level in Stokes I images, which is a conse-quence the MWA’s very large field-of-view.Finally, we calculated the theoretical thermal noisesensitivity for GLEAM mosaics and showed how the PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey
This scientific work makes use of the Murchison Radio-astronomy Observatory, operated by CSIRO. We acknowl-edge the Wajarri Yamatji people as the traditional ownersof the Observatory site. Support for the MWA comes fromthe U.S. National Science Foundation (grants AST-0457585,PHY-0835713, CAREER-0847753, and AST-0908884), theAustralian Research Council (LIEF grants LE0775621 andLE0882938), the U.S. Air Force Office of Scientific Research(grant FA9550-0510247), and the Centre for All-sky Astro-physics (an Australian Research Council Centre of Excel-lence funded by grant CE110001020). Support is also pro-vided by the Smithsonian Astrophysical Observatory, theMIT School of Science, the Raman Research Institute, theAustralian National University, and the Victoria Universityof Wellington (via grant MED-E1799 from the New ZealandMinistry of Economic Development and an IBM Shared Uni-versity Research Grant). The Australian Federal governmentprovides additional support via the Commonwealth Scien-tific and Industrial Research Organisation (CSIRO), Na-tional Collaborative Research Infrastructure Strategy, Ed-ucation Investment Fund, and the Australia India StrategicResearch Fund, and Astronomy Australia Limited, undercontract to Curtin University. This work was supported byresources provided by the Pawsey Supercomputing Centrewith funding from the Australian Government and the Gov-ernment of Western Australia. We acknowledge the iVECPetabyte Data Store, the Initiative in Innovative Computingand the CUDA Center for Excellence sponsored by NVIDIAat Harvard University, and the International Centre forRadio Astronomy Research (ICRAR), a Joint Venture ofCurtin University and The University of Western Australia,funded by the Western Australian State government.
REFERENCES
Arora, B. S., Morgan, J., Ord, S. M., Tingay, S. J.,Hurley-Walker, N., Bell, M., Bernardi, G., Bhat, R.,Briggs, F., Callingham, J. R., Deshpande, A. A.,Dwarakanath, K. S., Ewall-Wice, A., Feng, L.,Franzen, T. M. O., For, B.-Q., Hancock, P., Hazel-ton, B. J., Hindson, L., Jackson, C. A., Jacobs, D.,Johnston-Hollitt, M., Kapinska, A. D., Kudryavtseva,N., Lenc, E., McKinley, B., Mitchell, D., Oberoi, D.,Offringa, A. R., Pindor, B., Procopio, P., Riding, J.,Staveley-Smith, L., Wayth, R. B., Wu, C., Zheng, Q.,Bowman, J. D., Cappallo, R. J., Corey, B. E., Emrich,D., Goeke, R., Greenhill, L. J., Kaplan, D. L., Kasper,J. C., Kratzenberg, E., Lonsdale, C. J., Lynch, M. J.,McWhirter, S. R., Morales, M. F., Morgan, E., Prabu,T., Rogers, A. E. E., Roshi, A., Shankar, N. U., Sri-vani, K. S., Subrahmanyan, R., Waterson, M., Web-ster, R. L., Whitney, A. R., Williams, A., & Williams, C. L. 2015, PASA, submittedBernardi, G., Greenhill, L. J., Mitchell, D. A., Ord,S. M., Hazelton, B. J., Gaensler, B. M., de Oliveira-Costa, A., Morales, M. F., Udaya Shankar, N., Sub-rahmanyan, R., Wayth, R. B., Lenc, E., Williams,C. L., Arcus, W., Arora, B. S., Barnes, D. G., Bow-man, J. D., Briggs, F. H., Bunton, J. D., Cappallo,R. J., Corey, B. E., Deshpande, A., deSouza, L.,Emrich, D., Goeke, R., Herne, D., Hewitt, J. N.,Johnston-Hollitt, M., Kaplan, D., Kasper, J. C., Kin-caid, B. B., Koenig, R., Kratzenberg, E., Lonsdale,C. J., Lynch, M. J., McWhirter, S. R., Morgan, E.,Oberoi, D., Pathikulangara, J., Prabu, T., Remillard,R. A., Rogers, A. E. E., Roshi, A., Salah, J. E., Sault,R. J., Srivani, K. S., Stevens, J., Tingay, S. J., Wa-terson, M., Webster, R. L., Whitney, A. R., Williams,A., & Wyithe, J. S. B. 2013, ApJ, 771, 105Bhatnagar, S., Cornwell, T. J., Golap, K., & Uson, J. M.2008, A&A, 487, 419Bock, D. C.-J., Large, M. I., & Sadler, E. M. 1999, AJ,117, 1578Bowman, J. D., Cairns, I., Kaplan, D. L., Murphy, T.,Oberoi, D., Staveley-Smith, L., Arcus, W., Barnes,D. G., Bernardi, G., Briggs, F. H., Brown, S., Bun-ton, J. D., Burgasser, A. J., Cappallo, R. J., Chat-terjee, S., Corey, B. E., Coster, A., Deshpande, A.,deSouza, L., Emrich, D., Erickson, P., Goeke, R. F.,Gaensler, B. M., Greenhill, L. J., Harvey-Smith, L.,Hazelton, B. J., Herne, D., Hewitt, J. N., Johnston-Hollitt, M., Kasper, J. C., Kincaid, B. B., Koenig,R., Kratzenberg, E., Lonsdale, C. J., Lynch, M. J.,Matthews, L. D., McWhirter, S. R., Mitchell, D. A.,Morales, M. F., Morgan, E. H., Ord, S. M., Pathiku-langara, J., Prabu, T., Remillard, R. A., Robishaw,T., Rogers, A. E. E., Roshi, A. A., Salah, J. E., Sault,R. J., Shankar, N. U., Srivani, K. S., Stevens, J. B.,Subrahmanyan, R., Tingay, S. J., Wayth, R. B., Wa-terson, M., Webster, R. L., Whitney, A. R., Williams,A. J., Williams, C. L., & Wyithe, J. S. B. 2013, PASA,30, 31Brentjens, M. A. & de Bruyn, A. G. 2005, A&A, 441,1217Clarke, T. E., Kassim, N. E., Helmboldt, J. F., Ray,P. S., Peters, W. M., Hicks, B., Brisken, W., Perley,R. A., Owen, F. N., & Intema, H. 2015, in AmericanAstronomical Society Meeting Abstracts, Vol. 225,American Astronomical Society Meeting Abstracts,
PASA (2015)doi:10.1017/pas.2015.xxx Wayth et al.
F. K., & Weiler, K. W. 2013, IEEE Transactions onAntennas and Propagation, 61, 2540Franzen, T. M. O., Banfield, J. K., Hales, C. A., Hop-kins, A., Norris, R. P., Seymour, N., Chow, K. E.,Herzog, A., Huynh, M. T., Lenc, E., Mao, M. Y., &Middelberg, E. 2015, MNRAS, submittedFurlanetto, S. R., Oh, S. P., & Briggs, F. H. 2006, PhR,433, 181Golap, K., Shankar, N. U., Sachdev, S., Dodson, R.,& Sastry, C. V. 1998, Journal of Astrophysics andAstronomy, 19, 35Hancock, P. J., Murphy, T., Gaensler, B. M., Hopkins,A., & Curran, J. R. 2012, MNRAS, 422, 1812Haslam, C. G. T., Salter, C. J., Stoffel, H., & Wilson,W. E. 1982, A&AS, 47, 1Heald, G. H., Pizzo, R. F., Orru, E., Breton, R. P., Car-bone, D., Ferrari, C., Hardcastle, M. J., Jurusik, W.,Macario, G., Mulcahy, D., Rafferty, D., Asgekar, A.,Brentjens, M., Fallows, R. A., Frieswijk, W., Toribio,M. C., Adebahr, B., Arts, M., Bell, M. R., Bonafede,A., Bray, J., Broderick, J., Cantwell, T., Carroll, P.,Cendes, Y., Clarke, A. O., Croston, J., Daiboo, S., deGasperin, F., Gregson, J., Harwood, J., Hassall, T.,Heesen, V., Horneffer, A., van der Horst, A. J., Iaco-belli, M., Jelic, V., Jones, D., Kant, D., Martin, P.,McKean, J. P., Morabito, L. K., Nikiel-Wrocynski,B., Offringa, A., Pandey, V. N., Pandey-Pommier,M., Pietka, M., Pratley, L., Riseley, C., Rowlinson,A., Sabater, J., Scaife, A. M. M., Scheers, L. H. A.,Sendlinger, K., Shulevski, A., Sobey, C., Stewart,A. J., Stroe, A., Swinbank, J., Tasse, C., Trustedt,J., Varenius, E., van Velzen, S., Vilchez, N., vanWeeren, R. J., Wijnholds, S., Williams, W. L., deBruyn, A. G., Nijboer, R., Wise, M., Alexov, A., An-derson, J., Avruch, I. M., Beck, R., Bell, M. E., vanBemmel, I., Bentum, M. J., Bernardi, G., Best, P.,Breitling, F., Brouw, W. N., Bruggen, M., Butcher,H. R., Ciardi, B., Conway, J. E., de Geus, E., de Jong,A., de Vos, M., Deller, A., Duscha, S., Eisloffel, J.,Engels, D., Falcke, H., Fender, R., Garreett, M. A.,Greismeier, J., Gunst, A. W., Hamaker, J., Hessels,J. W. T., Hoeft, M., Hor and el, J., Holties, H. A.,Intema, H., Jackson, N. J., Jutte, E., Karastergiou,A., Klijn, W. F. A., Kondratiev, V. I., Koopmans,L. V. E., Kuniyoshi, M., Kuper, G., Law, C., vanLeeuwen, J., Loose, M., Maat, P., Markoff, S., McFad-den, R., McKay-Bukowski, D., Mevius, M., Miller-Jones, J. C. A., Morganti, R., Munk, H., Nelles,A., Noordam, J. E., Norden, M. J., Paas, H., Pola-tidis, A. G., Reich, W., Rrenting, A., Rottgering, H.,Schoenmakers, A., Schwarz, D., Sluman, J., Smirnov,O., Stappers, B. W., Steinmetz, M., Tagger, M.,Tang, Y., ter Veen, S., Thoudam, S., Vermeulen, R.,Vocks, C., Vogt, C., Wijers, R. A. M. J., Wucknitz,O., Yatawatta, S., & Zarka, P. 2015, Astronomy & Astrophysics, submittedHerne, D., Kennewell, J., Lynch, M., & Carrano, C.2014, in Australian Space Science Conference Series,Vol. 1, Proc. 13th Australian Space Science Con-ference (Sydney, Australia, 2013), ed. W. Short &I. Cairns (Sydney, Australia: National Space Societyof Australia Ltd)Holdaway, M. A. 1999, in Astronomical Society of thePacific Conference Series, Vol. 180, Synthesis Imagingin Radio Astronomy II, ed. G. B. Taylor, C. L. Carilli,& R. A. Perley, 401Hurley-Walker, N., Johnston-Hollitt, M., Ekers, R.,Hunstead, R., Sadler, E. M., Hindson, L., Hancock,P., Bernardi, G., Bowman, J. D., Briggs, F., Cap-pallo, R., Corey, B., Deshpande, A. A., Emrich, D.,Gaensler, B. M., Goeke, R., Greenhill, L., Hazel-ton, B. J., Hewitt, J., Kaplan, D. L., Kasper, J.,Kratzenberg, E., Lonsdale, C., Lynch, M., Mitchell,D., McWhirter, R., Morales, M., Morgan, E., Oberoi,D., Offringa, A., Ord, S., Prabu, T., Rogers, A.,Roshi, A., Shankar, U., Srivani, K., Subrahmanyan,R., Tingay, S., Waterson, M., Wayth, R. B., Webster,R., Whitney, A., Williams, A., & Williams, C. 2015,MNRAS, 447, 2468Hurley-Walker, N., Morgan, J., Wayth, R. B., Hancock,P. J., Bell, M. E., Bernardi, G., Bhat, R., Briggs, F.,Deshpande, A. A., Ewall-Wice, A., Feng, L., Hazel-ton, B. J., Hindson, L., Jacobs, D. C., Kaplan, D. L.,Kudryavtseva, N., Lenc, E., McKinley, B., Mitchell,D., Pindor, B., Procopio, P., Oberoi, D., Offringa,A., Ord, S., Riding, J., Bowman, J. D., Cappallo,R., Corey, B., Emrich, D., Gaensler, B. M., Goeke,R., Greenhill, L., Hewitt, J., Johnston-Hollitt, M.,Kasper, J., Kratzenberg, E., Lonsdale, C., Lynch, M.,McWhirter, R., Morales, M. F., Morgan, E., Prabu,T., Rogers, A., Roshi, A., Shankar, U., Srivani, K.,Subrahmanyan, R., Tingay, S., Waterson, M., Web-ster, R., Whitney, A., Williams, A., & Williams, C.2014, PASA, 31, 45Jacobs, D. C., Aguirre, J. E., Parsons, A. R., Pober,J. C., Bradley, R. F., Carilli, C. L., Gugliucci, N. E.,Manley, J. R., van der Merwe, C., Moore, D. F., &Parashare, C. R. 2011, ApJ, 734, L34Lane, W. M., Cotton, W. D., van Velzen, S., Clarke,T. E., Kassim, N. E., Helmboldt, J. F., Lazio,T. J. W., & Cohen, A. S. 2014, MNRAS, 440, 327Large, M. I., Mills, B. Y., Little, A. G., Crawford, D. F.,& Sutton, J. M. 1981, MNRAS, 194, 693Loi, S. T., Murphy, T., Cairns, I. H., Menk, F. W.,Waters, C. L., Erickson, P. J., Trott, C. M., Hurley-Walker, N., Morgan, J., Lenc, E., Offringa, A. R.,Bell, M. E., Ekers, R. D., Gaensler, B. M., Lons-dale, C. J., Feng, L., Hancock, P. J., Kaplan, D. L.,Bernardi, G., Bowman, J. D., Briggs, F., Cappallo,R. J., Deshpande, A. A., Greenhill, L. J., Hazel-
PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey
PASA (2015)doi:10.1017/pas.2015.xxx Wayth et al.
C. R., Benoit, E. E., Aguirre, J. E., Jacobs, D. C.,Carilli, C. L., Herne, D., Lynch, M. J., Manley, J. R.,& Werthimer, D. J. 2010, AJ, 139, 1468Sault, R. J., Teuben, P. J., & Wright, M. C. H. 1995, inAstronomical Society of the Pacific Conference Series,Vol. 77, Astronomical Data Analysis Software andSystems IV, ed. R. A. Shaw, H. E. Payne, & J. J. E.Hayes, 433Slee, O. B. 1995, Australian Journal of Physics, 48, 143Sotomayor-Beltran, C., Sobey, C., Hessels, J. W. T.,de Bruyn, G., Noutsos, A., Alexov, A., Anderson, J.,Asgekar, A., Avruch, I. M., Beck, R., Bell, M. E.,Bell, M. R., Bentum, M. J., Bernardi, G., Best, P.,Birzan, L., Bonafede, A., Breitling, F., Broderick, J.,Brouw, W. N., Br¨uggen, M., Ciardi, B., de Gasperin,F., Dettmar, R.-J., van Duin, A., Duscha, S., Eisl¨offel,J., Falcke, H., Fallows, R. A., Fender, R., Ferrari, C.,Frieswijk, W., Garrett, M. A., Grießmeier, J., Grit,T., Gunst, A. W., Hassall, T. E., Heald, G., Hoeft, M.,Horneffer, A., Iacobelli, M., Juette, E., Karastergiou,A., Keane, E., Kohler, J., Kramer, M., Kondratiev,V. I., Koopmans, L. V. E., Kuniyoshi, M., Kuper,G., van Leeuwen, J., Maat, P., Macario, G., Markoff,S., McKean, J. P., Mulcahy, D. D., Munk, H., Orru,E., Paas, H., Pandey-Pommier, M., Pilia, M., Pizzo,R., Polatidis, A. G., Reich, W., R¨ottgering, H., Sery-lak, M., Sluman, J., Stappers, B. W., Tagger, M.,Tang, Y., Tasse, C., ter Veen, S., Vermeulen, R., vanWeeren, R. J., Wijers, R. A. M. J., Wijnholds, S. J.,Wise, M. W., Wucknitz, O., Yatawatta, S., & Zarka,P. 2013, A&A, 552, A58Sutinjo, A., O’Sullivan, J., Lenc, E., Wayth, R. B.,Padhi, S., Hall, P., & Tingay, S. J. 2015, Radio Sci-ence, 50, 52Swarup, G., Ananthakrishnan, S., Kapahi, V. K., Rao,A. P., Subrahmanya, C. R., & Kulkarni, V. K. 1991,Current Science, Vol. 60, NO.2/JAN25, P. 95, 1991,60, 95Tasse, C., van der Tol, S., van Zwieten, J., van Diepen,G., & Bhatnagar, S. 2013, A&A, 553, A105Taylor, A. R., Stil, J. M., & Sunstrum, C. 2009, ApJ,702, 1230Tingay, S. J., Goeke, R., Bowman, J. D., Emrich,D., Ord, S. M., Mitchell, D. A., Morales, M. F.,Booler, T., Crosse, B., Wayth, R. B., Lonsdale, C. J.,Tremblay, S., Pallot, D., Colegate, T., Wicenec, A.,Kudryavtseva, N., Arcus, W., Barnes, D., Bernardi,G., Briggs, F., Burns, S., Bunton, J. D., Cappallo,R. J., Corey, B. E., Deshpande, A., Desouza, L.,Gaensler, B. M., Greenhill, L. J., Hall, P. J., Hazel-ton, B. J., Herne, D., Hewitt, J. N., Johnston-Hollitt,M., Kaplan, D. L., Kasper, J. C., Kincaid, B. B.,Koenig, R., Kratzenberg, E., Lynch, M. J., Mckin-ley, B., Mcwhirter, S. R., Morgan, E., Oberoi, D.,Pathikulangara, J., Prabu, T., Remillard, R. A., Rogers, A. E. E., Roshi, A., Salah, J. E., Sault,R. J., Udaya-Shankar, N., Schlagenhaufer, F., Sri-vani, K. S., Stevens, J., Subrahmanyan, R., Water-son, M., Webster, R. L., Whitney, A. R., Williams,A., Williams, C. L., & Wyithe, J. S. B. 2013, PASA,30, 7van der Tol, S. ., Jeffs, B. D., & van der Veen, A.-J. .2007, IEEE Transactions on Signal Processing, 55,4497van Haarlem, M. P., Wise, M. W., Gunst, A. W., Heald,G., McKean, J. P., Hessels, J. W. T., de Bruyn,A. G., Nijboer, R., Swinbank, J., Fallows, R., Bren-tjens, M., Nelles, A., Beck, R., Falcke, H., Fender,R., H¨orandel, J., Koopmans, L. V. E., Mann, G.,Miley, G., R¨ottgering, H., Stappers, B. W., Wijers,R. A. M. J., Zaroubi, S., van den Akker, M., Alexov,A., Anderson, J., Anderson, K., van Ardenne, A.,Arts, M., Asgekar, A., Avruch, I. M., Batejat, F.,B¨ahren, L., Bell, M. E., Bell, M. R., van Bemmel, I.,Bennema, P., Bentum, M. J., Bernardi, G., Best, P.,Bˆırzan, L., Bonafede, A., Boonstra, A.-J., Braun, R.,Bregman, J., Breitling, F., van de Brink, R. H., Brod-erick, J., Broekema, P. C., Brouw, W. N., Br¨uggen,M., Butcher, H. R., van Cappellen, W., Ciardi, B.,Coenen, T., Conway, J., Coolen, A., Corstanje, A.,Damstra, S., Davies, O., Deller, A. T., Dettmar, R.-J., van Diepen, G., Dijkstra, K., Donker, P., Do-orduin, A., Dromer, J., Drost, M., van Duin, A.,Eisl¨offel, J., van Enst, J., Ferrari, C., Frieswijk, W.,Gankema, H., Garrett, M. A., de Gasperin, F., Ger-bers, M., de Geus, E., Grießmeier, J.-M., Grit, T.,Gruppen, P., Hamaker, J. P., Hassall, T., Hoeft, M.,Holties, H. A., Horneffer, A., van der Horst, A., vanHouwelingen, A., Huijgen, A., Iacobelli, M., Intema,H., Jackson, N., Jelic, V., de Jong, A., Juette, E.,Kant, D., Karastergiou, A., Koers, A., Kollen, H.,Kondratiev, V. I., Kooistra, E., Koopman, Y., Koster,A., Kuniyoshi, M., Kramer, M., Kuper, G., Lam-bropoulos, P., Law, C., van Leeuwen, J., Lemaitre,J., Loose, M., Maat, P., Macario, G., Markoff, S.,Masters, J., McFadden, R. A., McKay-Bukowski, D.,Meijering, H., Meulman, H., Mevius, M., Middel-berg, E., Millenaar, R., Miller-Jones, J. C. A., Mo-han, R. N., Mol, J. D., Morawietz, J., Morganti, R.,Mulcahy, D. D., Mulder, E., Munk, H., Nieuwenhuis,L., van Nieuwpoort, R., Noordam, J. E., Norden, M.,Noutsos, A., Offringa, A. R., Olofsson, H., Omar, A.,Orr´u, E., Overeem, R., Paas, H., Pandey-Pommier,M., Pandey, V. N., Pizzo, R., Polatidis, A., Rafferty,D., Rawlings, S., Reich, W., de Reijer, J.-P., Reitsma,J., Renting, G. A., Riemers, P., Rol, E., Romein,J. W., Roosjen, J., Ruiter, M., Scaife, A., van derSchaaf, K., Scheers, B., Schellart, P., Schoenmakers,A., Schoonderbeek, G., Serylak, M., Shulevski, A.,Sluman, J., Smirnov, O., Sobey, C., Spreeuw, H.,
PASA (2015)doi:10.1017/pas.2015.xxx he GLEAM survey17Steinmetz, M., Sterks, C. G. M., Stiepel, H.-J., Stuur-wold, K., Tagger, M., Tang, Y., Tasse, C., Thomas, I.,Thoudam, S., Toribio, M. C., van der Tol, B., Usov,O., van Veelen, M., van der Veen, A.-J., ter Veen,S., Verbiest, J. P. W., Vermeulen, R., Vermaas, N.,Vocks, C., Vogt, C., de Vos, M., van der Wal, E., vanWeeren, R., Weggemans, H., Weltevrede, P., White,S., Wijnholds, S. J., Wilhelmsson, T., Wucknitz, O.,Yatawatta, S., Zarka, P., Zensus, A., & van Zwieten,J. 2013, A&A, 556, A2Wieringa, M. H. 1991, PhD thesis, , RijksuniversiteitLeiden, (1991)Williams, W. L., Intema, H. T., & R¨ottgering, H. J. A.2013, A&A, 549, A55Windhorst, R., Mathis, D., & Neuschaefer, L. 1990, inAstronomical Society of the Pacific Conference Series,Vol. 10, Evolution of the Universe of Galaxies, ed.R. G. Kron, 389–403