2.1 Radio data

The ASKAP (Johnston et al. Reference Johnston2008) is a new radio telescope approaching completion in Western Australia. It has a maximum baseline of 6 km and operates with a bandwidth of ~300 MHz over the frequency range 700–1800 MHz. Each of the 36 antennas is equipped with a Phased Array Feed (PAF; Schinckel et al. Reference Schinckel, Bunton, Cornwell, Feain and Hay2012) giving it a field of view of ~35 deg², resulting in a high survey speed. ASKAP’s continuum survey is the EMU (Norris et al. Reference Norris2011), which is expected to generate a catalogue of about 70 million galaxies at 1100 MHz.

At the time of the observations described here, the telescope was in a commissioning phase (McConnell et al. Reference McConnell2016). Only 12 of the antennas were used, with a maximum baseline of 2 km. An observation of PKS B1934–638 was performed immediately adjacent in time to each observation of the target field for purposes of instrumental calibration. Each calibration observation contained one calibrator scan of duration ~5 min at the centre of each of the 36 PAF beams. Using these data, the ASKAPsoft task ‘cbpcalibrator’ was run to solve for the instrumental bandpass of each beam and to set the initial flux density scale based on the model of Reynolds (Reference Reynolds1994). As is customary with ASKAP, a phase reference calibrator was not included in the schedule due to the large overhead that would be incurred by observing it at the centre of each beam. Instead, initial phases were transferred from the observation of the bandpass calibrator and further refined using self-calibration of the target field, and the astrometry was adjusted to match an external reference catalogue.

The observing parameters are listed in Table 1. The PAF beam configuration was 36 beams in a 6×6 square, with two observations A and B offset by half a beam width, at a position angle of 45°. The 936 MHz map covers a larger region (~7.3° by ~6.8°) than the 1320 MHz image (~6.6° by ~6.1°) because of the larger primary beam size at 936 MHz. The data were reduced in ASKAPsoft using W-snapshots (Cornwell, Voronkov, & Humphreys Reference Cornwell, Voronkov and Humphreys2012), which is a hybrid wide-field algorithm combining W-projection and warped snapshot imaging. The image was cleaned (deconvolved) using the Cotton-Schwab algorithm and a single (delta function) spatial scale.

Table 1 ASKAP observation details.

The resulting synthesised beam was 32.7 arcsec by 17.8 arcsec at 936 MHz and 15.8 arcsec by 12.0 arcsec at 1320 MHz. The synthesised beam of the higher frequency observations is more circular than the beam at lower frequency because of the differences in the U–V coverage, which is due primarily to differences in hour angle coverage and different amounts of antenna-based flagging. In both cases, the output images consisted of 7784 × 7387 pixel images, where each pixel is a 4-arcsec square.

Because these data were taken at an early stage of ASKAP commissioning, our flux density and astrometry calibration were still in a preliminary state, and so these had to be corrected after processing. This was done by comparing the ASKAP images with the NVSS (Condon et al. Reference Condon, Cotton, Greisen, Yin, Perley, Taylor and Broderick1998) and SUMSS (Bock, Large, & Sadler Reference Bock, Large and Sadler1999) catalogues. We used only non-blended, unresolved sources detected at signal-to-noise (hereafter SN) above 5σ in ASKAP, NVSS, and SUMSS, and which were not flagged as problematic.

The offsets of the raw 1320 MHz ASKAP positions from the NVSS positions are shown in the top panel of Figure 1. The scatter plot for 936 MHz is similar. The medians of the 1320-NVSS and 936-NVSS position offsets were used as the position corrections for the 1320 and 936 MHz images, respectively. The 1σ astrometric accuracy was estimated by using the median absolute deviation, converted to 1σ. At 936 MHz the resulting 1σ accuracy is 3.00 arcsec in R.A. and 3.40 arcsec in Dec. and at 1320 MHz the resulting 1σ accuracy is 2.37 arcsec in R.A. and 2.64 arcsec in Dec.

Figure 1 Top panel: offsets of the raw 1320 MHz ASKAP positions from the NVSS positions for sources detected in both surveys. The colour bar gives the scale for signal-to-noise (SN) of individual ASKAP sources. The offsets are small compared to the synthesised beam size of 15.8 arcsec by 12.0 arcsec at 1320 MHz. The median 1320 MHz-NVSS offset of −5.69 arcsec in R.A. and 0.26 arcsec in Dec. was used to correct the raw ASKAP 1320 MHz positions. The median 936 MHz-NVSS offset of −6.71 arcsec in R.A. and 1.04 arcsec in Dec. was used to correct the raw ASKAP 936 MHz positions. Bottom panel: ratios of NVSS-SUMSS predicted 1320 MHz flux density to ASKAP raw measured 1320 MHz flux density for sources measured in all 3 surveys. The median ratio for 1320 MHz sources of 0.8830 was used to correct the ASKAP 1320 MHz flux densities. The median ratio for 936 MHz sources of 0.8810 was used to correct the ASKAP 936 MHz flux densities.

The flux density scale was calibrated by using sources that were in both NVSS and SUMSS. We interpolated between SUMSS (843 MHz) and NVSS (1420 MHz) flux densities for each source assuming a power-law spectrum. We tabulated the ratios of the calculated 936 and 1320 MHz NVSS–SUMSS flux densities to the raw 936 and 1320 MHz ASKAP flux densities, respectively. The histogram of these ratios for 1320 MHz is shown in the bottom panel of Figure 1. The median calculated to raw 936 MHz flux density ratio was 0.8810 and the median for 1320 MHz was 0.8830. These median ratios were used as flux density correction factors for the ASKAP 936 and 1320 MHz images, respectively.

The resulting images are shown in Figures 2 and 3. The root-mean-square (r.m.s.) noise of source free regions in both 936 and 1320 MHz images is ~0.1 mJy/beam. To illustrate the image quality obtained with ASKAP in its commissioning phase, we show images on spatial scales of tens of arcminutes. Figures 4 and 5 show regions with typical r.m.s. noise level in the maps (0.1 mJy). The first illustrates some double radio sources. The latter shows one triple source (central source plus two lobes) at the top centre of the image and a fainter triple source at the lower left.

Figure 2 The 936 MHz final processed radio image for the GAMA 23 region. This covers a sky area of ~7.3° in R.A. by ~6.8° in Dec. The greyscale bar at the bottom is in units of Jy/beam.

Figure 3 The 1320 MHz final processed radio image for the GAMA 23 region. This covers a sky area of ~6.6° in R.A. by ~6.1° in Dec. The greyscale bar at the bottom is in units of Jy/beam.

Figure 4 Enlargement of the 1320-MHz image in an area centred on R.A. 23^h01^m10^s, Dec. −32°13′30′ in a region containing some double radio sources. The grid spacing is 0.2°. The intensity greyscale is linear, from −5 to +20 mJy/beam.

Figure 5 Enlargement of the 1320-MHz image in an area centred on R.A. 23^h10^m24^s, Dec. −33°10′30′, in a region containing two radio triples (central source plus two lobes). The grid spacing is 0.2° in R.A and in December. The intensity greyscale is linear, from −1 to +5mJy/beam.

2.1.1 Source extraction

We make the distinction between components, which are individual point-like detections in a radio image, and sources, which can be either a single component or composed of multiple components, such as a double-lobed radio galaxy. The Aegean software (Hancock et al. Reference Hancock, Murphy, Gaensler, Hopkins and Curran2012) was used for component extraction. We used a 4 σ threshold, resulting in a list of 6 053 components at 936 MHz, and 3 827 at 1320 MHz.

Small but significant residuals, of order 1% of the peak flux density, are found around bright components. The residuals occur in a spiral pattern which extends out to a radius of about 6 arcmin (~10 times the synthesised beam). Figure 6 shows a bright component exhibiting such residuals, the resulting false components, and our correction for them. The flux densities of the false components were all less than 1.25% of the integrated flux density of the bright central component at 936 MHz, and less than 1.6% at 1320 MHz. We started with the brightest component in the map and labelled it as the ‘source’. All components within 6 arcmin radius of the ‘source’ which were fainter than 1.25% (at 936 MHz) or 1.6% (at 1320 MHz) of the ‘source’ were added to a list of possible false components. This was repeated for the second brightest component in the map, and so on, until a complete list of possible false components was created. The false components were removed from the original component list except for those few not consistent with the spiral beam residual pattern. After artefact removal, the catalogue contained 5 968 components at 936 MHz, and 3 757 at 1320 MHz.

Figure 6 Enlargement of the 936 MHz image centred on a bright component (integrated flux density 0.78 Jy) which exhibits a spiral shaped pattern of residuals. The large circles are 240 arcsec in radius. The crosses show the detected components (4 sigma above background) before the correction. The small circles show the components after the correction. The intensity greyscale is expanded to show faint features and is linear from −1 mJy/beam (black) to +1.5 mJy/beam (white). Most sources are saturated at this scale.

2.1.2 Source counts

The source counts normalised by the Euclidean slope (S^2.5 dN/dS vs. flux density) are shown in Figure 7 for 936 and 1320 MHz. The smooth line is a fit to the compilation of published source count data from Hopkins et al. (Reference Hopkins, Afonso, Chan, Cram, Georgakakis and Mobasher2003). The flux densities for 936 MHz sources and 1320 MHz sources were adjusted to 1.4 GHz flux densities using a spectral index of α = –0.7.

Figure 7 Source counts normalised by the Euclidean slope, S^2.5dN/dS, from the 936 MHz and 1320 MHz observations, with Poisson error bars. The smooth line is a polynomial fit to the compilation of published source count data (Hopkins et al. Reference Hopkins, Afonso, Chan, Cram, Georgakakis and Mobasher2003).

The data for both frequencies match well the fit line between ~1.2 mJy and ~0.2 Jy. Above 0.2 Jy, the counts are dominated by small number statistics, reflected in the large error bars. Below ~1.2 mJy, the observations fall below the expected source counts, indicating that they are incomplete at this level, particularly at 1320 MHz. The map r.m.s. is 0.1 mJy excluding the edges. The r.m.s. rises nearly linearly from to ~0.1 mJy at ~ 0.5° from the edges to ~ 0.5 mJy at the edges. It also rises from ~ 0.1 mJy at ~ 0.25° away from ~0.5 Jy sources to ~1 mJy at ~0.05° away. The fraction of the map area with r.m.s above ~0.1 mJy is ~0.2. Thus a significant fraction of sources below ~ 1 mJy are not detected at the 4σ level.

2.1.3 Identifying complex radio sources

About 95% of radio sources at the mJy level, which we term ‘simple’, consist of a single component which is coincident with the optical host galaxy (e.g., Norris et al. Reference Norris2006). The remaining ~5% are complex sources, such as double-lobed radio galaxies which appear on the radio image as two isolated components typically separated by tens of arc seconds, with the optical host galaxy located roughly halfway between them. Cross-matching simple sources with optical/IR data are straightforward, and can be achieved using any of the several algorithms and tools such as those available within TopCat (Taylor Reference Taylor2011).

To identify the complex sources, we compiled one list of candidate complex sources from the list of ‘islands’ generated by Aegean, and a second list of candidates by using TopCat to identify pairs and groups of more than two sources within a radius of 6 arcmin. There was a significant overlap (~50–70%) between these two lists of candidates. The difference between the two lists illustrates the difficulty of using a single algorithm to identify complex sources. The visual inspection of Aegean islands and TopCat groups resulted in a revised list of singles, doubles, and triples. The singles include those components that were put in islands or groups by the software, but had no visual evidence of association. All islands and groups of 4 or more were found to consist of a double or triple plus unrelated singles.

We tested the doubles against the Magliocchetti criterion (Magliocchetti et al. Reference Magliocchetti, Maddox, Lahav and Wall1998), for which the flux density ratio of the two lobes is required to be between 1/4 and 4, and the separation is required to be $$ \lt 100\,{\rm{ arcsec}} \times \sqrt {{S_{{\rm{tot}}}}/100\,{\rm{ mJy}}} $$. We used a flux density ratio between 1/3 and 3, to err on the side of rejecting sources, but only found one source with flux density ratio between 1/4 and 1/3 (or 3 and 4) that also passed the separation test. Sources that failed this test were split into components and added back to the singles list.

We scanned the full ASKAP radio images for radio doubles or triples not identified by either Aegean or TopCat algorithms, and found several more radio doubles and triples, typically those with large angular separation. The resulting numbers of single, double, and triple radio sources are shown in Table 2.

Table 2 Number of sources, by morphology, in the radio source catalogue.

To estimate host galaxy positions and integrated flux densities for the double sources, we calculated the flux density-weighted centroid and the total integrated flux density. For the triples, we assumed the host position to be that of the component closest to the centre. The distribution of 1320 MHz integrated flux densities for the double sources, triple source and full set of singles, doubles and triples is shown in Figure 8.

Figure 8 Distribution of integrated 1320 MHz flux densities of all sources (black line), double sources (blue shaded histogram), and triple sources (red line). The all source category is dominated by single sources. The doubles are brighter on average than the triples and both are much brighter than single sources.

2.2 Comparison with NVSS and SUMSS surveys

We compared our 936 and 1320-MHz images and components with the 1420 MHz NVSS and SUMSS 843 MHz catalogues to verify the ASKAP imaging and source detection algorithms.

Figure 9 shows a region from the 936-MHz map comparing the 936-MHz detected components with components from the NVSS and SUMSS catalogues. In the full area covered by the 936-MHz image, there are 5 897 936-MHz components, 2 718 NVSS components, and 1 152 SUMSS components. There are 2 209 936-MHz—NVSS cross-matches within 20 arcsec, 879 936-MHz—SUMSS matches, and 943 NVSS—SUMSS matches. In the full area covered by the 1320-MHz image, there are 3 756 1320-MHz components, 1 724 NVSS components, and 735 SUMSS components. There are 1 532 1320-MHz—NVSS cross-matches within 20 arcsec, 702 1320-MHz—SUMSS matches, and 701 NVSS—SUMSS matches.

Figure 9 Enlargement of the 936-MHz image in an area centred on R.A. 23m 04m, December −29°40′. The small green circles show the 936-MHz detected sources, the large green circle is the area around a bright source within which false components were removed (see text, Section 2.1.1). Overlaid are the NVSS 1420 MHz sources (small magenta circles) and SUMSS 843 MHz sources (blue squares). The intensity greyscale is linear, from −1 to +2 mJy/beam, which is expanded to show the background noise level. The grid spacing in December is 5 arcmin and the grid spacing in R.A. is 30 s.

All bright components (≳ 20 mJy) are detected in all 3 data sets, ASKAP, SUMSS, and NVSS. The number of faint matches is consistent with expectations for detections of real components with noise, given the different sensitivities of the data.

2.3 Optical Data

The GAMA G23 imaging and i-band photometric data are from the VLT Survey Telescope (VST) Kilo-Degree Survey (KiDS, de Jong et al. Reference de Jong, Verdoes Kleijn, Kuijken and Valentijn2013), and ZYJHKs-bands data are from the VISTA Kilo-degree Infrared Galaxy survey (VIKING, Edge et al. Reference Edge, Sutherland, Kuijken, Driver, McMahon, Eales and Emerson2013). The GAMA photometry is described in Driver et al. (Reference Driver2016) and was obtained from the GAMA Data Management Unit (DMU) ‘G23InputCatv6’. All magnitudes are in the AB system. The G23 spectroscopic sample was VST KiDS i-band selected with a magnitude limit of 19.2. The GAMA spectral catalogue is described in Hopkins et al. (Reference Hopkins2013). The data reduction, spectral analysis, and redshift completeness are described in Liske et al. (Reference Liske2015). The spectral line information is from the GAMA DMU ‘SpecLineSFRv5’. There are 37359 galaxies with spectra and redshifts for the area overlapping the 936 MHz field.

Because full SED-derived stellar mass estimates were not yet available for G23, we obtained stellar mass estimates for G23 galaxies by matching each G23 galaxy to galaxies with similar redshift and iZYJHKs photometry in the GAMA equatorial catalogues, and assuming they had a similar mass. We use a Gaussian weighting kernel, with size of 0.005 in the redshift dimension and sizes of the photometric 1σ errors in the photometric dimensions, to find the average mass-to-light ratio of the ‘similar’ reference galaxies, and assigned that mass to the G23 galaxy. This idea is similar in spirit to kernel-density estimation photometric redshift estimation of Wolf et al. (Reference Wolf2017). We have validated this approach by testing our ability to recover the SED-fit mass estimates for half of the equatorial catalogue, using the other half of the catalogue as a reference sample. We find that the global random error in the mass estimates derived in this way is of the order of 0.15 dex, compared to a median formal uncertainty of 0.12 dex for the SED-fit mass estimates described in Taylor et al. (Reference Taylor2011). This yields 35353 galaxies with mass determinations.

2.4 IR data

The IR data were taken from the ALLWISE catalogue of the WISE satellite (Wright et al. Reference Wright2010). A detailed description of the WISE mission and catalogue is online at the Infrared Science Archive (IRSA) at NASA/IPAC (http://irsa.ipac.caltech.edu). The catalogue (hereafter referred to as WISE) contains Vega magnitudes and errors for wavebands at 3.4, 4.6, 12, and 22 micron wavelengths (bands W1,W2,W3,W4). The angular resolution is 6.1, 6.4, 6.5, and 12.0 arcsec in the four bands, respectively. The w1mpro, w2mpro, w3mpro, and w4mpro magnitudes and errors were used in the current analysis. The appendix of Cluver et al. (Reference Cluver2014) discusses the effect for resolved (nearby) sources on the WISE mpro magnitudes. The w1mpro and w2mpro magnitudes are fainter than isophotal magnitudes by ~0.4. Here we are using W1 - W2 colour which is much less affected for resolved sources.

3.1 Source cross-matching

We cross-matched the 936 and 1320 MHz catalogues of radio sources to the G23 galaxies by matching positions within a specified radius using TopCat. For each cross-match, we first plotted the separation distribution for the real catalogues and for the case where one of the catalogues had the positions randomised. Then we compared the separation distributions to determine an optimum radius for separating real from random matches. The 936 and 1320 MHz catalogues were matched using a radius of 7 arcsec. The 1320 MHz catalogue was matched with G23 using radius 5 arcses. The 936 MHz catalogue was matched with G23 using radius 7 arcsec. Because the 1320 MHz sources were essentially a subset of the 936 MHz sources, we mainly report results for the larger set of 936 MHz cross-matches.

We cross-matched the 936 and 1320 MHz catalogues and the matched 936/1320 MHz catalogue with WISE using a radius of 4 arcsec. This is smaller than for the cross-match of radio catalogues with G23 because of the much higher source density on the sky for WISE than G23.

G23 was cross-matched with WISE using radius of 1.5 arcsec. This gives low contamination (0.84%) and yields a large fraction of cross-matches (87.6%). For the GAMA G12 and G15 fields, Cluver et al. (Reference Cluver2014) found similar results: 77% (for G12) and 88% (for G15) of the galaxies had WISE W1 and W2 detections at > 5σ.

We compared the cross-match of the 936 MHz/WISE catalogue to G23 with the cross-match of the 936 MHz catalogue with the G23/WISE catalogue. The latter yields better results: the number of cross-matches is somewhat reduced, but there is much lower contamination with random cross-matches. The reason for this is the superior spatial resolution of both G23 positions (sub-arcsec) and WISE positions (≃0.2-0.3 arcsec) compared to the uncertainties of the radio positions (~5 arcsec).Footnote ^a

From these different catalogues, we then extracted the following subsets:

1. 1. all galaxies with spectra and masses;

2. 2. all galaxies with spectra, masses, and BPT line flux measurements;

3. 3. all galaxies with spectra, masses, and all BPT lines in emission;

4. 4. all galaxies with spectra, masses, and at least one BPT line in absorption;

5. 5. all galaxies with spectra, masses, and all BPT lines in absorption.

Summaries of the numbers of sources in the different subsets are given in Table 3 and, in part, in Figure 10. All galaxies with spectra have redshifts.

Table 3 Population measures for 936 and 1320 MHz sources, G23 galaxies^a, and cross-matches with WISE photometry.

a The GAMA23 stellarmasses were based on stellarmasses from the GAMA equatorial fields as described in Section 2.3.

b 4lineflux> 0 means Hα, Hβ, [O iii]λ5007, and [S ii]λλ6717,6731 all have lineflux> 0.

c lineflux< 0 means any one of Hα, Hβ, [O iii]λ5007, and [S ii]λλ6717,6731 has lineflux< 0.

d 4lineflux< 0 means Hα, Hβ, [O iii]λ5007, and [S ii]λλ6717,6731 all have lineflux< 0.

Figure 10 Number of matches between 936 MHz sources, 1320 MHz sources, G23 galaxies, and WISE sources. The central set of 889 in the left diagram was obtained by first matching the 35 353 G23 galaxies with spectra and masses to the WISE sources, and then matching the resulting 30 581+889 galaxies to the 5 791 936-MHz sources. The central set of 334 in the right diagram was obtained by first matching 5 791 936-MHz and 3 589 1320-MHz sources, and then matching those 2 955+334 to 28 179 G23 galaxies with linefluxes and masses.

3.2 Properties of cross-matched sources

A mass-redshift diagram for G23 galaxies and their 936 MHz radio counterparts are given in the top panel of Figure 11. At all redshifts, the radio sources occur in the high-mass end of the galaxy mass distribution. The radio source mean masses (‘936/G23 spectra/mass’ and ‘936/G23/WISE spectra/mass’) are significantly higher than for the full galaxy population (‘G23 spectra/mass’), by factors of 2.14 and 2.34, respectively. The 936 and 1320 MHz mass distributions are not significantly different.

Figure 11 Top panel: Stellar mass in units of log(M/M_⊙) versus redshift for the 936 MHz/G23 sources (red), and for all G23 galaxies (grey). This shows that galaxies with detected radio emission are mainly galaxies with larger masses and shows the effect of redshift-dependent completeness on the lower limit of detected G23 galaxies and radio counterparts. Middle panel: i-band magnitude versus redshift for the galaxy sample and for the galaxies with detected 936 MHz radio sources. The lines are for a galaxy of absolute i band magnitudes −17 and −19. Bottom panel: Integrated 936 MHz flux density versus redshift for the G23 galaxies with radio counterparts (red points). The blue lines are for sources of constant radio luminosity (differing by one order of magnitude). Radio counterparts which would have flux densities below the limits of the current ASKAP data fall below a horizontal line at ~5 × 10⁻⁴ Jy. Radio counterparts which would be beyond the current redshift limit of the G23 galaxies fall to the right of a line at z ~ 0.6.

The middle panel of Figure 11 shows i-band magnitude versus redshift for the G23 galaxies and for radio counterparts compared to lines of constant i-band absolute magnitude −17 and −19. The radio sources are associated with the optically most luminous galaxies, consistent with them having higher than average stellar masses. The fact that the radio counterparts extend down to the detection limit of the G23 region (a horizontal line at i band magnitude of 19.2) implies that the radio observations are fairly complete for redshifts z < 0.6.

The bottom panel of Figure 11 shows integrated radio flux density versus redshift for the 936 MHz radio counterparts. Lines of constant radio luminosity are shown. Cosmological volume increases rapidly with redshift, so the number of luminous radio sources (e.g. within a band between a pair of blue lines) should increase rapidly. This illustrates increasing incompleteness with redshift of radio counterparts and of galaxies.

There are two reasons why we do not observe more radio counterparts:

• Radio counterparts are not detected below the lower edge of the observed distribution because of the limited sensitivity of the radio observations.

• Radio counterparts are not observed at high redshift (z > 0.6) because of the lack of such galaxies in G23. The gradual decrease in radio counterparts between redshift 0.1 and 0.6 is consistent with the decrease in the number (i.e. completeness) of optically measured galaxies with redshift, as seen in the top and middle panels.

Both factors contribute to lack of observed radio counterparts. The number of observed radio sources (5791 at 936 MHz) is much larger than the number with optical counterparts (978). Those without optical galaxy counterparts may lie either at z < 0.6 with their optical counterpart fainter than the G23 magnitude limit, or at z > 0.6. The relatively high radio flux density limit of these observations suggests that most are likely to be high radio luminosity AGNs at high redshifts (e.g. Seymour et al. Reference Seymour2008) or, possibly, dust obscured galaxies at lower redshifts (z ≲ 0.6).

Radio sources, such as broad-line AGN and SFG, typically have bluer near-ultraviolet (NUV)–r colours than the overall galaxy population (Heckman & Best Reference Heckman and Best2014). We used NUV magnitudes from the G23 input catalogue derived from GALEX observations (Liske et al. Reference Liske2015). The mean NUV magnitude is 21.11 for galaxies detected at 936 MHz compared to 21.94 for all galaxies. For NUV magnitudes brighter than 19, the probability of a galaxy to have radio emission is higher by a factor of ~5. For SFG, brighter UV magnitudes imply higher star formation rates (Brown et al. Reference Brown2017). The UV could be from accretion disks of AGN; however, recent measurements of the AGN UV luminosity function (Ricci et al. Reference Ricci, Marchesi, Shankar, La Franca and Civano2017)Footnote ^b imply that the UV input to the universe from SFG is significantly larger than from AGN. Thus the brighter UV from radio-detected galaxies in most cases is dominated by star formation.

The brightest emission line galaxies in either Hα or Hβ are mostly detected as 936 MHz sources: 8 out of the 10 brightest Hα emitters and 7 out of the 10 brightest Hβ emitters are 936 MHz sources, whereas only 1 in 25 galaxies with Hα and Hβ emission lines is a 936 MHz source. Thus, radio sources are highly over-represented in the population of brightest Hα and Hβ galaxies.

Compared to the full optical sample, the fraction of strong Hβ absorption line systems is larger by a factor of ≃2 for the radio counterparts. The mass distributions are shown in the top panel of Figure 12. The mean log(M/M_⊙) is 10.37 for the whole galaxy sample, 10.68 for the optical galaxy Hβ-absorption-line sample, and 11.00 for the 936 MHz detected Hβ-absorption-line sample. The stronger Hβ absorption line strengths for 936 MHz galaxies are related to the higher masses for 936 MHz Hβ absorption line systems. This is similar to the result from Best et al. (Reference Best, Kauffmann, Heckman, Brinchmann, Charlot and White2005) that the fraction of galaxies that host a radio AGN rises strongly with host stellar mass. While the radio flux density limit of the current data is significantly lower than in that work, and the current set of radio sources includes a larger fraction of SFG, it is clear that the highest mass systems include those with old stellar populations, and their radio emission is likely driven by an AGN.

Figure 12 Top panel: The distribution of stellar masses (number of galaxies per mass bin, units of log(M/M_⊙)) for radio counterparts (936/G23 set) with Hβ in absorption (red), and for all radio counterparts (black). Overlaid on these are the distributions for G23 galaxies with Hβ in absorption (blue), and for all G23 galaxies (grey). This illustrates (i) the significantly larger masses for galaxies with Hβ in absorption compared to all galaxies; and (ii) the shift to even larger masses for both sets of galaxies when they have 936 MHz radio emission. Bottom panel: comparison of the 22 μm luminosity distribution for radio-emitting galaxies (red histogram) with that for a mass-matched set of non-radio galaxies (blue histogram).

Radio sources have much stronger mid-IR emission than non-radio galaxies in general (see Table 3). The 936/G23/WISE sources have a mass about a factor of ~4 higher than the G23/WISE galaxy population. We created a sample of not936/G23/WISE galaxies by excluding the radio-emitters. Then we selected a mass-matched set of non-radio galaxies by choosing the best match by mass from the not936/G23/WISE set for each radio galaxy in the 936/G23/WISE set. We verified that the mass distribution of the not936/G23/WISE/mass-matched set is essentially identical to that of the 936/G23/WISE set. The resulting 22 μm luminosity distributions of the radio and non-radio emitters are shown in the bottom panel of Figure 12. There is no difference, except for the 3 radio sources with highest 22 μm luminosity, so we can conclude that the higher mid-IR emission of radio sources is consistent with being associated with increased mass of the galaxy.

Both 22 μm and ~1.4 GHz luminosities are star formation rate indicators for SFG (e.g. Kennicutt et al. Reference Kennicutt2009, Rieke et al. Reference Rieke, Alonso-Herrero, Weiner, Pérez-González, Blaylock, Donley and Marcillac2009, Brown et al. Reference Brown2017, Cluver et al. Reference Cluver, Jarrett, Dale, Smith, August and Brown2017). For AGN, they are indicators of AGN activity (Gürkan, Hardcastle, & Jarvis Reference Gürkan, Hardcastle and Jarvis2014). We show the tight correlation between 22 μm and 936 MHz luminosities (L _v, units erg/s/Hz) for the 936/G23/WISE galaxies in the top panel of Figure 13.Footnote ^c We also show the range of ratio 936 MHz to 22 μm luminosity found by Rieke et al. (Reference Rieke, Alonso-Herrero, Weiner, Pérez-González, Blaylock, Donley and Marcillac2009) for SFG by the two black dashed lines. In all, 68% (95%) of the data falls within ±0.3 dex (±0.6 dex) of a 936 MHz to μm luminosity ratio of 0.13. Consistent with our results, Brown et al. (Reference Brown2017) finds that 150 MHz, 1.4 GHz, and μm luminosities as a function of Hα luminosity have scatter of 0.2 dex. Thus it is seen that the majority of our radio/optical/IR galaxies are consistent with their radio and μm emission powered by star formation.

Figure 13 Top panel: 936 MHz luminosity versus W4 band (22 μm) luminosity, both in units of erg s⁻¹ Hz⁻¹, for the 936/G23/WISE sources with WISE W4 signal-to-noise (SN) ≥3 (blue points), and for the AGN_IR subset (red points). Most sources (96%, 436 of 452) fall in the band for star-forming galaxies, delimited by the two lines shown (derived from Rieke et al. Reference Rieke, Alonso-Herrero, Weiner, Pérez-González, Blaylock, Donley and Marcillac2009). The regions outlined by the pink and magenta dashed lines indicate the regions occupied by HERGs and LERGs (Gürkan et al. Reference Gürkan, Hardcastle and Jarvis2014). The sources detected here mainly have lower L _{936 MHz} than HERGs and LERGs. Bottom panel: 936 MHz luminosity distribution for AGN_IR and notAGN_IR from the 936/G23/WISE sample.

3.3 AGN and SFG diagnostics

3.3.1 IR AGN diagnostic

The WISE mid-IR colour criterion W1 - W2 > 0.8 was introduced by Jarrett et al. (Reference Jarrett2011) to distinguish AGN from other galaxies. Stern et al. (Reference Stern2012) found that AGN can be identified, with 95% reliability and 78% completeness, using this criterion. Sources with W1 - W2 > 0.8 (> 1σ) are labelled AGN_IR and those with W1 - W2 < 0.8 (> 1σ) are labelled notAGN_IR. The W - W2 test gives an AGN _IR classification for 374 sources and a notAGN_IR classification for 29 983 sources.

The AGN_IR and notAGN_IR galaxies have strikingly different properties. Figure 13 (top panel) shows the AGN_IR constitute ~1/2 of the outliers from the radio versus 22 μm relation, whereas they are only a small fraction (0.08) of the radio and 22 μm emitting galaxies. The bottom panel of Figure 13 shows the radio luminosity distributions of AGN_IR and notAGN_IR. The AGN_IR are more luminous on average by a factor of 156 at 936 MHz.

Figure 14 shows the redshift, mass, and 22 μm luminosity distributions for G23/WISE and 936/G23/WISE samples. The mean redshift of AGN_IR is much higher than for notAGN_IR (see Table 4). The mean mass of G23/WISE AGN_IR is nearly the same as for notAGN_IR, and the mass distributions are nearly the same (Figure 14 middle panel). The mean 22 μm luminosity of AGN_IR is higher by a factor ~ 25 than for notAGN_IR (for the G23/WISE w4snr>3 sample).

Figure 14 Comparison of the optical/IR galaxy sample with 936 MHz emitting subsets. Shown are distributions of: redshift (top panel); mass (second panel); and 22 μm luminosity, L(22 μm), in erg/s/Hz (third panel, for subset with w4snr>3). Sets shown are G23/WISE notAGN_IR (blue), G23/WISE AGN_IR (red), 936/G23/WISE notAGN_IR (cyan), and 936/G23/WISE AGN_IR (magenta).

Table 4 Properties^a of SFG and AGN subsets using BPT and W1 - W2 criteria.

a The GAMA23 stellarmasses were based on stellarmasses from the GAMA equatorial fields as described in Section 2.3.

For the 936 MHz detected G23/WISE galaxies (whole and w4snr>3 subsample, see Table 4), the AGN_IR redshifts and 936 MHz radio flux densities are higher (by factor ~ 3 for red-shift and ~ 8 for flux density) than for notAGN_IR.There is an even more extreme difference considering luminosities: the 22 μm luminosities are higher by a factor of 20 than for notAGN_IR (for the w4snr>3 subsample). The AGN_IR mean masses are similar for the whole 936/G23/WISE sample and the subsample with w4snr>3. However, the notAGN_IR mean mass is higher (by a factor of 2.0) for the whole 936/G23/WISE sample compared to the subsample with w4snr>3.

The fact that such strong differences in redshift and luminosity are seen between the AGN_IR and notAGN_IR categories indicates that the contamination of AGN_IR by notAGN galaxies and of notAGN_IR by AGN is not a large fraction of either category. Contamination of notAGN_IR by low luminosity AGN would not strongly affect the redshift and radio luminosity difference we see between the AGN_IR and notAGN_IR sets.

3.3.2 Optical AGN/SFG diagnostic

As a complement to the W1−W2 colour criterion, we use the BPT diagnostic to distinguish AGN from SFG. Requiring observed BPT line fluxes rejects all galaxies which have z > 0.315 because the [S II]λλ6717,6731 lines are redshifted out of the observed spectra. This has the side effect of rejecting high mass galaxies (~1/3 to 2/3 of those above 5 × 10¹⁰M_⊙).

To classify a galaxy as AGN_opt or SFG_opt, we required the entire error box in the BPT diagram to lie on the AGN_opt or SFG_opt side of the diagnostic BPT line. Figure 15 shows the BPT diagram. Galaxies which have an ambiguous classification because of line flux uncertainties are shown by the grey points.

Figure 15 The BPT diagram, [O III]λ5007/Hβ versus [S II]λλ6717,6731/Hα, for the set of G23 galaxies with all of the required lines in emission (grey). The dividing line between AGN and SFG (Kewley et al. Reference Kewley, Dopita, Sutherland, Heisler and Trevena2001) is shown in black. The galaxies for which the error box lies entirely on the AGN side or on the SFG side of the dividing line are labelled AGN_opt (red) or SFG_opt (blue), respectively.

For the G23 sample, about half (Table 3) of the galaxies with measured line fluxes have one or more of the BPT lines in absorption, and of the ~15 000 with emission lines, ~4 400 had high enough SN to be classified by the BPT diagnostic. Table 4 gives the numbers of AGN and SFG for different subsets.

The mass distributions for the different categories are shown in the top and bottom panels of Figure 16. In order, from highest mean mass to lowest mean mass, the categories are: galaxies with all BPT lines in absorption; galaxies with at least one BPT line in absorption; SFG_opt;AGN_opt; and galaxies with all BPT lines in emission. The AGN_opt-classified galaxies have the broadest mass distribution, inconsistent with single-peaked distribution and characteristic of a bimodal mass distribution. A χ ² fit to the distribution shows it requires two components: a high mass component peaking at ~ 3 × 10¹⁰M_⊙, and a low mass component peaking at ~ 2 × 10⁹M_⊙.

Figure 16 The distribution of masses (number of galaxies per mass bin, in units of log(M/M_⊙)) for the different categories of G23 galaxies, all with measured BPT line fluxes. Top panel: the full sample (grey), galaxies with all 4 BPT lines in emission (blue), SFT_opt with BPT lines in emission (black), and AGN_opt with BPT lines in emission (red). Bottom panel: the full sample (grey), galaxies with at least one BPT line in absorption (cyan), and galaxies with all 4 BPT lines in absorption (blue). The top panel illustrates that galaxies with all BPT lines in emission have lowest mean mass, and AGN_opt have a broader, likely bimodal mass distribution. The bottom panel illustrates that galaxies with all BPT lines in absorption have highest mean mass.

To compare the BPT criterion with the W1−W2 criterion, we use the G23/WISE sample. The requirement of a WISE detection in effect rejects low mass galaxies (see Table 3): it results in rejection of ~1/6 or more of the galaxies below 3 × 10⁹M_⊙. Table 4 shows that the increase in mean mass for G23/WISE compared to G23 depends on the AGN classification: G23/WISE AGN_opt has mean mass higher than G23 AGN_opt by factor 2.24; and G23/WISE SFG_opt has mean mass higher than G23 SFG_opt by factor 1.35.

Next, the BPT diagnostic was applied to the radio detected 936/G23 sample. Figure 17 shows the mass distributions for the 936/G23 galaxies and their five sub-categories. Comparison of the mass distributions in Figure 17 with those in Figure 16 shows that masses for galaxies with 936 MHz emission are higher compared to galaxies without radio emission: AGN_opt with 936 MHz emission has mean mass higher by factor 2.5 than the whole AGN_opt set; and SFG_opt with 936 MHz emission has mean mass higher by factor 1.3 than the whole SFG_opt set. Similar results to that for 936/G23 are obtained when we apply the BPT diagnostic to 936/G23/WISE sample.

Figure 17 The distribution of masses (number of galaxies per mass bin, in units of log(M/M_⊙)) for the different categories of G23 galaxies with 936 MHz emission, all with measured BPT line fluxes. Top panel: the full radio/optical sample (grey), those with all 4 BPT lines in emission (blue), SFG_opt with BPT lines in emission (black), and AGN_opt with BPT lines in emission (red). Bottom panel: the full radio/optical sample (grey), those with at least one BPT line in absorption (cyan), and those with all 4 BPT lines in absorption (blue). The requirement of a 936 MHz detection constrains the sample to relatively high masses, and the mass distributions of the optically classified AGN and SFGs with radio detections are similar.

3.3.3 Comparison of optical-classified and IR-classified samples

The G23/WISE galaxies were separated into four categories: notAGN_IR/SFG_opt; notAGN_IR/AGN_opt;AGN_IR/SFG_opt;and AGN_IR/AGN_opt. These are shown on a BPT diagram in the top panel of Figure 18. The AGN_IR and notAGN_IR galaxies are scattered on both sides of the line which forms the BPT criterion demonstrating that there is no clear correlation seen between the BPT and W1−W2 diagnostics.

Figure 18 G23/WISE galaxies, classified as AGN or notAGN/SFG by the BPT and W1 − W2 diagnostics. The full optical/IR set of galaxies is shown in grey, notAGN_IR and SFG_opt galaxies are marked in blue, galaxies classified as notAGN_IR and AGN_opt are marked in yellow, galaxies classified as AGN_IR and SFG_opt are marked in magenta, and those classified as AGN_IR and AGN_opt are marked in red. The top panel shows the BPT diagram, with the BPT line (Kewley et al. Reference Kewley, Dopita, Sutherland, Heisler and Trevena2001) separating SFG_opt and AGN_opt in black; and with the line that marks the division (Sharp & Bland-Hawthorn Reference Sharp and Bland-Hawthorn2010) between AGN-photoionised gas (upper-left of the cyan line) and shock-ionised gas (lower-right of the cyan line). The middle panel shows W1−W2 colour versus W2−W3 colour for sources with W3snr≥3. The division between AGN_IR and notAGN_IR is at W1 − W2 = 0.8. The bottom panel shows the distribution of W2−W3 colours for the different subsets (histograms) and the colour ranges (pairs of vertical dashed lines) for spirals, for LIRGs and for starbursts/liners/ULIRGs from Figure 12 of Wright et al. (Reference Wright2010).

The middle panel of Figure 18 shows the various classes of galaxies placed in the WISE colour-colour diagram. Wright et al. (Reference Wright2010) and Jarrett et al. (Reference Jarrett2011) showed that the notAGN_IR types include: ellipticals with W2−W3 of 0.5 − 1.5; spirals with W2−W3 of 1.0 − 4.3; luminous IR galaxies (LIRGs) with W2−W3 of ≃2.7 − 5.3; and starbursts, liners, and ultra-luminous IR galaxies (ULIRGs) with W2−W3 of ≃3.6 − 5.1. The colour limits for these groups are shown in the bottom panel of Figure 18 overlaid on the distribution of W2−W3 colours. The notAGN_IR/SFG_opt have a W2−W3 colour range consistent with that for LIRGs or a mixture of LIRGS and starbursts/liners/ULIRGs. The notAGN_IR/AGN_opt have a wide W2−W3 colour range, consistent with a mixture of spirals and one or both of the other groups of galaxies (LIRGs and star-bursts/liners/ULIRGs).

Table 5 shows that there is little quantitative correlation between the W1−W2 criterion and BPT criterion. Generally, the BPT classes of W1−W2 classified sources show poor correlation, e.g. for the G23/WISE sample, AGN_IR are 6.4% classified as SFG_opt and 8.2% classified as AGN_opt.The W1−W2 classes of both SFG_opt and AGN_opt show most to be classified as notAGN_IR.

Table 5 Numbers of AGN/notAGN/SFG using W1-W2 and BPT criteria, or of Emission-line Galaxies.

a The samples are listed in the first column; the numbers and percentages within each sample are listed across the rows in columns two to six.

b The breakdown of AGNopt types into photoionised and shock-ionised categories is given in the lowest section of the table.

The redshift distributions for the various categories of G23/WISE galaxies are shown in the left panels of Figure 19. The Kolmogorov–Smirnov test was applied and showed that the notAGN_IR/AGN_opt subset has a different redshift distribution (lower redshifts) than the AGN_IR/SFG_opt subset at >99.9% confidence. The notAGN_IR/AGN_opt have lower redshifts than notAGN_IR/SFG_opt at the 99% confidence level, and the AGN_IR/AGN_opt have lower redshifts than AGN_IR/SFG_opt at only the 97.5% confidence level. The mass distributions for the various categories of G23/WISE galaxies are shown in the right panels of Figure 19.

Figure 19 Distributions of redshift (number of galaxies per redshift bin, left panels) and distributions of mass (number of galaxies per mass bin, units of log(M/M_⊙), right panels) for the various subsets of G23/WISE galaxies. Subsets shown in the top two panels are notAGN_IR galaxies (grey), AGN_IR galaxies (black), and G23/WISE with all BPT lines in emission (green). Subsets shown in the middle and bottom panels are notAGN_IR/SFG_opt (blue), notAGN_IR/AGN_opt (grey), AGN_IR/AGN_opt (red), and AGN_IR/SFG_opt (magenta).

We further split the G23/WISE AGN_opt galaxies into subsets based on the dominant mechanism of ionisation (Sharp & Bland-Hawthorn Reference Sharp and Bland-Hawthorn2010): gas dominated by photoionisation is left of the line (cyan line in the top panel of Figure 18) and shock-ionised gas is right of the line. Essentially the same line in the BPT diagram (Kewley et al. Reference Kewley, Groves, Kauffmann and Heckman2006) separates Seyferts (left of the line) from LINERs (right of the line). Of the AGN_opt galaxies, 64% are photoionised/Seyferts and 36% are shock-ionised/LINERs.

The redshift and mass distributions of the photoionised and shock-ionised subsets of AGN_opt galaxies are shown in Figure 20. The AGN_IR subsets are small in number with 26 in the photoionised subset and 5 in the shock-ionised subset. Thus the redshift distributions cannot be distinguished. The AGN_IR/photo subset has a higher mean mass than the AGN_IR/shock subset, by a factor of ~ 1.5.

Figure 20 Distributions of redshift and mass for G23/WISE AGN_opt galaxies split into a subset dominated by photoionisation (‘/photo’ in the label) and a subset dominated by shock ionisation (‘/shock’ in the label). The sets shown are notAGN_IR/AGN_opt/photo (light grey), notAGN_IR/AGN_opt/shock (blue), AGN_IR/AGN_opt/photo (dark grey), and AGN_IR/AGN_opt/shock (red).

Comparison of the notAGN_IR/photo subset with the notAGN_IR/shock subset shows that the shock-ionised fraction increases with redshift: from near 0 at z < 0.01 to ~50% for z > 0.15. The notAGN_IR/shock subset has a narrower mass distribution than the photoionised subset and higher mean mass, by a factor of ~ 1.6. For the notAGN_IR, the shock-ionised subsets are shifted to higher redshift and to higher mass compared to the photoionised subsets. Because of the correlation of mass with redshift (see Figure 11), which is a selection effect of the galaxy survey, these are not independent effects.