Global millimeter VLBI array survey of ultracompact extragalactic radio sources at 86 GHz
Dhanya G. Nair, Andrei P. Lobanov, Thomas P. Krichbaum, Eduardo Ros, J. Anton Zensus, Yuri Y. Kovalev, Sang-Sung Lee, Florent Mertens, Yoshiaki Hagiwara, Michael Bremer, Michael Lindqvist, Pablo de Vicente
aa r X i v : . [ a s t r o - ph . GA ] A ug Astronomy & Astrophysicsmanuscript no. DhanyaNair_3mmSurvey_accepted c (cid:13)
ESO 2018August 29, 2018
Global millimeter VLBI array survey of ultracompact extragalacticradio sources at 86 GHz
Dhanya G. Nair , Andrei P. Lobanov , , Thomas P. Krichbaum , Eduardo Ros , J. Anton Zensus ,Yuri Y. Kovalev , , , Sang-Sung Lee , Florent Mertens , Yoshiaki Hagiwara , Michael Bremer ,Michael Lindqvist , and Pablo de Vicente Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, 53121 Bonn, Germany Institut für Experimentalphysik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany Astro Space Center of Lebedev Physical Institute, Profsoyuznaya 84 /
32, 117997 Moscow, Russia Moscow Institute of Physics and Technology, Dolgoprudny, Institutsky per., 9, Moscow region, 141700, Russia Korea Astronomy and Space Science Institute, Daedeokdae-ro 776, Yuseong-gu, Daejeon 34055, Republic of Korea SRON, Kapteyn Astronomical Institute, Landleven 12, 9747 AD Groningen, Netherlands Institut de Radio Astronomie Millimétrique (IRAM), 300 rue de la Piscine, 38406 Saint Martin d’Hères, France Department of Space, Earth and Environment, Onsala Space Observatory, Sverige, Observatorievägen 90, Onsala, Sweden Observatorio Astronómico Nacional, Observatorio de Yebes, Cerro de la Palera S / N, 19141 Yebes, Spain
ABSTRACT
Context.
Very long baseline interferometry (VLBI) observations at 86 GHz (wavelength, λ = µ as, probing the collimation and acceleration regions of relativistic outflows in active galactic nuclei (AGN). The physical conditionsin these regions can be studied by performing 86 GHz VLBI surveys of representative samples of compact extragalactic radio sources. Aims.
To extend the statistical studies of compact extragalactic jets, a large global 86 GHz VLBI survey of 162 compact radio sourceswas conducted in 2010–2011 using the Global Millimeter VLBI Array (GMVA).
Methods.
The survey observations were made in a snapshot mode, with up to five scans per target spread over a range of hour angles inorder to optimize the visibility coverage. The survey data attained a typical baseline sensitivity of 0.1 Jy and a typical image sensitivityof 5 mJy / beam, providing successful detections and images for all of the survey targets. For 138 objects, the survey provides the firstever VLBI images made at 86 GHz. Gaussian model fitting of the visibility data was applied to represent the structure of the observedsources and to estimate the flux densities and sizes of distinct emitting regions (components) in their jets. These estimates were usedfor calculating the brightness temperature ( T b ) at the jet base (core) and in one or more moving regions (jet components) downstreamfrom the core. These model-fit-based estimates of T b were compared to the estimates of brightness temperature limits made directlyfrom the visibility data, demonstrating a good agreement between the two methods. Results.
The apparent brightness temperature estimates for the jet cores in our sample range from 2 . × K to 1 . × K, withthe mean value of 1 . × K. The apparent brightness temperature estimates for the inner jet components in our sample rangefrom 7 . × K to 4 . × K. A simple population model with a single intrinsic value of brightness temperature, T , is appliedto reproduce the observed distribution. It yields T = (3 . + . − . ) × K for the jet cores, implying that the inverse Compton lossesdominate the emission. In the nearest jet components, T = (1 . + . − . ) × K is found, which is slightly higher than the equipartitionlimit of ∼ × K expected for these jet regions. For objects with su ffi cient structural detail detected, the adiabatic energy lossesare shown to dominate the observed changes of brightness temperature along the jet. Key words. galaxies: active – galaxies: jets – galaxies: quasars: general – radio continuum: galaxies – techniques: interferometric –surveys
1. Introduction
VLBI (Very long baseline interferometry) observations at86 GHz (wavelength, λ = ∼ (40 –100) µ as. This resolution corresponds to linear scales as small as 10 –10 Schwarzschild radii and uncovers the structure of the jet re-gions where acceleration and collimation of the flow takes place(Vlahakis & Königl 2004; Lee et al. 2008, 2016; Asada et al.2014; Boccardi et al. 2016; Mertens et al. 2016).To date, five 86 GHz VLBI surveys have been conducted(Beasley et al. 1997; Lonsdale et al. 1998; Rantakyrö et al.1998; Lobanov et al. 2000; Lee et al. 2008, see Table 1), withthe total number of objects imaged reaching just over a hun- dred. No complete sample of objects imaged at 86 GHz hasbeen established so far. Recent works (e.g., Homan et al. 2006;Cohen et al. 2007; Lister et al. 2016) have demonstrated thathigh-resolution studies of complete (or nearly complete) samplesof compact jets yield a wealth of information about the intrinsicproperties of compact extragalactic flows.Measuring brightness temperature in a statistically viablesample enables the performance of detailed investigations of thephysical conditions in this region. The distribution of observedbrightness temperatures, T b , derived at 86 GHz can be combinedwith the T b distributions measured at lower frequencies (e.g.,Kovalev et al. 2005). This can help to constrain the bulk Lorentzfactor, Γ j , and the intrinsic brightness temperature, T , of the jetplasma, using di ff erent types of population models of relativis- Article number, page 1 of 25 ic jets (Vermeulen & Cohen 1994; Lobanov et al. 2000; Lister2003; Homan et al. 2006). Changes of T in the compact jetswith frequency can be used to distinguish between the emis-sion coming from accelerating or decelerating plasma and fromelectron-positron or electron-proton plasma. Theoretical modelspredict T ∝ ν ǫ , with ǫ ≈ .
8, below a critical frequency ν break atwhich energy losses begin to dominate the emission (Marscher1995). Above ν break , ǫ can vary from − +
1, depending onthe jet composition and dynamics. By measuring this break andthe power-law slopes above and below, it would be possible todistinguish between di ff erent physical situations in the compactjets.Previous studies (Lobanov et al. 2000; Lee et al. 2008) indi-cate that the value of ν break is likely to be below 86 GHz. Indeed,a compilation of brightness temperatures measured at 2, 8, 15,and 86 GHz (Lee et al. 2008) indicates that brightness tempera-tures measured at 86 GHz are systematically lower and ν break canbe as low as 20 GHz. This needs to be confirmed on a completesample observed at 86 GHz. If T starts to decrease at 86 GHz,there will be only a few sources suitable for VLBI >
230 GHzand higher frequencies. Such a decrease of T will also pro-vide a strong argument in favour of the decelerating jet modelor particle-cascade models as discussed by Marscher (1995). Inview of these arguments, it is important to undertake a dedicated86 GHz VLBI study of a larger complete sample of extragalacticradio sources.In this paper, we present results from a large global VLBIsurvey of compact radio sources carried out in 2010–2011 withthe Global Millimeter VLBI Array (GMVA) . This survey hasprovided images of 162 unique radio sources, increasing the to-tal number of sources ever imaged with VLBI at 86 GHz by afactor of 1.5. The combined database resulting from this surveyand Lee et al. (2008) comprises 256 sources. This informationprovides a basis for investigations of the collimation and accel-eration of relativistic flows and probing the physical conditionsin the vicinity of supermassive black holes.The survey data reach a typical baseline sensitivity of 0.1 Jyand a typical image sensitivity of 5 mJy / beam. A total of 162unique compact radio sources have been observed in this surveyand all the sources are detected and imaged. With the presentsurvey, the overall sample of compact radio sources imaged withVLBI at 86 GHz is representative down to ∼ . δ ≥ ◦ .Section 2 describes the source selection and the survey obser-vations. In Section 3, we describe the data processing, amplitudeand phase calibration, imaging, model fitting procedures and amethod for estimating errors of the model-fit parameters. Sec-tion 4 describes the images and derived parameters of the targetsources. Examples of images of four selected sources obtainedfrom the survey data are presented in Section 4.1 (the completeset of images of all of the target sources is presented in Appendixavailable electronically). Brightness temperatures of the surveysources are derived and discussed in Section 4.3. Section 5.1 de-scribes population modelling of the brightness temperature dis-tribution observed at the base (VLBI core) of the jet and in theinnermost moving jet components. Evolution of the observedbrightness temperature along the jet is studied in Section 5.2 forthe target sources with su ffi cient extended emission detected. http: // / div / vlbi / globalmm / .
2. GMVA survey of compact AGN
Dedicated VLBI observations at 86 GHz are made with theGMVA and with the Very Long Baseline Array (VLBA) work-ing in a stand-alone mode (VLBA also takes part in GMVAobservations). The GMVA has been operating since 2002, su-perseding the operations of the Coordinated Millimeter VLBIArray (CMVA; Rogers et al. 1995) and earlier ad hoc arrange-ments employed since the early 1980s (Readhead et al. 1983).The GMVA carries out regular, coordinated observations at 86GHz, providing good quality images with a typical angular res-olution of ∼ (50–70) µ as.The array comprises up to 16 telescopes located in Europe,the USA and Korea operating at a frequency of 86 GHz. The fol-lowing telescopes took part in the GMVA observations for thissurvey in 2010 and 2011: eight VLBA antennae equipped with3 mm receivers, the IRAM (Institut de Radio Astronomie Mil-limétrique) 30 m telescope on Pico Veleta (Spain), the phasedsix-element IRAM interferometer on Plateau de Bure (France),the MPIfR (Max-Planck-Institut für Radioastronomie) 100 m ra-dio telescope in E ff elsberg (Germany), the OSO (Onsala SpaceObservatory) 20 m radio telescope at Onsala (Sweden), the 14 mtelescope in Metsähovi (Finland), and the OAN (ObservatorioAstronómico Nacional) 40 m telescope in Yebes (Spain). The prime aims of the survey were to establish a complete sam-ple of compact radio sources imaged with VLBI at 86 GHz andto study their morphology and polarization, to study the distri-bution of brightness temperatures, to investigate collimation and -3 -2 -1 S (Jy) N u m b e r QuasarsBL Lac objectsGalaxiesUnidentifiedLee et al. 2008
Fig. 1.
Distribution of the total single dish flux density of the sources,measured at 86 GHz at Pico Veleta or Plateau de Bure during the obser-vations, S , broken down according to di ff erent host galaxy types andcompared to the respective distribution for the sources from the sam-ple of Lee et al. (2008). The present survey provides a nearly twofoldincrease in the number of objects imaged with VLBI at 3 mm. acceleration of relativistic flows and to probe physical condi-tions in the vicinity of supermassive black holes. To meetthese aims, the survey target source list has been compiledfrom the MOJAVE (Monitoring of Jets in Active Galactic Nu- Very Long Baseline Array of the National Radioastronomy Observa-tory, Socorro, NM; https: // / .Article number, page 2 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz clei with VLBA Experiments) sample (Kellermann et al. 2004;Kovalev et al. 2005; Lister & Homan 2005; Lister et al. 2009),using the following selection criteria: a)
15 GHz correlated fluxdensity, S c ≥ . ≥
400 M λ ; b) compactnessat longest spacings, S c / S VLBA ≥ . S VLBA is the 15 GHztotal clean flux density; c) declination δ ≥ ◦ . With these se-lection criteria, a total of 162 unique sources have been selected,comprising 89 quasars, 26 BL Lac objects, 22 radio galaxies and25 unidentified sources. Eight bright sources, 3C 84, OJ 287,3C 273B, 3C 279, 3C 345, BL Lac, 0716 +
714 and 3C 454.3 havebeen added to this list for fringe finding and calibration purposes.The basic information about the selected target sources is sum-marized in Table 5.The distribution of the total single dish flux of the sources,measured at 86 GHz at Pico Veleta or Plateau de Bure during theobservations, is shown in Figure 1 and compared with the re-spective distribution of the source sample observed in Lee et al.(2008). This comparison shows that our survey observationsprobe objects at about one order of magnitude weaker sourcesand provide a roughly twofold increase of the total number ofobjects imaged with VLBI at 3 mm wavelength (see Table 5 fordetails).
The survey observations have been made over a total of six days(144 hours), scheduled within three separate GMVA sessions.Up to 14 telescopes took part in the observations (see Table 2).The observations were typically scheduled with five scans perhour, each of 300 seconds in duration. Gaps of five to ten min-utes were introduced between the scans for antennae pointingat E ff elsberg (Eb) and Pico Veleta (Pv) and for phasing of thePlateau de Bure (Pb) interferometer. This observing schemeyielded the total of 720 scans distributed between 174 observingtargets (162 unique radio sources), ensuring that each object wasobserved with four to five scans distributed over a wide range ofhour angles. Despite the rather modest observing time spent oneach target, the large number of participating antennae ensuredgood uv -coverages for all survey sources down to the lowest de-clinations (see Figure 2).The observations were performed at a sampling rate of512 Mbit / sec and with a two–bit sampling. There were four in-termediate frequencies (IFs) in Epoch A and C, and two IFs inEpoch B. The typical baseline sensitivities for a 20–second in-tegration time are ≈ .
05 Jy on the Pb–Pv baseline, ≈ . ≈ . / Pv andother antennae, and ≈ . ∼ / beam, which is su ffi -cient to obtain robust images of most of the survey sources.
3. Data processing
The data were correlated at the DiFX correlator (Deller et al.2011) of the Max-Planck-Institut für Radioastronomie (MPIfR)at Bonn. After correlation, the data were loaded into AIPS (As-tronomical Image Processing System; Greisen 1990). After ap-plying the correlator model, the residual fringe delays and rateswere determined and corrected for both within the individualIFs (single-band fringe fitting) and between the IFs (multi-bandfringe fitting). At the first step of the fringe fitting, manual phasecal cor-rection was applied by obtaining the single band delay and de-lay rate solutions from a scan on a strong source that gives highsignal-to-noise ratio (SNR) of the fringe solutions (an SNR ≥ ≈
20 sec)for all the antennae. The resulting fringe solutions were ap-plied to the entire dataset. After the manual phasecal cor-rection, antenna-based global fringe fitting (Schwab & Cotton1983; Alef & Porcas 1986) was performed, setting the solutioninterval to the full scan length in order to improve the detectionSNR. Pico Veleta was used as the reference antenna for almostall the data. Whenever Pico Veleta was not present in the data,Plateau de Bure or Pie Town were used as the reference anten-nae. To minimize the chance of false detections, the data werefringe fitted with a SNR threshold of five and a search windowwidth of 200 nsec for the fringe delay and 400 mHz for the fringerate.Once the global fringe fit was done, the SNR of the fringesolutions were inspected for all the sources, and strong sourceswhich give relatively very high SNR were determined. When-ever feasible, the solutions from those strong sources were in-terpolated to nearby weak sources, using a procedure similar tothat adopted in the similar earlier VLBI survey observations at86 GHz (cf., Lee et al. 2008). Application of the interpolatedsolutions has resulted in the detection of amplitude and phasesignals for all of the survey targets.
A priori amplitude calibration was done using the measured val-ues of antenna gain and system temperature. The weather in-formation from each station during the observation was used tocorrect for the atmospheric opacity. The initial opacity correc-tion was implemented by setting the opacity τ = . T rec . At the second step, the fit-ted receiver temperatures were used as initial values for fittingsimultaneously for τ and T rec .The accuracy and self-consistency of the amplitude calibra-tion was checked with a procedure developed and used in the ear-lier 86 GHz survey experiments (Lobanov et al. 2000; Lee et al.2008). The calibrated visibility data were model fitted for eachof the survey targets, using two-dimensional Gaussian compo-nents and allowing for scaling the individual antenna gains by aconstant factor. The resulting average gain scale corrections arelisted in Table 4. The scale o ff sets are within 25 % for most ofthe antennae, except Metsähovi which had su ff ered from persis-tently bad weather during each of the three observing sessions.The averaged o ff sets are within about 3 % of the unity implyingthat there is no significant bias in the calibration and their r.m.s.(root mean square) is less than 10 % for each of the three observ-ing epochs. Based on this analysis, we conclude that the a prioriamplitude calibration should be accurate to within about 25 %,providing a su ffi cient initial calibration accuracy for the hybridimaging of the source structure. After the phase and amplitude calibration was applied on thedata, the visibility data were averaged for 10 sec for most ofthe sources and in some cases, the data were averaged for 30sec. The data were then processed in the the Caltech DIFMAPsoftware package (Shepherd et al. 1994), modelling them withcircular Gaussian patterns (model fitting; Fomalont 1999) and
Article number, page 3 of 25 able 1.
VLBI surveys at 86 GHz
Survey N ant B rec ∆ S ∆ I m D img N obs N det N img (1) (2) (3) (4) (5) (6) (7) (8) (8)Beasley et al. (1997) 3 112 ∼ . / ∼ . ∼ . ∼
30 70 68 16 12Lobanov et al. (2000) 3–5 224 ∼ . ∼
20 100 28 26 14Lee et al. (2008) 12 256 ∼ . This survey ∼ . ∼ >
400 162 162 162
Columns: / beam]; 6 – typical dynamic range of images; 7 – number of sources observed; 8 – number of sources detected; 9 – numberof sources imaged. Table 2.
Log of survey observations
Part Date N obj Pol. w bit BW n ch n bit Telescopes(1) (2) (3) (4) (5) (6) (7) (8) (9)A Oct 2010 68 LCP 512 128 (4IF x 32) 32 2 8 VLBA + (Eb,On,Mh,Pb,Pv)B May 2011 46 LCP 512 128 (2IF X 64) 64 2 8 VLBA + (Eb,On,Pb,Pv,Mh)C Oct 2011 60 LCP 512 128 (4IF x 32) 32 2 8 VLBA + (Eb,On,Pb,Pv,Mh,Ys) Columns:
Fig. 2.
Examples of uv -coverages of the survey observations for a low declination source (left; J1811 + δ = + ◦ ) and a high declinationsource (right; J0642 + δ = + ◦ ). obtaining hybrid images. The data were not uv -tapered and theimaging was performed using the natural weighting.The initial model fitting was performed on the calibrated dataand was used, in some cases, to facilitate the hybrid imaging.The final model fitting was done on the self-calibrated data re-sulting from the hybrid imaging. The total number of Gaussiancomponents used for model fitting a given source was deter-mined using the χ statistics of the fits. The final models wereobtained when the addition of another Gaussian component did not provide a statistically significant change of the χ agreementfactors (Schinzel et al. 2012).The hybrid imaging procedure comprised theCLEAN deconvolution (Clark 1980) and self calibration(Cornwell & Fomalont 1999; Cornwell 1995). For most ofthe objects, the hybrid imaging procedure was initiated witha point source model. For objects with sparse visibility data,the initial Gaussian model fits were used as the initial models.Only visibility phases were allowed to be modified during theinitial iterations of the hybrid imaging. At the last step, a single Article number, page 4 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Table 3.
Participating telescopes D G T sys η A SEFD ∆ , σ rms Name Code [m] [K / Jy] [K] [Jy] [mJy] [mJy](1) (2) (3) (4) (5) (6) (7) (8) (9)Brewster Br 25 0.033 110 0.22 3333.3 23.44 164.09E ff elsberg Eb 80 † ‡ Columns: ffi ciency; 7 – zenith SEFD; 8 – sensitivity on the baseline to Pico Veleta, for a 20 sec fringe fit interval and 512 Mbps recording rate; 9 – 7 σ detection threshold. Notes: † – e ff ective diameter at 86 GHz; ‡ – e ff ective diameter in the phased array mode. Table 4.
Average antenna gain corrections
Telescope Epoch A Epoch B Epoch C(1) (2) (3) (4)Br 1.008 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± Columns: time constant antenna gain correction factor was applied tothe visibility amplitudes (hence not allowing for time variableantenna gains in order to avoid the imprint of model errors intodata). The parameters of the final images are listed in Table 6,together with the correlated flux densities measured on shortand long baselines.The quality of the residual noise in the final images, whichideally should have a zero-mean Gaussian distribution, waschecked by calculating the expectation value for the maximumabsolute flux density | S r , exp | in a residual image (Lee et al. 2008), | S r , exp | = σ r √ N pix √ πσ r ! , (1) ξ N u m b e r Median: 1.09Mean: 1.10
Fig. 3.
Distribution of the noise quality factor ξ r for the residualimages of all the sources in the survey. where N pix is the total number of pixels in the image. The qualityof the residual noise is given by ξ r = S r / S r , exp , where S r is themaximum flux density in the residual image and σ r is the r.m.snoise in the residual image. When the residual noise approachesGaussian noise, ξ r tends to 1. If ξ r >
1, not all the structure hasbeen adequately recovered; if ξ r <
1, the image model has anexcessively large number of degrees of freedom (Lobanov et al.2006). Figure 3 shows the overall distribution of ξ r for the resid-ual maps of all the sources in this survey. Column 14 in Table 6shows the quality factor, ξ r obtained for all the 3 mm images im-plying that the images adequately represent the source structuredetected in the visibility data. The Gaussianity of the residualnoise is also reflected in the median and the mean of the ξ r dis-tributions, which are within 10 % of the unity factor.In order to check the e ff ect of the amplitude (antenna gain)corrections applied during the final self calibration step, we com- Article number, page 5 of 25
SNR N u m b e r o f o b j e c t s Median: 36.51Mean: 41.98
Fig. 4.
Distribution of the imaging signal-to-noise ratios (SNR) ofall the sources in the survey calculated from the ratio of the peak fluxdensity of the map, S p , to the r.m.s noise in the map, σ rms . pared the visibility amplitudes obtained without and with it. Thiswas done by comparing the ratios of the visibility amplitudes ob-tained without and with the antenna gain correction on short B S and long B L baselines (see Table 6). The average of the ratiosare found to be (1.24 ± ± The final self calibrated data were fitted with circular Gaussiancomponents, using the initial model fits as a starting guess. Theresulting models were used to obtain the total, S tot , and peak fluxdensity, S peak , the size, d , and the positional o ff set, (in polar co-ordinates r , θ ) of the component from the brightest region (core)at the base of the jet, taken to be at the coordinate origin. Theuncertainties of the model parameters were estimated analyti-cally, based on the SNR of detection of individual components,following (Fomalont 1999) and (Schinzel et al. 2012): σ peak = σ rms + S peak σ rms ! / , σ tot = σ peak (cid:18) + S S (cid:19) / ,σ d = d σ peak S peak , σ r = σ d , σ θ = atan (cid:18) σ r r (cid:19) , (2)where σ rms is the r.m.s. noise in the residual image after sub-straction of the Gaussian model fit. To assess whether a givencomponent is extended (resolved), the minimum resolvable sizeof the component was also calculated and compared with the sizeobtained with the model fitting. The minimum resolvable size, d min of a Gaussian component is given in Lobanov (2005) as d min = (1 + β/ π " π a b log SNR + ! / , (3)where a and b are the axes of the restoring beam, SNR is thesignal-to-noise ratio, and β is the weighing function that is 0 for natural weighting or 2 for uniform weighting. For componentsthat have size estimates < d min , the latter is taken as an upperlimit of the size and used for estimating the uncertainties of theother model fit parameters of the respective component (see Ta-ble 7). We use the total flux density S tot and size d of the model fit com-ponents to estimate the brightness temperature, T b = I ν c / k B ν (with ν , k B , and c denoting the observing frequency, the Boltz-mann constant, and the light speed, respectively) of the individ-ual emitting regions in the jets.For a circular Gaussian component, I ν = (4 log 2 / S tot / d ,and the respective brightness temperature can be obtained from T b [K] = . × S tot Jy ! d mas ! − (cid:18) ν GHz (cid:19) − (1 + z ) . (4)The factor (1 + z ) reflects the e ff ect of the cosmological redshift z on the observed brightness temperature. For the sources with un-known redshift, we calculated the brightness temperature simplyin the observer’s frame of reference. If the size of the Gaussiancomponent d is less than d min , given by Equation (3), the latteris used for estimating the lower limit on T b .In addition to this estimate, we also use visibility-based es-timates of brightness temperature (Lobanov 2015) and calculatethe minimum brightness temperature, T b , min [K] = . V q mJy ! (cid:18) B L km (cid:19) , (5)and limiting resolved brightness temperature, T b , lim [K] = . V q + σ q mJy ! (cid:18) B L km (cid:19) ln V q + σ q V q ! − , (6)directly from the visibility amplitude, V q , and its error, σ q , mea-sured at a given long baseline, B L , in the survey data.
4. Results
Using the procedures described above, we have made hybridmaps of all 174 observations of 162 unique sources in this sur-vey. For 138 objects, the survey provides the first ever VLBIimages made at 86 GHz. Most of the imaged sources show ex-tended radio emission, revealing the jet morphology down tosub-parsec scales. For a small number of weaker sources withpoor uv -coverages, only the brightest core at the base of the jetcould be imaged. To illustrate our results, we present imagesof four weak target radio sources J1130 + + + + S L , mea-sured on long baselines and the total flux density, S CLEAN , in theCLEAN images of the observed sources. Both distributions indi-cate that objects with flux densities &
80 mJy can be successfullydetected and imaged with the survey data, signifying the sensi-tivity improvement by a factor of approximately two comparedto the observations presented in Lee et al. (2008). The mean ofthe correlated flux density at the longest baseline, S L , is 0.2 Jy. Article number, page 6 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz -2 -1 S L (Jy) N u m b e r QuasarsBL Lac objectsGalaxiesUnidentified -2 -1 S CLEAN (Jy) N u m b e r QuasarsBL Lac objectsGalaxiesUnidentifiedLee et al. 2008
Fig. 5.
Distribution of the correlated flux densities corresponding to the longest baselines, S L (left) and the total clean image flux density, S CLEAN of the survey targets broken down according to di ff erent host galaxy types (right). The distribution of S CLEAN for the sources in this survey is alsocompared with the respective distribution for the sources from the sample of Lee et al. (2008) on the right panel.
Amongst 157 sources whose S L can be measured at projectedbaselines longer than 2000 M λ , 135 sources have an S L greaterthan 0.1 Jy.In Table 6, we present the basic parameters of the images,listing (1) source name, (2) observing epoch, (3) single dish86 GHz flux density, S , measured at Pico Veleta or Plateaude Bure, (4) correlated flux density on the shortest baseline, S S , (5) shortest baseline, B S , (6) correlated flux density on thelongest baseline, S L , (7) longest baseline, B L , (8) major axis, B a , (9) minor axis, B b , and (10) position angle, B PA of the majoraxis of the restoring beam, (11) total CLEAN flux density, S tot ,and (12) peak flux density, S peak , in the image, (13) image r.m.snoise, σ rms , and (14) the quality factor of the residual noise inthe image, ξ r .Table 7 summarizes the model fits obtained for all of the sur-vey sources providing (1) the source name, (2) observing epoch,(3) sequential number of the Gaussian component, (4) total fluxdensity, S t , and (5) peak flux density, S peak , of the component,(6) size, d , of the component, (7) separation, r , and (8) posi-tion angle, θ of the component with respect to the brightest fea-ture in the model (core, taken to be located at the coordinateorigin), (9) brightness temperature, T b , mod , estimated from themodel fit, and (10) minimum, T b , min and (11) limiting resolved, T b , lim , brightness temperatures estimated from the visibility am-plitudes (Lobanov 2015) at the longest baselines given in Col-umn 7 in Table 6.Table 7 contains the model fit parameters for a total 174VLBI cores and 205 jet components, with 42 and 37 of theseunresolved, as reflected also in the lower limits of the model-fit-based brightness temperature estimates, T b , mod , listed for thesecomponents. Compactness of the source structure can be evaluated by com-paring the single dish flux density, S , listed in Table 6, to thetotal clean flux density, S CLEAN , listed in Table 6 and the coreflux density, S CORE , listed in Table 7, to the total clean flux den-sity, S CLEAN . These comparisons are presented in Figure 7. To study the relation between the total and VLBI flux densi-ties, we apply the Pearson correlation test. The Pearson correla-tion coe ffi cient calculated for S and S CLEAN gives a significantvalue of 0.924 for this survey and 0.908 for this survey com-bined with the results from Lee et al. (2008). The respective plotin the left panel of Figure 7 indicates that almost all the fluxmeasured by a single dish (here Pv or PdB) is recovered in theVLBI clean flux. The median of the core dominance index de-fined as S CORE / S CLEAN is 0.84, and the two are also correlated,as demonstrated in the right panel of Figure 7.Figure 7 shows that the stronger sources have more struc-tures (right panel) some of which are completely resolved outeven on the shortest baselines of the survey observations (leftpanel). A small number of cases for which S CLEAN > S or S CORE > S CLEAN are observed for the weaker objects. These canbe reconciled with the errors in the measurements, and they es-sentially imply very compact objects, with S ≃ S CLEAN and S CORE ≃ S CLEAN , respectively.
In our further analysis, we use the model-fit-based and visibility-based estimates of the brightness temperature of the VLBI brightcore (base) and the inner ( r proj < . × K to 1 . × K. The brightness tem-perature estimates for the inner jet components in our samplerange from 7 . × K to 4 . × K. The median and meanof the brightness temperature distribution for the core regions are8 . × K and 1 . × K, respectively. For the inner jet com-ponents, the respective figures are 7 . × K and 2 . × K.This shows that the brightness temperature drops by approxi-mately an order of magnitude already on sub-parsec scales inthe jets, with inverse Compton, synchrotron, and adiabatic lossessubsequently dominating the energy losses (cf. Marscher 1995;Lobanov & Zensus 1999). Only 8 % of the jet cores show abrightness temperature greater than 5 × K and only 3 % havea brightness temperature greater than 10 K. Article number, page 7 of 25 ig. 6.
GMVA maps of J1130 + + + + uv -coverages (inset in the right panel) of the respective visibility datasets. The contouring of images ismade at 3 σ rms × ( − , , √ , , ... ) levels, with σ rms representing the o ff -source r.m.s noise in the residual image. The lowest contour in the maps, L = / beam, 15.8 mJy / beam, 18.8 mJy / beam, and 26.6 mJy / beam, respectively. A total of 174 contour maps of 162 unique sources at 3 mmin this survey are available in the online journal. We also inspect the distribution of the minimum and max-imum limiting brightness temperature of the core components(using averaged values of brightness temperature for objectswith multiple observations) in the sample, making these esti- mates from the visibility amplitudes on the longest baselines(Lobanov 2015). The minimum, T b , min , and limiting, T b , lim ,brightness temperatures are given in Table 7, in columns 10 and11, respectively. Article number, page 8 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz -1 log S CLEAN [Jy] -1 l o g S [ J y ] ρ (S ,S CLEAN ) = 0.908 This surveyLee et al. 2008 -1 log S CLEAN [Jy] -1 l o g S C O R E [ J y ] ρ (S CORE ,S CLEAN ) = 0.874 This surveyLee et al. 2008
Fig. 7.
Compactness parameters, S / S CLEAN and S core / S CLEAN are shown on the left and right panel respectively, where S is the single dish86 GHz flux density measured at Pico Veleta or Plateau de Bure. The Pearson correlation coe ffi cients ρ ( S , S CLEAN ) = ρ ( S CORE , S CLEAN ) = The median and mean of the maximum limiting brightnesstemperature distribution for the core regions is 1 . × K and3 . × K, respectively. We find that the limiting T b , lim cor-relates well with T b , mod estimated from imaging method as seenin Figure 8, supporting the fidelity of T b , mod measurements ob-tained from model fitting. The residual logarithmic distributionof the T b , mod / T b , lim ratio is well approximated by the GaussianPDF, with mean value, µ = σ =
5. Discussion
The brightness temperature distribution can be used for obtain-ing estimates of the conditions in the extra galactic radio sourcesand to test the models proposed for the inner jets (Marscher1995; Lobanov et al. 2000; Homan et al. 2006; Lee et al. 2008).A basic population model (Lobanov et al. 2000) can be usedfor representing the observed brightness temperature distribu-tion under the assumption that the jets have the same intrinsicbrightness temperature, T , Lorentz factor, Γ j , and synchrotronspectral index, α ( S ν ∝ ν α ), and they are randomly orientedin space (within the limits of viewing angles, θ , required byDoppler boosting bias). The jets are also assumed to remainstraight within the spatial scales ( ∼ . −
10 pc) probed by theobservations.The assumptions of single values of T and Γ j describing thewhole sample are clearly simplified, as jets are known to featurea range of Lorentz factors (see Lister et al. 2016, and referencestherein). However, as has been shown earlier (Lobanov et al.2000), factoring a distribution of Lorentz factors into the presentmodel is not viable without amending the brightness temperaturemeasurements with additional information, preferably about theapparent speeds of the target sources. We are currently compil-ing such a combined database, and will engage in a more de- tailed modelling of the compact jets after the completion of thisdatabase.In a population of jets described by the settings summa-rized above, the measured brightness temperature, T b , is de-termined solely by the relativistic Doppler boosting of the jetemission. Therefore, the observed brightness temperature , T b ,can be related to the intrinsic brightness temperature, T , so that T b = T δ /ǫ , where the power index ǫ is 1 / (2 − α ) for a contin-uous jet (steady state jet) and 1 / (3 − α ) for a jet with sphericalblobs (or optically thin “plasmoids”), and δ is the Doppler factor.The probability of finding a radio source with the brightnesstemperature T b in such a population of sources is p ( T b ) ∝ " Γ j ( T b / T ) ǫ − ( T b / T ) ǫ − Γ − . (7)The lower end of the observed distribution of brightnesstemperatures depends on the sensitivity of VLBI data sincethe flux of the observed sample is biased by Doppler boosting(Lobanov et al. 2000). The lowest brightness temperature thatcan be measured from our data, T b , sens , can be obtained from T b , sens [K] = . × σ rms mJy / beam ! b mas ! − , (8)where σ rms is the array sensitivity in mJy / beam and b is the av-erage size of the resolving beam. In this survey, the typical ob-servation time on a target source ∆ t is 20 minutes and band-width is 128 MHz. Therefore, the value of beam size for thesources in this survey is 0.12 mas and the σ rms of the array is0.54 mJy / beam. Thus, we have obtained a 3 σ level estimationof T b , sens as 2.0 × K using Equation 8, which is set as thelowest brightness temperature in modelling.We normalize the results obtained from Equation (7) to thenumber of objects in the lowest bin of the histogram. For ourmodelling, we first make a generic assumption of α = − . Γ j ≈
10 implied
Article number, page 9 of 25 .0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 log T b,mod [K] l o g T b ,li m [ K ] Resolved VLBI coresUnresolved VLBI cores −1.0 −0.5 0.0 0.5 1.0 1.5 2.0 log T b,lim - log T b,mod N u m b e r o f o b j e c t s µ =0.001, σ =0.460 Fig. 8.
Comparison of T b , mod measured from circular Gaussian rep-resentation of source structure and T b , lim estimated from the interfero-metric visibilities at uv -radii within 10% of the maximum baseline B max in the data for a given source (top panel). Correlation between the twodistributions is illustrated by the residual logarithmic distribution of the T b , mod / T b , limit ratio (bottom panel), which is well approximated by theGaussian distribution with µ = σ = from the kinematic analysis of the MOJAVE VLBI survey data(Lister et al. 2016). We assume that the jet is continuous, so ǫ = T are shown in Figures (9–10) for the VLBI cores andthe inner jet components, respectively.This approach yields T , core = (3 . + . − . ) × K for theVLBI cores and T , jet = (1 . + . − . ) × K for the in-ner jet components. The estimated T , core is in good agree-ment with the inverse Compton limit of ≃ × K(Kellermann & Pauliny-Toth 1969), beyond which the inverseCompton e ff ect causes rapid electron energy losses and extin-guishes the synchrotron radiation. The inferred T , jet of jet com-ponents are about a factor of three higher than the equipartitionlimit of ≃ × K (Readhead et al. 1983) for which the mag-netic field energy and particle energy are in equilibrium. Thismay indicate that opacity is still non-negligible in these regions
Brightness temperature [10 K] N u m b e r o f s o u r c e s γ =10 To =3.2x10^10 KTo =1.0x10^11 KTo =3.77x10^11 KTo =4.2x10^11 KBin size =5.0x10^10 K
Fig. 9.
Distribution of the brightness temperatures, T b , mea-sured in the core components and represented by the population mod-els calculated for Γ j =
10 and di ff erent values of T . The best ap-proximation of the observed T b distribution is obtained with T o , core = (3 . + . − . ) × K. For better viewing of the observed distribution, onecore component with a very high T b = . × K for the source BLLac obtained from Lee et al. (2008) is not shown but is included in themodelling.
Brightness temperature [10 K] N u m b e r o f s o u r c e s γ =10 To =5.0x10^9 KTo =5.0x10^10 KTo =1.42x10^11 KTo =2.0x10^11 KBin size =4.0x10^9 K
Fig. 10.
Distribution of the brightness temperatures, T b , measuredin the inner jet components and represented by the population mod-els calculated for Γ j =
10 and di ff erent values of T . The best ap-proximation of the observed T b distribution is obtained with T o , jet = (1 . + . − . ) × K. of the flow. The intrinsic brightness temperature obtained forthe cores is within the upper limit 5 . × K predicted for thepopulation modelling of the cores (Lobanov et al. 2000).A simultaneous fit for T and Γ j is impeded by the implicitcorrelation, T ∝ Γ a j (with a ≈ T [K] ≈ (7 . × ) Γ . canbe inferred for the fit to the brightness temperatures measured inthe VLBI cores. This correlation between T and Γ j precludessimultaneously fitting for both these parameters, and hence the Article number, page 10 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Intrinsic brightness temperature, T [K] L o r e n t z F a c t o r , Γ j T [K] ≈ (7.7 ×10 ) Γ j δ χ = χ + 2.3 (1σ contours) χ χ Fig. 11.
Two-dimensional χ distribution plot in the Γ j – T space, calculated for the brightness temperatures measured in the VLBI cores. Theblank area shows the ranges of the parameter space disallowed by the observed distribution. The distribution of the χ values indicates a ( Γ j – T )correlation, with T [K] ≈ (7 . × ) Γ . , thus precluding a simultaneous fit for Γ j and T . Lorentz factor has to be constrained (or assumed) separately.One should also keep in mind that this correlation results fromthe model description and does not have an immediate physicalimplication. Equation (7) clearly shows that the predicted distri-bution of T b is valid within the range( Γ j − q Γ − ≤ ( T T b ) ǫ ≤ ( Γ j + q Γ − . (9)The region outside this range is represented by the blank area inFigure 11.The intrinsic brightness temperature we obtained is higherthan the mean and median observed brightness temperature T b .This is readily explained by the Doppler deboosting. For a givenviewing angle, θ , sources with Γ j > /θ would be deboosted sothat the observed brightness temperature will be reduced belowits intrinsic value. It can be easily shown that the observed andintrinsic brightness temperatures are equal if the jet viewing an-gle is given by θ eq = arccos − (1 / Γ j ) ( T / T b ) ǫ q − Γ − . (10)For the VLBI cores, the mean of the observed T b is 1 . × Kand intrinsic T , core is 3 . × K, therefore, the resulting θ eq = ◦ for Γ j =
10 and ǫ = T b than intrinsic T . As discussed in Sections 4.3 and 5.1, intrinsic T and the ob-served T b in core and jets show that the brightness tempera-ture drops by approximately a factor of two to ten already onsub-parsec scales in the jets. This evolution might occur withthe inverse Compton, synchrotron, and adiabatic losses sub-sequently dominating the energy losses (cf., Marscher 1995;Lobanov & Zensus 1999).For four objects in our data (3C84, 0716 + + N ( E ) dE ∝ E − s dE , where s is the energy spectralindex that depends on spectral index α as α = (1 − s ) /
2, and ispervaded by the magnetic field B ∝ d − a , where d is the width ofthe jet and a depends on the type of magnetic field ( a = Article number, page 11 of 25 -2 -1 Component Size [mas] T b [ K ] J2322+5057 -2 -1 Component Size [mas] T b [ K ] J1033+6051 -2 -1 Component Size [mas] T b [ K ]
3C 345 -2 -1 Component Size [mas] T b [ K ] Fig. 12.
Changes of the brightness temperature as a funcion of jet width for four sources – J2322 + + + T b from this survey. The red circles connected with a dotted line represent theoreticallyexpected T b under the assumption of adiabatic jet expansion. The initial brightness temperature in each jet is assumed to be the same as thatmeasured in the VLBI core. these assumptions, we can relate the brightness temperatures, T b , J , of the jet components to the brightness temperature, T b , C ,of the core (Lobanov et al. 2000; Lee et al. 2008), T b , J = T b , C d J d C ! − ξ , (11)where d J and d C are the measured sizes of the jet component andcore, respectively, and ξ = s + + a ( s + . (12)Assuming the synchrotron emission with spectral index α = -0.5, we use s = . a = . T b , J for individual jet components and comparethem in Figure 12 to the measured brightness temperatures. Themeasured and predicted values of brightness temperature agreewell, and this suggests that the jet components can be viewedas adiabatically expanding relativistic shocks (cf., Kadler et al.2004; Pushkarev & Kovalev 2012; Kravchenko et al. 2016).
6. Summary
We have used the Global Millimeter VLBI Array (GMVA) toconduct a large global 86 GHz VLBI survey comprising 174snapshot observations of 162 unique targets selected from a sam-ple of compact radio sources. The survey observations havereached a typical baseline sensitivity of 0.1 Jy and a typical im-age sensitivity of 5 mJy / beam, owing to the increased recordingbandwidth of the GMVA observations and the participation ofvery sensitive European antennae at Pico Veleta and Plateau deBure. All of the 162 objects have been detected and imaged,thereby increasing the total number of AGN imaged with VLBIat 86 GHz by a factor of ∼ .
5. We imaged 138 sources for thefirst time with VLBI at 86 GHz through this survey.We have used Gaussian model fitting to represent the struc-ture of the observed sources and estimate the flux densities andsizes of the core and jet components. We used the model fit pa-rameters and visibility data on the longest baselines to make in-dependent estimates of brightness temperatures at the jet base asdescribed by the most compact and bright “VLBI core” compo-nent. These estimates are consistent with each other. For sourceswith extended structure detected, the model fit parameters havebeen also used to calculate brightness temperature in the jet com-
Article number, page 12 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz ponents downstream from the core. The apparent brightnesstemperature estimates for the jet cores in our sample range from2 . × K to 1 . × K, with the mean value of 1 . × K.The brightness temperature estimates for the inner jet compo-nents in our sample range from 7 . × K to 4 . × K. Theoverall amplitude calibration error for the observations is about25%.We describe the observed brightness temperature distribu-tions by a basic population model which assumes that all jets areintrinsically similar and can be described by a single value of theintrinsic brightness temperature, T , and Lorentz factor, Γ j . Thepopulation modelling shows that our data are consistent with apopulation of sources that has T = (3 . + . − . ) × K in theVLBI cores and T = (1 . + . − . ) × K in the jets, both ob-tained for Γ j =
10 adopted from the kinematic analysis of theMOJAVE VLBI survey of AGN jets (Lister et al. 2016). A cor-relation between T and Γ j inherent to the model description pre-cludes fitting for these two parameters simultaneously. We findthat a relation T [K] ≈ (7 . × ) Γ . is implied for this mod-elling framework by the survey data. For sources with su ffi cientstructural detail, there is an agreement between the brightnesstemperatures measured in multiple components along the jet andthe predicted brightness temperatures for relativistic shocks withadiabatic losses dominating the emission.The results of the survey can be combined with brightnesstemperature measurements made from VLBI observations atlower frequencies ( e.g., Kovalev et al. 2005; Petrov et al. 2007)to study the evolution of T o with frequency and along the jet(Lee et al. 2008, 2016). This approach can be used to better con-strain the bulk Lorentz factor and the intrinsic brightness tem-perature, to distinguish between the acceleration and decelera-tion scenario for the flow (cf., Marscher 1995), and to test sev-eral alternative acceleration scenarios including hydrodynamicacceleration (Bodo et al. 1985), acceleration by tangled mag-netic field (Heinz & Begelman 2000), and magnetohydrodynam-ics acceleration (Vlahakis & Königl 2004). Acknowledgments
We thank the sta ff of the observatories participating in the GMVA, theMPIfR E ff elsberg 100 m telescope, the IRAM Plateau de Bure Interfer-ometer, the IRAM Pico Veleta 30 m telescope, the Metsähovi Radio Ob-servatory, the Onsala Space Observatory, and the VLBA. The VLBA isan instrument of the National Radio Astronomy Observatory, which is afacility of the National Science Foundation operated under cooperativeagreement by Associated Universities, Inc. This research has made useof the NASA / IPAC Extragalactic Database (NED) which is operated bythe Jet Propulsion Laboratory, California Institute of Technology, un-der contract with the National Aeronautics and Space Administration.This research has made use of the SIMBAD database, operated at CDS,Strasbourg, France and also the Sloan Digital Sky Survey (SDSS).Dhanya G. Nair is a member of the International Max Planck Re-search School (IMPRS) for Astronomy and Astrophysics at the Univer-sities of Bonn and Cologne. Thanks to Biagina Boccardi, Jun Liu, LauraVega García, Jae-Young Kim, Ioannis Myserlis, Vassilis Karamanavis,Je ff Hodgson, Shoko Koyama, Bindu Rani and Karl M. Menten fortheir valuable suggestions and support in this research. The author alsothanks Walter Alef and Alessandra Bertarini for helping in the corre-lation of the 86 GHz VLBI data used in this research. Thanks to UweBach and Salvador Sánchez who have helped in the observation andcalibration at E ff elsberg radio telescope and IRAM Pico Veleta radiotelescope, respectively. Sang-Sung Lee was supported by the NationalResearch Foundation of Korea (NRF) grant funded by the Korea gov-ernment (MSIP) (No. NRF-2016R1C1B2006697). Yuri Y. Kovalev wassupported in part by the government of the Russian Federation (agree- ment 05.Y09.21.0018) and by the Alexander von Humboldt Founda-tion. References
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List of Sources
Source (J2000) Source (B1950) Common Name Epoch α δ z Type m v (1) (2) (3) (4) (5) (6) (7) (8) (9)J0013 + +
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813 B 00 17 08.474904 +
81 35 08.13656 3.3660 Q 16.5J0030 + +
703 B 00 30 14.412959 +
70 37 40.06069 . . . U 17.0J0034 + +
276 C 00 34 43.486179 +
27 54 25.72112 2.9642 G 18.0J0044 + +
677 B 00 44 50.759603 +
68 03 02.68574 . . . U . . .J0046 + +
246 A 00 46 07.825730 +
24 56 32.52437 0.7467 Q 17.1J0057 + +
300 NGC 315 A 00 57 48.883342 +
30 21 08.81194 0.0165 G 12.2J0102 + +
581 7C 0059 + +
58 24 11.13659 0.6440 Q 17.6J0109 + +
612 B 01 09 46.344370 +
61 33 30.45531 0.7830 G 19.4J0112 + +
351 A 01 12 12.944409 +
35 22 19.33615 0.4500 Q 17.8J0113 + +
495 A 01 13 27.006813 +
49 48 24.04306 0.3890 Q 18.4J0126 + +
705 B 01 26 7.8495750 +
70 46 52.38656 . . . U 18.7J0136 + +
476 DA 55 B,C 01 36 58.594700 +
47 51 29.10000 0.8590 Q 18.0J0137 + +
215 A 01 37 15.624949 +
21 45 44.27088 . . . U . . .J0154 + +
474 B 01 54 56.289889 +
47 43 26.53956 1.0260 Q . . .J0205 + +
319 A 02 05 04.925360 +
32 12 30.09541 1.4660 Q 18.2J0253 + +
320 A 02 53 33.650138 +
32 17 20.89168 0.8590 Q . . .J0254 + +
235 A 02 54 24.718127 +
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380 B 03 10 49.879930 +
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411 NRAO 128 B 03 13 01.962125 +
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222 C 03 25 36.814357 +
22 24 00.36551 2.0660 Q 18.9J0325 + +
467 C 03 25 20.303800 +
46 55 06.63500 . . . B 14.1J0333 + +
654 C 03 33 56.737600 +
65 36 56.18400 . . . B 19.3J0344 + +
683 A,C 03 44 41.441278 +
68 27 47.81028 . . . U . . .J0359 + +
322 A 03 59 44.912917 +
32 20 47.15548 1.3310 Q 19.9J0359 + +
508 NRAO 150 A 03 59 29.747200 +
50 57 50.16100 1.5200 Q 22.9J0428 + +
328 A 04 28 05.808725 +
32 59 52.04381 0.4760 Q 20.2J0512 + +
406 A 05 12 52.542864 +
40 41 43.62019 . . . Q . . .J0533 + +
483 A 05 33 15.865792 +
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245 4C 24.11 A 06 04 55.121380 +
24 29 55.03635 1.1330 G . . .J0612 + +
413 A 06 12 51.185236 +
41 22 37.40815 . . . B 15.7J0618 + +
421 A 06 18 08.619909 +
42 07 59.84609 . . . U . . .J0632 + +
320 A 06 32 30.782861 +
32 00 53.63193 1.8310 Q . . .J0638 + +
595 B 06 38 02.871950 +
59 33 22.21466 . . . B . . .J0639 + +
734 C 06 39 21.961200 +
73 24 58.04000 1.8500 Q 17.8J0642 + +
882 C 06 42 6.1363170 +
88 11 55.01734 . . . B 19.5J0650 + +
600 B 06 50 31.254355 +
60 01 44.55601 0.4550 Q 18.9J0700 + +
172 A 07 00 01.525539 +
17 09 21.70130 . . . U 21.0J0707 + +
612 B 07 07 00.615678 +
61 10 11.60689 . . . U 17.0J0713 + +
196 WB92 0711 + +
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714 S5 0716 +
71 B,C 07 21 53.448400 +
71 20 36.36300 0.3000 B 15.5J0733 + +
504 C 07 33 52.520500 +
50 22 09.06200 0.7200 Q 19.0J0741 + +
313 OI 363 C 07 41 10.703310 +
31 12 00.22894 0.6320 Q 16.7J0747 + +
767 B 07 47 14.607565 +
76 39 17.27140 . . . B 20.0J0748 + +
241 S3 0745 +
24 C 07 48 36.109275 +
24 00 24.11002 0.4092 Q 19.7J0753 + +
540 4C 54.15 C 07 53 01.384569 +
53 52 59.63709 0.2000 B 18.5J0808 + +
410 C 08 08 56.652043 +
40 52 44.88880 1.4193 Q 19.0J0809 + +
538 C 08 09 41.732819 +
53 41 25.09245 2.1330 Q 19.8J0814 + +
646 C 08 14 39.190224 +
64 31 22.02696 . . . B 17.9J0815 + +
367 C 08 15 25.944861 +
36 35 15.14876 1.0286 Q 18.0J0817 + +
326 C 08 17 28.542305 +
32 27 02.92601 . . . G 21.6J0824 + +
394 4C 39.23 C 08 24 55.483855 +
39 16 41.90401 1.2159 Q 18.3J0854 + +
202 OJ 287 B 08 54 48.874900 +
20 06 30.64100 0.3060 B 14.0J0909 + +
430 A 09 09 33.497140 +
42 53 46.48213 0.6704 G 20.0J0917 + +
657 C 09 17 55.568093 +
65 30 15.12741 . . . U . . .J0920 + +
449 A 09 20 58.458486 +
44 41 53.98499 2.1890 Q 18.1J0925 + +
364 A 09 25 51.851387 +
36 12 35.67435 1.0150 U 19.3J0927 + +
392 4C 39.25 C 09 27 03.013934 +
39 02 20.85186 0.6950 Q 17.9J0937 + +
503 C 09 37 12.327300 +
50 08 52.09700 0.2757 G 18.9J0945 + +
358 A 09 45 38.120719 +
35 34 55.08842 1.1283 Q 18.8J0956 + +
254 OK 290 A 09 56 49.875378 +
25 15 16.04976 0.7120 Q 17.5J0957 + +
556 C 09 57 38.184500 +
55 22 57.76800 0.8990 B 17.7J0958 + +
476 OK 492 C 09 58 19.671640 +
47 25 07.84244 1.8815 Q 18.8J1013 + +
250 A 10 13 53.428771 +
24 49 16.44062 1.6360 Q 15.4J1018 + +
359 B2 1015 +
35B C 10 18 10.988093 +
35 42 39.44094 1.2280 Q 18.6J1033 + +
415 C 10 33 03.707872 +
41 16 06.23282 1.1185 Q 19.6J1033 + +
611 C 10 33 51.428900 +
60 51 07.33500 1.4010 Q 18.9J1038 + +
430 C 10 38 18.190536 +
42 44 42.75990 0.3055 Q 18.4J1043 + +
244 B2 1040 +
24A A 10 43 09.035778 +
24 08 35.40922 0.5590 Q 17.7J1044 + +
811 B 10 44 23.062546 +
80 54 39.44301 1.2600 Q 16.5J1045 + +
178 A 10 45 14.359788 +
17 35 48.08359 0.9210 U 21.8J1058 + +
815 B 10 58 11.535395 +
81 14 32.67511 0.7060 Q 18.5J1103 + +
305 B 11 03 13.301905 +
30 14 42.70196 0.3838 G 18.3
Article number, page 14 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Table 5.
List of Sources (continued)
Source (J2000) Source (B1950) Common Name Epoch α δ z Type m v (1) (2) (3) (4) (5) (6) (7) (8) (9)J1130 + +
385 B 11 30 53.282615 +
38 15 18.54688 1.7330 Q 18.6J1146 + +
402 B 11 46 58.297920 +
39 58 34.30434 1.0880 Q 18.0J1152 + +
499 B 11 52 32.871056 +
49 39 38.76785 1.0931 Q 16.6J1153 + +
497 4C 49.22 B 11 53 24.466600 +
49 31 08.83000 0.3334 Q 17.1J1153 + +
812 B 11 53 12.499212 +
80 58 29.15456 1.2500 Q 18.5J1200 + +
532 C 12 00 11.384309 +
53 00 46.87708 1.9970 Q 19.7J1203 + +
483 C 12 03 29.853038 +
48 03 13.62592 0.8133 G 16.4J1219 + +
640 C 12 19 10.583100 +
63 44 10.71688 . . . U 22.5J1224 + +
216 4C 21.35 A 12 24 54.458398 +
21 22 46.38854 0.4335 Q 17.5J1229 + +
023 3C 273B A,B 12 29 06.699700 +
02 03 08.59800 0.1583 B 12.9J1241 + +
552 C 12 41 27.703846 +
54 58 19.05549 . . . U 22.1J1256-0547 1253-055 3C 279 B 12 56 11.166500 -05 47 21.52500 0.5362 Q 15.2J1259 + +
515 C 12 59 31.173983 +
51 40 56.26083 . . . U 19.9J1306 + +
557 C 13 06 03.351107 +
55 29 43.85746 1.6000 G 17.5J1310 + +
326 OP 313 B 13 10 28.663800 +
32 20 43.78200 0.9970 Q 19.0J1327 + +
224 B2 1324 +
22 A 13 27 00.861314 +
22 10 50.16277 1.4034 Q 17.2J1329 + +
321 A 13 29 52.864909 +
31 54 11.05443 0.3350 B 20.0J1341 + +
285 A 13 41 15.282755 +
28 16 05.07702 1.2750 Q 19.6J1353 + +
757 B 13 53 23.168007 +
75 32 57.73527 1.6190 Q 17.7J1357 + +
769 B 13 57 55.371536 +
76 43 21.05098 1.5850 Q 19.0J1407 + +
286 OQ 208 A 14 07 00.394415 +
28 27 14.69008 0.0766 G 16.0J1419 + +
385 A 14 19 46.613761 +
38 21 48.47496 1.8320 Q 19.3J1506 + +
428 A 15 06 53.041839 +
42 39 23.03555 0.5870 Q 21.5J1506 + +
835 B 15 06 24.715438 +
83 19 28.03538 2.5770 Q 18.7J1521 + +
437 A 15 21 49.613879 +
43 36 39.26807 2.1750 Q 18.4J1549 + +
507 C 15 49 17.468558 +
50 38 05.78820 2.1741 Q 18.9J1608 + +
403 5C 13.225 B 16 08 22.157698 +
40 12 17.83288 0.6275 Q 20.8J1624 + +
578 C 16 24 24.807566 +
57 41 16.28100 0.7890 G 17.3J1635 + +
382 4C 38.41 C 16 35 15.492900 +
38 08 04.50000 1.8130 Q 17.7J1637 + +
473 4C 47.44 B 16 37 45.130554 +
47 17 33.83090 0.7350 Q 17.5J1640 + +
398 B 16 40 29.632770 +
39 46 46.02835 1.6660 Q 18.5J1642 + +
399 3C 345 A,B 16 42 58.809900 +
39 48 36.99300 0.5950 B 16.5J1646 + +
410 B 16 46 56.858690 +
40 59 17.17204 0.8350 Q 20.7J1653 + +
312 A 16 53 29.910650 +
31 07 56.87239 1.2954 Q 13.6J1659 + +
265 4C 26.51 A 16 59 24.149448 +
26 29 36.94297 0.7947 Q 18.0J1701 + +
399 A 17 01 24.634812 +
39 54 37.09149 0.5071 B 17.4J1716 + +
686 C 17 16 13.938009 +
68 36 38.74465 0.7770 Q 18.5J1726 + +
322 A 17 26 35.124676 +
32 13 23.02210 1.0900 G 16.0J1735 + +
508 A 17 35 49.005166 +
50 49 11.56578 0.8350 G 23.1J1746 + +
624 4C 62.29 B 17 46 14.034133 +
62 26 54.73830 3.8890 Q 19.5J1751 + +
293 A 17 51 42.683934 +
29 20 50.20228 . . . U . . .J1753 + +
288 A 17 53 42.473647 +
28 48 04.93877 1.1180 Q 19.6J1800 + +
388 A 18 00 24.765361 +
38 48 30.69742 2.0920 Q 18.0J1800 + +
784 C 18 00 45.683900 +
78 28 04.01800 0.6797 B 17.0J1808 + +
456 C 18 08 21.885884 +
45 42 20.86639 0.8300 Q 19.3J1811 + +
170 A 18 11 43.183465 +
17 04 57.25713 . . . Q 20.5J1821 + +
682 B,C 18 21 59.491723 +
68 18 43.00867 1.6920 G . . .J1823 + +
689 B 18 23 32.853905 +
68 57 52.61247 . . . B 19.0J1849 + +
670 B 18 49 16.072283 +
67 05 41.68022 0.6570 Q 18.6J1850 + +
283 A 18 50 27.589824 +
28 25 13.15527 2.5600 Q 17.1J1922 + +
154 A 19 22 34.699313 +
15 30 10.03193 . . . U . . .J1927 + +
611 C 19 27 30.442616 +
61 17 32.87881 0.4730 B 17.5J1930 + +
154 4C 15.66 A 19 30 52.766983 +
15 32 34.42704 . . . U . . .J1933 + +
655 C 19 33 57.337206 +
65 40 16.82845 1.6870 Q 18.7J1939 + +
381 B 19 39 33.566865 +
38 17 35.38833 . . . U 17.5J1955 + +
513 OV 591 B 19 55 42.738264 +
51 31 48.54602 1.2230 Q 18.5J2002 + +
148 C 20 02 41.999236 +
15 01 14.57396 . . . U . . .J2002 + +
472 B 20 02 10.418256 +
47 25 28.77372 2.2660 Q 19.6J2007 + +
372 B 20 07 45.397822 +
37 22 02.31078 . . . U . . .J2012 + +
463 7C 2010 + +
46 28 55.77715 . . . B 18.2J2015 + +
340 C 20 15 28.831879 +
34 10 39.40992 . . . B . . .J2015 + +
370 B,C 20 15 28.729778 +
37 10 59.51495 0.8590 B 21.8J2016 + +
163 C 20 16 13.860029 +
16 32 34.11306 . . . B 1.0J2016 + +
358 A 20 16 45.618743 +
36 00 33.37332 . . . U . . .J2017 + +
745 4C 74.25 A 20 17 13.079301 +
74 40 47.99989 2.1870 Q 18.3J2022 + +
614 OW 637 A 20 22 06.681758 +
61 36 58.80486 0.2270 G 19.5J2022 + +
760 A 20 22 35.575939 +
76 11 26.17158 0.5940 B 17.8J2024 + +
171 C 20 24 56.563449 +
17 18 13.19767 1.0500 Q 17.5J2051 + +
175 C 20 51 35.582921 +
17 43 36.90076 0.1950 G 18.0J2109 + +
353 B2 2107 +
35A A 21 09 31.878718 +
35 32 57.59746 0.2023 G 13.9J2114 + +
463 A 21 14 32.875692 +
46 34 39.30126 . . . U . . .J2137 + +
508 A 21 37 00.986190 +
51 01 36.12894 . . . U . . .J2154 + +
172 C 21 54 40.900400 +
17 27 50.79300 1.0200 Q 18.0J2202 + +
420 BL Lac A,C 22 02 43.291371 +
42 16 39.97992 0.0686 B 14.5
Article number, page 15 of 25 able 5.
List of Sources (continued)
Source (J2000) Source (B1950) Common Name Epoch α δ z Type m v (1) (2) (3) (4) (5) (6) (7) (8) (9)J2203 + +
171 C 22 03 26.893600 +
17 25 48.24700 1.0760 Q 18.8J2203 + +
315 4C 31.63 C 22 03 14.975700 +
31 45 38.26900 0.2950 Q 15.5J2210 + +
199 A 22 10 51.652453 +
20 13 24.05454 0.2820 Q . . .J2212 + +
236 A 22 12 05.966311 +
23 55 40.54372 1.1250 Q 19.0J2217 + +
241 C 22 17 00.821100 +
24 21 45.95700 0.5050 B 17.2J2218 + +
150 A 22 18 10.913904 +
15 20 35.71746 2.3350 Q . . .J2253 + +
158 3C 454.3 A,B,C 22 53 57.747937 +
16 08 53.56094 0.8590 B 16.1J2305 + +
824 A 23 05 17.539999 +
82 42 49.15557 0.6200 B . . .J2311 + +
454 A 23 11 47.408964 +
45 43 56.01658 1.4470 Q . . .J2312 + +
724 C 23 12 19.697802 +
72 41 26.91735 . . . U 19.3J2322 + +
444 A 23 22 20.358080 +
44 45 42.35353 1.3100 U 20.7J2322 + +
506 A 23 22 25.982171 +
50 57 51.96363 1.2790 Q 18.6J2330 + +
335 C 23 30 13.737652 +
33 48 36.47152 1.8090 Q 18.5J2354 + +
456 4C 45.51 A 23 54 21.680218 +
45 53 04.23640 1.9860 Q 20.6
Columns: // simbad.u-strasbg.fr / simbad; Wenger et al. 2000), Sloan Digital Sky Survey (http: // / ) and NASA / IPACExtragalactic Database (https: // ned.ipac.caltech.edu); (This table is also available in a machine-readable and Virtual Observatory (VO) forms inthe online journal.)Article number, page 16 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz Table 6.
Image Parameters
Source (J2000) Obs S S S B S S L B L B a B b B PA S t S p σ ξ r (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)J0013 + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± Article number, page 17 of 25 able 6.
Image Parameters continued
Source (J2000) Obs S S S B S S L B L B a B b B PA S t S p σ ξ r (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)J1038 + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± Article number, page 18 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Table 6.
Image Parameters continued
Source (J2000) Obs S S S B S S L B L B a B b B PA S t S p σ ξ r (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)J2017 + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± + + ± ± + ± ± + ± ± + ± ± + ± ± + ± ± Columns: (1) – IAU Source name (J2000); (2) – observing epochs – A: October 2010; B: May 2011 and C: October 2011; (3) – total single dishflux density measured at 86 GHz obtained from the pointing and calibration scan measurements at Pico Veleta or Plateau de Bure [Jy];(4),(6) – correlated flux densities [Jy] measured on projected baseline lengths listed in columns (5) and (7) [M λ ]; (8) – major axis of the restoringbeam [ µ as]; (9) – minor axis of the restoring beam [ µ as]; (10) – position angle of the major axis [degrees]; (11) – total clean flux density [mJy];(12) – peak flux density [mJy / beam]; (13) – o ff -source r.m.s noise in the residual image [mJy / beam]; (14) – quality factor of the residual noise inthe image. (This table is also available in a machine-readable and Virtual Observatory (VO) forms in the online journal.)Article number, page 19 of 25 able 7. Model Fit Parameters
Source (J2000) Obs Comp S tot S peak d r θ T b T b , min T b , lim (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)J0013 + ±
71 278 ± <
14 . . . . . . > + ±
61 136 ±
35 34 ± ± ± ± + ±
22 69 ±
12 30 ± ± + ±
18 11 ± ±
38 431 ±
19 -179.3 ± ± + ±
26 90 ±
16 26 ± ± + ±
45 4 ± ±
24 53 ±
12 130.3 ± ± + ±
17 57 ±
10 26 ± ± + ±
36 13 ± ±
316 758 ±
158 -49.2 ± ± + ± ± <
41 1217 ± ± > + ± ± ±
26 1713 ±
13 -30.2 ± ± + ± ± <
37 1720 ± ± > + ±
24 100 ± <
10 . . . . . . > + ±
14 23 ± ± ± ± ± + ±
52 157 ±
32 28 ± ± + ±
31 39 ±
17 38 ±
16 171 ± ± ± + ±
72 208 ±
41 33 ± ± + ±
199 942 ±
134 15 ± ± + ±
481 239 ±
70 193 ±
56 51 ±
28 92.0 ± ± + ±
89 166 ± <
18 90 ± ± > + ±
66 231 ±
33 40 ± ± + ±
38 95 ±
16 52 ± ± + ±
12 34 ±
10 35 ±
10 182 ± ± ± + ±
75 235 ±
46 24 ± ± + ±
19 68 ±
12 22 ± ± + ±
166 874 ±
112 19 ± ± + ±
129 359 ±
72 41 ± ± ± ± + ±
73 154 ± <
26 274 ± ± > + ±
63 103 ±
41 41 ±
16 508 ± ± ± + ±
90 191 ±
54 31 ± ± ± ± + ±
150 737 ± <
14 . . . . . . > + ±
66 138 ±
48 248 ±
85 221 ±
43 -101.3 ± ± + ±
92 140 ±
48 149 ±
51 892 ±
25 -8.8 ± ± + ±
86 133 ±
47 219 ±
77 1145 ±
39 0.9 ± ± + ±
125 157 ±
50 266 ±
85 1458 ±
43 -9.3 ± ± + ±
34 166 ±
23 22 ± ± + ±
32 14 ± ±
131 342 ±
65 -20.4 ± ± + ±
31 18 ± ±
115 719 ±
57 -28.5 ± ± + ±
41 169 ±
26 23 ± ± + ±
16 31 ± <
32 899 ± ± > + ±
18 35 ± <
29 1068 ± ± > + ±
44 162 ±
26 33 ± ± + ±
69 23 ±
11 342 ±
158 1056 ±
79 -22.2 ± ± + ±
130 19 ±
10 470 ±
242 1551 ±
121 -23.0 ± ± + ±
47 210 ± <
15 . . . . . . > + ±
39 167 ± <
19 . . . . . . > + ±
67 190 ±
43 28 ± ± + ±
74 327 ± <
14 . . . . . . > + ±
53 88 ±
28 42 ±
13 138 ± ± ± + ±
43 90 ± <
25 177 ± ± > + ±
37 61 ± <
30 485 ± ± > + ±
245 463 ±
67 61 ± ± + ±
113 305 ±
55 41 ± ± ± ± + ±
171 158 ±
40 73 ±
19 200 ± ± ± + ±
152 125 ±
36 74 ±
21 441 ±
11 156.2 ± ± + ±
258 96 ±
32 230 ±
76 712 ±
38 179.3 ± ± + ±
595 103 ±
33 471 ±
150 1745 ±
75 173.1 ± ± + ±
654 126 ±
36 369 ±
105 2143 ±
53 175.4 ± ± + ±
287 710 ±
80 152 ±
17 . . . . . . 1.773 ± + ±
64 208 ± <
20 182 ± ± > + ±
63 122 ±
34 49 ±
14 240 ± ± ± + ±
241 134 ±
36 362 ±
96 365 ±
48 147.3 ± ± + ±
53 149 ±
38 47 ±
12 415 ± ± ± + ±
62 137 ±
36 156 ±
41 770 ±
21 -177.4 ± ± + ±
166 165 ±
39 259 ±
62 937 ±
31 166.0 ± ± + ±
52 227 ±
46 35 ± ± ± ± + ±
604 120 ±
34 385 ±
109 1667 ±
54 170.7 ± ± + ±
359 160 ±
39 432 ±
105 2065 ±
52 174.4 ± ± + ±
262 119 ±
34 499 ±
141 2694 ±
71 179.1 ± ± + ±
86 123 ±
34 349 ±
97 3088 ±
49 174.4 ± ± + ±
91 124 ±
34 329 ±
91 4508 ±
46 176.2 ± ± + ±
264 416 ±
52 278 ±
35 . . . . . . 0.450 ± + ±
50 192 ± <
30 202 ± ± > + ±
56 243 ± <
27 410 ± ± > + ±
181 103 ±
26 339 ±
87 594 ±
43 -176.5 ± ± Article number, page 20 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Table 7.
Model Fit Parameters continued
Source (J2000) Obs Comp S tot S peak d r θ T b T b , min T b , lim (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)J0319 + ±
69 216 ±
38 112 ±
19 991 ±
10 -142.9 ± ± + ±
93 196 ±
36 177 ±
32 1497 ±
16 163.4 ± ± + ±
213 76 ±
23 391 ±
118 1636 ±
59 172.0 ± ± + ±
22 47 ± <
71 1903 ±
14 -178.6 ± > + ±
61 216 ±
38 82 ±
14 2092 ± ± ± + ±
96 370 ± <
17 . . . . . . > + ±
77 55 ±
28 70 ±
36 71 ±
18 97.7 ± ± + ±
63 37 ±
24 67 ±
44 401 ±
22 102.9 ± ± + ±
40 86 ±
20 55 ±
13 . . . . . . 0.838 ± + ±
13 17 ± <
40 135 ±
11 -127.4 ± > + ±
22 62 ±
13 31 ± ± + ±
26 97 ± <
14 . . . . . . > + ±
21 63 ±
13 25 ± ± + ±
23 128 ±
14 31 ± ± + ± ± ±
21 321 ±
11 -139.4 ± ± + ±
39 21 ± ±
79 358 ±
39 -102.3 ± ± + ±
188 229 ±
77 59 ±
20 . . . . . . 6.162 ± + ±
88 141 ± <
34 299 ± ± > + ±
196 98 ±
53 85 ±
46 478 ±
23 -137.6 ± ± + ±
33 103 ± <
21 . . . . . . > + ±
52 222 ±
31 30 ± ± + ±
23 41 ±
14 31 ±
11 184 ± ± ± + ±
22 25 ±
11 76 ±
35 254 ±
17 11.3 ± ± + ±
68 254 ±
44 27 ± ± + ±
35 80 ± <
25 80 ± ± > + ±
35 41 ±
19 45 ±
20 197 ±
10 37.2 ± ± + ±
35 67 ± <
25 262 ± ± > + ±
48 197 ±
30 28 ± ± + ±
24 162 ±
16 20 ± ± + ±
18 7 ± ±
148 275 ±
74 161.5 ± ± + ±
12 7 ± ±
114 687 ±
57 130.3 ± ± + ±
19 7 ± ±
154 918 ±
77 167.9 ± ± + ± ± ±
22 1602 ±
11 160.2 ± ± + ±
28 145 ±
19 17 ± ± + ±
46 175 ± <
17 . . . . . . > + ±
33 70 ±
15 50 ±
11 . . . . . . 0.924 ± + ±
63 122 ±
26 52 ±
11 . . . . . . 4.618 ± + ±
38 45 ±
17 45 ±
17 413 ± ± ± + ±
22 74 ±
15 14 ± ± + ±
11 17 ± ±
25 58 ±
13 -51.1 ± ± + ±
15 13 ± ±
30 675 ±
15 -51.1 ± ± + ±
41 74 ±
17 50 ±
12 . . . . . . 1.567 ± + ±
86 214 ±
37 19 ± ± + ±
62 95 ±
25 51 ±
14 185 ± ± ± + ±
22 81 ±
13 29 ± ± + ±
16 91 ±
14 57 ± ± ± ± + ±
65 216 ± <
26 . . . . . . > + ±
275 1269 ±
178 18 ± ± + ±
178 416 ±
104 27 ± ± ± ± + ±
179 445 ±
108 25 ± ± ± ± + ±
175 139 ±
63 50 ±
23 276 ±
11 41.7 ± ± + ±
211 984 ± < > + ±
35 112 ±
21 32 ± ± + ±
63 266 ±
42 19 ± ± + ±
33 50 ±
19 44 ±
17 860 ± ± ± + ±
38 39 ±
17 204 ±
91 1285 ±
46 145.4 ± ± + ±
17 59 ± <
13 . . . . . . > + ±
112 376 ±
66 36 ± ± + ±
98 94 ±
34 88 ±
32 181 ±
16 -68.5 ± ± + ±
71 58 ±
28 74 ±
36 486 ±
18 -72.0 ± ± + ±
75 335 ± <
11 . . . . . . > + ±
40 42 ±
20 58 ±
28 158 ±
14 -21.0 ± ± + ±
52 34 ±
18 88 ±
48 587 ±
24 -37.5 ± ± + ±
50 223 ±
29 32 ± ± + ±
27 21 ±
10 79 ±
36 1038 ±
18 152.2 ± ± + ±
30 92 ± <
17 . . . . . . > + ±
59 318 ±
39 19 ± ± + ±
75 364 ±
50 19 ± ± + ±
71 372 ±
47 26 ± ± + ±
21 28 ±
14 67 ±
34 1295 ±
17 17.2 ± ± + ±
21 35 ± <
44 2385 ±
10 13.5 ± > + ±
37 230 ±
25 18 ± ± + ±
28 18 ± ±
65 1048 ±
32 -23.0 ± ± + ±
390 1250 ± <
25 . . . . . . > Article number, page 21 of 25 able 7.
Model Fit Parameters continued
Source (J2000) Obs Comp S tot S peak d r θ T b T b , min T b , lim (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)J0854 + ±
774 835 ±
228 72 ±
20 260 ±
10 -25.1 ± ± + ±
27 152 ±
19 13 ± ± + ±
13 26 ± ± ± ± ± + ±
77 187 ± <
20 . . . . . . > + ±
106 405 ±
68 24 ± ± + ±
71 163 ±
44 28 ± ± ± ± + ±
62 57 ±
28 58 ±
28 378 ±
14 -132.8 ± ± + ±
38 207 ±
29 20 ± ± + ±
65 332 ±
45 18 ± ± + ±
46 193 ± <
18 53 ± ± > + ±
217 111 ±
26 308 ±
73 181 ±
36 -149.5 ± ± + ±
173 122 ±
27 220 ±
50 203 ±
25 -20.0 ± ± + ±
114 58 ±
19 274 ±
91 1898 ±
46 -66.2 ± ± + ±
85 320 ± <
15 . . . . . . > + ±
35 155 ±
24 21 ± ± + ±
97 370 ±
59 26 ± ± + ±
76 129 ±
36 45 ±
12 181 ± ± ± + ±
44 42 ±
22 52 ±
27 330 ±
14 -129.8 ± ± + ±
74 231 ± <
16 . . . . . . > + ±
56 244 ±
35 29 ± ± + ±
48 185 ±
30 23 ± ± + ±
81 380 ± <
12 . . . . . . > + ±
32 47 ± <
32 535 ± ± > + ±
80 290 ±
38 44 ± ± + ±
66 36 ±
14 183 ±
72 482 ±
36 23.3 ± ± + ±
55 290 ±
36 12 ± ± + ±
49 31 ±
13 72 ±
29 93 ±
14 -133.4 ± ± + ±
52 24 ±
11 64 ±
30 627 ±
15 -171.6 ± ± + ±
72 22 ±
11 228 ±
112 1333 ±
56 176.9 ± ± + ±
47 184 ± <
15 . . . . . . > + ±
141 410 ±
82 32 ± ± + ±
97 152 ±
51 37 ±
12 256 ± ± ± + ±
101 192 ±
29 56 ± ± + ±
40 61 ±
17 45 ±
12 260 ± ± ± + ±
58 225 ±
36 28 ± ± + ±
62 245 ±
37 26 ± ± + ±
55 78 ±
21 48 ±
13 158 ± ± ± + ±
26 38 ±
15 24 ±
10 804 ± ± ± + ±
65 227 ±
36 42 ± ± + ±
40 82 ±
22 46 ±
12 114 ± ± ± + ±
75 275 ±
45 33 ± ± + ±
93 167 ±
35 79 ±
16 126 ± ± ± + ±
244 677 ±
114 46 ± ± + ±
91 196 ± <
31 273 ± ± > + ±
32 74 ±
18 32 ± ± + ±
297 1040 ± <
17 . . . . . . > + ±
210 269 ±
110 42 ±
17 484 ± ± ± + ±
23 75 ±
12 42 ± ± + ±
25 78 ±
15 32 ± ± + ±
35 81 ±
17 47 ±
10 . . . . . . 2.024 ± + ±
28 66 ± <
23 . . . . . . > + ±
121 383 ± <
33 . . . . . . > + ±
512 152 ±
54 614 ±
218 69 ±
109 27.8 ± ± + ±
713 1800 ±
357 202 ±
40 . . . . . . 1.456 ± + ±
517 1020 ±
273 170 ±
46 671 ±
23 -139.2 ± ± + ±
240 158 ±
124 157 ±
123 1391 ±
62 -138.1 ± ± + ±
254 384 ± <
103 1849 ±
24 -118.8 ± > + ±
722 1590 ±
356 219 ±
49 . . . . . . 1.122 ± + ±
22 65 ± <
19 . . . . . . > ± ± ±
19 . . . . . . 23.196 ± ± ±
692 80 ±
26 214 ±
13 -21.0 ± ± ± ±
685 370 ±
122 308 ±
61 -152.6 ± ± ±
911 902 ±
476 203 ±
107 838 ±
54 -107.6 ± ± + ±
51 138 ±
32 27 ± ± + ±
21 29 ± <
37 72 ±
10 -144.5 ± > + ±
21 57 ±
13 29 ± ± + ±
89 225 ±
45 38 ± ± + ±
60 98 ±
30 38 ±
12 147 ± ± ± + ±
44 47 ±
22 34 ±
16 275 ± ± ± + ±
165 52 ±
23 391 ±
174 491 ±
87 -67.1 ± ± + ±
63 288 ±
39 29 ± ± + ±
41 197 ±
28 19 ± ± + ±
15 36 ± <
35 107 ± ± > + ±
11 21 ± <
50 154 ±
12 -174.2 ± > Article number, page 22 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Table 7.
Model Fit Parameters continued
Source (J2000) Obs Comp S tot S peak d r θ T b T b , min T b , lim (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)J1341 + ±
54 194 ±
35 24 ± ± + ±
20 64 ±
11 34 ± ± + ±
41 174 ±
26 21 ± ± + ±
46 191 ±
30 23 ± ± + ±
45 30 ±
12 261 ±
109 551 ±
55 -23.1 ± ± + ±
72 136 ±
32 49 ±
11 . . . . . . 5.429 ± + ±
68 191 ±
39 31 ± ± + ±
19 65 ±
11 27 ± ± + ±
62 202 ± <
17 . . . . . . > + ±
56 221 ±
32 30 ± ± + ±
18 39 ± <
40 377 ± ± > + ±
83 305 ± <
17 . . . . . . > + ±
58 226 ±
32 35 ± ± + ±
290 1000 ±
156 38 ± ± + ±
109 367 ±
48 45 ± ± + ±
67 196 ±
29 46 ± ± + ±
53 96 ±
21 50 ±
11 137 ± ± ± + ±
40 26 ±
12 49 ±
22 261 ±
11 -110.7 ± ± + ±
52 40 ±
14 193 ±
67 261 ±
34 -62.3 ± ± + ±
234 396 ±
107 44 ±
12 . . . . . . 10.535 ± + ±
374 217 ±
81 182 ±
68 198 ±
34 -109.3 ± ± + ±
176 141 ±
67 37 ±
18 67 ± ± ± + ±
215 127 ±
65 73 ±
37 723 ±
19 -131.1 ± ± + ±
205 395 ±
70 55 ±
10 . . . . . . 9.413 ± + ±
258 201 ±
51 127 ±
32 176 ±
16 -105.2 ± ± + ±
234 100 ±
37 257 ±
94 807 ±
47 -109.2 ± ± + ±
74 109 ±
38 66 ±
23 1524 ±
12 -109.4 ± ± + ±
18 64 ±
12 22 ± ± + ± ± <
46 172 ±
12 -34.1 ± > + ±
23 170 ±
16 16 ± ± + ±
14 27 ± ±
19 388 ±
10 20.4 ± ± + ±
16 30 ± ±
24 1067 ±
12 -18.5 ± ± + ±
25 175 ±
16 22 ± ± + ±
16 32 ± ±
15 342 ± ± ± + ±
15 37 ± ±
13 1099 ± ± ± + ±
27 156 ± <
11 . . . . . . > + ±
17 32 ± ±
14 416 ± ± ± + ±
22 16 ± ±
73 426 ±
37 -167.6 ± ± + ±
75 217 ±
47 26 ± ± + ±
42 177 ± <
17 . . . . . . > + ±
22 148 ± < > + ± ± ±
41 286 ±
21 -25.2 ± ± + ± ± ±
15 301 ± ± ± + ±
11 16 ± ±
37 915 ±
18 -3.6 ± ± + ±
12 20 ± ±
32 1047 ±
16 -19.5 ± ± + ±
21 69 ±
13 30 ± ± + ±
72 241 ±
41 35 ± ± + ±
57 152 ±
32 34 ± ± + ±
52 197 ± <
18 . . . . . . > + ±
184 480 ±
73 47 ± ± + ±
87 87 ±
33 51 ±
19 263 ±
10 140.0 ± ± + ±
122 101 ±
35 67 ±
23 966 ±
12 -118.0 ± ± + ±
56 182 ± <
31 . . . . . . > + ±
76 251 ±
44 34 ± ± + ±
24 42 ± <
60 65 ±
14 71.9 ± > + ±
36 140 ±
24 19 ± ± + ±
19 40 ± <
19 181 ± ± > + ±
39 168 ±
27 15 ± ± + ±
20 20 ±
10 52 ±
26 108 ±
13 -161.2 ± ± + ±
18 19 ±
10 42 ±
22 824 ±
11 -164.3 ± ± + ±
18 70 ±
12 18 ± ± + ± ± <
25 41 ± ± > + ±
185 472 ±
105 30 ± ± + ±
135 179 ±
67 35 ±
13 85 ± ± ± + ±
105 168 ±
65 25 ±
10 165 ± ± ± + ±
64 199 ± <
27 . . . . . . > + ±
64 215 ± <
31 . . . . . . > + ±
116 125 ±
31 74 ±
18 . . . . . . 1.987 ± + ±
50 174 ±
29 33 ± ± + ±
26 56 ± <
37 252 ± ± > + ±
26 73 ±
14 39 ± ± + ±
21 64 ±
14 24 ± ± + ±
51 156 ±
29 33 ± ± + ±
47 30 ±
13 70 ±
31 514 ±
16 -23.6 ± ± Article number, page 23 of 25 able 7.
Model Fit Parameters continued
Source (J2000) Obs Comp S tot S peak d r θ T b T b , min T b , lim (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)J2002 + ±
48 180 ±
30 33 ± ± + ±
24 74 ±
14 32 ± ± + ±
15 15 ± ±
26 331 ±
13 106.9 ± ± + ±
28 59 ±
11 51 ±
10 . . . . . . 0.829 ± + ±
12 11 ± ±
30 152 ±
15 117.9 ± ± + ±
80 274 ±
45 34 ± ± + ±
17 50 ± <
25 . . . . . . > + ±
203 789 ± <
14 . . . . . . > + ±
420 195 ±
74 202 ±
76 102 ±
38 -117.3 ± ± + ±
154 128 ±
61 184 ±
88 349 ±
44 -129.6 ± ± + ±
430 1890 ±
252 34 ± ± + ±
167 378 ± <
25 172 ± ± > + ±
49 191 ±
31 31 ± ± + ±
32 25 ±
12 206 ±
102 611 ±
51 -75.6 ± ± + ±
42 225 ±
27 21 ± ± + ±
33 23 ± ±
61 1222 ±
30 -35.5 ± ± + ±
29 104 ±
20 16 ± ± + ±
23 109 ±
16 17 ± ± + ± ± <
26 83 ± ± > + ±
51 180 ±
32 26 ± ± + ±
39 38 ±
16 86 ±
35 105 ±
17 -51.2 ± ± + ±
34 63 ±
19 35 ±
11 170 ± ± ± + ±
94 50 ±
18 219 ±
76 338 ±
38 -122.3 ± ± + ±
50 146 ± <
31 . . . . . . > + ±
64 357 ±
39 39 ± ± + ±
24 37 ±
13 43 ±
15 330 ± ± ± + ±
30 211 ±
18 30 ± ± + ±
10 21 ± ±
10 199 ± ± ± + ±
14 28 ± ±
12 476 ± ± ± + ± ± ±
44 1688 ±
22 -147.3 ± ± + ±
42 188 ±
27 21 ± ± + ±
29 173 ±
20 13 ± ± + ±
12 20 ± ±
10 1273 ± ± ± + ± ± <
28 1444 ± ± > + ±
21 62 ± <
25 . . . . . . > + ±
844 699 ±
183 89 ±
23 . . . . . . 7.044 ± + ±
287 785 ± <
19 390 ± ± > + ±
314 397 ±
141 41 ±
14 571 ± ± ± + ±
343 456 ±
150 57 ±
19 577 ± ± ± + ±
233 371 ±
137 28 ±
10 711 ± ± ± + ±
664 3280 ± <
110 . . . . . . > + ±
73 224 ±
46 40 ± ± + ±
172 75 ±
28 254 ±
94 93 ±
47 36.0 ± ± + ±
73 132 ±
23 66 ±
11 . . . . . . 2.004 ± + ±
43 48 ±
14 66 ±
19 214 ±
10 -144.1 ± ± + ±
31 48 ±
14 50 ±
15 223 ± ± ± + ±
112 268 ± <
29 . . . 162.8 ± > + ±
38 95 ±
21 41 ± ± + ±
25 29 ±
12 41 ±
17 158 ± ± ± + ±
61 172 ±
34 37 ± ± + ±
60 214 ± <
22 . . . . . . > + ±
20 35 ± <
70 62 ±
17 -109.2 ± > + ± ± ±
44 . . . . . . 13.026 ± + ± ± ±
60 293 ±
30 -81.1 ± ± + ±
977 3960 ±
547 94 ±
13 . . . . . . 20.169 ± + ± ±
326 264 ±
63 159 ±
32 -102.4 ± ± + ±
331 466 ±
200 90 ±
39 324 ±
19 -84.2 ± ± + ±
533 382 ±
184 242 ±
116 445 ±
58 -63.2 ± ± + ±
467 723 ±
243 118 ±
40 511 ±
20 -86.7 ± ± + ±
429 441 ±
196 185 ±
82 868 ±
41 -53.9 ± ± + ±
856 658 ±
233 304 ±
108 945 ±
54 -36.1 ± ± + ±
315 416 ±
191 72 ±
33 995 ±
17 -75.4 ± ± + ±
377 300 ±
167 285 ±
159 1380 ±
79 -70.0 ± ± + ±
207 839 ±
135 19 ± ± + ±
722 150 ±
60 327 ±
131 56 ±
65 -97.9 ± ± + ±
284 111 ±
53 174 ±
83 377 ±
41 -62.2 ± ± + ±
270 168 ±
63 70 ±
26 473 ±
13 -79.1 ± ± + ±
227 107 ±
52 92 ±
45 582 ±
22 -101.2 ± ± + ±
29 145 ±
20 25 ± ± + ±
22 128 ±
15 14 ± ± + ±
10 28 ± <
21 93 ± ± > + ±
10 11 ± ±
21 758 ±
11 135.0 ± ± + ±
33 12 ± ±
164 1214 ±
82 143.7 ± ± + ±
32 105 ±
20 27 ± ± Article number, page 24 of 25hanya G. Nair et al.: GMVA survey of extragalactic radio sources at 86 GHz
Table 7.
Model Fit Parameters continued
Source (J2000) Obs Comp S tot S peak d r θ T b T b , min T b , lim (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)J2322 + ±
27 122 ±
18 12 ± ± + ±
11 25 ± <
30 107 ± ± > + ±
31 139 ±
21 19 ± ± + ±
23 20 ± ±
29 86 ±
14 170.9 ± ± + ±
17 29 ±
10 39 ±
13 194 ± ± ± + ±
22 27 ±
10 60 ±
21 253 ±
11 -116.3 ± ± + ±
12 19 ± <
31 477 ± ± > + ±
19 17 ± ±
29 736 ±
15 -118.7 ± ± + ±
39 133 ±
27 21 ± ± + ±
29 122 ± <
14 . . . . . . > Columns: (1) – IAU Source name(J2000); (2) – observing epochs – A: October 2010; B: May 2011 and C: October 2011; (3) – I.D. number ofGaussian model fit component; (4) – total flux density of the component [mJy]; (5) – peak flux density of the component [mJy / beam];(6) – component size [ µ as], with upper limits shown in italics; (7) – component’s o ff set from the core [ µ as]; (8) – position angle of the o ff set[degrees]; (9) – brightness temperature obtained from the model fits [ × K], with lower limits shown in italics; (10) – visibility based estimateof the minimum brightness temperature [ × K]; (11) – visibility based estimate of the maximum resolved brightness temperature [ ×10