The VLA-COSMOS 3 GHz Large Project: AGN and host-galaxy properties out to z ≲ 6

22 Pages·2017·3.22 MB·English

A&A602,A3(2017) Astronomy
DOI:10.1051/0004-6361/201629367
&
(cid:13)c ESO2017 Astrophysics
Special issue
The VLA-COSMOS 3 GHz Large Project
The VLA-COSMOS 3 GHz Large Project:
(cid:46)
AGN and host-galaxy properties out to z 6
I.Delvecchio1,V.Smolcˇic´1,G.Zamorani2,C.DelP.Lagos3,4,S.Berta1,(cid:63),J.Delhaize1,N.Baran1,D.M.Alexander5,
D.J.Rosario5,V.Gonzalez-Perez6,O.Ilbert7,C.G.Lacey8,O.LeFèvre7,O.Miettinen1,M.Aravena9,M.Bondi10,
C.Carilli11,12,P.Ciliegi2,K.Mooley13,M.Novak1,E.Schinnerer14,P.Capak15,F.Civano16,N.Fanidakis8,
N.HerreraRuiz17,A.Karim18,C.Laigle19,S.Marchesi20,H.J.McCracken19,
E.Middleberg17,M.Salvato21,andL.Tasca7
(Affiliationscanbefoundafterthereferences)
Received21July2016/Accepted21October2016
ABSTRACT
WeexplorethemultiwavelengthpropertiesofAGNhostgalaxiesfordifferentclassesofradio-selectedAGNouttoz(cid:46)6viaamultiwavelength
analysisofabout7700radiosourcesintheCOSMOSfield.ThesourceswereselectedwiththeVeryLargeArray(VLA)at3GHz(10cm)withinthe
VLA–COSMOS3GHzLargeProject,andcross-matchedwithmultiwavelengthancillarydata.Thisisthelargestsampleofhigh-redshift(z(cid:46)6)
radiosourceswithexquisitephotometriccoverageandredshiftmeasurementsavailable.Weconstructedasampleofmoderate-to-highradiative
luminosityAGN(HLAGN)viaspectralenergydistributiondecompositioncombinedwithstandardX-rayandmid-infrareddiagnostics.Withinthe
remainderofthesamplewefurtheridentifiedlow-to-moderateradiativeluminosityAGN(MLAGN)viaexcessinradioemissionrelativetothestar
formationratesintheirhostgalaxies.WeshowthatateachredshiftourHLAGNhavesystematicallyhigherradiativeluminositiesthanMLAGN
andthattheirAGNpoweroccurspredominantlyinradiativeform,whileMLAGNdisplayasubstantialmechanicalAGNluminositycomponent.
WefoundsignificantdifferencesinthehostpropertiesofthetwoAGNclasses,asafunctionofredshift.Atz < 1.5,MLAGNappeartoreside
insignificantlymoremassiveandlessstar-forminggalaxiescomparedtoHLAGN.Atz > 1.5,weobservedareversalinthebehaviourofthe
stellarmassdistributionswiththeHLAGNpopulatingthehigherstellarmasstail.Weinterpretthisfindingasapossiblehintofthedownsizingof
galaxieshostingHLAGN,withthemostmassivegalaxiestriggeringAGNactivityearlierthanlessmassivegalaxies,andthenfadingtoMLAGNat
lowerredshifts.OurconclusionisthatHLAGNandMLAGNsamplestracetwodistinctgalaxyandAGNpopulationsinawiderangeofredshifts,
possiblyresemblingtheradioAGNtypesoftenreferredtoasradiative-andjet-mode(orhigh-andlow-excitation),respectively,whoseproperties
mightdependonthedifferentavailabilityofcoldgassupplies.
Keywords. radiocontinuum:galaxies–galaxies:nuclei–galaxies:active–galaxies:evolution
1. Introduction the SMBH and its host (e.g. Boweretal. 2006; Crotonetal.
2006;Hopkinsetal.2008;Lagosetal.2008;Mencietal.2008),
Multiwavelength observations of galaxies hosting active galac- whichoccursintwoflavours:quasarmode(QSOmode)andra-
tic nuclei (AGN) in the past 20 yr have extensively shown that diomode.
supermassive black holes (SMBHs) are one of the key ingredi-
Ontheonehand,thequasarmodeisusuallyassociatedwith
ents in shaping the evolution of galaxies through cosmic time. aradiativelyefficientphaseofSMBHaccretionthroughisotropi-
In particular, it is now well-established that AGN activity and
callydistributedionisingwindsandmolecularoutflowsasmeans
star formation in their hosts are related processes, which are
topreventtherunawaygrowthofSMBHs(e.g.Booth&Schaye
likely driven by a common fuelling mechanism such as accre-
2009; Duboisetal. 2014). On the other hand, a subsequent
tion of cold gas supplies (e.g. Vitoetal. 2014). In the local
radio-modephaseisusuallyinvokedtopreventfurtherepisodes
Universe, hints of such a connection have been suggested by
of galaxy star formation through mechanical feedback, such as
the empirical correlations found between black hole mass and
collimatedandrelativisticjets(Monacoetal.2000;Duboisetal.
galaxy properties (e.g. Magorrianetal. 1998; Gebhardtetal.
2014),inordertoregulatethegalaxystellarmass(Crotonetal.
2000; Ferrarese 2002; Gültekinetal. 2009). In the distant Uni-
2006; Marullietal. 2008; Hopkins&Quataert 2010) and to
verse, this co-evolution scenario is supported by the similar-
reproduce the galaxy colours observed in the local Universe
itybetweenvolume-averagedcosmicstarformationhistoryand
(Stratevaetal.2001).
black hole accretion history, which both peak at z ∼ 2 and de-
Thoughitistodaywidelyacceptedthattheevolutionofac-
clinetowardsthelocalUniverse(e.g.Madau&Dickinson2014,
tive SMBHs is connected to the evolution of their hosts, the
forareview).Semi-analyticmodels(e.g.Boweretal.2006)and
underlyingmechanismsexplainingthetransitionbetweenthese
numerical simulations interpret these correlations as originated
twokeystagesoftheAGNandgalaxylifecyclesarestillpoorly
from a long-lasting ((cid:38)Gyr) self-regulation process between
constrained.Testingthisparadigmischallengingasthisissup-
posed to be a quick transition (on timescales of ∼100 Myr)
(cid:63) Visitingscientist. from highly accreting to fading AGN. Promising studies of
ArticlepublishedbyEDPSciences A3,page1of22
A&A602,A3(2017)
individual smoking-guns, mostly X-ray and optically detected and less dense environments. These results, which have been
AGN (e.g. Farrahetal. 2012; Ciconeetal. 2014; Pernaetal. corroborated through a similar analysis up to intermediate red-
2015;Brusaetal.2015,2016),haveshowncompellingevidence shifts (z (cid:46) 1.4; see Gouldingetal. 2014), strongly suggest that
of ongoing AGN feedback, but are currently limited to a small various AGN selection criteria might be sensitive to physically
numberofcandidates.AcombinedstudywithlargeAGNsam- distinctclassesofAGNandgalaxies.Inparticular,thepeculiar-
plesisnecessarytoconstraintheroleofAGNfeedbackinamore ityofblackholeandgalaxypropertiesobservedinradio-selected
statistical sense, and to shed light on the connection between AGNstandsoutmorethaninanyotherAGNsample.Forthese
AGNandtheirhostsatdifferentcosmicepochs. reasons,itisnowwidelyrecognisedthatamultiwavelengthin-
A fundamental, complementary perspective in the frame- vestigationofradio-selectedsourcesisessentialtoconstrainthe
work of the AGN-host evolution comes from radio observa- AGN-galaxypropertiesinakeystageoftheircosmicevolution.
tions. Indeed, radio observations are essential to capture possi- In this paper, we exploit the largest compilation of high-
ble signatures of relativistic jets powered by a central SMBH redshift(z (cid:46) 6)radio-selectedgalaxiesintheCosmicEvolution
(e.g.Hoganetal.2015),whicharedetectedviathesynchrotron Survey (COSMOS; Scovilleetal. 2007) field. The Karl G.
emission of the jet (e.g. Milleretal. 1993). In addition, radio Jansky Very Large Array (VLA) observations were conducted
continuumemissionmayarisefromthediffusionofcosmicray at 3 GHz (10 cm) over the entire COSMOS field, in the
electrons produced in supernovae and their remnants in high- framework of the VLA-COSMOS 3 GHz Large Project (PI:
massstar-formingregions,andthisemissionhasbeencalibrated V. Smolcˇic´, Smolcˇic´ etal. 2017a), reaching a 1σ sensitivity of
onstar-forminggalaxiestoprovideanalmostdust-unbiasedstar 2.3µJybeam−1.Therichmultiwavelength(X-raytoradio)data
formation rate (SFR) indicator (Condon 1992; Yunetal. 2001; setofphotometryandredshiftsavailableinthe COSMOSfield
Bell 2003). This underlines the great potential of radio obser- allowsustoinvestigatethephysicalpropertiesofthesesources
vations in unveiling a mixture of AGN and star-forming galax- fromapanchromaticperspective.Themaingoalsofthepresent
ies.Nevertheless,radioobservationsneedtobesupplementedby workaretwofold:first,toprovideavalue-addedcataloguethat
multiwavelengthdatatofullycharacterisethenatureoftheradio includes classification and physical properties for each 3 GHz
sources. VLA-selectedsourceintheCOSMOSfield,and,second,toex-
Outstanding progress has been made through the analy- plorethemultiwavelengthpropertiesofAGNhostsfordifferent
sis of large samples of radio-selected AGN in the local Uni- classesofradio-selectedAGNouttoz(cid:46)6.
verse (Smolcˇic´ 2009; Best&Heckman 2012). For instance, Thepaperisstructuredasfollows.InSect.2wedescribeour
Smolcˇic´(2009)identifiedatwofoldpopulationofradio-emitting sample selection and the cross-match with ancillary photome-
AGN,namelyhigh-excitationandlow-excitationradiogalaxies try. In Sect. 3 we decompose the multiwavelength spectral en-
(HERGs and LERGs, respectively), on the basis of the pres- ergydistribution(SEDs),whiletheclassificationofoursample
ence of high- or low-excitation lines in their optical spectra is discussed in Sect. 4. A brief description of the value-added
taken from the Sloan Digital Sky Survey (SDSS; Yorketal. catalogue is given in Sect. 5. Section 6 illustrates the average
2000).Interestingly,theauthorfoundthatHERGspreferentially radio-selected AGN host-galaxy properties out to z (cid:46) 6, while
live in galaxies within the green valley (in terms of op- the interpretation of our results are presented and discussed in
tical [nuv-r] colours and stellar mass, M(cid:63)), while LERGs detail in Sect. 7. We list our concluding remarks in Sect. 8.
usually populate the red sequence of massive and passive sys- In Appendix A we show the results of infrared stacking, while
tems. Such a dichotomy observed in the host-galaxy proper- Appendix B shows a portion of the value-added 3 GHz radio
ties between HERGs and LERGs may reflect physically dif- catalogueincludingsomephysicalparametersusedinthiswork.
ferent modes of SMBH accretion and presumably different Throughout this paper, magnitudes are given in the AB system
stages of AGN-galaxy evolution (Hardcastleetal. 2006; see (Oke1974).WeassumeaChabrier(2003)initialmassfunction
Heckman&Best2014,forareview).WhileSMBHsinHERGs (IMF) and a flat cosmology with Ωm = 0.30, ΩΛ = 0.70, and
arethoughttoaccreteviacoldgasinflowsfromgalaxymergers H =70kms−1Mpc−1(Spergeletal.2003).
0
or secular processes (Sijackietal. 2007; DiMatteoetal. 2008;
Bournaudetal. 2012), AGN activity in LERGs is probably in-
2. Sampleselection
duced by a continuous gas inflow coming from the atmosphere
of the hot halo (Boweretal. 2006; Ellisonetal. 2015). In the
2.1. 3GHzradiosources
former case, accretion is radiatively efficient and covers a wide
rangeoftheelectromagneticspectrum(uptoX-rayfrequencies), Radiodataat3GHzwerecollectedfrom384hofobservations
while for the latter scenario the feedback is predominantly me- with VLA over 2.6 deg2, reaching an average rms sensitivity
chanical and does not outshine the host galaxy in most bands of 2.3 µJy beam−1 and an angular resolution of about 0(cid:48).(cid:48)75. A
exceptradio. detailed description of the survey strategy, data reduction, and
In their comprehensive study, Hickoxetal. (2009) have radio source catalogue is given in Smolcˇic´ etal. (2017a). The
thoroughly investigated the AGN, host galaxy, and environ- catalogue includes 10830 radio sources, identified at peak sur-
mental properties of X-ray, mid-IR (MIR), and radio-selected face brightness ≥5σ, out of which 67 are multi-components.
AGN at 0.25 < z < 0.8 in the Böotes field (Jannuzi&Dey Thepresentcataloguerepresentsthedeepestcompilationsofra-
1999). In particular, Hickoxetal. (2009) defined as “radio dio sources available to date across an area of 2.6 deg2. Our
AGN” those sources with (rest-frame) 1.4 GHz luminosity sample covers a wide redshift range (0 < z (cid:46) 6, see Sect.
L > 1024.8 WHz−1 to minimise the contamination from 2.3) and is around three times larger than the 1.4 GHz sample
1.4GHz
star-forming galaxies. These authors found that most radio- taken from the Westerbork Synthesis Radio Telescope (WSRT,
selected AGN have very low accretion rates (Eddington ra- 3172sources)intheNOAODeepWide-FieldSurvey(NDWFS,
tio λ (cid:46) 10−3) and populate overdense regions similarly deVriesetal.2002).Moreover,oursampleoutnumbersthepre-
Edd
to the most massive galaxies (e.g. Georgakakisetal. 2007; vious1.4GHzVLA-COSMOSsurveybyafactorofaboutfour
Silvermanetal. 2009; Coiletal. 2009). In contrast, X-ray and (2865 sources; see Schinnereretal. 2007, 2010) and by more
MIR selected AGN are characterised by active star formation than one order of magnitude the 1.4 GHz VLA survey in the
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I.Delvecchioetal.:TheVLA-COSMOS3GHzLargeProject
1000 domain1.Cross-matchingour3GHzselectedsampletoexisting
3 GHz sample ancillary data is essential to derive physical properties of
(spec + phot) galaxies. The multiwavelength photometry is taken from the
100 COSMOS2015 catalogue (Laigleetal. 2016), which combines
spec optical photometry2, the most recent UltraVISTA (DR23) data
phot
N overthecentral1.5deg2 inthenear-infrared(NIR)bandsY, J,
10 H,andKs4,andMIRphotometryobtainedfromtheInfraredAr-
rayCamera(IRAC),whichisrecentlycomplementedbydeeper
IRAC3.6and4.5µmobservationswiththeSpitzer LargeArea
Survey with Hyper-Suprime-Cam (SPLASH; Steinhardtetal.
1 2014; Capak et al., in prep.). In addition, this data set has been
cross-matched with 24 µm photometry (LeFloc’hetal. 2009)
from the Multi-Band Imaging Photometer for Spitzer (MIPS).
26
26 Laigleetal.(2016)providesfurtherdetails.
Hz ]−1 25 25Hz ]−1 terpTarhtewcitrhosesa-cmhartacdhiotosoausrscoeciiastefuallypodsessicbrliebeodpitnicSalm-NoIlcRˇic´ceotuanl-.
W 24 spec 24W (2017b,seetheirSect.3).First,theyexcludedstarsandmasked
phot
L [log 3GHz 2223 limit L (5σ) 2223L [log 1.4GHz rctpheulgeeriaotCtoenOs8oS6ipMn9ti6tcOhareSladCpfiihOoeolSdstooMtmuoOrec1Ster.s27y.,07S1wd5eheccgioca2nhtdaallrnyoed,gdtuuohecueerybse3ptcheaGreufHsoeerzffmoesfecedtltiehvcaeetenladeersaessraaeamsoct-f--
3GHz
21 (1σ = 2.3 µJy beam−1 ) neighbourmatching,byselectingforeachradiosourceonlycan-
21
didatecounterpartswithin0(cid:48).(cid:48)8searchingradiusand,atthesame
20
time,requiringafalsematchprobability(i.e.probabilityofbeing
0 1 2 3 4 5 6
aspuriousassociation)lowerthan20%.Thisapproachyieldsan
redshift
average expected fraction of spurious associations of about 1%
Fig.1.Toppanel:redshiftdistributionofour7729radiosources.Spec- (seeSmolcˇic´ etal.2017b).Thepercentageofradiosourceswith
troscopicandphotometricredshiftsareshowninredandblue,respec- multiple optical-NIR counterparts within 0(cid:48).(cid:48)8 is about 1%, for
tively,whiletheblacklineisthesumofthetwo.Thescaleoftheyaxis which the cut in false-match probability ensures the selection
islogarithmic.Bottompanel:circlesshowtherest-frame3GHzlumi- of the most probable counterpart. After this cut, our final sam-
nosityasafunctionofredshift,bothspectroscopic(red)andphotomet-
pleconsistsof7729radiosourceswithoptical-NIRcounterparts,
ric (blue). The horizontal bars indicates the average ±1σ uncertainty
correspondingtoabout89%ofourradio-selectedsamplewithin
rangeofthephotometricredshiftsinthevariousredshiftbins.Thecor-
responding1.4GHzluminosity(scaledbyusingα=–0.7)isshownfor thecommon1.77deg2.
comparison on the right y axis. The black solid line indicates the 5σ Toenrichthespectralcoverageofouranalysisandderivero-
luminositylimitat3GHz. buststarformationrates(SFRs)forasmanysourcesaspossible,
we used also Herschel photometry at far-infrared and submil-
Extended Chandra-Deep Field South (E-CDFS; 883 sources, limetre wavelengths provided in the COSMOS2015 catalogue.
Milleretal.2013)survey. Herschel imaging covers the entire COSMOS field with the
We derived (rest-frame) 3 GHz radio luminosity (L ) Photoconductor Array Camera and Spectrometer (PACS; 100
3GHz
for radio sources with multiwavelength counterparts and red- and160µm,Poglitschetal.2010)andSpectralandPhotometric
shifts (see Sects. 2.2 and 2.3). Under the assumption of Imaging Receiver (SPIRE; 250, 350, and 500 µm, Griffinetal.
purely synchrotron emission, the radio spectrum behaves like 2010) data, as part of the PACS Evolutionary Probe (PEP;
a power law S ∝ να, where the spectral index α is set to Lutzetal. 2011) and the Herschel Multi-tiered Extragalactic
ν
the observed 1.4–3 GHz slope for sources detected also at Survey (HerMES; Oliveretal. 2012). Herschel fluxes were ex-
1.4 GHz (about 30%) in the 1.4 GHz VLA-COSMOS survey tracted and de-blended by using 24 µm positional priors and
(Schinnereretal.2010);thespectralindexissetto–0.7,which unambiguously associated with the corresponding optical-NIR
isconsistentwithanon-thermalsynchrotronindex,(e.g.Condon counterpartvia24µmsourceslistedinbothcatalogues.Intotal,
1992;seealsoSmolcˇic´ etal.2017a)ifthesourcesaredetectedat thenumberofradiosourceswith(≥3σ)Herscheldetectioninat
3GHzalone.InFig.1(bottompanel)weshowL asafunc- leastonePACSorSPIREbandare4836/7729(63%).Thisper-
3GHz
tionofredshiftwithrespecttothe5σluminositylimit.Forcom- centagedecreaseswithredshift,being87%atz < 0.3and45%
parison,weshowthecorresponding1.4GHzluminosityL atz>3.5.
1.4GHz
ontherightyaxis.Oursampleclearlyspansawideluminosity
range(upto4–5dex),whichallowsustoinvestigatethemulti-
wavelengthpropertiesofoursampleindifferentradioluminosity 1 AnexhaustiveoverviewoftheCOSMOSfieldandmultiwavelength
dataproductsisavailableat:http://cosmos.astro.caltech.edu/
regimes.
2 Optical photometry is taken from Subaru Hyper-Suprime Cam
In particular, we are able to detect 2.5 times intrinsically
observations over the full 2 deg2 (Capaketal. 2007), and also
faintersources(undertheassumptionα=−0.7),atagivenred-
fromtheCanada-France-HawaiiTelescopeLegacySurvey(CFHT-LS;
shift,comparedtotheprevious1.4GHzVLA-COSMOSsurvey McCrackenetal.2001)inthecentral1deg2.
(Schinnereretal.2007,2010). 3 DR2replacesthepreviousDR1byMcCrackenetal.(2012).Ade-
tailed description of the survey and data products can be retrieved at:
2.2. Opticalto(sub)millimetrephotometry http://ultravista.org/release2
4 OutsidetheUltraVISTAcoverage,NIRphotometryincludesCFHT
The COSMOS field benefits from an exquisite photomet- H and K observations obtained with the WIRCam (McCrackenetal.
s
ric data set, covered from the X-rays to the submillimetre 2001).
A3,page3of22
A&A602,A3(2017)
To obtain reliable dust-based SFRs also in potential high- very secure measurements5. In addition, we included the latest
redshift candidates (z > 3), where Herschel observations spectroscopic redshifts from the VIMOS Ultra Deep Survey
are incomplete even towards ultraluminous infrared galaxies (VUDS;LeFèvreetal.2015;Tascaetal.2017),fromwhichwe
(ULIRGs,i.e.havingrest-frame8–1000µminfraredluminosity found25associationstoourradiosources.
L ≥ 1012 L , e.g. Sanders&Mirabel 1996), photometry at Afterthesechecks,thenumberofradiosourceswithspectro-
IR (cid:12)
longer wavelengths is essential. For around 115 radio sources, scopic redshift is 2734/7729 (around 35%). Every radio source
weretrievedadditional(sub)millimetrephotometryfromatleast withmultiwavelengthcounterparthasitsownredshiftestimate.
one of the following data sets: JCMT/SCUBA-2 at 450 and Figure1(toppanel)showsthefinalredshiftdistributionforour
850µm(Caseyetal.2013),LABOCAat870µm(F.Navarrete 7729radiosources.Thenumberofspectroscopicandphotomet-
et al., priv. comm.), Bolocam (PI: J. Aguirre), JCMT/AzTEC ricredshiftsarecomparableouttoz∼1,whilephotometricred-
(Scottetal. 2008) and ASTE/AzTEC (Aretxagaetal. 2011) at shifts become more numerous at higher redshift. We tested the
1.1 mm, MAMBO at 1.2 mm (Bertoldietal. 2007), and in- accuracy of the photometric redshifts in our sample based on
terferometric observations at 1.3 mm with ALMA (PI: M. thespectroscopicmeasurementsavailablefor2734sources.We
Aravena, M. Aravena et al., in prep.) and PdBI (Smolcˇic´ etal. found a median (cid:104)|∆z/(1+z)|(cid:105) = 0.010, which becomes as high
2012;Miettinenetal.2015).The(sub)mmpositionswerecross- as0.035atz > 3.Therefore,theprovedaccuracyofthephoto-
matchedtotheCOSMOS2015positionsviaanearestneighbour metricredshiftsallowsustopushouranalysisouttoz(cid:46)6,even
matching, using 1(cid:48).(cid:48) searching radius (the smallest beam width ifthenumberofsourcesatz>4isrelativelysmall(84sources).
of the (sub)mm data we collected). A thorough visual inspec-
tion of the counterpart associations has been performed for the
1.3mmdetectedALMAsources(68%ofthe(sub)mmphotom- 3. SED-fittingdecompositionof3GHzsources
etrywecollected),whichisdetailedinBrisbinetal.(2017)and
In this section, we fit the multiwavelength SEDs of our radio
Miettinenetal.(2017).
sourcestodisentangletheAGNemissionfromthatrelatedtothe
We also collected X-ray data from the Chandra-COSMOS host-galaxy.Itiswellknownthatradio-selectedsamplescontain
(Elvisetal. 2009; Civanoetal. 2012) and COSMOS-Legacy distinctgalaxypopulations(e.g.Condon1984;Windhorstetal.
catalogues(Civanoetal.2016).Theoptical-NIRcounterpartsof 1985;Gruppionietal.1999)intermsofstarformationandAGN
X-ray sources were matched via a maximum likelihood algo- properties. Therefore, fitting the multiwavelength SEDs may
rithm and are presented in Marchesietal. (2016). We matched provide meaningful results only if AGN and galaxy templates
their catalogue to our 3 GHz selected sample of 7729 optical- arebothtakenintoaccount.
NIR counterparts via COSMOS2015 IDs. This match yields We used both the SED-fitting code magphys6 (da Cunha
903X-raysources,correspondingto12%(903/7729)ofourra- etal.2008),andthethree-componentSED-fittingcodesed3fit
dio sample, and to 32% (903/2804) of the X-ray sources with by Bertaetal. (2013), which accounts for an additional AGN
optical-NIRassociationinunmaskedareas. component7. The aforementioned references provide for a full
description of these SED-fitting codes. Here we briefly outline
2.3. Spectroscopicandphotometricredshifts themainprescriptionsthatarerelevantforouranalysis.
magphys
The code is designed to reproduce a variety of
We collected photometric redshifts for the 7729 radio sources galaxy SEDs, from weakly star-forming to starbursting galax-
with a counterpart in the COSMOS2015 catalogue. Photomet- ies, over a wide redshift range8. This code relies on the energy
ricredshiftestimatesareincludedinthecatalogueandwerede- balance between the dust-absorbed stellar continuum and the
rivedusingtheLePhareSED-fittingcode(Arnoutsetal.1999; reprocessed dust emission at infrared wavelengths. This recipe
Ilbertetal.2006)followingtheproceduredetailedinIlbertetal. ensures that optical and infrared emission originating from star
(2009, 2013). Based on the comparison with the spectroscopic formation are linked in a self-consistent manner, but does not
redshiftsavailableintheCOSMOSfield,Laigleetal.(2016)re- account for a possible AGN emission component. The three-
portanaveragephotometricredshiftaccuracyof(cid:104)|∆z/(1+z)|(cid:105)= component SED-fitting code presented by Bertaetal. (2013)
0.021 for K > 22, which becomes less than 0.010 for brighter combines the emission from stars, dust heated by star forma-
s
sources. tion, and a possible AGN-torus component from the library of
Feltreetal.(2012,seealsoFritzetal.2006).Thisapproachre-
ForX-raysources,weusedadifferentsetofphotometricred- sultsinaneffectivelysimultaneousthree-componentfit.Foreach
shiftsfromM.Salvatoetal.(inprep.),whicharemoresuitable best-fit parameter, the code provides a corresponding probabil-
forAGN-dominatedsourcesastheyaccountforAGNvariability itydistributionfunction(PDF),whichenablestheusertoobtain
andadoptadditionalAGNtemplates(Salvatoetal.2009,2011).
An exhaustive list of spectroscopic redshifts was compiled 5 The reliability of each spectroscopic redshift is determined
by its quality flag. In case of spectroscopic redshift from the
(April 2015, Salvato et al., in prep.) and made internally ac-
zCOSMOS survey (Lillyetal. 2007, 2009), we followed the
cessible to the COSMOS team. Most of the spectroscopic
prescription recommended on the zCOSMOS IRSA webpage:
redshifts used in this paper were taken from the zCOSMOS
https://irsa.ipac.caltech.edu/data/COSMOS/spectra/
survey (Lillyetal. 2007, 2009), either the public zCOSMOS- z-cosmos/Z-COSMOS_INFO.html For the other surveys we selected
bright or the proprietary zCOSMOS-deep database, the DEep qualityflagQf ≥ 3anddiscardedlessreliablespectroscopicredshifts
ImagingMulti-ObjectSpectrograph(DEIMOS,Capaketal.,in fromouranalysis.
prep.),andtheFOcalReducerandlowdispersionSpectrograph 6 Theoriginalmagphyscodeispubliclyavailableatthislink:
(FORS2,Comparatetal.2015).Salvatoetal.(inprep.)provide http://www.iap.fr/magphys/magphys/MAGPHYS.html
forafullreferencelist. 7 The three-component SED-fitting code sed3fit can be retrieved
fromhttp://cosmos.astro.caltech.edu/page/other-tools
For each radio source with a multiwavelength counterpart 8 For extensive application of the magphys code in deriving physi-
in this spectroscopic compilation, we replaced the photometric calpropertiesofgalaxies,seealsoSmithetal.(2012);Rowlandsetal.
redshiftswithnewspectroscopicvaluesonlyincaseofsecureor (2014);Michałowskietal.(2014);Hayward&Smith(2015).
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I.Delvecchioetal.:TheVLA-COSMOS3GHzLargeProject
reliable confidence ranges for parameter estimates (see e.g. SED-selectedAGN)andMLAGN(radio-excesssourcesthatare
CalistroRiveraetal.2017,forasimilarSED-fittingtechnique). notHLAGN),asexplainedinthenextsections.
WedecomposedeachobservedSEDbyusingthebestavail- Thisnamingconventioncomesfromtheideathattheselec-
ableredshift(eitherspectroscopicorphotometric,seeSect.2.3) tion criteria based on SED-fitting, X-ray, and MIR data prefer-
as input, and we derived integrated galaxy properties, such as entially select higher luminosity AGN, where the term “lumi-
SFRand M(cid:63),foreachindividualsource.TheSFRwasderived nosity” here refers to the AGN radiative luminosity (Lrad,AGN),
from the total IR (rest 8–1000 µm) luminosity taken from the which is a proxy of the SMBH accretion rate (BHAR; e.g.
best-fit galaxy SED (i.e. corrected for a possible AGN emis- Alexander&Hickox2012).Thisclassificationdoesnottranslate
sion), assuming a Kennicutt (1998) conversion factor scaled to into a sharp threshold in the accretion efficiency (or Eddington
a Chabrier (2003) IMF. We note that about 37% of our sam- ratio)betweenHLAGNandMLAGN,butratherreflectsthereli-
plearenot≥3σdetectedinanyHerschelbands.Toobtainbetter abilityoftheadopteddiagnosticsinidentifyingsuchAGNpop-
constrainedIRluminosities,weperformedSED-fittingusingthe ulations combined with the sensitivity of our survey at various
nominal PACS and SPIRE 3σ upper limits, which are equal to wavelengths. Moreover, the tags “low to moderate” and “mod-
5.0(100µm),10.2(160µm),8.1(250µm),10.7(350µm),and eratetohigh”intentionallyimplyapotentialoverlapinL
rad,AGN
15.4(500µm)mJy,includingconfusionnoise(Lutzetal.2011; betweenthetwoclassesatvariousredshifts.However,atagiven
Oliveretal. 2012). We modified the χ2 calculation to correctly redshift,thesedifferentlyselectedAGNdisplaysignificantlydis-
account for those Herschel bands that have only upper limits, tinctdistributionsofAGNluminosity,asdetailedinSect.4.4.1.
similartotheapproachadoptedbydaCunhaetal.(2015). Therefore,thepresentclassificationshouldbeconsideredasob-
As a sanity check, we verified that the IR luminosi- servationally based, and aimed at dissecting our radio sources
ties based on our three-component fit are in good agreement onthebasisofAGNdiagnosticsthatareknowntobeluminosity
with those calculated independently using a different set of dependent.Adetailedinvestigationonthedistributionofradio-
IR templates (from Chary&Elbaz 2001; Dale&Helou 2002; selectedAGNasafunctionoftheirintrinsicEddingtonratiowill
Siebenmorgen&Krügel 2007; Pollettaetal. 2007; Wuytsetal. bepresentedinaforthcomingpaper(Delvecchioetal.,inprep.).
2008; Elbazetal. 2011; Nordonetal. 2012, see Bertaetal. In Sects. 4.1 and 4.2 we describe in more detail the multi-
2013, for a comprehensive discussion). We briefly discuss the wavelengthdiagnosticsusedtoidentifyMLAGNandHLAGN,
comparisonwiththeHerschelfluxesderivedthroughstackingin respectively,whileinSect.4.4wejustifythisnamingconvention
Sect.4.4.3.The M(cid:63) isderivedfromtheSEDdecompositionit- bystudyingtheirLrad,AGNdistributions.
self,whichallowsustoobtainrobustestimatesiftheoptical-NIR
SEDisdominatedbythehost-galaxylight(e.g.Bongiornoetal.
2012). 4.1. Moderate-to-highradiativeluminosityAGN
InordertoquantifytherelativeincidenceofapossibleAGN
Aspreviouslymentioned,theso-calledHERGpopulationiden-
component,wefittedeachindividualSED,bothwiththethree-
magphys tifiedinthelocalUniverseconsistsofhighlyaccretingSMBHs
component approach and the code. The fit obtained
onthebasisofthepresenceofhigh-excitationlinesintheirop-
withtheAGNispreferredifthereducedχ2valueofthebestfitis
ticalspectra(e.g.Smolcˇic´ etal.2008),whichimpliesradiatively
significantly(at≥99%confidencelevel,onthebasisofaFisher
efficientaccretion.InordertodetectpotentialHERGanalogues
test)smallerthanthatobtainedfromthefitwithouttheAGN;see
in our sample, we combine SED decomposition (Sect. 3) with
Delvecchioetal.(2014)fordetails.Fromouranalysis,wefound
X-rayandMIRindicators.Alltheseselectioncriteriaaresensi-
that1169outof7729radiosources(about15%)showa≥99%
tive to an excess of emission likely arising from accretion onto
significantAGNcomponentintheirbestfit.
the central SMBH rather than from star formation. As a conse-
We extensively tested this technique against independent
quence,despitethedifferentbiasesintrinsictoeachcriterion,all
AGNindicatorsintheCOSMOSfield,suchasMIRcoloursand
ofthesecriteriapreferentiallyselecthigherradiativeluminosity
X-rays(seeDelvecchioetal.2014).Forinstance,Lanzuisietal.
AGN. The selection criteria used to identify this AGN popula-
(2015)showedthattheAGNradiativeluminositiesderivedfrom
tion are briefly summarised below. Smolcˇic´ etal. (2017b) pro-
SEDdecompositionwereconsistent(1σ = 0.4dex)withthose
vide a detailed description of the X-ray and MIR-based AGN
calculated from X-ray spectra and assuming a set of bolomet-
indicators.
ric corrections (e.g. Lussoetal. 2012). Moreover, the unprece-
First, SED-fitting decomposition identifies 1169 sources
dented accuracy of photometric redshifts and the photometric
with ≥99% significant AGN component in their global SED,
coverage exploited in this work, strengthened by our sizeable
SEDAGNhereafter(seeSect.3).
sample,furtherincreasethereliabilityofourmethod.However,
if the galaxy light outshines the AGN in the full optical-to-mm Second, we used X-ray luminosities (Lx) in the rest-frame
SED,thisstatisticaltechniquebecomesprogressivelylesseffec- [0.5–8]keV.TheLxestimateswerecalculatedforthe903X-ray
tiveinidentifyingAGN. detectedsources,byassumingafixedX-rayspectralslopeΓ =
1.8, and correcting for nuclear obscuration on the basis of the
measured hardness ratio (e.g. Xueetal. 2010). We identified
855 sources with X-ray luminosity L ≥ 1042 erg s−1 as X-
4. Classificationof3GHzradiosources x
ray AGN (e.g. Szokolyetal. 2004). We verified that the X-ray
We combine SED-fitting decomposition (Sect. 3) with other emission expected from recent L –SFR relations (taken from
x
multiwavelength AGN diagnostics to reach a more complete Symeonidisetal.2014)isalwaysnegligibleforourX-rayAGN
census of AGN in our sample. These additional indicators are (about a few percent). On the basis of the aforementioned re-
taken from X-ray, MIR and radio data, which allow us to iden- lation, about 30 X-ray detected sources with L < 1042 ergs−1
x
tify two main populations of radio-selected AGN in our sam- show an X-ray excess and, therefore, could be considered low-
ple:moderate-to-highradiativeluminosityAGN(HLAGN)and luminosity X-ray AGN. However, we prefer to apply the same
low-to-moderate radiative luminosity AGN (MLAGN). Here- cutatL ≥1042ergs−1foralloursourcestoavoidpotentialcon-
x
after,werefertothesepopulationsasHLAGN(X-ray,MIR,and taminationfromoutlierswithrespecttotheL –SFRrelation.
x
A3,page5of22
A&A602,A3(2017)
Third, MIR colours can be very useful in identifying AGN, SED AGN
bothunobscuredandheavilyobscured.Donleyetal.(2012)pro-
posed a conservative criterion to select AGN, on the basis of
MIR AGN
the MIR colour-colour diagram drawn from a combination of
the four Spitzer-IRAC (3.6, 4.5, 5.8, and 8.0 µm) bands. We 32.5%
followed Eqs. (1) and (2) of their paper to identify AGN at 13.5%
z < 2.7, while at higher redshift we applied the additional
conditions stated in their Eqs. (3) and (4) to minimise the 0.6%
contaminationfromhigh-redshiftstarburstswithoutAGN.This
method is highly reliable for bright AGN, but becomes incom-
pleteatL <1044ergs−1.Intotal,455outof7729radiosources 0.3% 13.9%
x
(about6%)satisfytheDonleyetal.(2012)criterion,andthere-
foreareclassifiedasMIRAGN.
12.9%
Hereafter, we will use the term “moderate-to-high radiative
luminosityAGN”(HLAGN)tocollectivelyrefertotheunionof
X-ray, MIR, and SED-selected AGN identified in our sample,
foratotalof1604objects(21%oftheradiosample).
26.2%
Figure 2 shows the percentages of HLAGN classified from
each criterion: the percentage of AGN that fulfills all the crite-
ria simultaneously is only about 14% of the full HLAGN pop-
ulation. This small overlap further suggests that different AGN X-ray AGN
diagnosticsaresensitivetodistinctAGNpopulations.Thisover-
lapincreaseswithincreasingX-rayluminosity,whichis7%for Fig.2.Venndiagramillustratingthepercentagesofthe1604HLAGN
1042 < L <1043 ergs−1,25%for1043 < L <1044 ergs−1,and inoursampleidentifiedfromdifferentAGNdiagnostics:X-rays(blue),
x x
49% for L > 1044 erg s−1. These relatively small percentages MIR (red) and SED decomposition (green). Areas roughly scale with
x
percentages.
are mainly driven by the incompleteness of the MIR classifica-
tion, as the Donleyetal. (2012) criterion is very conservative.
We checked that the agreement between X-ray and SED-fitting
diagnosticsisashighas21%for1042 < L <1043 ergs−1,52% By using different and complementary tracers of highly
x
for1043 < L <1044ergs−1,and79%forL >1044ergs−1. accreting AGN, we can build a more representative (though
x x
not 100% complete) sample of HLAGN. Our analysis would
InFig.3weillustratesomeexamplesofbest-fitSEDs,show-
ing different levels of agreement between the AGN diagnostics certainly benefit from optical-NIR spectroscopy to identify
AGN at lower intrinsic luminosities. Unfortunately, the spec-
describedabove.Inallthepanels,redcirclesindicatethe(rest- trallinesusedtocalculatetheemissionlineratios[Oiii]/Hβand
frame) multiwavelength photometry, while downward pointing [Nii]/Hα)intheBPTdiagram(fromBaldwinetal.1981)arede-
arrowssetthe3σupperlimitsintheHerschelbands.Solidlines
tectedonlyinalowpercentage(about5%)ofourradiosample,
representthebest-fittemplatesofAGN(red),galaxystarforma-
mostlyatz < 0.5,assomeopticallines(e.g.Hα)wouldbered-
tion(blue),andthesumofthetwo(black).
shiftedoutsidetheobservedspectralwindowathigherredshifts.
TheleftpanelshowstheSEDofanunambiguousAGN,suc-
Forconsistency,inthisworkwepreferredtomakeuseofAGN
cessfully identified from X-rays, MIR-colours, and SED-fitting
selectioncriteriathatareapplicabletotheentiresample.
decomposition.ThecentralpanelshowsanAGNidentifiedonly
For our 1604 HLAGN, we took the SFR and M estimates
from SED decomposition. Indeed, galaxies hosting heavily ob- (cid:63)
from the best-fit solution obtained with the three-component
scuredAGNmightbeundetectedintheX-rays,butalsomisclas-
SED-fittingcodebyBertaetal.(2013).Thisapproachallowsus
sifiedfromMIRcolourssincetheDonleyetal.(2012)criterion
toaccountforapossibleAGNcontaminationingalaxyparame-
ishighlyincompleteatL <1044ergs−1.However,neitherSED-
x terestimatesandtostudyuncertaintiesanddegeneracies,which
fitting decomposition nor MIR colours can identify an AGN
is important when comparing galaxy properties between AGN
when the optical-IR SED is outshined by the host-galaxy light
and non-AGN hosts. However, we checked that the AGN con-
(right panel), although the X-ray luminosity suggests the pres-
tributiontothetotal(8–1000µm)IRluminosityisverysmall(a
enceofamoderatelyluminousX-rayAGN(L ∼ 1043 ergs−1).
x fewpercent)formostoftheHLAGNsample,asarguedbyprevi-
We looked at the observed distribution of the X-ray to optical-
UVindex,definedasα =−Log[L /L ]/2.605,where ousstudiesofX-rayandIR-selectedAGN(e.g.Mullaneyetal.
ox 2keV 2500Å 2011;Santinietal.2012;Rosarioetal.2012).
L and L are the rest-frame monochromatic luminosi-
2500Å 2keV
ties at 2500 Å and 2 keV, respectively (e.g. Zamoranietal.
1981). We verified that the observed distribution of αox for 4.2. Low-to-moderateradiativeluminosityAGNviaradio
HLAGN identified solely from X-rays peaks at αox ∼1, unlike excess
the average value α ∼ 1.37 found for X-ray selected AGN in
ox
the COSMOS field (Lussoetal. 2010). The lower α suggests RadiosourcesthatarenotclassifiedasHLAGNinSect.4.1do
ox
that HLAGN identified only from X-rays are optically fainter notshowevidenceofAGNactivityaccordingtoX-ray,MIR,or
than the rest of X-ray AGN in the COSMOS field, as expected SED decomposition. However, this does not necessarily mean
from their galaxy-dominated SEDs. This is also confirmed by that SMBH accretion is not occuring at all, but rather that the
the fact that in more than 80% of them, the optical-NIR pho- AGN diagnostics described above might fail in detecting sig-
tometryhasbeenfittedwithoutAGNtemplateswhencalculating naturesoflessefficientaccretionepisodes.Asmentionedinthe
the photometric redshifts (see Marchesietal. 2016; M. Salvato previoussections,radioobservationsarecrucialforchasingsuch
etal.,inprep.). anelusiveAGNpopulation.
A3,page6of22
I.Delvecchioetal.:TheVLA-COSMOS3GHzLargeProject
105 105
SED+MIR+X−ray AGN SED−only AGN X−ray−only AGN
104 104
103 103
] ]
y y
J 102 102 J
µ µ
[ [
S ν 101 101 S ν
100 star formation 100
AGN
total
10−1 10−1
1 10 100 1000 1 10 100 1000 1 10 100 1000
λ(rest−frame) [µm] λ(rest−frame) [µm] λ(rest−frame) [µm]
Fig.3.Threeexamplesofbest-fitSEDsofHLAGNselectedfromdifferentcriteria.Colouredlinesrepresentthecorrespondingbest-fittemplates
ofAGN(red),galaxystarformation(blue),andthesumofthetwo(black).Leftpanel:AGNidentifiedfromX-rays,MIRcolours,andSEDfitting.
Centralpanel:AGNidentifiedonlyfromSED-fitting.Rightpanel:AGNidentifiedonlyfromX-rays.ThereddashedlineindicatesthattheAGN
componentis<99%significantonthebasisoftheFishertest(seetextformoredetails).Redcirclesindicatetheopticaltofar-IR(FIR)photometry
(rest-frame),whiledownwardpointingarrowsrepresent3σupperlimitsintheHerschelbands.
2266
To identify lower radiative luminosity AGN in our sample, log[L / L ]
wsifieefidrsatscHonLsAidGeNred(it.he.e739G%H).zFsoerleecatcehdosfotuhrecmes,tthhaetLarIReonbottacinlaesd- yr)yr)-1-1 2255 ppeeaakk+3σ 340000−4 −3 −2 1.4 G−H1z I0R, SF 1 2
via SED fitting without AGN (daCunhaetal. 2008) has been M M OO • • N 200
converted to IR-based SFR (SFRIR hereafter) by assuming a / / 100
Kennicutt (1998) scaling factor and a Chabrier (2003) IMF. To z z -1-1 2244 0
identify the possible AGN contribution in radio emission, we HH 20 21 22 23 24 25 26
analysedtheratiobetweenthe1.4GHzradioluminosityL W W log[L / SFR ]
1.4GHz 1.4 GHz IR
((
athnedirthraetSioF(Ri.IeR.fLo1r.4eGaHczh/SsoFuRrIcRe,.iFnilgougraer4ithshmoiwcssctahleed)iasstraibfuutnioctnioonf ] ] RR 2233
of redshift (black points). Typical 1σ uncertainties of the ob- RR I I
FF
served ratio are of the order of 0.15 dex. The histogram in the SS 2222 3σ radio excess
ttvoiaoplnureoisgfhoLtf1c.t4ohGrenHrezar/StisFoh,RoswIRusg.gtThehesetdindisgitsrttirhbiabututitAoionGnNoifsaoscuktrievswioteyudrmcteoisgwhaatsrbdaesfhcuoingnch-- L / L / 1.4 GHz 1.4 GHz 2211
[[
tributingtotheintegratedradioemission.However,theaverage gg
oo best−fit threshold: 21.984 (1+z)0.013
L /SFR alsoincreaseswithredshift,whichpartlyexplains ll
1.4GHz IR
2200
theskewnessoftheobserveddistribution.Toquantifythesefac-
tors,wesplitoursampleintosevenredshiftbins(0.01<z<0.3, 00 11 22 33 44 55 66
0.3 < z < 0.7, 0.7 < z < 1.2, 1.2 < z < 1.8, 1.8 < z < 2.5, zz
2.5 < z < 3.5, and 3.5 < z < 5.7) and fit each single distri-
Fig.4.DistributionoftheratiobetweenL andSFR asafunction
butionwithalog-normalfunctionthatreproducesthepeakand 1.4GHz IR
ofredshift(blackpoints)forsourcesnotclassifiedasHLAGN(79%of
thenegativepartoftheobserveddistributionwell.Thevaluesof
oursample).Thebluefilledcircles(anderrors)indicatethepeak(and
the peak (and dispersion) of the Gaussian function identified at dispersion) of the Gaussian distribution identified in a given redshift
eachredshiftbinarerepresentedinFig.4withbluefilledcircles bin,whilethecorresponding3σdeviationissetbytheredopencircles.
(and relative errors). The position of the peak generally shifts Theredsolidlineindicatestheredshift-dependentthresholdderivedby
to higher L /SFR ratios with increasing redshift, which fittingtheopencirclesateachredshiftbin.Sourcesabovetheredline
1.4GHz IR
justifiesourchoiceofaredshift-dependentapproach.Moreover, are identified as “low to moderate radiative luminosity AGN” (here-
some recent studies (e.g. Magnellietal. 2015; Delhaizeetal. afterMLAGN)viaradioexcess.ThefullhistogramofL1.4GHz/SFRIRis
showninthetoprightcorner.
2017) have found a slight, but significant decrease of q (pro-
IR
portionaltoSFR /L )withredshiftthroughacarefultreat-
IR 1.4GHz
mentofnon-detectionsviastackingordouble-censoredsurvival Fromthisexpression,wesetathresholdabovewhichtheradio
analysis. emission shows a >3σ excess compared to that expected from
We calculated the 3σ deviation from the peak of the log- star formation. The aforementioned threshold identifies 1333
normal function at each redshift bin (see red open circles in low-to-moderateradiativeluminosityAGN(hereafterMLAGN)
Fig. 4). By fitting the open circles with a power-law function via radio excess, corresponding to 17% of our radio sample.
(red solid line in Fig. 4), we derived the analytical expression The percentage of MLAGN, which would have been identified
that describes a redshift-dependent threshold in radio excess as throughasinglethresholdatallredshifts,wouldbearound18%
follows: insteadofthe17%foundfromEq.(1);thiswouldnotaffectour
results.
(cid:32) (cid:33)
L Thechoiceofa3σradioexcessimposedineachredshiftbin
log 1.4GHz =21.984×(1+z)0.013. (1)
SFR ensures a negligible contamination from star-forming galaxies
IR excess
A3,page7of22
A&A602,A3(2017)
withoutradioexcess(about0.15%).Ontheotherhand,ourse- Table 1. Comparison between our classification method and that pre-
sentedinBonzinietal.(2013).
lectionmightmissasignificantnumberofpotentialMLAGNin
oursample,whichisestimatedtobearound1000sources(75%
oftheidentifiedsampleofMLAGN)basedonthedifferencebe- Classifications (B13)
tween the distribution below the threshold and the best-fitting
(thiswork, RQAGN RLAGN SFGs
Gaussian profile, in all redshift bins. A comparison with other
S >37µJy) total (609) (865) (3099)
definitionsofradioexcessfoundintheliteratureispresentedin 1.4
HLAGN (1044) 609 169 266
Sect.4.3.
MLAGN (1032) 0 569 463
The Kennicutt (1998) L –SFR conversion assumes that
IR IR Restofthesample (2497) 0 127 2370
the total IR luminosity arises entirely from optically thick,
dust-obscured regions. While this assumption is reasonable in
Notes. Forthischeck,wecutoursampleattotal1.4GHzfluxS >
1.4
highlystar-forminggalaxies,suchasthosedetectedbyHerschel 37µJytomatchtheradioselectionadoptedbytheauthors.
(Wuytsetal. 2011; Magnellietal. 2013), this is not true for
weakly star-forming (or passive) systems, where a significant
portion of the IR luminosity may originate from (> few Gyr) andMLAGN)inoursampledemonstratethehighreliabilityof
oldstellarpopulations(e.g.Grovesetal.2012).Weverifiedthat ourclassificationmethod.
theunobscuredSFRderivedfromtheUVgalaxyemission(e.g.
Papovichetal. 2007) is around 5% of the obscured SFR , on
average,thereforeitscontributionwouldnotsignificantlyIaRffect 4.3.2. ComparisonwithBonzinietal.(2013)
ourdefinitionofradioexcesspresentedabove. In a similar study, Bonzinietal. (2013, B13 hereafter) carried
Moreover, our threshold is calibrated on a radio-selected out a panchromatic analysis of about 800 high-redshift (z ≤ 4)
sample, which is expected to bias the observed distribution to- radio sources in the E-CDFS, selected with VLA at 1.4 GHz.
wardshighervaluesof L1.4GHz/SFRIR comparedtothetrue(i.e. They separated radio sources into radio-loud AGN (RL-AGN),
unbiased)distribution.Theseargumentssuggestthatourdefini- radio-quiet AGN (RQ-AGN) and star-forming galaxies (SFGs)
tion of radio excess is likely to be fairly conservative and the on the basis of the observed 24 µm-to-1.4 GHz flux ratio (also
number of MLAGN selected in this way should more properly called q , see Donleyetal. 2005). Briefly, B13 selected
24,obs
beconsideredasalowerlimit. RL-AGNthatarebelowthe2σdeviationfromtheaverageq
24,obs
In summary, by combining multiwavelength AGN diagnos- at a given redshift. In case q was an upper limit, the au-
24,obs
tics, we managed to isolate two populations of AGN in our thors selected RL-AGN that are below the 1σ deviation from
3 GHz selected sample. We identified 1604 HLAGN (21%) the average value. Within and above the 2σ deviation, they se-
and1333MLAGN(17%),whichcollectivelymakeoursample lectedRQ-AGNthatarenotRL-AGNandatthesametimeful-
of radio-selected AGN. The remainder of the sample (62%) is filling either X-ray or MIR diagnostics (similar to those dis-
characterised in detail in Smolcˇic´ etal. (2017b). Moreover, we cussed in Sect. 4.1); the rest of the sample was classified as
found that about 30% of HLAGN shows also a ≥3σ radio ex- SFGs.Ontopofthesecriteria,B13appliedfurtherchecks(see
cess.WecheckedthattherelativenumbersofHLAGNidentified theirSect.3.5.1)toimprovethesamplecharacterisation,which
fromeachcriterionandshowninFig.2donotchangebetween led the authors to reclassify 11 sources from SFGs to RQ or
sources with and without significant radio excess. A more de- RLAGNintheirsample.
tailedanalysisoftheaveragegalaxyandAGNpropertiesforthe Despite the larger area, our 3 GHz data in COSMOS are
aforementionedAGNclasses(MLAGN,HLAGN,includingthe deeper than the E-CDFS data at 1.4 GHz, which allows us to
subsamplewithradioexcess)ispresentedinSect.6. compare our classification with B13 in the same flux density
range. First, we scaled our 3 GHz flux density to the observed
4.3. Comparisonwithradio-basedclassifications
1.4 GHz for each source (as discussed in Sect. 2.1). Secondly,
In this section we compare our source classification with other we cut our sample at total 1.4 GHz flux S1.4GHz > 37 µJy as
independentmethodsfromtheliterature. in B13, yielding 4573 sources (around 59% of the full sample)
andwecomputedq forallofthem.Thirdly,weappliedthe
24,obs
same criteria of B13 to identify RQ-AGN, RL-AGN and SFGs
4.3.1. ComparisonwithVLBIsources
in our sample (including their additional AGN diagnostics for
We cross-matched our 3 GHz selected sample of 7729 sources consistency,seeSect.4.4.2),andshowthenumbersinTable1.
with the Very Large Baseline Interferometry (VLBI) 1.4 GHz This comparison suggests that the HLAGN and MLAGN
sourcecataloguefromN.HerreraRuizetal.(inprep.).Theau- identified in this work fairly overlap with the RQ-AGN and
thors targeted the radio sources selected by the 1.4 GHz VLA- RL-AGNclasses,respectively,evenifourclassificationtendsto
COSMOS survey (Schinnereretal. 2010) with VLBI at (cid:46)0(cid:48).(cid:48)01 classifymoreobjectsasAGN(45%)thantheB13classification
angular resolution, reaching a 1σ sensitivity of 10 µJy beam−1 (32%).TheRQ-AGNpercentagefoundbyB13(24%)ishigher
in the central part of the field. They detected 468 radio sources than that listed in Table 1 (13%), and is likely driven by the
at signal-to-noise ratio higher than 5.5. A total of 354 matches higher incompleteness of X-ray observations in the COSMOS
havebeenfoundwithin0(cid:48).(cid:48)4(half-beamsizeof3GHzVLAob- field towards moderately luminous X-ray AGN (1042 < L <
x
servations).Giventhehighangularresolution,VLBIissensitive 1044ergs−1),especiallyathighredshifts(z>2).Theaimofthis
totheradioemissiononcircum-nuclearscales(fromd ∼ 20pc comparisonisnottoinvalidateeitherofthemethods,butsimply
atz=0.1tod ∼80pcatz=2),likelyarisingfromanAGN. to clarify how different nomenclatures compare to each other.
Interestingly,wefoundthat91%ofVLBIsourcesareclassi- Themaindifferenceinthesourceclassificationliesinthediffer-
fiedasAGNbyourmethod,where55%areMLAGNand36% entdefinitionsofradioexcess.Intheirwork,B13usedaredshift-
areHLAGN.About88%oftheHLAGNalsoshowa>3σradio dependentthresholdinq ,whichwascalibratedontheM82
24,obs
excess compared to the SFR (Sect. 4.2). These notably high template. The dash-dotted line in Fig. 5 (top panel) shows the
IR
percentages of VLBI sources classified as AGN (both HLAGN redshift-dependent threshold defined by B13. Black symbols
A3,page8of22
I.Delvecchioetal.:TheVLA-COSMOS3GHzLargeProject
redshift
indicate the distribution of our 3 GHz radio sources (7729) as
0.1 0.5 1 5
a function of q and redshift with our radio-excess sources
24,obs
3
(1814intotal,being1333inMLAGNand481inHLAGN)high-
Bonzini et al. (2013) full sample (this work)
lightedingreen.Downwardpointingarrowsindicate(5σ)upper 2 Donley et al. (2005) radio−excess (this work)
limitsduetonon-detectionat24µm.Theblackdashedlinesets
thethresholdq <0adoptedbyDonleyetal.(2005)toiden-
24,obs 1
tifyradio-excesssources.DelMoroetal.(2013)alreadypointed
outthatq24,obs isareliabletracerofradioexcess,althoughitis 4 OBS 0
notcomplete.Weconfirmthisstatement,asmostofthesources 2
belowtheq threshold(byB13)alsosatisfyourradio-excess q
24,obs −1
definition. However, the B13 criterion at z > 1 becomes even
morestringentthanthatproposedbyDonleyetal.(2005).This
−2
decreasingtrendofq withredshiftisdrivenbytheshapeof
24,obs
theM82templateSED,whichisratherpeculiarcomparedtothe −3
average SED of star-forming galaxies at 0 < z < 3, implying
asteeperdeclinewithredshiftcomparedtowhatisobservedin 3 Del Moro et al. (2013)

oursample.However,thepercentageofz > 2sourcesinB13is
relativelysmallcomparedtooursample,whichimpliesthatthe
2
M82 template SED shape should not have a large effect on the
T
sourceclassificationintheE-CDFSsample. ES
R
R 1
I
F
q
4.3.3. ComparisonwithDelMoroetal.(2013) 0
An alternative method to search for radio excess is by using −1
the (rest-frame) FIR-to-radio flux ratio q (e.g. Sargentetal.
FIR
2010), where the FIR flux refers to the rest-frame range 42.5– 0.1 0.5 1 5
122.5µm,andtheradiofluxreferstotherest-frame1.4GHz.Re- reds hift
cently, DelMoroetal. (2013) used q < 1.68 in star-forming
FIR
galaxieswithintheGOODS-Northfieldtoidentifysourceswith Fig. 5. Redshift distribution of q24,obs (top panel) and qFIR (bottom
>3σradioexcess. panel)forour3GHzsample(blackdots).Thesubsamplewithradioex-
cessishighlightedwithgreencircles.Thedash-dottedline(toppanel)
AsproposedbyDelMoroetal.(2013,seetheirFig.5),we indicatestheradio-excessthresholdbyBonzinietal.(2013,B13),while
the horizontal dashed line indicates the threshold in q defined by
calculatetheq forour3GHzsourcesandshowinFig.5(bot- 24,obs
FIR Donleyetal.(2005).Thedashedlineofthebottompanelindicatesthe
tom panel) their distribution with redshift with respect to the
thresholdintherest-frameq identifiedbyDelMoroetal.(2013).
threshold set by DelMoroetal. (2013). DelMoroetal. (2013) FIR
calibrated the q threshold on a sample of sources detected
FIR
at both 1.4 GHz and 24 µm, which are, therefore, on average
4.4.1. Thechoiceofthenamingconvention
morestar-formingthanourradio-selectedgalaxiesinCOSMOS.
Iflimitingoursampleto24µmdetectedsources,weestimatethe
Our samples of HLAGN and MLAGN include AGN identified
percentageofradio-excesssourcestobearound13%,whichisin through different diagnostics. As shown in Fig. 2, only 14%
agreementwiththepercentagefoundbyDelMoroetal.(2013).
of HLAGN meet simultaneously the three diagnostics (X-ray,
We checked that the average q values of our 3 GHz sources
FIR MIR, and SED decomposition), suggesting that various AGN
alsodetectedat24µmcloselyresemblethoseofDelMoroetal.
selection criteria might be sensitive to a broad range of AGN
(2013) in the common redshift range. This is expected, given
luminosities.WestudythedistributionofMLAGNandHLAGN
that the radio-to-24 µm sensitivity limits are similar between
as a function of AGN radiative luminosity (L ), as de-
the GOODS-North and COSMOS fields. For comparison with rad,AGN
rivedfromSED-fittingdecomposition,convertedtoBHARfol-
DelMoroetal. (2013), we calculated the q for our radio-
FIR lowing Eq. (1) from Alexander&Hickox (2012) and assum-
excess sources and verified that 100% of these sources satisfy ingacanonicalmass-energyefficiencyconversionof10%(e.g.
the condition q < 1.68, while around 72% of sources with
FIR Marconietal. 2004). Each estimate of L is calculated
q < 1.68 satisfy our definition of radio excess. This check rad,AGN
FIR fromthecorrespondingbest-fitAGNtemplate(Sect.3)obtained
furthersupportsthereliabilityofourdefinitionofradioexcess.
fromSED-fittingdecomposition.Thisparametershouldbecon-
sidered an upper limit if the AGN component is not significant
fromSED-decomposition,whichisthecaseforallMLAGN(by
4.4. Furthertestsofthesourceclassification definition)andforabout27%ofHLAGNidentifiedsolelyfrom
X-ray or MIR criteria. In the latter case, the L has been
rad,AGN
The classification scheme presented in Sects. 4.1 and 4.2 was taken from the 95th percentile of the corresponding PDF ob-
sed fit
based on a few assumptions that we test in this section. In tained from the 3 code, which is equivalent to an upper
particular, we detail the motivation for our naming convention limitat90%confidencelevel.
(Sect.4.4.1),showhowourclassificationwouldchangeifcon- Figure 6 shows the L distribution separately for
rad,AGN
sidering additional AGN diagnostics (Sect. 4.4.2), and com- MLAGN (red dashed line), HLAGN (blue solid line), and the
paretheIRluminositiesderivedforHerschel-undetectedsources subsample of HLAGN not identified from SED fitting (blue
againstIRstacking(Sect.4.4.3). dashed line) in seven redshift bins. The vertical lines represent
A3,page9of22
A&A602,A3(2017)
SMBH rate [log M yr-1 ] SMBH rate [log M yr-1 ] SMBH rate [log M yr-1 ]
O • O • O •
-4 -3 -2 -1 0 1 -4 -3 -2 -1 0 1 -4 -3 -2 -1 0 1
0.01 < z < 0.30 0.30 < z < 0.70 0.70 < z < 1.20
1.2
)
d
e 1.0
s
i
l 0.8
a
m

0.6
r
o
n 0.4
(

N 0.2

1.20 < z < 1.80 1.80 < z < 2.50 2.50 < z < 3.50
1.2
)
d
e 1.0
s
i
l 0.8
a
m

0.6
r
o
n 0.4
(

N 0.2

1.2 3.50 < z < 5 .70 4 2 4 3 4 4 4 5 4 6 4 7 4 8 4 2 4 3 4 4 4 5 4 6 4 7 4 8
)
d
lloogg LL [[eerrgg ss--11 ]] lloogg LL [[eerrgg ss--11 ]]
e 1.0
s rraadd,, AAGGNN rraadd,, AAGGNN
i
l 0.8
a
m
r 0.6 MLAGN (upp. limits)
o
n 0.4 HLAGN (detections + upp. limits)
( HLAGN (upp. limits)
N 0.2

42 43 44 45 46 47 48
log L [erg s-1 ]
rad, AGN
Fig.6.NormaliseddistributionofL (orBHAR),asafunctionofredshift,separatelyforMLAGN(reddashed)andHLAGN(bluesolid).
rad,AGN
ThesubsampleofHLAGNnotidentifiedas“SED-AGN”(27%ofallHLAGN)isrepresentedbythebluedasheddistribution.Theleft-pointing
arrowsindicateupperlimitsat90%confidencelevelinL forthecorrespondingdistribution.
rad,AGN
themedianofthecorrespondingdistributionateachredshiftbin. which were all pre-classified as HLAGN on the basis of
Themedianvaluesshowasignificantdifference(around1dex) X-rayandmid-IRcriteria.
in L between MLAGN and HLAGN at all redshifts. De- – VLBIsample:asmentionedinSect.4.3.1,354radiosources
rad,AGN
spite the non-negligible overlap between the two distributions, selected at 3 GHz were also identified in the VLBI sample
westressthatthe L estimatesforMLAGNconsistofup- (N. Herrera Ruiz et al., in prep.) available in the COSMOS
rad,AGN
per limits, which implies that the difference between the true field.Ofthese,30(8%)werenotidentifiedaseitherMLAGN
distributions,atagivenredshift,isevenmoresignificant. orHLAGN,althoughtheyarelikelytobeAGN.
Thistestsuggeststhat,ateachredshift,HLAGNaresignif- – Inverted radio spectra: we found a total of 11 radio sources
icantly more powerful than MLAGN and justifies the naming not classified as radio-selected AGN, but that have in-
conventionproposedinthisworkinastatisticalsense. verted radio spectra (α > 0), where the spectral in-
dex α is set to the observed 1.4–3 GHz slope. This fea-
turemayindicatethepresenceofacompactradiocore(e.g.
4.4.2. AdditionalAGNdiagnostics Kellermann&Pauliny-Toth1969).
– Hardnessratio:wefoundatotalofsevenX-raysourcesthat
AscarriedoutinB13,weappliedadditionaldiagnosticstoverify were not classified as AGN in our sample with a positive
therobustnessofourAGNidentificationmethod. hardness ratio (HR > 0), indicating the likely presence of
obscuredAGN(e.g.Brusaetal.2010).
– Optical spectra: we searched for sources flagged as broad – Polycyclicaromatichydrocarbon(PAH)features:sourcesly-
line AGN inthe optical spectra taken from the zCOSMOS- ingintheIRACcolour-colourwedgediscussedinB13(see
Brightsurvey(Lillyetal.2007,2009);wefound15intotal, theirSect.3.5.5)likelydisplayPAH-dominatedSEDs,which
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