The COSMOS-WIRCam near-infrared imaging survey: I: BzK selected passive and star forming galaxy candidates at z>1.4

0.94 MB·English

by  H. J. McCracken

ACCEPTEDFORPUBLICATIONINTHEASTROPHYSICALJOURNAL
PreprinttypesetusingLATEXstyleemulateapjv.11/10/09
THECOSMOS-WIRCAMNEAR-INFRAREDIMAGINGSURVEY:I:BZK SELECTEDPASSIVEANDSTARFORMING
GALAXYCANDIDATESATZ&1.41
H.J.MCCRACKEN2,P.CAPAK3,4,M.SALVATO3,H.AUSSEL5,D.THOMPSON6,E.DADDI5,D.B.SANDERS7,J.-P.KNEIB8,C.J.
WILLOTT9,C.MANCINI10,A.RENZINI10,R.COOK11,O.LEFÈVRE8,O.ILBERT7,8,J.KARTALTEPE8,A.M.KOEKEMOER12,Y.
MELLIER2,T.MURAYAMA13,N.Z.SCOVILLE3,Y.SHIOYA13 ANDY.TANIGUCHI13
AcceptedforpublicationinTheAstrophysicalJournal
ABSTRACT
0
1 Wepresentanewnear-infraredsurveycoveringthe2deg2 COSMOSfieldconductedusingWIRCamatthe
0 Canada–France–HawaiiTelescope.Bycombiningournear-infrareddatawithSubaruBandzimages,wecon-
2 structadeep,wide-fieldoptical-infraredcatalogue. AtK <23(ABmagnitudes),oursurveycompletenessis
s
greaterthan90%and70%forstarsandgalaxies,respectively,andcontains143,466galaxiesand13,254stars.
n
Using the BzK diagram, we divide our galaxy catalogue into quiescent and star-forming galaxy candidates.
a
J At z∼2, our catalogues contain 3931 quiescent and 25,757 star-forming galaxies representing the largest
and mostsecure sample at these depthsand redshiftsto date. Our countsof quiescentgalaxiesturnsoverat
6
K ∼22,an effectwhichwedemonstratecannotbeduetosampleincompleteness. Boththenumberoffaint
s
] andbrightquiescentobjectsinourcataloguesexceedsthepredictionsofarecentsemi-analyticmodelofgalaxy
O formation,indicatingpotentiallytheneedforfurtherrefinementsintheamountofmergingandactivegalactic
C nucleusfeedbackatz∼2inthesemodels. Wemeasuretheangularcorrelationfunctionforeachsampleand
findthattheslopeofthefieldgalaxycorrelationfunctionflattensto1.5byK ∼23. Atsmallangularscales,
. s
h the angular correlation function for passive BzK galaxies is considerably in excess of the clustering of dark
p matter. We use precise30-bandphotometricredshiftsto derivethe spatialcorrelationlengthandtheredshift
o- distributionsforeachobjectclass. AtKs<22wefindr0γ/1.8=7.0±0.5h- 1MpcforthepassiveBzKcandidates
r and4.7±0.8h- 1Mpcforthestar-formingBzK galaxies. Our pBzK galaxieshaveanaveragephotometricred-
st shiftofzp∼1.4,inapproximateagreementwiththelimitedspectroscopicinformationcurrentlyavailable.The
a stackedK imagewillbemadepubliclyavailablefromIRSA.
s
[
Subjectheadings:cosmology:observations—cosmology:darkmatter—galaxies:largescalestructureofthe

2 universe—galaxies:surveys
v
5
0 1. INTRODUCTION Understanding the formation and evolution of galaxies is
7 oneofthecentralthemesinobservationalcosmology. Toad-
2 1BasedondatacollectedattheSubaruTelescope, whichisoperatedby dress this issue considerable work is underway to construct
. theNationalAstronomicalObservatoryofJapan;theEuropeanSouthernOb- complete galaxy samples over a broad redshift range using
0
servatoryunderLargeProgram175.A-0839,ChileandtheCanada-France- many diverse ground and space-based facilities. The ulti-
1 HawaiiTelescopewithWIRCamandMegaPrime/MegaCamthelatteroper-
mate aim of these studies is to construct distribution func-
9 atedasajointprojectbytheCFHTCorporation, CEA/DAPNIA,theNRC
0 andCADCofCanada, theCNRSofFrance, TERAPIXandtheUniversity tionsofgalaxypropertiessuchasstellarmass,starformation
: ofHawaii. ThisresearchhasmadeuseoftheNASA/IPACInfraredScience rate,morphologyandnuclearactivityasafunctionofredshift
v Archive,whichisoperatedbytheJetPropulsionLaboratory(JPL),Califor- andenvironmentandto use these measurementsin conjunc-
i niaInstituteofTechnology,undercontractwithNASA.Supportforthiswork tionwiththeoreticalmodelstoestablishtheevolutionarylinks
X wasprovidedbytheSpitzerScience Centerwhichisoperated byJPLand
CaltechunderacontractwithNASA. fromonecosmicepochtoanother. Essentiallywewouldlike
r 2Institutd’AstrophysiquedeParis,UMR7095CNRS,UniversitéPierreet tounderstandhowthegalaxypopulationatdistanttimesbe-
a
MarieCurie,98bisBoulevardArago,75014Paris,France camethegalaxiesweseearoundustodayandtoidentifythe
3SpitzerScienceCenter,314-6Caltech,Pasadena,CA9112,USA
physical mechanisms driving this transformation. Improve-
4California Institute ofTechnology, MS104-25, Pasadena, CA,91125,
ments in both modelling and observations are the ultimate
USA
5Serviced’Astrophysique,CEA/Saclay,91191Gif-sur-Yvette,France driversinachievingthisunderstanding.
6LargeBinocularTelescopeObservatory, UniversityofArizona,933N. The cold dark matter (CDM) model of structure forma-
CherryAve.Tucson,AZ85721-0065,USA tion remains our best description of how structures grow on
7Institute forAstronomy, University ofHawaii, 2680WoodlawnDrive, largescalesfromminutefluctuationsinthecosmicmicrowave
Honolulu,HI,96822,USA
8Laboratoire d’Astrophysique de Marseille, CNRS- Université d’Aix- background(Mo&White1996;Springeletal.2006). Inthis
Marseille,38rueFrédéricJoliot-Curie,13388MarseilleCedex13,France picture, structures grow “hierarchically”, with the smallest
9Herzberg Institute of Astrophysics, National Research Council, 5071 objectsformingfirst. Unfortunately,CDMonlytellsusabout
WestSaanichRoad,Victoria,BCV9E2E7,Canada theunderlyingcollisionlessdarkcomponentofthe universe;
10INAF,OsservatorioAstronomicoDiPadova,VicoloOsservatorio2,I-
what we observe are luminous galaxies and stars. At large
35122,Padova,Italy
11Department ofPhysics, BrownUniversity, Box1843, Providence, RI scales,therelationshipbetweendarkmatterandluminousob-
02912,USA jects (usually codified as the “bias”) is simple, but at small
12SpaceTelescopeScienceInstitute, 3700SanMartinDrive,Baltimore, scales (less than a few megaparsecs) the effects of baryonic
MD21218,USA
physicsintervenetomaketherelationshipbetweenluminous
13Research Center for Space and Cosmic Evolution, EhimeUniversity,
2-5Bunkyo-cho,Matsuyama790-8577,Japan andnon-luminouscomponentsparticularlycomplex. Under-
2 McCrackenetal.
standinghowluminousobjects“lightup”in densehaloesof arcmin2 and ∼ 30 arcmin2 K20 and GDDS respectively.
dark matter one is essentially the problem of understanding WhileGlazebrooketal.(2004)andCimattietal.(2008)pro-
galaxy formation. “Semi-analytic” models avoid computa- videdspectroscopicconfirmationofevolvedsystemsz>1.4
tionallyintensivehydrodynamicsimulationsbyutilisingaset and provided further evidence for the downsizing picture
of scaling relations which connect dark matter to luminous (Juneauetal.2005)theirlimitedcoveragemadethemhighly
objects (as will be explained later in this paper), and these susceptible to the effects of cosmic variance. It became in-
models are now capable of predicting how host of galaxy creasinglyclearthatmuchlargersamplesofpassivelyevolv-
properties, mass assembly and star-formation rate evolve as inggalaxieswerenecessary.
afunctionofredshift. AtK<20thenumberofpassivegalaxiesatz∼2redshifts
Observationally, at redshifts less than one, various spec- issmallandspectroscopicfollowupofacompletemagnitude-
troscopic surveys such as the VVDS (LeFèvreetal. 2005; limited sample can be time-consuming. For this reason a
Ilbertetal. 2005; Pozzettietal. 2007) DEEP2 (Faberetal. number of groups have proposed and validated techniques
2007;Noeskeetal.2007)andzCSOSMOS-bright(Lillyetal. basedonapplyingcutsincolour-colourspacetoisolatepopu-
2007b; Silvermanetal. 2009; Mignolietal. 2009) have lations in certain redshift ranges. Starting with the Lyman-
mapped the evolution of galaxy and active galactic nu- break selection at z ∼ 3 (Steideletal. 1996), similar tech-
clei (AGNs) populations over fairly wide areas on the niques have been applied at intermediate redshifts to select
sky. There is now general agreement that star forma- extremelyredobjects(EROs; Hu&Ridgway(1994))ordis-
tion in the Universe peaks at 1 < z < 2 and that ∼ tantred galaxies(DRGs; Franxetal. (2003))andthe “BzK”
50%- 70% of mass assembly took place in the redshift techniqueusedin thispaper(Daddietal.2004). Theadvan-
range1<z<3(Connollyetal.1997;Dickinsonetal.2003; tageofthesemethodsisthattheyareeasytoapplyrequiring
Arnoutsetal. 2007; Pozzettietal. 2007; Noeskeetal. 2007; atmostonlythreeorfourphotometricbands;theirdisadvan-
Pérez-Gonzálezetal. 2008). Alternativelystated, half of to- tage being that the relationships between each object class
day’sstellarmassappearstobeinplacebyz∼1(Droryetal. is complicated and some selection classes contain galaxies
2005; Fontanaetal. 2004). This is largely at odds with with a broadrangeof intrinsicproperties(Daddietal. 2004;
the predictions of hierarchical structure formation models Laneetal.2007;Grazianetal.2007). Therelationshiptothe
which have difficulty in accounting for the large number of underlying complete galaxy population can also be difficult
evolved systems at relatively early times in cosmic history tointerpret(Fèvreetal.2005).Ideally,oneliketomakecom-
(Fontanaetal. 2006). Furthermore, there is some evidence plete mass-selected samples at a range of redshifts but such
that around half the stellar mass in evolved or “passive” calculations require coverage in many wave bands and can
galaxiesassembledrelativelyrecently(Belletal.2004). Itis depend sensitively on the template set (Pozzettietal. 2007;
thusofparamountimportancetogatherthelargestsampleof Longhetti&Saracco2009).Moreover,forredderpopulations
galaxiespossibleatthisredshiftrange. themassuncertaintiescanbeevenlarger;Conroyetal.(2009)
Intheredshiftrange1.4<z<3.0identifiablespectralfea- estimateerrorsaslargeras0.6dexatz∼2.
turesmoveoutoftheopticalwavebandsandsonear-infrared Atz∼1.4Daddietal.(2004)usedspectroscopicdatafrom
imagingandspectroscopybecomeessential. Theroleofenvi- theK20surveyincombinationwithstellarevolutionarytracks
ronmentandlarge-scalestructureattheseredshiftsislargely to define their “BzK” technique. They demonstrated that in
unexplored(Renzini&Daddi2009).Itisalsoworthmention- the (B- z) (z- K) colour-colourplane, star-forming galaxies
ingthatinadditiontomakingitpossibletoselectgalaxiesin andevolvedsystemsarewellseparatedatz>1.4,makingit
thisimportantrange,near-infraredgalaxysamplesoffersev- possibleaccumulatelargersamplesofpassivegalaxiesatin-
eraladvantagescomparedtopurelyopticalselections(see,for termediateredshiftsthatwaspossiblepreviouslywithsimple
exampleCowieetal. (1994)). Theyallow us to select z>1 one-colourcriterion.
galaxies in the rest-frame optical, correspond more closely Subsequently, several other surveys have applied these
to a stellar-mass-selected sample and are less prone to dust techniquesto largersamples of near-infraredselected galax-
extinction. As k- corrections in K- band are insensitive to ies. In one of the widest surveysto date, Kongetal. (2006)
galaxytypeoverawideredshiftrange,near-infrared-selected constructed K-band selected samples over a ∼920 arcmin2
samples provide a fairly unbiased census of galaxy popula- field reaching K ≃20.8 reaching to K ≃ 21.8 over a 320
s s
tionsathighredshifts(providingthattheextinctionisnottoo arcmin2 sub-field. The exploration of a field of this size
high, as in the case of some submillimeter galaxies). Such made possible to measure the clustering properties of star-
samples represent the ideal input catalogues from which to formingandpassivegalaxysampleandtoestablishthatpas-
extracttargetsforspectroscopicsurveysaswellasfordeter- sively evolving galaxies in this redshift range are substan-
miningaccuratephotometricredshifts. tiallymorestronglyclusteredthanstar-formingones,indicat-
Cowieetal. (1996) carried out one of the first extremely ing that a galaxy-type - density relation reminiscent of the
deep, complete K- selected surveys and made the impor- localmorphology-densityrelationmustbealreadyinplaceat
tantdiscoverythatstar-forminggalaxiesatlowredshiftshave z>∼1.4.
smaller masses than actively star-forming galaxies at z ∼ TheUKIDSSsurveyreachesK ∼22.5overa∼0.62-deg2
1, a phenomenon known as “downsizing”. Stated another s
area includedin the Subaru-XMMNewton Deep Surveyand
way, the sites of star-formation “migrate” from higher-mass
Laneetal. (2007) used this data set to investigatethe differ-
systems at high redshift lower-mass systems at lower red-
ent commonly-usedselected techniques at intermediate red-
shifts. More recentK-selected surveysinclude the K20 sur-
shifts,concludingmostbrightDRGgalaxieshavespectraen-
vey (Cimattietal. 2002) reaching K ≃21.8 and the GDDS
s ergydistributionsconsistentwithdustystar-forminggalaxies
survey (Abrahametal. 2004) which reached Ks ≃22.4 pro- or AGNs at ∼ 2. They observe a turn-over in the number
vide further evidence for this picture. The areas cov-
countsofpassiveBzK galaxies.
ered by these surveys was small, comprising only ∼ 55
Other recent works include the MUSYC/ECDFS survey
COSMOS-WIRCamNEAR-INFRAREDIMAGINGSURVEY.I. 3
covering∼900arcmin2toK ∼22.5overtheCDFSouthfield runsbetween2005and2007.Alistoftheseobservationsand
s
(Tayloretal. 2009), not to be confused with the GOODS- the total amountof on-skyintegrationtime for each run can
MUSIC catalog of Fontanaetal. (2006), which covers 160 befoundinTable1.
arcmin2 of GOODS-South field to K ∼23.8. This K-band Observingtargetswerearrangedinasetofpointingcentres
s
selected catalogue, as well as the FIREWORKS catalog by arrangedinagridacrosstheCOSMOSfield.Ateachpointing
Wuytsetal. (2008), are based on the ESO Imaging Survey centreobservationswereshiftedusingthepredefined“DP10”
coverageoftheGOODS-Southfield14 Thesestudieshavein- WIRCAMditheringpattern,inwhicheachobservingcubeof
vestigated, amongst other topics, the evolution of the mass fourmicro-ditheredobservationsisoffsetby1′12′′inRAand
functionat z∼2 and whatnumberof red sequencegalaxies 18′′ in decl. Our overall observing grid was selected so as
whichwerealreadyinplaceatz∼2. to fill all gaps between detectors and provide a uniform ex-
Finally,oneshouldmentionthatmeasuringthedistribution posure time per pixel across the entire field and to ensure a
ofa“tracer”population,eitherredpassivegalaxiesornormal the WIRCAM focal plane was adequatelysampled to aid in
field galaxies can provide useful additional information on thecomputationoftheastrometricsolution. Allobservations
the galaxyformationprocess. In particularone canestimate were carried out in queue-scheduled observing mode. Our
themassofthedarkmatterhaloeshostingthetracerpopula- programconstraintsdemandeda seeing betterthan 0.8′′ and
tion and, given a suitable model for halo evolution, identify an air mass less than 1.2. Observations were only validated
the present-day descendants of the tracer population, as has byCFHTiftheseconditionsweremet. Inpractice,afewval-
beendoneforLymanbreakgalaxiesatz∼3. Afewstudies idated images were outside these specifications (usually due
have attempted this for passive galaxies at z∼2, but small toshort-termchangesinobservingconditions),andwerere-
fields of view have made these studies somewhat sensitive jectedatlatersubsequentprocessingsteps.
to the effects of cosmic variance. The “COSMOS” project Observations were made in the Ks filter (“K-short”;
(Scovilleetal. 2007) comprising a contiguous 2 deg2 equa- (Skrutskieetal.2006)),whichhasabluercutoffthanthestan-
torialfieldwithextensivemulti-wavelengthcoverage,iswell dard K filter, and unlike the K′ filter (Wainscoat&Cowie
suitedtoprobingtheuniverseatintermediateredshift. 1992) has a “cut-on” wavelength close to standard K. This
InthispaperwedescribeaK-bandsurveycoveringtheen- reducesthethermalbackgroundandfortypicalgalaxyspec-
s
tire ∼1.9deg2 COSMOS field carried out with WIRCam at tra decreases the amount of observing time needed to reach
a given signal-to-noiseratio (S/N) comparedto the standard
the Canada-France-Hawaii Telescope (CFHT). The addition
of deep, high resolution K- data to the COSMOS field en- K- filter. A plot of the WIRCam Ks filter is available from
CFHT.16
ables us to address many of scientific issues outlined in this
introduction,inparticulartoaddressthenatureofthemassive
2.2. Pre-reductions
galaxypopulationintheredshiftrange1<z<2.
Our principal aims in this paper are to (1) present a cat- WIRCam images were pre-reduced using IRAF17 using a
alogue of BzK-selected galaxies in the COSMOS field; (2) two-passmethod. Toreducethedatavolumethefourmicro-
present the number counts and clustering properties of this dithers were collapsed into a single frame at the beginning
sampleinorderprincipallytoestablishthecataloguereliabil- of the reduction process. This marginally reduced the im-
ity;(3)presenttheCOSMOSK- imagingdataforthebenefit age quality (by less than 0.1′′ FWHM) but made the reduc-
ofotherpaperswhichmakeindirectuseofthisdataset(forex- tionprocessmanageableonasinglecomputer.Afterstacking
ample,inthecomputationofphotometricredshiftsandstellar the sub-framesthe data were bias subtracted and flat fielded
masses). using the bias and flat field frames provided by the CFHT
Several papers in preparation or in press make use of the WIRCam queue observing team. A global bad pixel mask
data presented here. Notably, Ilbertetal. (2009b) combine was generated using the flat to identify the dead pixels; the
thisdatawithIRACandopticaldatatoinvestigatetheevolu- dark frameswere used to identify hot pixels. A median sky
tionofthegalaxymassfunction. ThedeeppartofthezCOS- wasthencreatedandsubtractedfromtheimagesusingallim-
MOS survey(Lillyetal. 2007a) is currentlycollecting large agesinagivenditherpattern. Theimageswerethenstacked
numbers galaxies spectra at z>1 in the central part of the usingintegerpixeloffsetsandtheWCSheaderswithIRAF’s
COSMOSfieldusingacolour-selectionbasedontheK-band imcombinetask. Theseinitialstacksofthesciencedataare
datasetdescribedhere. used to generate relatively deep object masks through SEx-
Throughout the paper we use a flat lambda cosmology tractor’s ’CHECKIMAGE_TYPE = OBJECTS’ output file.
(Ωm = 0.3, ΩΛ = 0.7) with h = H0/100 km s- 1 Mpc- 1. Theseobjectmasksareusedtoexplicitlymaskobjectswhen
AllmagnitudesaregivenintheABsystem,unlessotherwise re-generatingthe sky in the second pass reduction. Supple-
stated. The stacked K image presented in this paper will mentary masks for individual images are made to mask out
s
madepubliclyavailableatIRSA.15 satellites or otherbad regionsnotincludedin the globalbad
pixelmaskonaframe-by-framebasis.
2. OBSERVATIONSANDDATAREDUCTIONS In the secondpass reduction, we individuallysky-subtract
each science frame using the objectmasked imagesand any
2.1. Observations
residualvariationsintheskyisremovedbysubtractingacon-
WIRCam (Pugetetal. 2004) is a wide-field near-infrared stant to yield a zero mean sky level. These individual sky-
detectoratthe3.6mCFHTwhichconsistsoffour2048×2048 subtractedimagesofasinglescienceframearethenaveraged
cryogenicallycooledHgCdTearrays. Thepixelscaleis0.3′′ with both sigma-clipping to remove cosmic rays and mask-
giving a field of view at prime focus of 21′×21′. The data ing using a combinationof the object mask and any supple-
described in this paper were taken in a series of observing mentarymask to removethe realsourcesandbad regionsin
14http://www.eso.org/science/goods/releases/20050930./ 16http://www.cfht.hawaii.edu/Instruments/Filters/wircam.html
15http://irsa.ipac.caltech.edu/Missions/cosmos.html 17http://iraf.noao.edu/
4 McCrackenetal.
Table1
COSMOS-WIRCamobservations
Year RunID totalintegrationtime(hrs)
2005 BH36 8.1
2005 BH89 3.5
2006 AH97 12.8
2006 AC99 2.1
2006 BF97 12.7
2006 BH22 13.3
2007 AF34 6
2007 AC20 6.1
2007 AH34 17
the sky frames. The region around the on-chip guide star is
also masked. These images are further cleaned of any non-
constant residual gradients as needed by fitting to the fully
masked (object + supplementary + global bad pixel masks)
background on a line-by-line basis. Any frames with poor
skysubtractionorotherartifactsafterthisstepwererejected.
NextamplifiercrosstalkisremovedforbrightTwoMicron
AllSkySurvey(2MASS)starswhichcreates“donut”shaped
ghostsatregularlyspacedintervals. Theseare unfortunately
variable,with theirshapeandleveldependingon thebright-
nessofthestarandtheamplifierthestarfallson.Weproceed Figure1. ThedifferencebetweenCOSMOS-WIRCamtotalmagnitudesand
2MASSmagnitudesasafunctionofCOSMOS-WIRCamtotalmagnitude.
in three steps: we first build for each star a median image
of the potential cross talk pattern it could generate. This is
donebytakingthemedianof13×13pixelssub-framesat64 tions for large numbersof images. The relative positions of
pixelintervalsaboveandbelowthe starposition,takinginto eachwircamdetectoraresuppliedbyprecomputedheaderfile
accountthefullbadpixelmask. Next,wecheckwhetherthe whichallowsustousetheinitial,approximateastrometricso-
cross-talkissignificantbycomparingthelevelofthemedian lutionsuppliedbyCFHTasafirstguess.
imagetotheexpectednoise. Ifcross-talkisdetected,wesub- Ourinternalandexternalastrometric accuraciesare ∼0.2
tract it by fitting at every position it could occur the median and∼0.1arcsecondsrespectively. ScampproducesanXML
shapedeterminedintheprecedingsteps. summaryfilecontainingalldetailsoftheastrometricsolution,
After pre-reduction, the TERAPIX tool QualityFITS andanyimageshowingalargereducedchisquaredisflagged
was used to create weight-maps, catalogues, and quality as- andrejected.
sessment Web pages for each image. These quality assess- We do not use Scamp to compute our photometric solu-
ment pages provide information on the instrument point- tions(theversionweused(1.2.11MP)assumesthattherela-
spreadfunction(PSF),galaxycounts,starcounts,background tivegainsbetweeneachWIRCamdetectorisfixed). Instead,
maps and a host of other information. Using this infor- we first use the astrometric solutioncomputedby scamp to
mation, images with focus or electronic problems were re- match 2MASS stars with objects in each WIRCam image.
jected. QualityFITSalsoproducesaweight-mapforeach Wethencomputethezero-pointofeachWIRCamdetectorby
WIRCam image; this weightmap is computedfrom the bad comparingthe fluxesof2MASS sourceswith the onesmea-
pixelmaskandtheimageflat-field. Observationswithseeing sured by SExtractor in a two-pass process. First, satu-
FWHMgreaterthan1.1′′wererejected. ratedobjectsbrighterthanK =13.84magnitudesorobjects
AB
where the combined photometric error between SExtractor
2.3. Astrometricandphotometricsolutions
and2MASS is greaterthan 0.2magnitudesare rejected. An
In the next processing step the TERAPIX software tool initial estimate of the zero-point is produced by computing
Scamp (Bertin 2006) was used to compute a global astro- the median of the difference between the two cleaned cata-
metricsolutionusingtheCOSMOSi*catalogueCapaketal. logues.Anyobjectwherethisinitialestimationdifferbymore
(2007)asanastrometricreference. than3σfromthemedianisrejected,andthefinaldifferenceis
Scamp calculates a global astrometric solution. For each computedusinganerror-weightedmean. Thedifferencebe-
astrometric "context" (defined by the QRUNID image key- tween2MASSandCOSMOScataloguesinthestackedimage
wordsuppliedbyCFHT)wederiveatwo-dimensionalthird- isshowninFigure1. Notethatthemainsourceofscatterat
order polynomial which minimises the weighted quadratic thesemagnitudes(13.84<KAB<17)comesfromuncertain-
sum of differences in positions between the overlapping tiesin2MASSphotometry. Themagnituderangewith good
sourcesandtheCOSMOSreferenceastrometriccataloguede- sourcesbetweenobjectsin2MASSandWIRCamcatalogues
rived from interferometric radio observations. Each obser- isquitenarrow(aroundtwomagnitudes)sosettingthesepa-
vation with the same context has the same astrometric so- rametersisquiteimportant.
lution. Note that we use the STABILITY_MODE “instru- Finally,allimagesandweight-mapswere combinedusing
ment”parametersettingwhichassumesthatthederivedpoly- Swarp(Bertinetal.2002).Thetangentpointusedinthispa-
nomialtermsareidenticalexposuretoexposurewithinagiven per was 10h00m15s,+02◦17′34.6′′ (J2000) with a pixel scale
contextbutallowsforanamorphosisinducedbyatmospheric of 0.15”/pixel to match COSMOS observations in other fil-
refraction. This provides reliable, robust astrometric solu- ters. The final image has an effective exposure time of one
COSMOS-WIRCamNEAR-INFRAREDIMAGINGSURVEY.I. 5
secondand a zero pointof 31.40AB magnitudes. This data
will be publically available from the IRSA web site. The
seeing on the final stack is excellent, around 0.7′′ FWHM.
Thankstorigorousseeingconstraintsimposedduringqueue-
scheduled observations, seeing variation over the final stack
issmall,lessthan∼5%.
2.4. Complementarydatasets
We also add Subaru-suprime B , i+ and z+ imaging data
J
(following the notation in Capaketal. (2007)). We down-
loaded the image tiles from IRSA18 and recombined them
with Swarp to producea single largeimage astrometrically
matchedtotheK- bandWIRCamimage(theastrometricso-
s
lutionsfortheimagesatIRSAwerecalculatedusingthesame
astrometricreferencecatalogueasourcurrentK- image,and
s
theysharethesametangentpoint).Catalogueswereextracted
usingSExtractor(Bertin&Arnouts1996)indual-image
mode, using the K- band image as a detection image. An
s
additionalcomplicationarisesfromthefactthattheB- Sub-
aru images saturate at B∼19. To account for this, we use
the TERAPIX tool Weightwatcher to create “flag-map”
images in which all saturated pixels are indicated (the satu-
rationlimitwasdeterminedinteractivelybyexaminingbright
stars in the images). Duringthe subsequentscientific analy-
Figure2. Recoveryfractionforpoint-likesources,bulgesanddisksforthe
sis, all objects which have flagged pixels are discarded. We
centralregionoftheCOSMOS-WIRCamstack.Notethattheslightdeclinein
alsomanuallymaskedallbrightobjectsbydefiningpolygon completenessatrelativelybrightmagnitudes(KAB∼22)isduetoconfusion.
region files. In addition, we also automatically masked re-
gionsatfixedintervalsfromeachbrightstartoremoveposi-
tivecrosstalkin theK- image. Thefinalcataloguecoversa
totalareaof1.9deg2asftermasking. Btot=BJ- 0.1093 (3)
3. CATALOGUEPREPARATIONANDPHOTOMETRIC Forthez+ ourcorrectionsaremoreinvolved.
CALIBRATION As noted in Capaketal. (2007) the Subaru z-band im-
agesweretakenoverseveralnightswithvariableseeing. To
3.1. Computingcolours
mitigate the effects of seeing variation on the stacked im-
We used SExtractor in dual-image mode with the age PSF individual exposures were smoothed to the same
K- bandasa referenceimageto extractourcatalogues. For (worst) FWHM with a Gaussian before image combination.
s
thisK- selectedcatalogue,wemeasuredK- bandtotalmag- This works well at faint magnitudes where many exposures
s s
nitudesusingSExtractor’sMAG_AUTOmeasurementand were taken so the non-Gaussian wings of the PSF average
aperturecolours. Ouraperturemagnitudesaremeasuredina out. However, at bright magnitudes (z+ ∼20) the majority
diameterof2′′andwecomputeacorrectionto“total”magni- oflongerexposuresaresaturated,sothenon-Gaussianwings
tudesbycomparingthefluxofpoint-likesourcesinthissmall ofthePSF inthe fewremainingexposurescanbiasaperture
aperturewithmeasurementsinalarger6′′ diameteraperture. photometry. To correct for this non-linear effect we apply
WeverifiedthatfortheB andz+ Subaru-suprimeimagesthe a magnitude dependent aperture correction in the transition
J
differencebetweentheseaperturesvarieslessthan0.05mag- magnitudesbetween19<z<20.Afterfirstapplyingthecor-
nitudes,indicatingthatseeingvariationsaresmallacrossthe rectiontototalmagnitude,
images which was confirmed by an analysis of the variation
ofthebest-fitGaussianFWHMforB,zandKimagesoverthe z+ =z+- 0.1093 (4)
tot
full2deg2field. We apply a further correction, for z+ < 19.0, z+ = z+ -
Obviouslyforextendedbrightobjectsthiscolourmeasure- 0.023andforz+>20.0,z+ =z+ +0.1.For19<z+to<t 20,tot
mentwillbedominatedtheobjectnucleusasthemajorityof tot tot
the z∼2 objects studied in this paper are unresolved, dis- z+ =z+ +(z+ - 19.0)×0.077+0.023 (5)
tot tot tot
tant galaxies we will neglect this effect. We verified that
for these objects, variable-aperture colours computed using Flux errors in SExtractor are underestimated (in part
MAG_AUTO gave results very similar (within 0.1 mag) to due to correlated noise in the stacked images) and must be
thesecorrectedaperturecolours. corrected. For a given4000×4000image section, we com-
Basedontheseconsiderations,weapplythefollowingcor- pute a correction factor from the ratio of the one-sigma er-
rectionstoouraperturemeasurementstocomputecolours: rorbetweena seriesof2′′ aperturesonemptyregionsofthe
skyandthemedianSExtractorerrorsforallobjects. The
i+ =i+- 0.1375 (1) mean correctionfactor is derivedfrom several such regions.
tot
For B,i and z imageswe multiply our flux errorsby 1.5; for
theK imageweapplyacorrectionfactorof2.0.
K =K′- 0.1568 (2) s
tot
3.2. Cataloguecompletenessandlimitingmagnitude
18http://irsa.ipac.caltech.edu/
6 McCrackenetal.
We conducted an extensive set of realistic simulations to
determinelimitingmagnitudeasa functionofobjectmagni-
tudeandprofile. Inoursimulations,wefirstcreatedanoise-
lessimagecontainingarealisticmixofstars,disk-dominated
and bulge-dominatedgalaxies using the TERAPIX software
stuff and skymaker. Type-dependent luminosity func-
tions are their evolution with redshift are taken from the
VVDS survey (Zuccaetal. 2006; Ilbertetal. 2006). The
spectral energy distribution (SED) of each galaxy type was
modelledusingempiricaltemplatesofColemanetal.(1980).
Thedisksizedistributionwasmodelledusingthefittingfor-
mulaandparameterspresentedindeJong&Lacey(2000).
Next, we used SExtractor to detect all objects on the
stacked image (using the same configuration used to detect
objects for the real catalogues) and to produce a CHECK-
IMAGE in which all these objects were removed (keyword
CHECKIMAGE_TYPE -OBJECTS). In the next step this
empty background was added to the simulated image, and Figure3. Depth map for the COSMOS-WIRCam survey. This map was
SExtractorrunagainin“assoc-mode”inwhichamatchis constructed fromtheweight-map fromthefinalstacked image. Thegrey-
scalecorrespondstothemagnitudeatwhichapointsourceisdetectedat5σ
attemptedbetweeneachdetectedgalaxyandtheoutputsimu- ina2′′aperture.
latedgalaxycatalogueproducedbystuff. Inthelaststep,
the magnitude histograms of the number output galaxies is
comparedtothemagnitudehistogramsintheinputcatalogue;
thisratiogivesthecompletenessfunctionofeachtypeofob-
ject. Intotalaround30,000objects(galaxyandstars)inone
imagewereusedinthesesimulations. Theresultsfromthese
simulationsare shown in Figure 2. The solid line shows the
completenesscurveforstarsandthedottedlinefordisks.The
completenessfractionis70%fordisksand90%forstarsand
bulgesatK ∼23.
s
In addition to these simulations, we compute upper limits
foreachfilterbasedonsimplenoisestatisticsinaperturesof
2′′ (after applying the noise correction factors listed above).
The 1σ, 2′′ limiting magnitude for our data at the centre of
the field are 29.1,27.0and25.4 AB magnitudesfor B, z and
K magnitudesrespectively.
s
Arelatedissueistheuniformityofthelimitingmagnitude
over the full image. Figure 3 shows the limiting magnitude
as a function of position for the K stack. This was created
s
by converting the weight map to an rms error map, scaling
this error map from 1σ per pixelto units of 5σ in the effec-
tive area of an optimally weighted 0.7′′ aperture, and then
converting this flux to units of AB magnitude. This depth
mapagreeswellwiththecompletenesslimitforpointsources
shownFigure2. NotethatfutureCOSMOS-WIRCamobser-
vations (which will be available in around one years’ time) Figure4. The(B- Z)ABvs(z- K)AB diagramforallgalaxiesintheCOS-
areexpectedtofurtherreducethedepthvariationsacrossthe MOSfield.Fourdistinctregionsareshown:stars(lowerpartofthediagram),
galaxies(middle),star-forminggalaxies(left)andpassively-evolvinggalax-
surveyarea.
ies(topright). ThesolidlineshowsthecoloursofstarsintheBzKfilterset
Based on the considerations outlined in this section, we ofDaddietal.computedusingthemodelsofLejeuneetal.(1997)
adoptK =23asthelimitingmagnitudeforourcatalogues.At
s
thislimitourcatalogueisgreaterthan90%and70%complete
forpoint-sourcesandgalaxiesrespectively.Atthismagnitude forming galaxies at z ∼3, provided they are not too heav-
thenumberofspurioussources(basedoncarryingoutdetec- ily reddened. Similar techniques can be used at 1<z<3
tionsonanimageoftheK stackmultipliedby-1)islessthan (Adelbergeretal. 2004; Erbetal. 2003) and large samples
s
1%ofthetotal. of UV-selected star-forminggalaxies now exist at these red-
shifts. At intermediate redshifts, spectroscopy has shown
3.3. TheBzKselection
that “ERO” galaxies which are galaxies selected according
One of the principal objectives of this paper is to pro- to red optical-infrared colours contains a mix of old pas-
duce a reliable catalogue of objects at z∼2 using a colour- sive galaxies and dusty star-forming systems in the redshift
colour selection technique. A number of different methods range0.8<z<2(Cimattietal.2002;Yanetal.2004). The
now exist to select galaxies in colour-colour space. For in- “DRG” criteria, which selects galaxies with (J- K) >
Vega
stance, the “dropout” technique (Steideletal. 1996) makes 2.3 is affected by similar difficulties (Papovichetal. 2006;
use of Lyman-break spectral feature and the opacity of the Krieketal. 2006). On the other hand, the “BzK” criterion
high-redshift universe to ultraviolet photons to select star- introduced by Daddietal. (2004) can reliably select galax-
COSMOS-WIRCamNEAR-INFRAREDIMAGINGSURVEY.I. 7
iesintheredshiftrange1.4<∼z<∼2.5withrelativelyhighcom-
pleteness and low contamination. Based on the location of
star-forming and reddened systems in a spectroscopic con-
trol sample lie in the (B- z) and (z- K) plane and consider-
ationsofgalaxyevolutionarytracks,ithasbeenadoptedand
testedinseveralsubsequentstudies(e.g.,Kongetal.(2006);
Laneetal. (2007);Hayashietal.(2007);Blancetal. (2008);
Dunneetal. (2009); Popessoetal. (2009)). BzK- selected
galaxiesareestimatedto havemasses of∼1011M atz∼2
⊙
(Daddietal.2004;Kongetal.2006).
Comparedtoothercolourcriteria,itofferstheadvantageof
distinguishing between actively star-forming and passively-
evolving galaxies at intermediate redshifts. It also sharply
separates stars from galaxies, and is especially efficient for
z>1.4 galaxies. The criterion was originally designed us-
ingtheredshiftevolutionintheBzK diagramofvariousstar-
forming and passively-evolving template galaxies (i.e., syn-
thetic stellar populations)located over a wide redshift inter-
val. Daddietal. carried out extensive verifications of their
selectioncriteriausingspectroscopicredshifts.
To make the comparison possible with previous studies
we wanted our photometric selection criterion to match as
closely as possibleas the original“BzK” selection proposed
inDaddietal.andadoptedbytheauthorscitedabove.Asour Figure5. Ks- selected galaxy andstarcounts fromtheCOSMOS survey
filtersetisnotthesameasthisworkweappliedsmalloffsets (opencirclesandstarsrespectively)comparedtomeasurementsfromrecent
(based on the tracks of synthetic stars), following a similar wide-fieldnear-infraredsurveys.
procedureoutlinedinKongetal.(2006).
ToaccountforthedifferencesbetweenourSubaruB- filter the empirically corrected spectra presented in Lejeuneetal.
andtheB- VLTfilterusedbyDaddietal.(2004)weusethis (1997),anditagreesverywithourcorrectedstellarlocus.
empirically-derivedtransformation, defining bz=B - z+ ,
thenforblueobjectswithbz<2.5, Jtotal tot 4. SOURCECOUNTS
Wenowpresentnumbercountsofthethreepopulationsse-
bzcosmos=bz+0.0833×bz+0.053 (6) lectedinthepreviousSection.
otherwise,forobjectswithbz>2.5,
4.1. Starandgalaxycounts
bz =bz+0.27 (7) Figure5showsourdifferentialgalaxynumbercountscom-
cosmos
paredtoaselectionofmeasurementsfromtheliterature. We
This “bz ” quantity is the actual corrected (B- z)
cosmos AB note that at intermediate magnitudes (20<K <22) counts
colourwhichweuseinthispaper. s
from the four surveys presented here are remarkably con-
Finally we divide our catalogue into galaxies at z <1.4,
sistent (Elstonetal. 2006; Huangetal. 1997; Hartleyetal.
stars,star-forminggalaxiesandpassivelyevolvinggalaxiesat
2008). At 16 < K < 20 discrepancies between different
1.4<z<2.5,byfirstdefiningtheBzKquantityintroducedin s
groupsconcerningmeasurementoftotalmagnitudesandstar-
Daddietal.(2004):
galaxyseparationleadstoanincreasedscatter. Atthesemag-
nitudes, shot noise and large-scale-structure begin to domi-
BzK≡(z- K)- (B- z) (8)
natethenumbercounterrors.
For galaxies expected at z > 1.4 star-forming galaxies TheCOSMOS-WIRCamsurveyiscurrentlytheonlywork
(hereafter sBzK) are selected as those objects with BzK > toprovideunbrokencoverageovertherange16<Ks<23.In
- 0.2. One should also note that the reddening vector in the addition, our colour-selectedstar-galaxyseparation provides
BzKplaneisapproximatelyparalleltothesBzKselectioncri- a very robust way to reject stars from our faint galaxy sam-
teria, which ensure that the selection is not biased against ple. These stellar counts are shown by the asterisks in Fig-
heavilyreddeneddustygalaxies. ure 5. We note that at magnitudes brighter than Ks ∼18.0
Old, passively evolving galaxies (hereafter pBzK) can be ourstellarnumbercountsbecomeincompletebecauseofsat-
selectedasthoseobjectswhichhave uration in the Subaru B image (our catalogues exclude any
objectswithsaturatedpixelswhichpreferentiallyaffectpoint-
BzK<- 0.2,(z- K)>2.5. (9) likesources).Ourgalaxyandstarnumbercountsarereported
inTable2.
Starsareselectedusingthiscriteria:
4.2. sBzK and pBzKcounts
(z- K)<- 0.5+(B- z)×0.3 (10)
Figure 6 shows the counts of star-forming BzK galaxies
Finally, the full galaxy sample consists simply of objects comparedtomeasurementsfromtheliterature. Thesecounts
whichdonotfulfillthisstellaritycriterion. Theresultofthis are summarisedin Table 2. We note an excellentagreement
division is illustrated in Figure 4. The solid line represents withthecountsinKongetal.(2006)andthecountspresented
thecoloursofstars inthe BzK filter set ofDaddietal. using by the MUYSC collaboration (Blancetal. 2008). However,
8 McCrackenetal.
Table2
DifferentialNumberCounts
ofStars,GalaxiesandStar-ForminggalaxiesperHalf-magnitudeBin.
Galaxies Stars sBzK′s
KAB Ngal log(Ngal)deg- 2 Nstars log(Nstars)deg- 2 NsBzK log(NsBzK)deg- 2
16.25 102 1.73 ··· ··· ··· ···
16.75 204 2.03 ··· ··· ··· ···
17.25 487 2.41 ··· ··· ··· ···
17.75 838 2.65 ··· ··· ··· ···
18.25 1479 2.89 750 2.60 ··· ···
18.75 2588 3.14 928 2.69 ··· ···
19.25 4073 3.33 1038 2.74 24 1.10
19.75 6410 3.53 1138 2.78 61 1.51
20.25 9433 3.70 1257 2.82 195 2.01
20.75 12987 3.84 1397 2.87 710 2.57
21.25 17027 3.95 1425 2.88 1982 3.02
21.75 22453 4.07 1586 2.92 4191 3.35
22.25 29502 4.19 1504 2.90 7684 3.61
22.75 36623 4.29 1596 2.93 11109 3.77
Note.—Note.Logarithmiccountsarenormalisedtotheeffectiveareaofoursurvey,1.89deg2.
Figure6. Numbercountsforstar-formingBzKgalaxies intheCOSMOS- Figure7. SelectiondiagramforthepassiveBzKpopulation. Objectswith
WIRCamsurvey(opencircles)comparedtomeasurementsfromtheliterature rightward-pointingarrowsaregalaxiesplottedatthelowerlimitoftheir(B-
andthepredictionsofthemodelofKitzbichler&White(dashedline). z)AB colours. Circles areobjects selected as pBzK galaxies; normalsBzK
galaxiesarenotshown.
thecountspresentedbytheUKIDSS-UDSgroup(Laneetal.
2007;Hartleyetal.2008)aresignificantlyoffsetcomparedto sBzK with B-band non-detections(shown with the green ar-
ourcountsatbrightmagnitudes,andbecomeconsistentwith rows)maybescatteredrightwardintothe pBzKregion.
itbyK ∼22. Theseauthorsattributethediscrepancytocos- Counts for our passive galaxy population including these
s
mic variance but we find photometric offsets a more likely “additional”objectsarerepresentedbythehatchedregionin
explanation(seebelow). Figure 8. The upper limit for the source counts in this fig-
Figure7showsinmoredetailthezoneoccupiedbypassive urerepresentsthecaseinwhichallthe(z- K) >2.5sources
s
galaxiesinFigure4. Leftofthediagonallineareobjectsclas- undetected in B are scattered into the pBzK region. Even
sified as star-formingBzK galaxies. Objects not detected in accounting for these additional objects we unambiguously
Bareplottedasright-pointingarrowswithcolourscomputed observe a flattening and subsequent turnover in the passive
fromtheupperlimitoftheirB- magnitudes.Anobjectiscon- galaxy counts at around K ∼22, well above the complete-
s
sideredundetectedif thefluxin a2′′apertureisless thanthe ness limit of either our K- or B- data in agreement with
s
corrected1σnoiselimit. FortheB- bandthiscorrespondsto (Hartleyetal.2008).
approximately 29.1 mag. This criterion means that in addi- This upper limit, however, is a conservativeestimate. We
tiontothegalaxiesalreadyinthe pBzK selectionbox,fainter havemadeabetterestimateofthisupperlimitbycarryingout
COSMOS-WIRCamNEAR-INFRAREDIMAGINGSURVEY.I. 9
Table3
DifferentialNumberCountsforthepassiveBzKpopulation.
PassiveBzK PassiveBzK(upperlimits)a
KAB NpBzK log(NpBzK)deg- 2 NpBzK log(NpBzK)deg- 2
19.25 13 0.84 13 0.84
19.75 69 1.56 69 1.56
20.25 265 2.15 280 2.17
20.75 553 2.47 621 2.52
21.25 837 2.65 1015 2.73
21.75 963 2.71 1285 2.83
22.25 757 2.60 1229 2.81
22.75 475 2.40 984 2.72
Note. —Logarithmiccountsarenormalisedtotheeffectiveareaofour
survey,1.89deg2.
aTheupperlimittothepBzKwascomputedbyincludingallthesBzKgalax-
iesundetectedinBwith(z- K)>2.5
mationtotheDaddietal.filterset.
4.3. ComparisonwiththeSemi-analyticModel
ofKitzbichler&White
In Figures 5, 6 and 8 we show counts of galax-
ies extracted from the semi-analytical model presented in
Figure8. DifferentialnumbercountsforthepassiveBzKpopulationinthe
COSMOS-WIRCamsurvey(opencircles)comparedtomeasurementsfrom Kitzbichler&White(2007).
theliteratureandthepredictionsofthemodelofKitzbichler&White(dashed Semi-analyticmodelsstartfromeitherananalytic“merger
line). Theshadedregionrepresentsanupperlimitonthenumbercountsof tree” of dark matter haloes or, in the case of the model
passiveBzKsifallstar-formingBzKsinFigure7weremovedintotheregion
usedhere,mergertreesderivedfromanumericalsimulation,
ofthefigureoccupiedbythepassivelyevolvingpopulation.
the Millennium simulation (Springeletal. 2005)). Galax-
ies are “painted” onto dark matter haloes using a variety
a stacking analysis of the objects not detected in B- in both
of analytical recipes which include treatments of gas cool-
thepassiveandstar-formingregionsoftheBzK diagram. For
ing, star-formation, supernovae feedback, and black hole
eachapparentK magnitudebininTablewemedian-combine
s growth by accretion and merging. An important recent ad-
Subaru B- band postage stamps for objects with no B-band
vance has been the addition of “radio mode” AGN feed-
detection,producingseparatestacksforthestar-formingand
back Boweretal. (2006); Crotonetal. (2007) which helps
passive regions of the BzK diagram. In both cases, objects
provide a better fit to observed galaxy luminosity func-
below our detection limit are clearly visible (better than a
tions. The Kitzbichler&White model is derived from the
three-sigmadetection)in ourstacked imagesat each magni-
workpresentedbyCrotonetal.(2006)andfurtherrefinedby
tudebintoK 23.ByassumingthatthemeanBmagnitudeof
s Lucia&Blaizot (2007). It differsonly from these papersin
thestacked sourceto be theaveragemagnitudeofourunde-
theinclusionofarefineddustmodel. Wereferthereadersto
tectedsources,wecancomputetheaverage(B- z)colourof
theseworksforfurtherdetails. Anextensivereviewofsemi-
ourundetectedsources,andreassigntheirlocationintheBzK
analyticmodellingtechniquescanbefoundinBaugh(2006).
diagramifnecessary.Thisexperimentshowsthatatmostonly
To derive counts of quiescent galaxies, we follow the ap-
15%ofthestar-formingBzK galaxiesundetectedinB- move
proach of Daddietal. (2007) and select all galaxies at z>
tothepassiveBzK region.
1.4 in the star-formation rate - mass plane (Figure 18 from
OurnumbercountsaresummarisedinTable3,whichalso
Daddietal.) which have star-formation rates less than three
indicates the upper count limits based on B- band observa-
times the median value for a given mass. Star-forming ob-
tions.Asbefore,ourcountsareingoodagreementwiththose
jectsweredefinedasthosegalaxieswhichdonotobeythis
presentedinKongetal.(2006)andBlancetal.(2008)butare
criterion, in this redshift range. (Unfortunately the publicly
abovethecountsinHartleyetal.(2008).
available data do not contain all the COSMOS bands so we
Toinvestigatetheoriginofthisdiscrepancy,we compared
cannotdirectlyapplytheBzK selectioncriteriontothem.).
our BzK diagram with Hartleyetal.’s, which should also be
In all three plots, the models over-predict the number of
intheDaddietal.filterset. WesuperposedourBzK diagram faintgalaxies,aneffectalreadyobservedfortheK- selected
onthatofHartleyetal.andfoundthattheHartleyetal.stellar
samples investigated in Kitzbichler&White. We also note
locus is bluer by ∼0.1 in both (B- z) and (z- K) compared
that adding an upper redshift cut to the model catalogues to
toourmeasurements19. Wehavealreadyseenthatourstellar
match our photometric redshift distributions (see later) does
locus agrees well with the theoretical stellar sequence com-
notchangeappreciablythenumberofpredictedgalaxies.
putedusingtheLejeuneetal. (1997) syntheticspectrain the
Consideringinmoredetailthecountsofquiescentgalaxies
Daddietal.filtersetandalsowiththestellarlocuspresented
wefindthatat20<K <20.5modelsarebelowobservations
inDaddietal.andKongetal.. Weconcludethereforethatthe s
byafactoroftwo,whereasat22.5<K <23.0modelcounts
numbercountsdiscrepanciesarisefromanincorrecttransfor- s
areinexcessofobservationsbyaroundafactorof1.5.Given
the narrow redshift range of our passive galaxy population,
19Sincethefirstdraftofthismanuscriptwasprepared,acommunication
apparentKmagnitudeis a good proxyfor absolute K mag-
withW.Hartley hasconfirmedthat thetransformations totheDaddietal. s s
systemwereincorrectlycomputedintheirwork. nitudewhichcanitself bedirectlyrelatedtounderlyingstel-
10 McCrackenetal.
lar mass Daddietal. (2004). This implies that these models
predict too many small, low-mass passively-evolving galax-
iesandtoofewlargehighmasspassivelyevolvinggalaxiesat
z∼1.4.
It is instructive to compareour results with Figure 7 from
Kitzbichler&White, which shows the stellar mass function
fortheirmodels. Atz∼2,themodelsbothunder-predictthe
numberofmassiveobjectsandover-predictthenumberofless
massiveobjects,aneffectmirroringtheoverabundanceoflu-
minouspBzKobjectswithrespecttotheKitzbichler&White
modelseeninourdata.
A similar conclusion was drawn by Fontanaetal. (2006)
whorecentlycomparedpredictionsforthegalaxystellarmass
functionformassivegalaxiesforavarietyofmodelswithob-
servations of massive galaxies up to z ∼ 4 in the GOODS
field. They also concluded that models incorporating AGN
feedbacksimilar to Kitzbichler&White under-predictedthe
numberofhighmassgalaxies.
Thankstothewide-area,deepB- banddataavailableinthe
COSMOSfield,weareabletomakereliablemeasurementsof
the number of faint passive BzK galaxies. Reassuringly, the
turnoverincountsofpassivegalaxiesobservedinourdatais
qualitativelyinagreementwiththemeasurementsofthefaint
endofthemassfunctionofquiescentgalaxiesat1.5<z<2
Figure9. TheRedshiftdistributionforfieldgalaxies(toppanel)sBzK(mid-
madeinIlbertetal.(2009b). dlepanel)and pBzK galaxies (bottompanel), computedusingthe30-band
photometricredshiftspresentedinIlbertetal.(2009a).
5. PHOTOMETRICREDSHIFTSFORTHEPBZKAND
SBZKPOPULATION Anewmethodtoaccountforemissionlineswasimplemented
For many years studies of galaxy clustering at z∼2 have usingrelationsbetweenthe UV continuumandthe emission
linefluxesassociatedwithstarformationactivity.
beenhinderedbyourimperfectknowledgeofthesourcered-
Basedonacomparisonbetweenphotometricredshiftsand
shift distribution and small survey fields. Coverage of the
4148 spectroscopic redshifts from zCOSMOS, we estimate
2deg2 COSMOS field in thirty broad, intermediate and nar-
row photometricbands has enabled the computationof very anaccuracyofσ∆z/(1+z)=0.007forthegalaxiesbrighterthan
i+ =22.5. We extrapolate this result at fainter magnitude
precisephotometricredshifts(Ilbertetal.2009a). AB
basedontheanalysisofthe1σ errorsonthephoto-z. Atz<
These photometric redshifts were computed using deep
1.25,weestimateanaccuracyofσ =0.02,σ =0.07ati+ ∼
Subaru data described in Capaketal. (2007) combinedwith 24,i+ <25.5,respectively. z z AB
intermediatebanddata,theKs datapresentedinthispaper,J AB
datafromnear-infraredcameraWFCAMattheUnitedKing-
5.1. Photometricredshiftdistributions
dom Infrared Telescope and IRAC data from the Spitzer-
COSMOS survey(sCOSMOS, Sandersetal. (2007)). These We have cross-correlated our catalogue with photomet-
near- and mid-infrared bandpasses are an essential ingredi- ric redshifts to derive redshift selection functions for each
entto computeaccuratephotometricredshiftsin theredshift photometrically-defined galaxy population. Note that al-
range 1.4 < z < 2.5, in particular because they permit the though photometric redshifts are based on an optically-
location of the 4000 Å break to be determined accurately. selectedcatalogue,thiscatalogueisverydeep(i′<26.5)and
Moreover,spectroscopicredshiftsof148sBzK galaxieswith containsalmostalltheobjectspresentintheKs-bandselected
a¯z∼2.2fromtheearlyzCOSMOSsurvey(Lillyetal.2007b) catalogue. AtKs <23.0,138376weresuccessfullyassigned
havebeenusedtocheckandtrainthesephotometricredshifts photometric redshifts, representing 96% of the total galaxy
inthisimportantredshiftrange. population.
A set of templates generated by Pollettaetal. (2007) us- Figure9 shows the redshiftdistributionfor all Ks-selected
ing the GRASIL code Silvaetal. (1998) are used . The galaxies, as well as for BzK-selected passively-evolvingand
nine galaxy templates of Pollettaetal. include three SEDs star-forming galaxies in the magnitude range 18.0 < Ks <
of elliptical galaxies and six spiral galaxies templates (S0, 23.0. We have computed the redshift selection function in
Sa, Sb, Sc, Sd, Sdm). This library is complemented with several magnitude bins and found that the effective redshift
12 additional blue templates generated using the models zeff doesnot dependsignificantly on apparentmagnitudefor
ofBruzual&Charlot(2003). thesBzK and pBzK populations.
Thephotometricredshiftsarecomputedusingastandardχ2 By using only the blue grism of the VIMOS spectrograph
templatefittingprocedure(usingthe“LePhare”code).Biases at the VLT, the zCOSMOS-Deep survey is not designed to
inthephoto-zareremovedbyiterativecalibrationofthepho- target pBzK galaxies,andsonospectroscopicredshiftswere
tometricbandzero-points. Thiscalibrationisbasedon4148 available to train the photometric redshifts of objects over
spectroscopicredshiftsati+ <22.5fromthezCOSMOSsur- theCOSMOSfield. Attheseredshiftsthemainspectralfea-
AB
vey Lillyetal. (2007b). As suggested by the data, two dif- tures of pBzK galaxies, namely Ca II H& K and the 4000
ferentdustextinctionlawsPrevotetal.(1984);Calzettietal. Å break, have moved to the near infrared. Hence, optical
(2000) were applied specific to the differentSED templates. spectroscopy can only deliver redshifts based on identifying