AEGIS-X: Deep Chandra imaging of the Central Groth Strip
K. Nandra, E.S. Laird, J.A. Aird, M. Salvato, A. Georgakakis, G. Barro, P.G. Perez Gonzalez, P. Barmby, R.-R. Chary, A. Coil, M.C. Cooper, M. Davis, M. Dickinson, S.M. Faber, G.G. Fazio, P. Guhathakurta, S. Gwyn, L.-T. Hsu, J.-S. Huang, R.J. Ivison, D.C. Koo, J.A. Newman, C. Rangel, T. Yamada, C. Willmer
AAEGIS-X:
Deep Chandra imaging of the Central Groth Strip
K. Nandra , , E.S. Laird , J.A. Aird , , M. Salvato , A. Georgakakis , G. Barro , , P.G.Perez-Gonzalez , P. Barmby , R.-R. Chary , A. Coil , M.C. Cooper , M. Davis , M.Dickinson , S.M. Faber , G.G. Fazio , P. Guhathakurta , S. Gwyn , L.-T. Hsu , J.-S.Huang , R.J. Ivison , D.C. Koo , J.A. Newman , C. Rangel , T. Yamada , C. Willmer ABSTRACT
We present the results of deep
Chandra imaging of the central region of the Extended GrothStrip, the AEGIS-X Deep (AEGIS-XD) survey. When combined with previous
Chandra observa-tions of a wider area of the strip, AEGIS-X Wide (AEGIS-XW; Laird et al. 2009), these providedata to a nominal exposure depth of 800ks in the three central ACIS-I fields, a region of approx-imately 0 .
29 deg . This is currently the third deepest X-ray survey in existence, a factor ∼ − ∼ Chandra observations.We present identifications of our X-ray sources from deep ground-based, Spitzer, GALEX andHST imaging. Using a likelihood ratio analysis, we associate multi band counterparts for 929/937of our X-ray sources, with an estimated 95 % reliability, making the identification completenessapproximately 94 % in a statistical sense. Reliable spectroscopic redshifts for 353 of our X-raysources are provided predominantly from Keck (DEEP2/3) and MMT Hectospec, so the currentspectroscopic completeness is ∼
38 per cent. For the remainder of the X-ray sources, we computephotometric redshifts based on multi-band photometry in up to 35 bands from the UV to mid-IR.Particular attention is given to the fact that the vast majority the X-ray sources are AGN andrequire hybrid templates. Our photometric redshifts have mean accuracy of σ = 0 .
04 and anoutlier fraction of approximately 5%, reaching σ = 0 .
03 with less than 4% outliers in the areacovered by CANDELS . The X-ray, multi-wavelength photometry and redshift catalogues aremade publicly available.
Subject headings: galaxies: active — galaxies: nuclei — surveys — X-rays: galaxies Max Planck Institute for Extraterrestrial Physics,Giessenbachstrasse, 85741 Garching, Germany Astrophysics Group, Blackett Laboratory, ImperialCollege London, London SW7 2AZ, UK Center for Astrophysics and Space Science, Universityof California, San Diego, CA 92093, USA University of Durham, UK UCO/Lick Observatory, Department of Astronomyand Astrophysics, University of California, Santa Cruz, CA95064 Departamento de Astrof´ısica, Facultad de CC. F´ısicas,Universidad Complutense de Madrid, E-28040 Madrid,Spain Department of Physics and Astronomy, University ofWestern Ontario, London, Ontario N6A 3K7, Canada MS220-6, Caltech, Pasadena, CA 91125, USA Department of Physics, Center for Astrophysics and Space Sciences, University of California at San Diego, 9500Gilman Dr., La Jolla, San Diego, CA 92093 Center for Galaxy Evolution, Department of Physicsand Astronomy, University of California, Irvine, CA 92697,USA Department of Astronomy, University of California,Berkeley, CA 94720 NOAO, Tucson, AZ 85719, USA Harvard-Smithsonian Center for Astrophysics, Cam-bridge, MA 02138 CADC, HIA, Victoria, Canada Institute for Astronomy, University of Edinburgh,Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ,UK University of Pittsburgh and Pitt-PACC, 3941 O’HaraSt., Pittsburgh, PA 15260 Tohoku University, Aramaki, Aoba, Sendai 9808578, a r X i v : . [ a s t r o - ph . H E ] M a r . Introduction Deep X-ray surveys trace the accretion historyof the universe, offering a highly efficient methodof pinpointing growing black holes in galaxies overa wide range of redshifts.
Chandra and
XMM-Newton surveys have yielded samples of ActiveGalactic Nuclei (AGN) capable of characteris-ing the evolution of accretion power in the Uni-verse, via the X-ray luminosity function (XLF; e.g.Hasinger et al. 2005; Barger et al. 2005; Silver-man et al. 2008; Aird et al. 2010; Ueda et al.2014). These surveys have also been highly influ-ential in broadening our understanding of the co-evolution of supermassive black holes and galax-ies via the characterisation of various host proper-ties of AGN. The extraordinary sensitivity of thecurrent generation of X-ray observatories, partic-ularly
Chandra , to point-like X-ray sources hastransformed such investigations by revealing largepopulations of AGN in galaxies where the accre-tion activity in other wavebands is either obscured,or overwhelmed by host galaxy light (e.g. Brandt& Hasinger 2005).The deepest X-ray surveys thus far are theChandra Deep Fields (CDFs; Giacconi et al. 2002;Alexander et al. 2003; Luo et al. 2010; Xue et al.2011). While these reach extremely faint flux lev-els they can only do so over relatively small areas.Complementary large-area, but shallower surveyshave therefore been performed, such as XBootes(Murray et al. 2005), XMM-LSS (Pierre et al.2007), XMM-COSMOS (Hasinger et al. 2007) and
Chandra
COSMOS (Elvis et al. 2009).Determination of the accretion history andits relationship to galaxy evolution cannot beachieved using X-ray data alone. For example,a basic requirement is also to determine the red-shifts of the X-ray sources to determine their lu-minosities and evolution. This has proved surpris-ingly difficult, for a number of reasons. Firstly,the depth of current X-ray observations is suchthat the multiwavelength counterparts of the X-ray sources are often extremely faint. This makeseven the identification e.g. of optical or NIR coun-terparts challenging. Determining their redshiftsis even more difficult, because the vast major-
Japan Steward Observatory, University of Arizona, 933 NorthCherry Avenue, Tucson, AZ 85721, USA ity are too faint for spectroscopic identification.Despite major efforts, the spectroscopic complete-ness of the deepest X-ray samples are <
50 % (e.g.Szokoly et al. 2004; Trouille et al. 2008). Photo-metric redshifts can be used to mitigate this spec-troscopic incompleteness, but require very deepdata in as many bands as possible. This can bedifficult to acquire in wide fields. Also, becausethe vast majority of X-ray point sources in deepsurveys are AGN, special consideration is also re-quired to yield accurate photo-z’s (Salvato et al.2009, 2011).One area of the sky which benefits from deepmulti wavelength coverage is the Extended GrothStrip (EGS), a region of 0.25 x 2’ centered at ap-proximately α = 14 h m , δ = 52 ◦ (cid:48) . Deepobservations of the EGS have been performed us-ing ground and space-based observatories, manyof them as part of the AEGIS multiwavelengthproject (Davis et al. 2007). This includes X-rayimaging with Chandra /ACIS, which covers the en-tire EGS to a nominal depth of 200ks, which wehenceforth designate the AEGIS-X Wide (AEGIS-XW) survey (Nandra et al. 2005; Laird et al. 2009hereafter L09). These observations have been ef-fective in helping characterizing the accretion his-tory to relatively high redshifts (Aird et al. 2008;2010). In combination with the AEGIS multiwavelength data they have also provided new in-sights into the relationship of AGN with their hostgalaxies (e.g. Nandra et al. 2007; Pierce et al.2007; Bundy et al. 2008; Georgakakis et al. 2008c,2009) and large scale structure environments (e.g.Georgakakis et al. 2007, 2008a Coil et al. 2009).In the current paper we present deeper
Chandra imaging (800ks nominal depth) of the central EGSregion, hereafter the AEGIS-X Deep (AEGIS-XD)survey. The AEGIS-XW data are sufficient to de-tect essentially the full population of X-ray emit-ting AGN to z ∼ z = 3 the luminous QSO popu-lation is known to decline rapidly (e.g Wall et al.2005). Whether this also applies to the obscuredand more moderate luminosity AGN populationsprobed in X-ray surveys is an open question Brusaet al., 2009; Civano et al., 2011; Vito et al. 2013).The CDFs reach sufficient depths to detect suchsources at z > Chandra surveysare severely photon-starved, this is very challeng-ing without long exposures.The AEGIS-XD data occupy a unique regionof parameter space, being larger in area than eachCDF by a factor 3, but of sufficient depth to probethe high redshift and obscured X-ray source pop-ulations of interest. The AEGIS-XW data weredesigned to probe down to Seyfert level AGN ac-tivity ( L X ∼ erg s − at z ∼ z ∼
5, inprinciple with sufficient area to extend our under-standing of the evolution of the X-ray luminosityfunction to at least that redshift. At the sametime, in the harder X-ray band (2-10 keV), theAEGIS-XD images are sensitive to these kind ofSeyfert level luminosities at z ∼
2, even for sourcesabsorbed by a column density of N H = 10 cm − .At these flux limits, sources with even higher col-umn densities may be detected via their scatteredlight in either or both bands, via considerationof their X-ray spectra (e.g. Tozzi et al. 2006;Brightman & Ueda 2012). When combined withthe exceptional multiwavelength data in AEGIS,the AEGIS-XD data therefore provide a unique re-source to trace the growth of supermassive blackholes, and its influence on galaxies, over a majorfraction of cosmic time.In the present paper we describe the basic ob-servational parameters and analysis of the AEGIS-XD data, deriving an X-ray point source cata-logue, a multi wavelength photometric catalog ofthe X-ray source counterparts, and a redshift cata-logue. A companion paper presenting an extendedsource catalogue based on the same deep Chan-dra data has been presented in Erfanianfar et al.(2013). An X-ray point source catalogue basedon almost the same
Chandra data used here hasalso been previously presented by Goulding et al.(2012; hereafter G12). The present paper employsa different data reduction and source detectionprocedure, as well as a different technique for asso- ciation of optical and near-infrared counterparts tothe X-ray sources. Comparisons with this previouswork are given in Sections 3.3 and 4.2. In addition,we provide a catalogue of spectroscopic and pho-tometric redshifts for the X-ray source counter-parts. The paper is structured as follows: Section2 describes the X-ray observations and data reduc-tion; Section 3 describes the source detection andphotometry, which comprises an updated versionof the AEGIS-XW methodology presented earlierby L09. The point source catalogue and sensi-tivity maps are presented in Section 4. Section5 describes the multi-wavelength identificationsand multi band photometry, the latter based onthe methodology of the
Rainbow database (Perez-Gonzalez et al. 2008, Barro et al. 2011a, 2011b).In Section 6 we present redshift estimates of thesources, including accurate photometric redshiftsaccounting for the AGN nature of the sources us-ing the methods of Salvato et al. (2011). A sum-mary of our results is given in Section 7.
2. Observations and Data Reduction2.1. X-ray data
The new AEGIS-XD
Chandra data were takenat three nominal pointing positions, which wehave designated AEGIS-1, AEGIS-2 and AEGIS-3. Each field was approved to receive approxi-mately 600ks in exposure as part of Chandra Cycle9, supplementing the ∼ ∼ −
100 ks.These observations were all taken in the time pe-riod 2007 Dec 11 to 2009 June 26 using the ACIS-I instrument (Garmire et al. 2003) without anygrating in place. All new AEGIS-XD data weretaken in VFAINT mode. Full details of the new
Chandra observations are given in Table 1. Thethree subfields AEGIS-1, 2, and 3 were defined asthe spatial limits of ObsIDs 9450, 9454 and 9458respectively, with a border of ±
20 pixels in the Xand Y directions. These sub-fields were analyzedseparately but have considerable overlap: commonsources were removed at a later stage.The total exposure times for the Cycle 9 point-ings before screening were 583ks (AEGIS-1), 597ks(AEGIS-2) and 596ks (AEGIS-3). The centre ofthese fields correspond fairly closely to those of3ig. 1.— Layout of the AEGIS field showing the location of the
Chandra
X-ray imaging, and a subset of themulti wavelength coverage. The 200ks AEGIS-XW area (L09) is show as the greyscale image. The deeper800ks coverage is contained in the area delineated within the thick black lines.4 able 1Observation Log
Fielda ObsIDb RAc DECc Start Timed On timee Exposuref Roll AnglegName (J2000) (J2000) (UT) (ks) (ks) (deg)AEGIS-1 9450 14 20 17.24 +53 00 34.22 2007-12-11 04:24:07 28.91 28.78 40.2AEGIS-1 9451 14 20 17.23 +53 00 34.23 2007-12-16 10:52:06 25.38 25.21 40.2AEGIS-1 9452 14 20 16.80 +53 00 36.20 2007-12-18 05:45:49 13.56 13.29 48.7AEGIS-1 9453 14 20 14.22 +52 59 43.05 2008-06-15 21:28:03 44.75 44.64 229.2AEGIS-1 9720 14 20 14.21 +52 59 42.96 2008-06-17 05:14:02 28.14 27.74 229.2AEGIS-1 9721 14 20 13.78 +52 59 45.13 2008-06-12 08:09:14 16.55 16.55 220.2AEGIS-1 9722 14 20 13.76 +52 59 45.19 2008-06-13 07:02:28 20.01 19.89 220.2AEGIS-1 9723 14 20 14.22 +52 59 43.00 2008-06-18 13:42:40 34.54 34.47 229.2AEGIS-1 9724 14 20 16.82 +53 00 36.22 2007-12-22 13:37:26 14.09 14.08 48.7AEGIS-1 9725 14 20 12.35 +53 00 16.04 2008-03-31 05:21:42 31.13 31.13 150.2AEGIS-1 9726 14 20 13.77 +52 59 45.15 2008-06-05 08:45:04 39.63 39.62 220.2AEGIS-1 9793 14 20 16.81 +53 00 36.27 2007-12-19 02:53:51 24.08 23.83 48.7AEGIS-1 9794 14 20 16.82 +53 00 36.13 2007-12-20 04:27:59 10.34 10.03 48.7AEGIS-1 9795 14 20 16.82 +53 00 36.32 2007-12-20 21:36:20 8.91 8.91 48.7AEGIS-1 9796 14 20 16.81 +53 00 36.27 2007-12-21 20:28:33 16.33 16.33 48.7AEGIS-1 9797 14 20 16.82 +53 00 36.38 2007-12-23 13:12:28 12.63 12.15 48.7AEGIS-1 9842 14 20 12.35 +53 00 16.01 2008-04-02 21:01:59 30.45 30.44 150.2AEGIS-1 9843 14 20 12.34 +53 00 16.13 2008-04-02 01:11:09 15.32 13.48 150.2AEGIS-1 9844 14 20 12.35 +53 00 15.94 2008-04-05 13:07:54 19.78 19.78 150.2AEGIS-1 9863 14 20 13.76 +52 59 45.14 2008-06-07 00:33:47 22.01 22.01 220.2AEGIS-1 9866 14 20 13.77 +52 59 45.16 2008-06-03 22:43:14 25.83 25.83 220.2AEGIS-1 9870 14 20 13.77 +52 59 44.99 2008-06-10 15:11:23 11.08 11.00 220.2AEGIS-1 9873 14 20 13.77 +52 59 45.16 2008-06-11 14:22:06 30.81 30.75 220.2AEGIS-1 9875 14 20 14.32 +52 59 42.61 2008-06-23 22:54:14 25.21 25.20 231.2AEGIS-1 9876 14 20 14.21 +52 59 43.03 2008-06-22 00:22:03 33.29 33.28 229.2AEGIS-2 9454 14 19 14.72 +52 48 22.75 2008-09-11 04:47:10 59.81 56.80 310.7AEGIS-2 9455 14 19 14.72 +52 48 22.78 2008-09-13 19:38:46 100.20 99.72 310.7AEGIS-2 9456 14 19 15.06 +52 48 29.45 2008-09-24 08:15:30 58.82 58.35 325.2AEGIS-2 9457 14 19 11.06 +52 48 10.35 2008-06-27 07:08:38 32.75 32.74 235.7AEGIS-2 9727 14 19 14.72 +52 48 22.82 2008-09-12 16:44:12 36.16 34.94 310.7AEGIS-2 9729 14 19 11.31 +52 48 09.80 2008-07-09 16:47:58 48.29 48.04 240.2AEGIS-2 9730 14 19 15.06 +52 48 29.41 2008-09-25 16:50:54 53.97 53.72 325.2AEGIS-2 9731 14 19 11.25 +52 48 09.91 2008-07-03 10:58:47 21.38 21.38 239.2AEGIS-2 9733 14 19 15.06 +52 48 29.44 2008-09-27 01:15:33 58.82 58.36 325.2AEGIS-2 9878 14 19 11.07 +52 48 10.42 2008-06-28 06:03:20 15.74 15.73 235.7AEGIS-2 9879 14 19 11.07 +52 48 10.36 2008-06-29 03:39:20 27.02 26.80 235.7AEGIS-2 9880 14 19 11.25 +52 48 09.87 2008-07-05 17:00:17 29.89 29.45 239.2AEGIS-2 9881 14 19 15.06 +52 48 29.47 2008-09-28 08:15:12 54.53 53.93 325.2AEGIS-3 9458 14 18 06.09 +52 37 17.03 2009-03-18 12:20:16 6.66 6.65 136.9AEGIS-3 9459 14 18 12.11 +52 36 57.84 2008-09-30 19:20:28 69.91 69.55 329.7AEGIS-3 9460 14 18 12.12 +52 36 58.08 2008-10-10 06:17:49 21.91 21.36 330.2AEGIS-3 9461 14 18 07.78 +52 36 37.50 2009-06-26 09:30:12 23.73 23.73 230.2AEGIS-3 9734 14 18 11.83 +52 36 50.93 2008-09-16 11:01:21 49.98 49.47 315.2AEGIS-3 9735 14 18 11.83 +52 36 50.95 2008-09-19 03:14:15 50.00 49.47 315.2AEGIS-3 9736 14 18 11.83 +52 36 50.97 2008-09-20 11:07:10 50.13 49.48 315.2AEGIS-3 9737 14 18 11.83 +52 36 50.94 2008-09-21 17:53:00 49.99 49.48 315.2AEGIS-3 9738 14 18 12.11 +52 36 57.84 2008-10-02 06:56:22 61.89 60.60 329.7AEGIS-3 9739 14 18 12.12 +52 36 58.09 2008-10-05 11:28:12 42.91 42.59 330.2AEGIS-3 9740 14 18 06.30 +52 37 19.96 2009-03-09 22:24:18 20.38 20.37 130.2AEGIS-3 10769 14 18 05.99 +52 37 14.25 2009-03-20 13:38:26 26.69 26.68 143.0AEGIS-3 10847 14 18 09.85 +52 37 32.39 2008-12-31 05:06:27 19.27 19.27 57.2AEGIS-3 10848 14 18 09.86 +52 37 32.43 2009-01-01 17:11:57 17.91 17.91 57.2AEGIS-3 10849 14 18 09.85 +52 37 32.52 2009-01-02 21:25:57 15.93 15.92 57.2AEGIS-3 10876 14 18 06.30 +52 37 19.99 2009-03-11 01:37:20 17.21 17.21 130.2AEGIS-3 10877 14 18 06.31 +52 37 20.03 2009-03-12 15:15:57 16.23 16.22 130.2AEGIS-3 10896 14 18 07.50 +52 36 38.72 2009-06-15 18:46:14 23.29 23.29 224.7AEGIS-3 10923 14 18 07.77 +52 36 37.40 2009-06-22 07:38:22 11.62 11.62 230.2aField Name: note that there is an approximate correspondence between, respectively AEGIS1-3 and EGS 3-5, in theAEGIS-XW survey of L09b
Chandra
Observation IDcNominal position of pointing (J2000)dStart date and time (UT)eRaw exposure timefExposure time after data screening as described in § The data reduction was performed using theCIAO data analysis software v4.1.2 (Fruscioneet al. 2009) and follows the scheme describedin L09, with some minor changes and improve-ments, as detailed here. Briefly, for each individ-ual Obsid, we corrected the data for aspect off-sets, applied the bad pixel removal and destreak-ing algorithms, removed cosmic ray afterglows us-ing standard tools, and corrected for CTI and gaineffects. We also applied the ACIS particle back-ground cleaning algorithm to the VFAINT modedata. Analysis was restricted to ACIS chips 0-3,and ASCA-style event grades 0,2,4 and 6. To re-ject periods of high background we used the proce-dure of Nandra et al. (2007), adopting a thresholdof 1.4 times the quiescent background level, deter-mined as the count rate at which the backgroundshows zero excess variance over that expected from statistical fluctuations alone. As in L09 and Nan-dra et al. (2005) we relaxed this criterion in Ob-sID 4365 which contains a period of relatively highbut stable background. As in L09, a flare was alsomanually removed from ObsID 5850.Following this basic reduction and screening,the astrometry of the individual image frames wascorrected using a reference catalogue. Specifi-cally, we use the CFHTLS i-band selected cata-logue to register the AEGIS-XD images to the op-tical reference frame. We first ran the
Chandra wavelet source detection task wavdetect on the0.5-7 keV image, using a detection threshold of10 − , then used the CIAO task reproject aspect to correct the astrometry compared to the refer-ence image, and create new aspect solution files.The new aspect solutions were then applied tothe original event files. The parameters used for reproject aspect were a source match radius of12 and a residual limit of 0.5. Typically around100 sources were detected in the individual ObsIDswith around 60 per cent of these having a counter-part used in the reprojection. The absolute valueof the offset was typically small ( < . merge all task. The exposure maps werecreated at multiple energies with weights appro-priate for a Γ = 1 . Source detection proceeded the same fashion asthat described in L09 and the reader is referred to6 able 2AEGIS-XW 200ks ObsIDs combined with new AEGIS-XD fields (Table 1)
AEGIS-XD field AEGIS-XW 200ks ObsIDsAEGIS-1 5845, 5846, 6214, 6215AEGIS-2 5847, 5848, 6216, 6217AEGIS-3 3305, 4357, 4365, 5849, 5850, 6218, 6219
Table 3Weights used for exposure map calculations
Energy Energy band(keV) Full Soft Hard Ultrahard0.65 0.2480 0.3867 . . . . . .0.95 0.1509 0.2352 . . . . . .1.25 0.1042 0.1625 . . . . . .1.55 0.0776 0.1209 . . . . . .1.85 0.0607 0.0947 . . . . . .2.50 0.1359 . . . 0.3789 . . .3.50 0.0842 . . . 0.2346 . . .4.50 0.0590 . . . 0.1645 0.42565.50 0.0445 . . . 0.1240 0.32086.50 0.0352 . . . 0.0980 0.2536 wavdetect task run at a low probability threshold (10 − ) onthe mosaic images. This low threshold is intendedto capture all potential sources, but likely containsmany spurious sources. Aside from this threshold-ing, the only information used from wavdetect inthe final catalogue is the source position. Usingthese positions for the candidate sources, countswere extracted from the mosaic images using a cir-cular aperture with radius equal to the exposure-weighted 70% encircled energy fraction (EEF) ofthe Chandra point spread function (PSF). ThePSFs were taken from a lookup table calculatedusing the MARX simulation software as describedin L09. Background was determined using an an-nulus with inner radius equal to 1.5 times the 95%EEF at the source position and outer radius 100pixels larger than this, excluding detected sources.The background was then scaled to the size ofthe source region and the Poisson false probabilityof observing the total counts given the expectedbackground was calculated, masking out the 95%EEF of candidate sources. A significance thresh-old of 4 × − was then applied, and a furtherdetection iteration performed masking out onlysources more significant than this. This itera-tion assures that the background is not underes- Right Ascension (J2000) D ec li n a t i on ( J2000 ) aegis3aegis2aegis1 Fig. 3.— Mosaic full band image of the ExtendedGroth Strip showing the location and overlap ofthe 3 central AEGIS-XD fields, which have nomi-nal 800ks depth. The sub-fields AEGIS-1, AEGIS-2 and AEGIS-3 are shown as red squares.timated due to the masking of random positivevariations identified as candidate sources in the wavdetect seed list. Any source detected at this4 × − probability level in the second iteration inany individual band was included in the final cat-alogue. The sources considered significant wereband-merged using the matching criteria specifiedin Table 2 of L09. Photometry was then performedto estimate the fluxes in several energy ranges,even if the source was not considered a signifi-cant detection in that particular band. After per-forming the band merging we visually inspectedthe images of the sources in each of the fields andchecked that the correct cross-band counterpartswere identified. Two sources in the catalogue weredetected in the soft and full bands but not cor-rectly matched with their hard (and in one caseultra-hard) band counterparts. These were com-bined manually. Two single-band detected sources(one soft, one ultra hard) were removed from thecatalogue after visual inspection revealed strongcontamination by nearby bright sources. Theseremoved sources were most likely incorrectly iden-tified in the initial wavdetect seed catalogue.Finally the source catalogs for the individualsub-fields AEGIS 1,2 and 3 were merged to remove8 able 4Sources detected in one band but not another Detection Total number Non-detection bandband (keV) of sources Full Soft Hard UltrahardFull (0.5–7) 859 . . . 190 299 562Soft (0.5–2) 732 63 . . . 282 478Hard (2–7 ) 574 14 124 . . . 277Ultrahard (4–7) 299 2 45 2 . . . duplicate sources in the overlapping regions. A2” search radius was adopted, and as in L09 thesource was chosen from the field with the smallestoff-axis angle for the final catalog.One significant change in the current papercompared to L09 is in the X-ray photometry.Specifically, here we have adopted elliptical aper-tures to extract the counts from the individualObsIDs, using the 90%EEF PSF appropriate forthe ObsID in question (95% in the case of thesoft band). This contrasts with the source detec-tion described above, and the photometry in L09,which adopt circular apertures. Fluxes were esti-mated using the Bayesian methodology describedin L09, using a Γ = 1 . N H of 1 . × cm − (Dickey & Lockman 1990).The count rates in the full, hard and ultrahardbands were also extrapolated to fluxes in standardenergy bands: 0.5–10, 2–10, and 5–10 keV, respec-tively. Hardness ratios were calculated using theBayesian methodology BEHR (Park et al. 2006). The IRAC Guaranteed Time Observations ofthe AEGIS field cover a region approximately 2 ◦ by 10 (cid:48) (Barmby et al. 2006, 2008). The ACISfield of view is wider than this (see Fig 3) meaningthat the GTO IRAC observations miss the edgesof the deep Chandra imaging. As shown by, e.g.,L09, and discussed below, Spitzer IRAC observa-tions are critical for secure identifications of X-ray sources. For this reason, as part of the
Chan-dra program we obtained additional Spitzer IRACimaging of the edges of the strip. The IRAC cover-age map is shown in Fig. 1 and the data reductionwas performed as described in Barro et al. (2011),and is incorporated into the (cid:127)
Rainbow database.
3. Point Source Catalog
The final point source catalogue in the AEGIS-X Deep area consists of 937 sources. Of these,respectively 859, 732, 574 and 299 were detectedat p < × − in the full, soft, hard and ultrahard bands. Sources detected in one band but notanother are detailed in Table 4. The AEGIS-XDX-ray source catalog with full X-ray informationis made publicly available in FITS table formatas detailed in an Appendix to this paper and at http.mpe.mpg.de/XraySurveys/ . As a demon-stration of the properties of the AEGIS-XD X-raysoruces, Figure 4 presents the hardness ratio dis-tribution of the hard-band (2-7 KeV) selected sam-ple. This is compared to the hardness ratio sourcesof hard-band detected sources in the AEGIS-X(L09) and the 4Ms CDFS (Rangel et al. 2013).Hardness ratios are estimated from the counts inthe 0.5-2 and 2-7 keV spectral bands. Sensitivity maps were computed according tothe procedure described in Georgakakis et al.(2008b) as implemented by L09. This approachaccounts for incompleteness and Eddington biasin the sensitivity calculation, which is performedin a manner which is also fully consistent with thesource detection procedure. The flux limits forthe new AEGIS-XD survey as a function of areaare shown for various energy bands in Fig 5, com-pared to the deepest X-ray survey in existence,the
Chandra
Deep Field South, together with thesensitivity curves of the G12 source catalogue ofthe entire Extended Groth Strip Chandra survey.Following L09, we define the limiting flux of ourobservations as the flux to which at least 1% ofthe survey area is sensitive. We find the limit-9ig. 4.— Hardness ratio distribution of hard-band (2-7 keV) selected sources in the AEGIS-XD (left panel;this paper), AEGIS-X (middle panel; L09) and 4Ms CDFS (right panel; Rangel et al. 2013). The hardnessratio is determined from the counts in the 0.5-2 and 2-7 keV bands.ing fluxes so defined to be 1 . × − (FB; 0.5–10 keV), 3 . × − (SB; 0.5–2 keV), 2 . × − (HB; 2–10 keV), and 3 . × − erg cm − s − (UB; 5–10 keV). We also show in Table 5 the 50%and 90% completeness limits of the survey. The source detection algorithm applied here(and in L09) is designed to provide an accurateestimate of the sensitivity of the X-ray observa-tions at each position. The detection thresholdcan be altered depending on the number of likelyspurious detections to be deemed acceptable in thecatalogue. Here we adopt a relatively conservativethreshold which should result in only a small num-ber of spurious X-ray detections: L09, for exam-ple, estimated that < . Chandra optics, inherent in the Wolter-1design, and the nature of the spectra of the un-derlying source population, it is unlikely for realsources to be detected in only the UB, as it is theleast sensitive of all the detection bands. As aresult, UB-only sources must have heavy obscura-tion, at just the right level to suppress the soft,full and hard band detections below the thresh-old, but not so high that it suppresses the UB fluxas well. Furthermore, in practice even heavily ob-scured sources are often detected in the soft X-rayband, due to the presence of scattered X-ray light(e.g. Brightman & Nandra 2012). None of theseconsiderations applies to spurious sources which,if present in the ultra-hard band, should not bedetected in any other band. Just one source inour catalogue is detected only in the UB, and isthus a candidate for being spurious in the UB cat-alogue, which contains a total of 299 sources. Thisconsideration suggests that the simulations mightover-estimate the number of spurious sources inour catalogue.With our deeper X-ray data, we can also makea post-hoc check of the number of spurious sources10ig. 5.— Sensitivity curves for the AEGIS-XD survey in the soft, hard, full and ultra hard bands (solid lines),calculated using the methodology of Georgakakis et al. (2008b). These are compared to the 4Ms ChandraDeep Field South (dashed lines). The 4Ms CDFS reaches the deepest limits of any X-ray survey, but theAEGIS-XD data provide a considerable increase in area. Also shown in the plot are the sensitivity curvesof the G12 in the entire Extended Groth Strip Chandra survey (deep and wide). For this comparison weapply conversions to account for the different power-law X-ray spectral index assumed by G12 to determinefluxes and the different energy bands used in their work compared to this paper. Note, however, that theirsensitivity calculation follows a different methodology as does their calculation of the exposure maps.11 able 5X-ray flux completeness limits for the AEGIS-XD survey
Completeness limit a Band 1% b b b Full 1 .
46 8 .
22 35 . .
33 2 .
02 9 . .
48 13 . . .
27 18 . . a Flux to which 1, 50 and 90% of thesurvey area is complete. b Fluxes are in units of 10 − erg cm − s − . Table 6AEGIS-XW sources from L09 not included in AEGIS-XD catalog
L09 RA J2000 a Dec J2000 a p mina ,b Det. a Bayesian flux a ,c i (cid:48) AB d Classical flux limit e cat ID (J2000) (J2000) bands (10 − erg s − cm − ) (mag) (10 − erg s − cm − )egs 0379 f . × − fs 8 . +3 . − . < . . × − s < . < . . × − s < . < . f . × − f 20 . +5 . − . < . . × − s < . > . < . . × − f 5 . +3 . − . < . . × − fs 9 . +3 . − . < . . × − f 4 . +3 . − . < . . × − s < . < . . × − fs 4 . +3 . − . > . < . . × − s 3 . +2 . − . < . . × − s < . < . . × − h 2 . +1 . − . > . < . . × − h 2 . +1 . − . > . < . f . × − s 5 . +3 . − . < . f . × − fs 1 . +0 . − . < . f . × − s 3 . +2 . − . < . a Values from L09. b Minimum false detection probability found for the four analysis bands. c Full band flux or upper limit. d Optical identification from L09 or upper limit where no counterpart exists e Values from this work. f Source also detected in G12. Fig. 6.— Sources in the 200ks AEGIS-XW catalogue of L09 not significantly detected in the deeper 800ksdata. In each case the green circle shows the L09 position overlaid on the 800ks images from this work.Generally these are low significance detections which are not confirmed in the deeper data, but in a few casesthe L09 detection appears in the wings of a nearby brighter source. The size of the circle is equal to the 90%EEF in the full band, while the cutouts have a size of 25x25”.in the 200ks L09 catalogue. Naively, it would beexpected that all real sources in the AEGIS-XWcatalogue also appear in our deeper observationsin the overlapping area. This is not the case, how-ever, if the sources are spurious, as the significancewould tend to go down (and eventually below thedetection threshold) with deeper data. There arein fact 17 sources in the AEGIS-XW catalogue,which are covered in the deeper
Chandra point-ings but are not listed as significant sources in ourAEGIS-XD catalogue. These are listed in Table 6,with postage-stamp images of the objects shownin Fig. 6. The images show that for the majorityof the cases they are low significance detectionsin the 200ks catalogue which are not confirmedin the deeper data. Two (egs 0511 and egs 0529)are sources which were detected in the wings ofnearby bright (and possibly extended) sources. Arelatively large number of the others are in thevery central regions of the image where the PSFis small, and where the original detections by L09 are based only on a very small number of photons.In these and indeed other cases the objects identi-fied by L09 may not be truly spurious but simplyrepresent sources whose true flux lies below the de-tection limit even of the 800ks data, but which dueto Poisson statistics generated a significant num-ber of counts in the 200ks observation. In otherwords, they may be sources which were originallydetected due to the Eddington bias. This asser-tion is supported by the fact that many of themhave optical counterparts (see Table 6. This mayalso be explained if the X-rays are variable, andthe true flux has dropped by a large factor sincethe initial observations by L09.
G12 have already published a catalogue of X-ray sources and optical associations in this field.The set of
Chandra data used is similar but not13dentical to ours, in that they analyse the en-tire AEGIS-X area, both deep and wide, whilewe use only the regions with nominal 800ks expo-sure. Further more we use two further ObsIDs inthese areas, 9876 and 9881, not analysed by G12.The other 55 of our pointings are in common withG12, who nonetheless adopt a different procedurefor data reduction, source detection and identifi-cation of the X-ray sources. A comparison of thelatter can be found in Section 4.2.We have cross-correlated the X-ray source listof G12 with our catalogue using a match radius of3”, and restricting to the common area. From thiswe find 115 sources in G12 that have no matchin our catalogue. The vast majority (108) arefaint source close to the detection threshold (seeFig 7). In this cases small differences in the analy-sis or source detection procedure (in particular theadopted detection threshold) can easily accountfor a detection in one catalogue, but not the other.In the photon-starved regime of
Chandra the in-clusion or exclusion of a single count in the sourcedetection cell can easily change a “detection” toa “non-detection” or vice versa. Relatively minordifferences in the determination of the backgroundcan have a similar effect. The other 7 sources inG12 but not in our catalogue are brighter and po-tentially a greater cause for concern. Visual exam-ination of these shows three which are far off axis,and which do have a counterpart in our cataloguebut just outside the 3” match radius. The remain-ing four are in crowded/bright source regions. Vi-sual inspection suggest that these may indeed bedistinct sources, but which have not been sepa-rated or identified as such by our detection algo-rithm.Performing the opposite comparison, we find 73sources in our catalogue that have no counterpartwithin 3” in G12. An examination of Fig 7 showsthat a number of these sources are rather X-raybright ( F . − > − erg cm − s − ). Examin-ing the spatial distribution of these sources in ourimages, we find that the majority of them are atlarge off-axis angles, where the PSF is relativelybroad.We have also compared the positions of our X-ray sources with those of G12, with the results ofthe comparison being shown in Fig. 8. A system-atic offset is found amounting to 0.37”. This maybe attributed in part to the different astrometric Fig. 7.— X-ray flux distribution of the sourcesthat are in our catalog and not that of G12, orvice versa. G12 include a number of faint sourcesin their catalogue which do not satisfy our falseprobability threshold. A number of bright sourcesare included in our catalogue, but not in that ofG12. These are generally at the edges of the field.where the PSF is relatively large.14olutions adopted for the X-ray images, with ourbeing tied to the CFHTLS i-band, and the G12 po-sitions registered to the DEEP2 reference frame.
4. Multiwavelength counterparts and pho-tometry
We have identified multiwavelength counter-parts to sources in our merged X-ray catalog usingthe likelihood ratio method (Ciliegi et al. 2003;Brusa et al. 2007; L09’ Luo et al. 2010) andphotometry from the
Rainbow
Cosmological Sur-veys Database (Barro et al. 2011a; Barro et al.2011b). The Rainbow database is a compilationof the photometric datasets in several of the deep-est extragalactic fields, including the AEGIS field.Table 7 lists the relevant datasets. The multi-wavelength images were registered to a commonastrometric reference frame and photometry wasperformed in consistent apertures to produce spec-tral energy distributions that span from the UV tomid-IR.To identify our X-ray sources, we first searchedfor counterparts in any of the multiwavelength im-ages (based on SExtractor catalogs generated fromeach of the images) within 3.5” of the X-ray po-sition. All the possible counterparts were thencross-matched to each other using a 2 (cid:48)(cid:48) search ra-dius to create a single multiband catalog. Next,we performed photometry using the same ellip-tical (Kron) aperture across all the optical andnear-infrared bands. The aperture was defined ina reference image for each source, typically thedeepest available ground-based optical image. Ifthe source had a Kron radius < . (cid:48)(cid:48) then we ex-tracted IRAC photometry using a 2 (cid:48)(cid:48) circular aper-ture and applied standard aperture corrections,thus accounting for the larger PSF of the IRACimages. If the source was detected in IRAC only,we applied a 1.5 (cid:48)(cid:48) aperture in the optical/near-IRimages and forced a photometric measurement. Ifa single IRAC source was associated with multipleoptical/near-IR counterparts, the positions of theoptical/near-IR sources were adopted and used todeblend the IRAC photometry. The full procedureis described in Barro et al. (2011a).We note that our procedure does not require a significant detection in IRAC or any specific http://rainbowx.fis.ucm.es/Rainbow_Database/Home.html optical/near-IR band and instead identifies poten-tial counterparts to the X-ray sources in any avail-able image (cf. the catalog presented by Barroet al. 2011a, where an IRAC 3.6 µ m or 4.5 µ m de-tection was required).All of our X-ray sources (within the Rainbow coverage) have at least one candidate counterpartwithin the 3.5 (cid:48)(cid:48) search radius, with ∼
58% having2 or more.In the next step we applied the likelihood ratiotechnique to determine which of these candidatesare likely to be the true counterpart to the X-raysource, as opposed to a chance alignment. We firstrestricted the list of candidates to those with sig-nificant detections in a single, given optical, near-IR or mid-IR band with a measured magnitude, m . The likelihood ratio compares the probabilitythat a candidate counterpart with magnitude m found at a distance r from the X-ray source po-sition is the true counterpart and the probabilitythat it is a spurious background source.The likelihood ratio ( LR ) is given by LR = q ( m ) f ( r ) n ( m ) (1)where q ( m ) is the expected magnitude distributionof the true counterparts to the X-ray sources, n ( m )is the surface density of background sources as afunction of magnitude, and f ( r ) is the probabilitydistribution of angular separations of the sources.We assume f ( r ) can be described by a symmetrictwo-dimensional Gaussian distribution, f ( r ) = 12 πσ exp (cid:18) − r σ (cid:19) (2)where the standard deviation, σ , combined theX-ray and counterpart positional uncertainties,added in quadrature. The X-ray positional un-certainties used depend on the source counts andoff-axis angle, as described in L09. As our Rainbow counterpart catalog was limited to sources within3.5 (cid:48)(cid:48) of an X-ray source, we estimated the back-ground source density, n ( m ), using the originalSExtractor catalogs for the given band over theentire field, restricting to sources with significantdetections and measured magnitudes, m , in thatband. This approach provides an accurate esti-mate of the background source density using theentire photometric coverage.15 able 7Multiwavelength photometric datasets included in the Rainbow database in our fields. Data λ eff (˚A) Depth (mag AB ) LR priority N cntrprt A λ /E(B-V) zp offset (1) (2) (3) (4) (5) (6) (7)IRAC [3 . µ m] 35416.6 23.9 1 881 (94.02%) 0.162 0.086IRAC [4 . µ m] 44826.2 23.9 ... ... 0.111 0.114IRAC [5 . µ m] 56457.2 22.3 ... ... 0.076 0.000IRAC [8 µ m] 78264.8 22.3 ... ... 0.045 0.000Subaru R c V I K S u ∗ g (cid:48) r (cid:48) i (cid:48) z (cid:48) u (cid:48) g (cid:48) i (cid:48) z (cid:48) B R I J K S J J H J J J H H K Note.— (1) Instrument and filter/band (2) Effective wavelength of the filter (3) Likelihood ratio priority. Ahigher priority means the counterpart is taken from that catalogue where a match is found in more than one(4) Number of counterparts assigned in that band (5) Galactic extinction (6) Zeropoint offset. The relevantreferences are listed in Barro et al., (2011a and 2011b), except that for NEWFIRM data (Whitaker et al. 2011)and CANDELS/ WFC3 (Grogin et al. 2011, Koekemoer et al. 2011). able 8Summary of likelihood ratio matching results for AEGIS-XD Catalog Area/deg N σ L th R C N X N ID N NoID N Multi N Pri (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)RAINBOW [3.6 µ m] 0.26 65675 0.20 0.80 0.98 0.94 902 860 42 451 860Subaru R I K i i R K s Note.—
Col 1:Catalog name and detection band used to match counterparts. Col 2: Area covered by both the multiwave-length data and deep X-ray data. Col 3: Number of multiwavelength sources in the X-ray area. Col 4:1 σ positional accuracyof multiwavelength catalog in arcseconds. Col 5: Likelihood ratio threshold determined by the iterative procedure describedin section 4. Col 6; Sample reliability, the mean of the individual reliabilities of each secure counterpart, as in Luo et al (2010)Col 7: Sample completeness, the sum of the reliabilities for all counterparts divided by the total number of X-ray sources.Col 8: Total number of X-ray sources in the area covered by the multiwavelength data. Col 9: Number of secure counterpartsto X-ray sources. Col 10: Number of X-ray sources without secure counterparts. Col 11: Number of X-ray sources with morethan 1 candidate counterpart within the 3.5 (cid:48)(cid:48) search radius. Col 12: Number of X-ray sources assigned a primary counterpartin this band. Fig. 8.— Offset between the X-ray positions ofsources in our catalogue, and those in G12, incases where the source is matched within 3” ra-dius. There is a systematic offset of around 0.4”. The magnitude distribution of true counter-parts, q ( m ), was estimated via the iterativemethod described in Luo et al. (2010). Briefly, afirst estimate of q ( m ) was determined by match-ing counterparts to X-ray sources within a smallradius (we adopted 1.5 (cid:48)(cid:48) ), and subtracting thebackground density. The LR was then calculatedfor all counterparts to X-ray sources within our3.5 (cid:48)(cid:48) search radius. We found the counterpartwith the highest LR value for each X-ray sourceand applied a threshold, LR thresh , that maximisesthe sum of the sample completeness and reliabilityto identify a sample of “secure” matches. Thesesecure matches were then used for a new estimateof q ( m ), and the likelihood ratios recalculated.This process was repeated 10 times, resulting ina stable number of matches and threshold LR values.We repeated the entire LR matching processfor the bands indicated in column 3 of Table 7.Finally, we combined the matches to produce amaster list of counterparts. We first took thesecure counterparts in the highest priority band(indicated by LR priority=1). Next, we loopedthrough the remaining match bands and assigneda final counterpart if a secure match was avail-able in that band (and was not available in anyof the higher priority bands). No additional cross-matching is required to obtain the full multibandphotometry as this is provided through matched17 -16 -15 -14 -13 -16 -15 -14 -13 -16 -15 -14 -13 Subaru R c i ′ Subaru K S f . − (erg s − cm − ) M a g n i t ud e ( A B ) M a g n i t ud e ( A B ) M a g n i t ud e ( A B ) M a g n i t ud e ( A B ) IRAC [ . µ m]full band f . − (erg s − cm − )soft band f − (erg s − cm − )hard band Fig. 9.— X-ray flux versus AB magnitude in various matching bands for all AEGIS-XD 800ks sources (orangesymbols), and those also identified earlier in the shallower AEGIS -XW 200ks survey (black symbols). Fromtop to bottom the comparison bands are the Subaru R c -band, CFHTLS i (cid:48) , Subaru K s and IRAC 3 . µ m.Anything with less than 3 sigma detection is shown as a limit (downward arrow) and stars are indicated witha star symbol. Note that the K s imaging covers a significantly smaller area than the other bands, accountingfor the smaller bunker of matches sources. Lines denoting a constant ratio of the X-ray flux to the flux inthe corresponding optical/IR band are shown as the dotted lines, with the dashed line representing a ratioof 1:1. 18pertures for all the Rainbow counterparts, re-gardless of the detection band (c.f. Luo et al.2010). In practice, the vast majority ( ∼ . µ m.IRAC is known to give the highest match rate forfaint X-ray sources in deep Chandra surveys (Car-damone et al. 2008; L09). The additional stepshelp us identify counterparts when the IRAC can-didate is faint, blended, or non-existent. We as-signed a match to 929 of the 937 sources.The X-ray fluxes in the full, soft and hard bandsare plotted against the counterpart magnitude invarious matching bands in 9. The lines of constant F X /F opt show a clear effect that the counterpartsare generally brighter in the Subaru MOIRCS NIR( K s ) and IRAC 3.6 µm bands than the are in theoptical bands (CFHT i (cid:48) or Subaru R c . This illus-trates the well-known fact that the X-ray sources- which are dominated by AGN - reside in rela-tively red host galaxies (Barger et al. 2003; Nan-dra et al. 2007; Brusa et al. 2009; Civano et al.2012), a fact which accounts for the much higherIRAC identification rate, compared to optical pho-tometry. The figure also identifies objects whichare newly detected in the 800ks survey, as op-posed to those which were already in the 200kscatalogue of L09. While the fainter 800ks X-raysources are typically identified also with fainter op-tical counterparts, a small but significant fractionof the faintest X-ray sources are identified withvery bright optical sources (R AB =20 or brighter).Most of these sources are secure stars as classi-fied via spectroscopy, multiple color-color selection(see Barro et al. 2011a and 2011b) or SED fitting.Some of these sources are galaxies with a low X-ray Luminosity indicating that their X-ray emis-sion may be dominated by stellar processes (e.g.via X-ray binaries and diffuse hot gas), rather thanan accreting black hole. Looking more specificallyat this issue, we find a total of 49 sources with F X /F opt < −
2, where F X if the soft band fluxand F opt is based on the Subaru R band, whichare not flagged as stars. 44 of these have a securespectroscopic redshift ( z spec >
0) while the otherhave reliable photo-z >
0. All but one of thesesources has log L X <
42 meaning that in principlethey could be normal galaxies, rather than AGN.They represent 6 . F X > . × − erg cm − s − , our 1 percent completeness soft flux limit. We nonethelesscaution that separating AGN and normal galax-ies based on these criteria is difficult, and requiresdetailed consideration of the properties of the in-dividual objects.There is also some evidence from this figureto suggest that the fainter X-ray sources do notbecome significantly fainter in the longer wave-length NIR or IRAC bands. The IRAC 3 . µ mmagnitude, for example, remains relatively con-stant over the full range of X-ray fluxes probedby the AEGIS-XD survey. The interpretation ofthis is not straightforward, but may be related tothe fact that X-ray selection tends to identify themost massive galaxies at any given redshift (e.g.Bundy et al. 2008; Aird et al. 2013), and/or thatthe optical faintness of many of the X-ray sourcesis due to dust reddening. Following the cross-matching procedure we canmake a post-hoc estimate of the astrometric ac-curacy of the X-ray positions in our catalogue.Fig. 10 shows the offsets between the X-ray po-sition and that of the multi band counterpart.Overall, we find that 84 per cent of the of thecounterparts lie within 1” of the X-ray position,and 97 per cent within 2”. As discussed by L09,the astrometric accuracy is a function of both off-axis position and source counts (see their Fig. 7and Table 8). Fig. 10 demonstrates the latter ef-fect, whereby the positions degrade somewhat forfainter sources. For relatively bright X-ray sources( >
100 net counts) we find 92 per cent of counter-parts within 1” and 99 per cent within 2”. With <
100 net counts, we find 78 per cent of the coun-terparts within 1”, but still 96 percent within 2”.The RMS error for all sources is 0.83” (0.62” for >
100 net couthnts and 0.93” for <
100 counts).
For the 864 X-ray sources that are in commonbetween our catalogue and that of G12, we havecompared the counterpart identifications. Thereis a substantial difference in the multi wavelengthdatasets used: G12 used only the DEEP2 optical19 ∆ RA (arcsec) ∆ D ec ( a r c s ec ) > full net cts < full net ctsInsecure match Fig. 10.— Offset between the X-ray and counter-part positions for the AEGIS-XD sources. Blackcrosses show bright objects where the X-ray posi-tion is statistically well determined. With < >
5. Redshifts
The AEGIS field has been the subject of a num-ber of dedicated redshift surveys, most notably theDEEP2 and DEEP3 surveys (Davis et al. 2003;Cooper et al. 2011, Cooper et al. 2012, Newmanet al 2013) with the Keck telescope. The outstand-ing multi wavelength photometry in the field alsopermits the determination of accurate photomet-ric redshifts, and the spectroscopic data allow cal-ibration of those redshifts and estimates of theiraccuracy and reliability.
A total of 353 sources in our AEGIS-XD X-ray sample have a reliable spectroscopic data, ob-tained from a variety of sources, listed in prior-ity order in Table 9. The largest number (167)of these were derived from the DEEP2 redshiftsurvey (Newman et al. 2013). DEEP2 was amagnitude-limited redshift survey (to R AB =24.1)over several fields covering approximately 2.8square degrees over 4 fields. Among these fieldsthe AEGIS area features the most extensive multiwavelength coverage (Davis et al. 2007). Fur-thermore, the target selection in the AEGIS fieldwas largely based on optical magnitude, unlikethe other fields in DEEP2 where color selectionswere also applied to isolate high redshift galaxies.The redshift success for the AEGIS-XD sourcestargeted in DEEP2 is very high ( >
77 per cent).Note that we count only spectra with redshiftquality 3 and 4 as defined by Newman et al.(2013) as secure redshifts, ignoring lower qualities.On the other hand, the sampling rate of DEEP2,combined with selection against presumed stellarobjects in the survey means that not all X-raysource counterparts brighter than the magnitudelimit were covered. In addition, because the X-raysources were not known at the time the DEEP2survey was designed, they could not be targetedexplicitly.The DEEP3 survey (Cooper et al. 2011), an ex-tension of DEEP2, addressed this issue by specif-ically targeting the counterparts of X-ray sourcesin the field regardless of their optical properties.DEEP3 provides an additional 89 spectroscopicredshifts for the AEGIS-XD survey. The successrate in DEEP3 ( ∼
51 per cent) was lower than inDEEP2 because targets fainter than the DEEP221 able 9Spectroscopic redshifts
Survey a N targ b N spec c N used d N star e DEEP3 174 89 89 3DEEP2 223 172 167 0MMT 162 93 91 10CFRS 5 5 0 0SDSS 14 14 6 1LBG 7 7 6 0Total 464 339 14 a The redshift origins are listed in priority order, i.e. the redshift is taken preferentially from DEEP3 if available, then DEEP2 andso on down to SDSS, which has the lowest priority. Secure redshifts and stellar identifications are those with redshift quality 3 or 4 inthe catalogues. Lower quality flags are assumed to be redshift failures. b Number of AEGIS-XD counterparts targeted for spectroscopy c Secure redshifts and stellar identifications are those with redshift quality 3 or 4 in the catalogues. Lower quality flags are assumedto be redshift failures. d Unique reliable spectroscopic identifications used in this work. e Number of spectroscopically confirmed stars. The difference between N used and N star provides the number of galaxies. magnitude limit were included. These spectra of-ten failed to yield a secure redshift. A furtherimportant spectroscopic dataset was provided us-ing the MMT/Hectospec instrument (Coil et al.2009), again explicitly targeting X-ray sourceswhich were not already covered by DEEP2 . Thiscampaign provided a total of 81 secure redshifts forAEGIS-XD sources. Finally, a handful of spectro-scopic redshifts of X-ray source counterparts havebeen obtained by other campaigns, for examplethe Canada-France Redshift Survey (Lilly et al.1995), the Keck Lyman Break Galaxy (LBG) sur-veys of Steidel et al (2003, 2004), and the SDSS(Ahn et al., 2012). Of these, SDSS provides 6 ad-ditional redshifts, and the LBG survey additional6. The 5 redshifts from CFRS were all duplicatedin DEEP2/3 or the MMT surveys, so we use thosein preference.The grand total of 353 spectra implies a to-tal spectroscopic completeness of the sample of ∼
38 per cent. This is, however, a very strongfunction of optical magnitude, as can be seen fromFig. 12. Only 20 spectroscopic redshifts have beenobtained at magnitudes fainter than R C = 24, de-spite this being the peak of the magnitude distri-bution of the X-ray counterparts. This accountsfor the relatively low spectroscopic completeness ofthe whole sample, despite major efforts in termsof spectroscopy in this field. A total of 111 X-raysource counterparts were targeted in the course of
14 16 18 20 22 24 26 28050100150200
Subaru R C magnitude N u m b e r All (detected)Good spec-zFailed spec-zPhoto-z onlyUpper limit
Fig. 12.— Subaru R C magnitude distribution ofthe AEGIS-XD counterparts. The distributionpeaks at R C ∼
24. The vast majority of successfulspectroscopic redshifts are at brighter magnitudesthan this. Redshift failures start to rise sharplyat R C >
23, below which we must largely relyon photometric redshifts. The upper limits curverefers to the upper limit on the magnitude in thecase where there is no detected counterpart in theSubaru imaging.22he various surveys without a reliable redshift be-ing obtained.
Despite the intensive spectroscopy in this field,a relatively large fraction of the AEGIS-XDsources do not have spectroscopic redshifts. Pho-tometric redshifts were therefore computed for theremaining of the sources with multiwavelengthcounterparts using SED fitting. The photometricredshifts have been computed following the anal-ysis procedure described in Salvato et al. 2011,which takes into account knowledge of the opticalmorphology, optical variability and X-ray emis-sion to determine the most appropriate libraryand priors to be used. This method has been suc-cessfully applied in the COSMOS field (Salvatoet al. 2009), the Lockman Hole (Fotopoulou et al.2012) and in the Extended Chandra Deep South(Hsu et al., 2014). More details regarding theadopted libraries can be found in Hsu et al 2014.Morphological classifications for the opticalcounterparts was taken from the Rainbow sur-vey. There, for the separation of the sourcesin point-like and extended, the HST-ACS im-ages where primarily used, with the analysisdone alternatively on the Subaru R c band image(FWHM ∼ . The EXTNV group was alsosplit on the basis of the soft X-ray flux, with 529sources fainter than F (0 . − = 8 × − ergcm − s − and with the remaining 6 brighter thanthat.Source variability can be a major issue in deter-mining the photometric redshifts for type I AGN,as the multi-band data were usually taken at dif-ferent epochs, meaning that there can be signifi-cant flux-offsets worsening the SED fits or causingthe wrong template to be selected. In addition, in we adopt the same classification as defined in Salvato et al.(2009) for ease of comparison Fig. 13.— Comparison between spectroscopic andphotometric redshifts for the extragalactic spec-troscopic sample . Filled dots indicate sourceswith a possible unique redshift solution while opencircles represent sources for which there is at leasta second significant peak in the redshift proba-bility distribution. In green we show the sourceswithin the CANDELS area, where deeper and bet-ter resolved NIR data are available, yielding supe-rior photo-z results. The solid lines correspondto z phot =z spec and z phot = ± spec ), re-spectively. The dotted lines limit the locus wherez phot = ± spec ).23any cases the photometry in a given band wasproduced by adding the results from different ob-servation runs separated in time. This means thata multi-epoch variability analysis was not possi-ble. However, we do find that 59 sources have aclear offset in (typically 0.5 magnitudes and up to ∼
1) when comparing photometry from the sameor similar filters, suggesting variability. Visual in-spection shows that 38 of these sources are point-like, and while the morphological classification isa strong function of magnitude and image reso-lution, this suggests that the variability is likelyreal and due to the QSO or stellar nature of thesource. For the remainder, classified as opticallyextended, half are located close to nearby stars,and the variability is likely more related to vari-ation in the flux of the stars or the backgroundin their vicinity. For lack of further information,all the 59 apparently-variable sources have beenflagged, as the variability might have a significanteffect on the redshift determination. As in Sal-vato et al. (2011), we used the LePhare code(Ilbert et al. 2006), to compute the photomet-ric redshifts. The first step was to correct thephotometry for Galactic extinction using a medianE(B-V)=0.04 (see second-last column of Table 7,as in Barro et al. 2011a). Then we searched forpossible zeropoint offsets that could affect the ac-curacy of the photometric redshift. To do this wecomputed the photometric redshift of a sample ofnormal galaxies (i.e. non X-ray detected) with re-liable spectroscopic redshift available. For eachsource, we kept the redshift fixed and we searchedfor the best fitting template in the library of nor-mal galaxies used in Ilbert et al. (2009). Then,for each photometric band, we computed the av-erage difference between the photometry of all thesources and the photometry of the template. Inthis way, we can correct for second order problemsin the photometric calibration. We adopted thesezeropoints (reported in the last column of Table7) when computing the photometric redshifts forthe X-ray selected sources. We note that the ze-ropoint corrections depend on the templates used,and different libraries could provide slightly differ-ent values for the correction. For this reason we donot apply these corrections to the photometric cat-alogue released with this paper. Furthermore, thesame procedure could not be applied directly tothe X-ray sources as a) variability could affect the results and b) the relative host/AGN contributionto the SED in a given band is unknown. Ignor-ing these fact can potentially introduce a greateruncertainty in the zeropoints when applying a rel-atively limited number of templates.We compute the photometric redshift for theEXTNV sources using the new hybrid templatesof Hsu et al. (2014). These templates are tunedfor sources dominated by galaxies, with specialcare give in reproducing the emission lines. Forthe QSOV sample we used the AGN dominatedhybrids of Salvato et al. (2009). Different abso-lute magnitude priors were considered for EXTNV( − < M B < −
8) and QSOV ( − < M B < − ∼ σ NMAD =0.040, with an out-lier fraction of η = 5.1% (Fig. 13). The accuracyis slightly higher ( σ NMAD =0.030, with an outlierfraction of η = 3.8%, where deeper and better re-solved NIR photometry from CANDELS is avail-able). A close look to the outliers revealed thatmost of those for which the photometric redshiftsolution was not unique (empty circles in the fig-ure), had the correct solution in the second higherpeak. The use of redshift probability distribu-tion function (made publicly available with thiswork) is recommended. The remaining outlierscan be explained by blending with nearby sourcesfor which the low resolution of the ground-basedimaged misplace the sources in the ”EXTNV”group, rather than in the ”QSOV”, thus adopt-ing the wrong templates/priors. The effect of theresolution of the images used for the classificationhas been addresses in Hsu et al. (2014). Theseauthors demonstrate that the fraction of outliersincreased significantly when using the morpholog-ical classification from the ground-based imagesrather than from the space-based ones. We breakdown the results in redshift, magnitude and typein Table 10. The outlier fraction and uncertaintiesin the QSOV sample are larger, partly due to de-24eneracies associated with the typical power-lawSED of this subsample. This is a general problemfor photometric redshift for AGN, which can bemitigated when narrower filters sensitive to strongemission lines are used in the photo-z determina-tion (e.g. Salvato et al. 2009; Cardamone et al.2010; Hsu et al. 2014).The full probability distribution function forthe photometric redshifts is made available for allthe sources in our catalogue (see Appendix A). Wecaution that the errors associated with the pho-tometry can easily be underestimated, with theresult that the 1-3 σ errors associated with thephotometric redshift can also be underestimated.This is true for photometric redshift in general (seeDahlen et al. 2013) for a recent test with a sampleof normal galaxies in the CANDELS fields). Weverified that the situation is similar for our sam-ple where z phot − σ < z spec < z phot + 1 σ onlyfor 57% of the sources, while for 79% of the sam-ple the spectroscopic sample is within the 3 σ er-ror of the photometric redshift. Thus, while us-ing the 3 σ errors associated with photometric red-shifts provide a reasonably accurate estimate ofthe uncertainty for most of the sources, we recom-mend again to use the entire redshift probabilitydistribution function for a more complete analysis. The redshift distribution of our X-ray sources(after excluding the stars) is shown in Figure 14,distinguishing between spectroscopic and photo-metric redshifts. There is a peak in the spectro-scopic redshift distribution around z ∼ z < η (%) σ NMAD
N. of sources η (%) σ NMAD (1) (2) (3) (1) (2) (3)z < > <
22 mag 41 7.3 0.067 111 2.7 0.040R >
22 mag 84 8.3 0.061 114 4.4 0.028Combined 125 8.0 0.063 225 3.6 0.033lower than 50% (34 sources, 6%), with a distribu-tion over a broad redshift range. The majority ofthe high redshift sources (i.e. z > z = 3 . − . > . L X − z plane.The left panel distinguishes between sources withspectroscopic redshifts and those with photomet-ric redshifts. This clearly shows that that vastmajority of sources at z > . − up to around z erg s − , above L ∗ , the knee in theXLF, is relatively sparsely sampled by our dataand larger area surveys are required e.g. to deter-mine the bright end of the XLF with good accu- racy. The right panel of Fig. 15 shows the objectscolour-coded by the best fit template fitted to themulti-wavelength photometry during the photo-z determination. There is a considerable mix oftemplate types, depending on whether the lightis dominated by the AGN, the galaxy, or a mix-ture at longer wavelengths. Previous work usingthe same photometric redshift methods as use herehas shown good agreement between the SED typeand the spectroscopic classification, where avail-able (Salvato et al. 2009; Lusso et al. 2010, Lussoet al. 2012, Civano et al. 2012)
6. Summary
A catalogue of X-ray sources detected in thedeep (800ks)
Chandra imaging of the AEGIS fieldhas been presented. This is currently the thirddeepest X-ray survey in existence, after the Chan-dra Deep Fields North and South. A total of 937X-ray sources have been detected down to a Pois-son false probability of 4 × − , calculated basedon the counts detected in a PSF-sized detectioncell and a local background, following the method-ology of L09. The source detection algorithm en-ables an accurate determination of the sensitivityof the observations over the field using the tech-nique of Georgakakis et al. (2008b), and hence thecatalogue can be used effectively when statisticalinvestigations requiring corrections for complete-ness are needed (e.g. luminosity functions). Wehave identified multi-wavelength counterparts toour sources using a wide variety of complemen-tary data in this field, ranging from the UV to themid-infrared. Using a likelihood-based associationmethod, we find possible counterparts for 929/93726ig. 15.— Left panel: X-ray luminosity in the rest frame 2-10 keV as a function of spectroscopic (black filledcircles) or photometric redshift (gray open circles). Right panel: same plot but this time the sources arecolor coded on the basis of the best-fit template to the photometric data. Here filled symbols indicate sourcesbest-fit by an AGN template (type 1 or 2), or a hybrid with some contribution (from 10 to 100%) from anAGN. Galaxy templates are shown as open symbols and include Ellipticals (Ell), various spiral/irregulartemplates (SF) and starbursts (SB). The number of sources of each SED type is also reported in the figure.Note that the sources fit by a AGN/hybrid are on average more luminous in the X-ray, as might be expected.Even if the optical/IR SED is better fit with a galaxy template, however, the X-rays will in the vast majorityof cases be dominated by an AGN. In both figures the black solid curve corresponds to a flux limit of f X (2 −
10 keV) = 2 . − erg s − cm − , where the 2 -10 keV sensitivity curve drops to 1% of the maximumvalue. For the calculation of 2-10 keV luminosity we used the 0.5-10 keV flux, k-corrected using a power-lawX-ray spectrum with spectral index Γ = 1 .
4. Because the 0.5-10 keV band is more sensitive than the 2-10keV band, a few sources appear below the line corresponding to the flux limit.27r ∼
99 per cent of the X-ray sources, the vastmajority from the deep Spitzer/IRAC imaging inthe field. We note, however, that the statisticallyreliability of likelihood-based associations is not100 %, so the notional completeness of the coun-terpart identifications is closer to 94 per cent ina statistical sense. 353 ( ∼
38 per cent) of theX-ray source counterparts have a reliable spectro-scopic redshift mostly from Keck spectroscopy inthe DEEP2 and DEEP3 surveys, supplementedby a significant number from MMT/Hectospecspectroscopy. For all X-ray source associations,we have performed multi-wavelength photometryin up to 35 bands using the methodology pi-oneered in the
Rainbow database (Barro et al.2011). This provides SEDs for the sources and fur-thermore enables accurate photometric redshift tobe determined, using the methodology of Salvatoet al. (2011), which is tuned particularly for X-ray sources detected in deep surveys, which mostlycomprise AGN. Despite greater difficulties and un-certainties associated with determining photo-z forsuch sources, the reliability and accuracy of thephotometric redshifts is excellent, with an outlierfraction of just η = 5% and σ = 0 .
05. Even bet-ter results η = 4% and σ = 0 .
03 is reached inthe CANDELS area where deeper and superiorNIR data are available. The AEGIS-XD datasetlies in a unique area of parameter space in termsof deep X-ray surveys and the excellence of theredshift determinations and the supporting multi-wavelength data make it a powerful tool to investi-gate the AGN population. The dataset describedhere as already been used to investigate the coloursof AGN hosts (Georgakakis et al. 2014a), AGNclustering (Georgakakis et al. 2014b), Comptonthick AGN (Brightman et al. 2014) and the evo-lution of AGN obscuration (Buchner et al. 2014),typically in combination with other deeper and/orwider datasets. Further work investigating theseand related phenomena should greatly enhanceour knowledge of black hole growth over cosmictime, and its relationship to galaxy evolution.All of our catalogues, including the detailed X-ray information, multi wavelength identifications,aperture-matched photometry and redshift infor-mation (including the SED fits and photometricredshift p ( z ) are released publicly, as described inthe Appendix to this paper. We thank those who have built and operatethe Chandra
X-ray observatory so successfully.We acknowledge financial support from Chan-dra grant G08-9129A, NSF grant AST-0808133,US National Science Foundation via grant AST-0806732. PGP-P acknowledges support from theSpanish Programa Nacional de Astronom´ıa y As-trof´ısica under grant AYA2012-37727. This workhas made use of the
Rainbow
Cosmological SurveysDatabase, which is operated by the UniversidadComplutense de Madrid (UCM) partnered withthe University of California Observatories at SantaCruz (UCO/Lick,UCSC). Facilities: CXO(ACIS),CFHT, Spitzer(IRAC).
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This 2-column preprint was prepared with the AAS L A TEXmacros v5.2. . Catalogues and Data Release The catalogues described in this paper are available via the journal and will be updated whenever newdata will be available at the public websites at MPE and via
Rainbow ( http://rainbowx.fis.ucm.es/Rainbow_Database/Home.html ). Specifically, we release the following products: • The X-ray source catalogues. • The optical/NIR/MIR association catalog listing the X-ray sources with corresponding multi-bandphotometry. • The redshifts, including spectroscopic redshifts, photometric redshifts and photometric redshift prob-ability distributions.In this appendix, we show extracts from each of the catalogues, with the information provided in theelectronic edition of the journal. The full information is provided on the web site in FITS format.
A.1. X-ray catalogs
A subset of the basic X-ray properties of the AEGIS-XD sources are given in Table 11 and in Table 12.In the first Table we provide co-ordinates of the sources and detection properties in the various X-ray bands.In the second we provide X-ray properties such as fluxes and hardness ratios. Each table is fully describedin the corresponding notes.
A.2. Multi-wavelength catalog
The multi wavelength properties of the counterparts are provided in Table 13 and Table 14. In the firstTable we provide the coordinates of the counterparts in the optical and near/mid-infrared catalogs, togetherwith their ID and offset from the X-ray coordinates. In the second table, for each of the counterparts weprovide the magnitude in the AB system for all the bands listed in the Table 7. The photometry is correctedfor Galactic extinction but is not corrected for zero point offset as this value is dependent on the SED usedfor its computation. In Table 14 an excerpt from the photometric catalog is shown.
A.3. Redshift catalog
For each X-ray source we list the spectroscopic redshift where available, the origin of the redshift, andthe redshift quality flag. In addition, we provide the photometric redshift values and their associated 1and 3 sigma, including possible second solution when appropriate. LePhare also provides the full redshiftprobability distribution, P(z), which is available on request. In the current catalog we provide the peak valueof P(z) for the first and second solutions, As is visible in the excerpt of Table A.3 the peak P(z) is related tothe number of photometric points available for the fit, with lower value of the peak associated with sourceswith fewer photometric points available. This should be borne in mind when assessing the reliability of anygiven photometric redshift. The Table also shows the templates that were selected for the best fit, which arepublicly available at .90 32 a b l e C ha n d r a A E G I S - X s o u r c e c a t a l o g : b a s i c s o u r c ep r o pe r t i e s R A D ec F B c t s S B c t s H B c t s U B c t s D e t ec t i o n I D I AUN a m e ( J )( J ) P o s . e rr O AAN B N B N B N B b a nd s ( )( )( )( )( )( )( )( )( )( )( )( )( )( )( ) a e g i s A E G I S X D J . + . . . . . . . . . F S H a e g i s A E G I S X D J . + . . . . . . . . . F S HU a e g i s A E G I S X D J . + . . . . . . . . . F S H a e g i s A E G I S X D J . + . . . . . . . . . F H a e g i s A E G I S X D J . + . . . . . . . . . F S a e g i s A E G I S X D J . + . . . . . . . . . F S HU a e g i s A E G I S X D J . + . . . . . . . . . F S a e g i s A E G I S X D J . + . . . . . . . . . F S a e g i s A E G I S X D J . + . . . . . . . . . F H a e g i s A E G I S X D J . + . . . . . . . . . F S U n i q u e s o u r ce n a m e I AU s o u r ce n a m e X - r a y p o s i t i o n R A i nd e g r ee s X - r a y p o s i t i o n D ec i nd e g r ee s X - r a y p o s i t i o n a l e rr o r i n a r c s ec O ff a x i s a n g l e i nd e g r ee s . . - k e V ( f u ll b a nd )t o t a l c o un t s e x tr a c t e d a tt h e s o u r ce p o s i t i o n w i t h i n t h e % EE F r a d i u s . B a c k g r o und c o un t s i n t h e . - k e V b a nd s c a l e d t o t h e a r e a t h a t c o rr e s p o nd s t o t h e % EE F r a d i u s . . - k e V ( s o f t b a nd )t o t a l c o un t s e x tr a c t e d a tt h e s o u r ce p o s i t i o n w i t h i n t h e % EE F r a d i u s . B a c k g r o und c o un t s i n t h e . - k e V b a nd s c a l e d t o t h e a r e a t h a t c o rr e s p o nd s t o t h e % EE F r a d i u s . - k e V ( h a r db a nd )t o t a l c o un t s e x tr a c t e d a tt h e s o u r ce p o s i t i o n w i t h i n t h e % EE F r a d i u s . B a c k g r o und c o un t s i n t h e - k e V b a nd s c a l e d t o t h e a r e a t h a t c o rr e s p o nd s t o t h e % EE F r a d i u s . - k e V ( u l t a - h a r db a nd )t o t a l c o un t s e x tr a c t e d a tt h e s o u r ce p o s i t i o n w i t h i n t h e % EE F r a d i u s . B a c k g r o und c o un t s i n t h e - k e V b a nd s c a l e d t o t h e a r e a t h a t c o rr e s p o nd s t o t h e % EE F r a d i u s . Sp ec tr a l b a nd s t h a tt h e s o u r ce i s d e t ec t e d w i t h P o i ss o nb a c k g r o und f l u c t u a t i o np r o b a b ili t y < × − . T h e l e tt e r s c o rr e s p o nd t o f u ll - b a nd ( F ) , s o f t - b a nd ( S ) , h a r d - b a nd ( H ) a ndu l tr a - h a r db a nd ( U ) N o t e . — T a b l e i s pub li s h e d i n i t s e n t i r e t y i n t h ee l ec tr o n i ce d i t i o n o f t h e j o u r n a l. able 12 Chandra AEGIS-X source catalog: source fluxes and HRs
Bayesian flux Bayesian Phot.ID f . − f . − f − f − HR flag(1) (2) (3) (4) (5) (6) (7)aegis 001 29 . +6 . − . . +2 . − . . +9 . − . < . − . +0 . − . . +8 . − . . +2 . − . . +11 . − . . +13 . − . − . +0 . − . . +8 . − . . +2 . − . . +11 . − . . +13 . − . − . +0 . − . . +6 . − . . +1 . − . . +10 . − . < .
85 0 . +0 . − . . +4 . − . . +1 . − . . +7 . − . < .
55 0 . +0 . − . . +6 . − . . +1 . − . . +10 . − . . +10 . − . . +0 . − . . +4 . − . . +1 . − . . +7 . − . < .
92 0 . +0 . − . . +4 . − . . +1 . − . < . < . − . +0 . − . . +5 . − . . +1 . − . . +9 . − . . +11 . − . . +0 . − . . +4 . − . . +1 . − . . +6 . − . < . − . +0 . − . Unique source name Flux in the 0.5-10 keV band in units of 10 − erg s − cm − estimated using the Bayesianmethodology of L09 Flux in the 0.5-2 keV band in units of 10 − erg s − cm − estimated using the Bayesianmethodology of L09 Flux in the 2-10 keV band in units of 10 − erg s − cm − estimated using the Bayesianmethodology of L09 Flux in the 5-10 keV band in units of 10 − erg s − cm − estimated using the Bayesianmethodology of L09 Hardness ratio determined by BEHR (Park et al. 2006) using the counts in the 0.5-2 and2-7 keV spectral bands Quality of the X-ray photometry. A flag of “1” indicates the presence of a nearby sourcethat may be contaminating the photometry. A flag of “2” indicates that another source wasdetected with the 90% EEF and that the photometry is likely heavily contaminated and thesource position uncertain. All other sources have a flag of “0”.
Note.—
Table 12 is published in its entirety in the electronic edition of the journal. able 13Optical and IR counterparts to the AEGIS-X sources. XID a OBJ NO b AEGIS ID (Rainbow) c X-ray R.A. d X-ray Dec. d Ctrp. R.A. e Ctrp. Dec. e PRIM MATCH f ROBUST Ctrp. g (J2000) (J2000) (J2000) (J2000)aegis 293 533 aegis 293 1 214.448561 52.695391 214.4488572 52.6953656 SubaruR 1aegis 901 1620 aegis 901 215.225446 53.118118 215.2257595 53.1182402 RAINBOW 1aegis 819 1488 aegis 819 214.769967 53.047322 214.7703197 53.047412 CFHTLS 1aegis 291 531 aegis 291 214.409987 52.693303 214.4098638 52.6932229 RAINBOW 1aegis 418 762 aegis 418 214.585343 52.788107 214.5855658 52.7883566 RAINBOW 1aegis 355 647 aegis 355 214.959983 52.743431 214.9594025 52.7435032 RAINBOW 1aegis 486 894 aegis 486 214.723504 52.839885 214.7237642 52.8398494 SubaruR 1aegis 529 962 aegis 529 214.792841 52.86416 214.7927908 52.864219 RAINBOW 1aegis 296 538 aegis 296 214.529397 52.697265 214.5293663 52.6971555 RAINBOW 1aegis 541 980 aegis 541 214.671679 52.871095 214.6720393 52.8710399 RAINBOW 1 Note.—
Table 13 is published in its entirety in the electronic edition of the journal. a X-ray Identification b Object number in Rainbow c Object Identification in Rainbow d X-ray position e Counterpart position f Band first used to identify multi wavelength counterpart. ”none” indicate no counterpart identified g Flag indicating whether the association with a counterpart is secure (1) or not (0).
Table 14Extract from the AEGIS-XD Photometric catalog
XID AEGIS ID (
Rainbow ) RA opt
DEC opt
R err R ... ... FUV err FUV (1) (2) (3) (4) (5) (6) (...) (...) (73) (74)549 aegis 293 1 214.4488572 52.6953656 14.86 0.02 ... ... 22.027 0.03551 aegis 294 214.4789369 52.6955591 21.94 0.02 ... ... -99.0 -99.0598 aegis 321 214.9992079 52.7125128 20.69 0.02 ... ... -99.0 -99.0749 aegis 399 1 214.9281189 52.7771454 21.9 0.02 ... ... -99.0 -99.01195 aegis 626 214.7869854 52.9435878 23.2 0.03 ... ... -99.0 -99.01276 aegis 669 215.198185 52.969059 18.62 0.02 ... ... 22.627 0.036 aegis 004 1 214.6103281 52.4330603 24.65 0.05 ... ... -99.0 -99.011 aegis 005 4 214.55811309 52.44051303 25.27 0.08 ... ... -99.0 -99.016 aegis 008 214.5951844 52.4524551 17.69 0.02 ... ... 24.147 0.1717 aegis 009 1 214.6241732 52.4526771 22.6 0.02 ... ... -99.0 -99.0
Note.—
Excerpt from the photometric catalog. Column 1: X-ray ID; Column 2: Optical identifier number from the
Rainbow catalog; Columns 3 and 4; Right Ascension and Declination in degrees of the counterpart; Column 5 and followingodd columns : AB magnitude in the filters listed in Table 7.; Column 6 and following even columns: associated photometricerrors. a b l e : E x t r a c t f r o m t h e A E G I S - X D r e d s h i f t c a t a l og X I D z s p e c z c o n f z s p e c R e f . N b a n d s z p z p L σ z p U σ z p L σ z p U σ P ( z p ) M o d z p P ( z p ) M o d ( )( )( )( )( )( )( )( )( )( )( )( )( )( )( ) . . . . . . . - . . -
999 5510 . . . . . . . - . . -
999 598 - . . . . . . . - . . -
999 7490 . . . . . . . - . . -
999 11951 . . . . . . . - . . -
999 12760 . . . . . . . - . . -
999 6 - . . . . . . . - . . -
999 11 - . . . . . . . - . . -
999 160 . . . . . . . - . . -
999 170 . . . . . . . - . . - N o t e . — E x ce r p t f r o m t h e ph o t o - zc a t a l og . C o l u m n : X - r a y I D ; C o l u m n : s p ec t r o s c o p i c r e d s h i f t , w h e n a v a il a b l e ; o t h e r w i s e - ; C o l u m n : s p ec t r o s c o p i c r e d s h i f t q u a li t y fl ag . W ec o n s i d e rr e li a b l e o n l y r e d s h i f t s f o r w h i c h t h i s v a l u e i s r h i g h e r . C o l u m n : s p ec t r o s c o p i c r e d s h i f t r e f e r e n ce ( = n o z s p e c ; = D EEP + ; = MM T ( C o il e t a l. ) ; = C F R S ( L ill y e t a l, ) ; = S D SS ( D R ; A hn e t a l. ) ; = L B G ( S t e i d e l e t a l. )) ; C o l u m n : N u m b e r o f ph o t o m e t r i c p o i n t s a v a il a b l e f o r t h e fi t ; C o l u m n : P h o t o m e t r i c r e d s h i f t ; C o l u m n nd : σ L o w e r a nd U pp e r v a l u e o f ph o t o m e t r i c r e d s h i f t ; C o l u m n nd : σ L o w e r a nd U pp e r v a l u e o f ph o t o m e t r i c r e d s h i f t ; C o l u m n :[ e a k P ( z ) ; C o l u m n : B e s t fi tt i n g t e m p l a t e : f r o m t o31 t h e t e m p l a t e s a r e f r o m S , t e m p l a t e s f r o m + ( ... ) a r e f r o m t h e I li b r a r y ; C o l u m n , nd : a s c o l u m n s , , f o r t h e s ec o ndb e s t ph o t o m e t r i c r e d s h i f t w h e n a v a il a b l e , e l s e - , . , - ..