Draft version June 21, 2013 Preprint typeset using LATEX style emulateapj v. 5/2/11

arXiv:1204.5148v2 [astro-ph.CO] 20 Jun 2013

THE CHANDRA MULTI-WAVELENGTH PROJECT: OPTICAL SPECTROSCOPY AND THE BROADBAND SPECTRAL ENERGY DISTRIBUTIONS OF X-RAY SELECTED AGN
Markos Trichas1 and Paul J. Green1, John D. Silverman2, Tom Aldcroft1, Wayne Barkhouse3, Robert A. Cameron 4, Anca Constantin5, Sara L. Ellison 6, Craig Foltz 7, Daryl Haggard8, Buell T. Jannuzi9,
Dong-Woo Kim1, Herman L. Marshall10, Amy Mossman1, Laura M. Pe´rez11, Encarni Romero-Colmenero12, Angel Ruiz13, Malcolm G. Smith14, Paul S. Smith 15, Guillermo Torres 1, Daniel R. Wik 16, Belinda J. Wilkes1,
Angie Wolfgang 17
(Received 2012 March) Draft version June 21, 2013
ABSTRACT
From optical spectroscopy of X-ray sources observed as part of the Chandra Multiwavelength Project (ChaMP), we present redshifts and classiﬁcations for a total of 1569 Chandra sources from our targeted spectroscopic follow up using the FLWO/1.5m, SAAO/1.9m, WIYN 3.5m, CTIO/4m, KPNO/4m, Magellan/6.5m, MMT/6.5m and Gemini/8m telescopes, and from archival SDSS spectroscopy. We classify the optical counterparts as 50% broad line AGN, 16% emission line galaxies, 14% absorption line galaxies, and 20% stars. We detect QSOs out to z∼5.5 and galaxies out to z∼3. We have compiled extensive photometry, including X-ray (ChaMP), ultra-violet (GALEX), optical (SDSS, ChaMPNOAO/MOSAIC follow-up), near-infrared (UKIDSS, 2MASS, ChaMP-CTIO/ISPI follow-up), midinfrared (WISE) and radio (FIRST, NVSS) bands. Together with our spectroscopic information, this enables us to derive detailed spectral energy distributions (SEDs) for our extragalactic sources. We ﬁt a variety of template SEDs to determine bolometric luminosities, and to constrain AGN and starburst components where both are present. While ∼58% of X-ray Seyferts (1042<L2−10 keV <1044 erg s−1) require a starburst event (>5% starburst contribution to bolometric luminosity) to ﬁt observed photometry only 26% of the X-ray QSO (L2−10 keV >1044 erg s−1) population appear to have some kind of star formation contribution. This is signiﬁcantly lower than for the Seyferts, especially if we take into account torus contamination at z>1 where the majority of our X-ray QSOs lie. In addition, we observe a rapid drop of the percentage of starburst contribution as X-ray luminosity increases. This is consistent with the quenching of star formation by powerful QSOs, as predicted by the merger model, or with a time lag between the peak of star formation and QSO activity. We have tested the hypothesis that there should be a strong connection between X-ray obscuration and star-formation but we do not ﬁnd any association between X-ray column density and star formation rate both in the general population or the star-forming X-ray Seyferts. Our large compilation also allows us to report here the identiﬁcation of 81 X-ray Bright Optically inactive Galaxies (XBONG), 78 z>3 X-ray sources and 8 Type-2 QSO candidates. Also we have identiﬁed the highest redshift (z=5.4135) X-ray selected QSO with optical spectroscopy.

mtrichas@cfa.harvard.edu 1 Harvard-Smithsonian Center for Astrophysics, Cambridge,
MA 02138 2 Institute for the Physics and Mathematics of the Universe
(IPMU), University of Tokyo, Kashiwanoha 5-1-5, Kashiwa-shi, Chiba 277-8568, Japan
3 Department of Physics and Astrophysics, University of North Dakota, Grand Forks, ND 58202, USA
4 W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA
5 Department of Physics and Astronomy, James Madison University, PHCH, Harrisonburg, VA 22807
6 Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia V8P 1A1, Canada
7 Division of Astronomical Sciences, National Science Foundation, 4201 Wilson Blvd., Arlington, VA 22230
8 Center for Interdisciplinary Exploration and Research in Astrophysics, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA
9 NOAO, Kitt Peak National Observatory, Tucson, AZ 85726 USA
10 Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
11 Department of Astronomy, California Institute of Technol-

ogy, 1200 East California Blvd, Pasadena, CA 91125, USA 12 South African Astronomical Observatory, P.O. Box 9, Ob-
servatory, 7935, South Africa 13 Osservatorio Astronomico di Brera - INAF, Milan, Italy 14 Cerro Tololo Interamerican Observatory, La Serena, Chile 15 Steward Observatory, University of Arizona, 933 Cherry
Ave., Tucson, AZ 85721, USA 16 NASA Goddard Space Flight Center, Greenbelt, MD 20771 17 Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA

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1. INTRODUCTION
Our understanding of how galaxies form and evolve has signiﬁcantly advanced in the last few years. Large spectroscopic programs (e.g. 2dFGRS, SDSS, DEEP2) have shown that the evolution of galaxies strongly depends on their position in the cosmic web. A striking manifestation of this link is the suppression of the star formation in increasingly dense environments (e.g. Kauﬀmann et al. 2004; Cooper et al. 2006; Netzer 2009; Schawinski et al. 2009). In addition, there is now strong evidence that powerful active galactic nuclei (AGN) play a key role in the evolution of galaxies. The correlation of central black hole and stellar bulge mass (MBH -σ; e.g. Magorrian et al. 1998), and the similarity between the cosmic star formation history (e.g. Hopkins & Beacom 2006) and cosmic black hole mass assembly history (e.g. Aird et al 2010) in massive galaxies, both suggest that the growth of supermassive black holes (SMBH) is related to the growth of host galaxies. The apparently independent observational trends above are believed to hold the key to galaxy assembly, but the detailed physical mechanism(s) behind them remain poorly understood. For example, although processes like galaxy suﬀocation, harassment and ram-pressure stripping are proposed to explain the star formation/density relation (e.g. Haines et al. 2006), they usually operate in rich and hence rare environments (i.e. massive clusters). The vast majority of galaxies inhabit less dense regions (poor clusters, groups, ﬁeld), where alternative mechanisms should dominate. Understanding what drives the formation and evolution of galaxies and their central SMBHs remains one of the most signiﬁcant challenges in extragalactic astrophysics.
Recent attention has focused on models where AGN feedback regulates the star formation in the host galaxy. These scenarios are consistent with the MBH - σ relation and make various predictions for AGN properties, including the environmental dependence of the AGN/galaxy interplay and the relative timing of periods of peak star formation and nuclear accretion activity. The key feature of these models is that they can potentially link the apparently independent observed relations between star formation, AGN activity and large scale structure to the same underlying physical process. For example, in the “radio-mode” model of Croton et al. (2006), accretion of gas from cooling ﬂows in dense environments (e.g. group, cluster) may produce relatively low-luminosity AGN, which in turn heat the bulk of the cooling gas and prevent it from falling into the galaxy center to form stars. Alternatively, Hopkins et al. (2006) propose that mergers trigger luminous QSOs and circumnuclear starbursts, which both feed and obscure the central engine for most of its active lifetime. In this scenario, AGN outﬂows eventually sweep away the dust and gas clouds, thereby quenching the star formation. This “QSO-mode” likely dominates in poor environments (e.g. ﬁeld, group), as the high-velocity encounters, common in dense regions, do not favour mergers. These proposed models make clear, testable predictions about the properties of AGN, while observational constraints provide ﬁrst-order conﬁrmation of this theoretical picture (e.g. Lehmer et al.

2009). Merger-driven scenarios for example, predict an association between optical morphological disturbances, star formation and an intense obscured AGN phase in low density regions. The “radio mode” model, in contrast, invokes milder AGN activity in early-type hosts and relatively dense environments with little or no star formation.
While it is now recognized that black holes play a fundamental role in shaping the galaxy population, the sequence in which galaxies build up their stellar and black hole mass and the relationship between the two components are, as yet, poorly understood. In some models (e.g. Di Matteo et al. 2005, Hopkins et al. 2006) the stellar population and the SMBHs form almost simultaneously and therefore predict a correlation between star formation and AGN activity. Contrary to that scenario, it is also proposed that the stellar population of galaxies is accumulated ﬁrst, followed by the main epoch of SMBH growth (e.g. Archibald et al. 2002, Cen 2011). In the latter class of models, one expects star formation and AGN activity to be unrelated, or even negatively correlated. A major complexity in addressing this question observationally, is assessing the level of star formation in AGN. Particularly at z > 1, the main epoch of galaxy and SMBH formation, it is diﬃcult to decompose the stellar from the AGN emission, especially in the case of dust enshrouded systems. When they are accreting rapidly, AGN can dominate the radiation from stars over almost the entire electromagnetic spectrum. There are, however, two key energy ranges which allow the most eﬀective separation between the radiation from accretion and from star formation. The X-ray band provides a clean window in which the radiation from luminous AGN (LX (2 − 10keV) > 1042 erg s−1), can be observed with minimal contamination from star formation, while star-forming galaxies emit a large fraction of their energy in the infrared band where the AGN contribution is minimal. Combining X-ray with longer wavelength data and optical spectroscopy can provide a handle on this issue (e.g. Trichas et al. 2009; 2010, Kalfountzou et al. 2011). X-ray surveys have proved to be by far the most eﬃcient way of ﬁnding AGN, and in relatively shallow surveys, AGN will completely dominate the source population. When a hard bandpass is available (>2 keV), as with Chandra, one can detect X-ray AGN that might otherwise be completely missed in other surveys due to obscuration. However, lack of observational data limits the information on the interplay between AGN, star formation and local density, particularly at z>1, close to the peak of the AGN and star formation activity of the Universe (e.g. Barger et al. 2005). Addressing these key questions requires the identiﬁcation of large numbers of AGN at z>1 over a broad range of environments for which a precise estimation of their bolometric luminosity will allow us to determine the relative contribution of AGN and star formation to the bolometric emission.
The above questions have motivated eﬀorts to study the multi-wavelength properties of AGN combining data from various space and ground-based telescopes. The Chandra and XMM-Newton Observatories are, for the ﬁrst time, resolving the hard (2-10

ChaMP Optical Spectroscopy

Fig. 1.— Redshift distribution for all 1242 spectroscopically identiﬁed ChaMP extragalactic sources.
keV) Cosmic X-ray Background (CXRB) into individual sources. Based on the spectral shape of the CXRB, the majority of emission from accretion powered sources has been obscured from our view. While unabsorbed AGN dominate the soft (0.1-2 keV) CXRB (Hasinger et al. 1998), the high energy CXRB spectrum (2-30 keV) is harder than that of known AGN (Gilli et al 2001). With recent Chandra observations of the Chandra Deep Field North (CDF-N; Brandt et al. 2001), South (CDF- S; Rosati et al. 2002) and XMM observations of the Lockman Hole (Hasinger et al. 2001) , ∼75% of the hard (2-8 keV) XRB has been resolved into point sources. The resolved fraction decreases with increasing X-ray energy (Worsley et al. 2006), but approaches 80% e.g., when X-rays at the position of faint optical sources are stacked (Hickox & Markevitch 2006). Many of the hardest serendipitous sources found so far arise in otherwise unremarkable bright galaxies (Hornschemeier et al. 2001; Tozzi et al. 2001), which may contain very heavily obscured AGN. In addition, Chandra has begun to detect the extremely rare, heavily obscured, dust enshrouded quasars (Norman et al., 2001; Stern et al., 2002). Wider area surveys are needed to study these X-ray emitting populations with signiﬁcant statistics. The Chandra Multiwavelength Project (ChaMP) is a medium-depth, wide area sample of serendipitous X-ray sources from archival Chandra ﬁelds. The ChaMP eﬀectively bridges the gap between ﬂux limits attained by past large-area X-ray surveys and recent Chandra Deep ﬁelds. The complete project has detected a total of >19,000 X-ray sources (Green et al. 2009) over 33 deg2 with >9000 X-ray sources positionally matched to SDSS optical sources (Kim et al. 2007). However, to fully study the properties of X-ray detected AGN, good quality spectra are needed for redshifts, luminosities and source classiﬁcation.
In this paper we describe the large sample of optical spectroscopy available for our ChaMP sources with a suite of available multi-wavelength data ranging from Xrays to radio. These data are used to test the predictions of the diﬀerent feedback models proposed to explain the apparent relationship between AGN and star formation

activity. In §2 we describe our optical spectroscopy and ancillary multi-wavelength data. §3 summarizes the template ﬁtting method used to produce spectral energy distributions for all our extragalactic objects while §4 and §5 describe the X-ray spectral ﬁtting, star formation rates and black hole mass estimates. §6, §7 and §8 discuss what our observations suggest regarding the diﬀerent feedback models while §9 and §10 brieﬂy summarize the interesting populations of XBONG and high redshift objects found within our sample. §11 is a summary of our ﬁndings. A cosmological model with Ωo = 0.3, λo = 0.7 and a Hubble constant of 72 km s−1 M pc−1 is used throughout.
2. CHAMP OBSERVATIONS
2.1. Imaging
The Chandra Multiwavelength Project (ChaMP) is a wide-area serendipitous X-ray survey based on archival X-ray images of the (|b| > 20 deg) sky observed with the AXAF CCD Imaging Spectrometer (ACIS) onboard Chandra. The ChaMP covers a total of 392 ﬁelds, omitting pointings from dedicated serendipitous surveys like the Chandra Deep Fields as well as ﬁelds with large bright optical or X-ray sources. The list of Chandra pointings avoids any overlapping observations by eliminating the observation with the shorter exposure time. As described in Green et al. (2004), we also avoid ﬁelds with extended sources (>3 ) in either optical or X-rays. Spurious X-ray sources have been ﬂagged and removed as described in Kim et al. (2007). Of the 392 ChaMP obsids, which average 0.1 deg2 sky area each, at the brightest ﬂuxes, 323 overlap with the SDSS (DR5) footprint (Covey et al. 2008; Green et al. 2009; Haggard et al. 2010).
Optical imaging provides optical ﬂuxes, preliminary source classication, and accurate centroiding for spectroscopic follow-up. As a result, the ChaMP team supplemented observed Chandra imaging with deep optical observations (Green et al. 2004). ChaMP ﬁelds were observed with NOAO 4-meter imaging with the Mosaic CCD cameras (Muller et al. 1998) which provided adequate depth, spatial resolution (∼0.6”/pixel), and a large ﬁeld of view (36 ×36 ) over the full Chandra ﬁeld of view. NOAO ﬁlters similar to Sloan Digital Sky Survey (SDSS) g , r and i passbands were used for 66 such ﬁelds, reaching down to AB magnitudes of 26.1, 25.4 and 24.4 respectively (Green et al. 2004). The positional uncertainty of ChaMP X-ray source centroids has been analyzed via X-ray simulations by Kim et al. (2007). An automated matching procedure between each optical position and the ChaMPs X-ray source catalog was ﬁrst performed with ∼95% of the matched sample having an X-ray/optical position diﬀerence of <3 yielding a sample of 1376 unique matches. In addition to the automated matching procedure, we also performed visual inspection of both X-ray and optical images, overplotting the centroids and their associated position errors retaining the highest conﬁdence matches (Green et al. 2009).
2.2. Optical Spectroscopy
The spectroscopic follow-up of Chandra sources operated in three modes based on optical magnitude. Spectra

4 Trichas et al.

Fig. 2.— Multi-wavelength magnitude distributions for all our 1242 spectroscopically identiﬁed ChaMP extragalactic sources. UV and optical magnitudes are in the AB system, near- and mid-infrared magnitudes are in the Vega system.
for the brightest sources (r<17) are obtained primarily with the FLWO/1.5m FAST spectrograph and the SAAO/1.9m grating spectrograph. For most sources with 17<r<21, we used the WIYN and the CTIO/4m with HYDRA, a multi-ﬁber spectrograph. To obtain spectra for the faint source population (r>21), slit and multi-object spectroscopy with a 4 to 8 m class telescope is required (i.e. KPNO/4m, MMT, Magellan, Gemini). In total, 22 nights of WIYN/Hydra (multi-ﬁber) time, 32 nights of Magellan/IMACS and LDSS-2 (multi-slit), 9 nights of MMT with Hectospec (multi-ﬁber) or Blue Channel (single slit), 7 nights of CTIO-4m/Hydra (multi-ﬁber), 5 nights of KPNO-4m/MARS (multi-slit), and 2 nights of Gemini-N/GMOS (multi-slit) were used to obtain optical spectroscopy for our ChaMP sources. These spectra were supplemented with optical spectra from the SDSS DR6 archive. Among the 1569 spectra, 50% are broad line AGN (BLAGN; FWHM>1000 km/sec), 16% narrow emission line galaxies (NELG; EW>5˚A, FWHM<1000 km/sec), 14% absorption line galaxies (ALG; no emission lines with EW>5˚A) and 20% stars. Results from the stellar sample are published in Covey et al. (2008).
A table of our ﬁnal extragalactic spectroscopic catalog is provided in electronic format. The catalog omits the 327 stars, and so contains a total of 1242 entries. The columns listed are:
CHANDRAOBSID, Chandra observation identiﬁer SPECOBJID, Spectroscopic observation identiﬁer CXOMPNAME, ChaMP identiﬁer RA, optical RA (J2000) DEC, optical DEC (J2000) TELESCOPE, telescope used for obtaining spectrum SPEC, spectrograph used for obtaining spectrum DATE, date of spectroscopic observation REDSHIFT, spectroscopic redshift CLASS, spectroscopic classiﬁcation, BLAGN (broadline AGN), NELG (narrow emission line galaxy), ALG

(absorption line galaxy) NETB, number of counts and associated errors FSC, soft (0.5 - 2 keV ) X-ray ﬂux in units of 10−13 erg s−1 cm−2 and associated errors FHC, hard (2 - 8 keV ) X-ray ﬂux in units of 10−13 erg s−1 cm−2 and associated errors FUV, far-UV AB magnitude and associated errors NUV, near-UV AB magnitude and associated errors U, u-band AB magnitude and associated errors G, g-band AB magnitude and associated errors R, r-band AB magnitude and associated errors I, i-band AB magnitude and associated errors Z, z-band AB magnitude and associated errors Y, Y-band Vega magnitude and associated errors J, J-band Vega magnitude and associated errors H, H-band Vega magnitude and associated errors K, K-band Vega magnitude and associated errors MAG34, 3.4µm Vega magnitude and associated errors MAG46, 4.6µm Vega magnitude and associated errors MAG12, 12µm Vega magnitude and associated errors MAG22, 22µm Vega magnitude and associated errors S20, 20cm radio ﬂux in mJy and associated errors LOG LX, logarithmic 2-10keV X-ray luminosity in units of erg s−1 GAMMA, power-law slope from X-ray spectral ﬁtting and associated 90% conﬁdence NHINT, NiHntrand associated 90% conﬁdence NPHOT, number of photometric bands per catalogue used for the SED ﬁtting (X: Chandra, G: GALEX, O: Optical, N: near-infrared, W: WISE, R: radio) AGNTEMP: AGN template used for the SED ﬁt (0: No AGN used, 1: Elvis et al. 1994 + Richards et al. 2006, 2: Hopkins et al. 2007, 3-6: Seyfert-2 from Bianchi et al. 2006, 7: NGC1068 by Matt et al. 1997, 8: Mrk231 by Berta et al. 2006, 9: IRAS19254-7245 by Berta et al. 2003, 10: IRAS22491-1808 by Farrah et al. 2003 GALTEMP: Galaxy template used for the SED ﬁt (0: No galaxy template used, 1: NGC5253 by Beck et al. 1996, 2: NGC7714 by Brandl et al. 2004, 3: M82 by Strickland et al. 2004, 4: IRAS12112+0305 by Imanishi et al. 2007, 5: Elliptical from Rowan-Robinson et al. 2008, 6: Young elliptical from Maraston 2005) FSB: Fraction of starburst contribution to the bolometric luminosity FA: Fraction of AGN contribution to the bolometric luminosity LBOL: Bolometric luminosity (109-1019 Hz) in erg s−1 MBH: logarithmic estimate of black hole mass
Figures 1 and 2 show the redshift and multi-wavelength photometry distributions respectively of all our 1242 extragalactic sources. Our sample includes a signiﬁcant population of 78 z>3 X-ray QSOs, including two with redshifts greater than ﬁve. Figures 3, 4, 5 and 6 show examples of the various types of spectra found in our sample. Figure 7 shows the distribution of broad-band X-ray ﬂux versus optical magnitude to illustrate the parameter space spanned by the various populations. The majority of BLAGN follow the trend of 0<log (fX / fr)<1. However, there is a signiﬁcant population of BLAGN that lie at fX / fr>10. From the latter 30% of them appear to be X-ray Seyferts (1042<L2−10 keV <1044 erg s−1) with NiHntr>1022 which

ChaMP Optical Spectroscopy

Fig. 3.— Example ChaMP spectra of stellar objects observed with FAST. CHANDRAOBSID, SPECOBJID, REDSHIFT and CLASS are given in the top of each plot.

is consistent with previous studies that ﬁnd that this parameter space is occupied by obscured X-ray Seyferts (e.g. Silverman et al. 2010). NELG seem to span a wide range of fX / fr as expected, as among them we can ﬁnd Seyferts, LINERs and star-forming sources. At faint ﬂux levels, a signiﬁcant number of ALGs are evident, spanning a wide range of optical magnitudes.

2.3. Multi-Wavelength Photometry
A prime advantage of ChaMP in comparison to deeper pencil-beam X-ray surveys, is its relatively shallow depth that allows for easier source identiﬁcation in other wavelengths. We have cross-correlated our spectroscopic sample with GALEX (Morrissey et al. 2007), UKIDSS DR4 (Lawrence et al. 2007), 2MASS (Skrutskie et al. 2006), VLA (Condon et al. 1998) and WISE (Wright et al. 2010) catalogs. In the case of GALEX, the list

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Fig. 4.— Example ChaMP spectra of absorption line galaxies observed with Magellan, MMT and WIYN telescopes. Spectra are not ﬂux calibrated. CHANDRAOBSID, SPECOBJID, REDSHIFT and CLASS are given in the top of each plot.

was generated from a search for GALEX counterparts to optical counterpart positions in the ChaMP X-ray catalog. We retrieved the GALEX GR6 catalog using the Virtual Observatory (VO) TOPCAT tool (Taylor 2005). Using Monte-Carlo simulations and the Fadda et al (2002) method, we have concluded that a search radius of 2.5 arcsec provides us with a P (d) < 0.02, where P (d) is the Poisson probability of a GALEX source to have a random association within a distance d, yielding an expected rate of random associations of

less than 5%. The catalog contains only sources that were detected at S/N > 5 in at least one of the NUV, FUV ﬁlters. All matches were then visually inspected to remove any apparent spurious associations.
We adopted a similar method for near-infrared with the 2MASS and UKIDSS (DR4) catalogs. The ChaMP team has also obtained deep near-infared imaging for 35 ﬁelds using the ISPI camera on the CTIO 4m Blanco telescope. We shifted the ChaMP source coordinates

ChaMP Optical Spectroscopy

Fig. 5.— Example ChaMP spectra of narrow emission line galaxies observed with Magellan, MMT and WIYN telescopes. Spectra are not ﬂux calibrated. CHANDRAOBSID, SPECOBJID, REDSHIFT and CLASS are given in the top of each plot.

6 arcmin in both RA and Dec in a large number of directions, performing positional cross-correlation with UKIDSS and 2MASS using a search radius of 5 arcsec. We thereby conclude that P (d)< 0.02, corresponding here to 4.5% random associations. In cases of multiple matches where one of the matches is at separation <1.5 arcsec and the other at separation >1.5 arcsec, the nearest match has been selected. In all other cases where matches are at similar distances, or both below 1.5 arc-

sec, visual inspection usually has broken the counterpart ambiguity. When both 2MASS and UKIDSS imaging are available, we use the deeper UKIDSS photometry for SED ﬁtting (§3). The same method and statistics were used for WISE data.
In the case of NVSS and VLA-FIRST radio catalogs, a 5 arcsec match radius yields less than 2% random associations. All matches were visually inspected to

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Fig. 6.— Example ChaMP spectra of broad line AGN observed with Magellan, MMT and WIYN telescopes. Spectra are not ﬂux calibrated. CHANDRAOBSID, SPECOBJID, REDSHIFT and CLASS are given in the top of each plot.

remove any possible spurious associations. In the cases of FIRST/ChaMP associations where the radio/X-ray position is associated with an extended feature of the radio galaxy (e.g. radio lobe) the NVSS ﬂux is used instead.
From our 1242 ChaMP spectroscopic extragalactic sources, 63% have detections in UV, 100% in optical, 33% in near-infrared, 30% in mid-infrared and 15% in radio.

3. BROAD-BAND SPECTRAL ENERGY DISTRIBUTIONS
To characterize the Spectral Energy Distributions (SEDs) of extragalactic objects, estimate bolometric luminosities and check for the presence of starburst and/or AGN activity in our sample, we ﬁt the X-ray-to-radio ﬂuxes with various empirical SEDs of well-observed sources as presented in Ruiz et al. (2010). We have used a total of 16 such templates: two QSO templates (Elvis et al. 1994 + Richards et al. 2006, Hopkins et

ChaMP Optical Spectroscopy

Fig. 7.— Broad-band X-ray ﬂux in logarithmic scale versus r-band magnitude for all our 1242 extragalactic sources. Red circles, green squares and blue triangles denote broad-line AGN, narrow emission line and absorption line galaxies respectively. Line of constant X-rayto-optical ﬂux ratio (0.1, 1, 10) are given by Equation 1 of Szokoly et al. (2004).
al. 2007), four Seyfert-2 galaxies (Bianchi et al. 2006), four starburst galaxies (NGC5253 by Beck et al. 1996, NGC7714 by Brandl et al. 2004, M82 by Strickland et al. 2004, IRAS12112+0305 by Imanishi et al. 2007) with star formation rates (SFR) ranging from 6 to 600 M yr−1, two absorption line galaxy templates (RowanRobinson et al. 2008, Maraston 2005) and 4 composite templates that are known to harbour both an AGN and a starburst (NGC1068 by Matt et al. 1997, Mrk231 by Berta et al. 2006; 2007, IRAS19254-7245 by Berta et al. 2003, IRAS22491-1808 by Farrah et al. 2003). Except Mrk231 which is optically classiﬁed as a Broad Line QSO with a massive young nuclear starburst, the remainder three composite objects are all optically classiﬁed as Seyfert-2s with intense starbursts. We have adopted the model described in Ruiz et al. (2010) which ﬁts all SEDs using a χ2 minimization technique within the ﬁtting tool Sherpa (Freeman et al. 2001). Our ﬁtting allows for two additive components, one associated with the AGN emission and the other associated with the starburst emission. The SEDs are built and ﬁtted in the rest-frame. We have chosen the ﬁt with the lowest reduced χ2 as our best ﬁt model. Fractions of AGN and starburst contributions are derived from the SED ﬁtting normalisations as these are derived from Ruiz et al. (2010) model,

Fν = FBOL (α uAν GN + (1 − α) uSν B)

(1)

where FBOL is the total bolometric ﬂux, α is the relative contribution of the AGN to FBOL , Fν is the total ﬂux at frequency ν, while uAν GN and uSν B are the normalized AGN and SB templates.

Among our 758 broad emission line objects (FWHM > 1000 km/sec) all are best ﬁtted with one of our two available QSO SED templates, with 150 also requiring starburst contributions of at least 5%. Among the 252 narrow emission line objects (EW > 5˚A; FWHM < 1000 km/sec), 17 have been ﬁtted with one of the composite templates which harbor a Seyfert-2, 208 have been ﬁtted with a Seyfert-2 template (65 having

signiﬁcant starburst contribution), 12 have been ﬁtted with a starburst template, and 15 have been ﬁtted with a QSO template (10 of which require > 5% starburst contribution). Among the 230 absorption line galaxies, 130 have been ﬁtted with an elliptical SED template, 91 with a mixture of Seyfert-2 and starburst templates and 9 objects with a QSO template. Since the best ﬁt model was determined only using the lowest reduced χ2 value with no preselection based on spectroscopic classiﬁcation, these results indicate an excellent overall agreement between the SED ﬁtting code and optical spectroscopic classiﬁcation in the cases of broad line and narrow emission line objects and fair agreement in the ALGs. Figure 8 shows examples of sources ﬁtted with QSO, Seyfert-2 and composite templates.
4. X-RAY SPECTRAL FITTING
For all ChaMP X-ray sources in our spectroscopic sample, we perform X-ray spectral ﬁtting using the CIAO Sherpa18 tool in an automated script. For each source we ﬁt three power-law models. While quasars are typically well-ﬁt by a power-law, it is well-known that AGNdominated spectra are complex, including potentially a soft excess and/or reﬂection component, Fe Kα line emission, and neutral, partially ionized and/or partially covering absorption (e.g. Reeves & Turner, 2000). When active SMBH accretion is weak or non-existent, emission related to the stellar component or ISM give rise to the X-ray emission in galaxies. X-ray spectra from lower luminosity objects may have a signiﬁcant power-law component arising from X-ray binary populations (e.g. Persic & Rephaeli, 2002; Fragos et al. 2009). Thermal components arising from hot ISM or shocked gas may be present, which at high signal-to-noise would be poorly ﬁt with power-law models. However, since our sample has a median of 45 net broadband counts, detailed spectral ﬁts are not warranted, so we remain content with power-law models. The three X-ray spectral models we ﬁt all contain an appropriate neutral Galactic absorption component frozen at the 21 cm value:19 (1) photon index Γ, with no intrinsic absorption component (model “PL”) (2) an intrinsic absorber with neutral column NHintr at the source redshift, with photon index frozen at Γ = 1.8 (model “PLfix”). Allowed ﬁt ranges are −1.5 < Γ < 3.5 for PL and 1018 < NHintr < 1025 for PLfix. (3) a twoparameter absorbed power-law where both Γ and the NHintr are free to vary within the above ranges while NHGal is ﬁxed (model “PL abs”). All models are ﬁt to the ungrouped data using Cash statistics (Cash, 1979). The latter model, PL abs, is our default, for several reasons described below. Overall, we ﬁnd (Figure 9) that the best-ﬁt Γ from our default model is not correlated with NHintr, which illustrates that these parameters are ﬁt with relative independence even in low count sources. The best-ﬁt Γ in the default PL abs model correlates well with that from the PL model for the majority of sources; the median of the diﬀerence in ﬁtted slopes for these two models∆Γ is just 15% of the median uncertainty in slopes σΓ. On
18 http://cxc.harvard.edu/sherpa 19 Neutral Galactic column density NHGal taken from Dickey et al. (1990) for the Chandra, aimpoint position on the sky.

10 Trichas et al.

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Fig. 8.— Examples of best-ﬁt SEDs (blue line). Red solid and green dashed lines are the starburst and AGN templates respectively. Square boxes indicate available photometry. Vertical lines are associated >10% errors. Top Left : XS0518B7007 with L2−10 keV =1.1×1040 erg s−1 at z = 0.08. Best ﬁtted with a Seyfert-2 NGC3393 template. Top Right : XS05618B6006 with L2−10 keV =3.1×1040 erg s−1 at z = 0.08. Best
ﬁtted with a Seyfert-2 NGC4507 and a starburst NGC7714 templates, contributing 15% and 85% respectively to the LBOL. Middle Left : XS00546B2012, with L2−10 keV =9.1×1043 erg s−1 at z = 1.01. Best ﬁtted with an Elvis et al QSO template. Middle Right : XS02251B7002, with L2−10 keV =9.5×1043 erg s−1 at z = 1.1. Best ﬁtted with an Elvis et al QSO and a starburst NGC5253 templates, contributing 15% and 85% respectively to the LBOL. Bottom Left : XS0907B3001 with L2−10 keV =9.6×1044 erg s−1 at z = 2.08. Best ﬁtted with a Hopnkins et al (2007) QSO template. Bottom Right : XS04151B6006 with L2−10 keV =4.1×1044 erg s−1 at z = 1.92. Best ﬁtted with a Hopkins et al. QSO and
a starburst NGC7714 templates, contributing 20% and 80% respectively to the LBOL

ChaMP Optical Spectroscopy

Fig. 9.— Best ﬁst X-ray spectral slope Γ versus column density in logarithmic scale. Downward arrows represent the 90% upper limits to NiHntr, whenever the 90% lower limit encompassed zero. Red circles, green squares and blue triangles denote broad-line AGN, narrow emission line and absorption line galaxies respectively.
the other hand, 67 (5.4%) of sources have their best-ﬁt power-law slope “pegged” at Γ = 5. Most (42 or 63%) of these are optical ALG, likely passive elliptical galaxies poorly ﬁt by a power-law model. Only 10 (15%) are QSOs. Many of the sources with ∆Γ larger than σΓ also have detectable NHintr (which we deﬁne as those ﬁts where 90% conﬁdence lower limit of NHintr > 0), which justiﬁes the softer Γ result.
5. BLACK HOLE MASSES & STAR FORMATION RATES
Black hole masses are only available for sources with available SDSS spectra. For our broad line objects, black hole masses have been retrieved from Shen et al (2011), who have compiled virial black hole mass estimates of all SDSS DR7 QSOs using Vestergaard & Peterson (2006) calibrations for Hβ and C IV and their own calibrations for Mg II. There are 329 broad-line objects within our sample with black hole mass estimates. For our narrow line objects, a total of 119 NELG for which high quality SDSS spectra are available, MBH values are calculated using the M-σ relation of Graham et al. (2011). A suite of optical and X-ray properties of these NELG are presented and discussed in Constantin et al. (2009). Star formation rates have been estimated using the output of our SED ﬁtting code. In the case that a starburst template is required in the ﬁtting we extract the 8 - 1000 µm starburst luminosity which is a proxy for the farinfrared luminosity attributed to star formation. The LSB (8 -1000 µm) is then converted to a star formation rate using Kennicutt (1998) relation.
SF R (M yr−1) = 4.5 × 10−44 × LSB (erg s−1) (2)
6. X-RAY LUMINOSITY - REDSHIFT PLANE
X-ray luminosity is by itself an important discriminator of the primary power source. The maximum achievable X-ray emission by young stellar populations in an ultra-luminous starburst is L2−10 keV ∼1.5×1042 erg s−1 (Persic et al. 2004). Figure 10 shows the hard X-ray luminosity versus redshift for all hard X-ray detected

Fig. 10.— Distribution of rest-frame Logarithmic 2-10 keV X-ray luminosity and spectroscopic redshift for the 1202 hard-band X-ray detected sources from ChaMP. Red circles are sources that require a starburst component to ﬁt available photometry. Black crosses are sources that their SED ﬁts do not require any contribution from a starburst component. It is evident that as the X-ray luminosity increases, the occurrence of star formation activity decreases.
sources in our sample. By restricting the sample to those sources detected in the most penetrating 2−10 keV band we can minimize the inﬂuence of obscuration on our results. However, among our 1242 extragalactic ChaMP sources with available spectroscopy, 1202 have hard-band detections and as a result selecting them does not bias our results. Here LX is the restframe 2-10 keV X-ray luminosity calculated with the method described in the Appendix of Green et al. (2011). Red circles are those sources that require a starburst component to ﬁt the observed photometry.
The LX - z plane of Figure 10 shows a striking trend. Star formation occurrence increases from 43% in sources with log L2−10 keV < 42 to 58% amongst objects with 42 < log L2−10 keV < 44 erg s−1 and drops sharply to 26% when X-ray luminosity reaches QSO limits i.e. when log L2−10 keV >44. However, the latter can be considered as a conservative upper limit to the occurrence of star formation in QSOs since the majority (69%) of X-ray QSOs with starburst events lie at z>1 where contamination from torus emission to the mid-infrared can be signiﬁcant (Rowan-Robinson et al. 2009; Mor & Netzer 2011). Since the longest infrared wavelength used for our SED ﬁts is the 22µm band from WISE we expect that the number of apparent star forming QSOs at z>1 may be signiﬁcantly lower, which would make the trend we see in Figure 10 even stronger.
Figure 11 shows the average fractional contribution of AGN and/or starburst components to the bolometric luminosity per 2-10 keV luminosity bin of 0.6. Again, there is a striking trend which seems to support the aforementioned indication of quenching of star formation in powerful QSOs. Although there seems to be a broad ﬂat evolution of AGN and starburst contributions in low and moderate X-ray luminosities (LX <1041.5 erg s−1), when powerful AGN activity is triggered (LX >1042 erg s−1), star formation seems to pick up and reaches its

12 Trichas et al.

Fig. 11.— Fractional contribution of AGN (blue dots) and starburst components (red dots) to bolometric luminosity versus log LX . Points represent the fractional AGN and/or starburst contributions for all objects with LX(2−10keV >1040 erg s−1. Solid red line represents the average value of starburst fractional contribution per log LX bin of 0.6. Dashed blue line represents the average value of AGN fractional contribution per log LX bin of 0.6.
maximum at log LX ∼ 42.5. At this stage AGN and star formation appear to contribute the same fraction of the bolometric output but as the AGN becomes more powerful, as indicated both from the X-ray emission and AGN contribution, star formation decreases rapidly and eventually quenched when the AGN reaches extreme rates of accretion. At this stage of the evolution, AGN reaches its maximum emission (100% contribution from an AGN component) without the presence of any identiﬁable starburst events. This ﬁnding is consistent with the picture drawn by Figure 10. If the absence of star formation in QSOs, as depicted in Figure 10 were a detection bias, then we would expect that the QSOs with SFR to follow the relationship of Figure 11 and show enhanced starburst contribution compared to X-ray Seyferts. However, this is not the case, suggesting that intense SFR has stopped while accretion continues to rise in agreement with QSO-mode feedback models (e.g. Hopkins et al. 2005, Netzer 2009).
7. STARBURST DETECTABILITY
Figures 10 and 11 suggest that star formation is either quenched (weak or absent compared to the LBol) in QSOs or simply not detectable by our SED ﬁtting method using the currently available photometry. The latter may occur because a given host (LSB) falls below photometric survey detection limits towards higher redshift, and/or because a given host (LSB) becomes more diﬃcult to detect in contrast to a more luminous nuclear source.
To address the detectability issue we have performed a series of SED ﬁts to a large set of simulated sources drawn from our original sample. We have focused our tests to the population of 987 sources with LX(2−10keV ) > 1042 erg s−1. Of them, 456 have 1042 < LX(2−10keV ) < 1044 erg s−1 (XSEY hereafter), and 531 have LX(2−10keV ) > 1044 erg s−1 (XQSO hereafter). To compare starbust detectability (i.e., completeness) between the predominantly lower redshift XSEY and

Fig. 12.— Star formation rates versus column density in logarithmic scale. Downward arrows represent the 90% upper limits to NiHntr, whenever the 90% lower limit encompassed zero. Red circles, green squares and blue triangles denote broad-line AGN, narrow emission line and absorption line galaxies respectively.
the XQSOs, from the observed SEDs of sources that originally required at least 5% starburst contribution to their LBol (the “SF” sample hereafter), we ﬁrst artiﬁcially remove the appropriately normalized ﬂuxes of the best-ﬁt starburst template from the observed photometric bands. The resulting ”stripped” sample can then be treated identically in our detectability experiment as the ”naked” sample - those sources whose observed SEDs were originally ﬁtted with a pure AGN template. In this way, we can then add back in a starburst component at various levels to the observed SEDs, and reﬁt the simulated SEDs, to test the sensitivity of our method. 384 of 531 XQSOs are naked, and 176 of 456 XSEY are naked. Combining the “stripped” and the “naked” samples yields 987 pure AGN SEDs with no starburst contribution.
In the next step, for each of these 987 objects we ﬁt a pure AGN template to estimate of its bolometric ﬂux. Then, using each one of our 4 starburst templates, we compute an additional starburst component representing a ﬁxed fraction of the total bolometric ﬂux. The additional component ranges from 0% to 50% in intervals of 5%. We then interpolate the new starburst component at the frequency points of original SED, thus obtaining starburst ﬂuxes. Finally we add these simulated starburst ﬂuxes to the ”striped/naked” ﬂuxes of the source. From each object/template pair, we thus create 11 new simulated SEDs, yielding 987 × 4 × 11 = 43428 simulated sources. We then run again our SED ﬁtting code on all these simulated sources to constrain the starburst contribution. Of the XQSOs simulated with ≥ 5% SB, our best-ﬁt SED that includes SB = 5% is CQ=39%. By contrast, of all the XSEY simulated with ≥ 5% SB, our best-ﬁt that includes SB = 5% is CS=52% Thus, our completeness for XQSOs relative to XSEY is RC = CQ/CS=39/52=0.75. We can compensate crudely for this relative incompleteness by dividing our actual sample fraction of XQSO with SB ≥ 5% with RC, F SBQ/RC which yields 26%/0.75=35% of XQSO. Since that fraction is still signiﬁcantly lower than the actual fraction of XSEY with SB ≥ 5%, F SBS = 58%, we can

ChaMP Optical Spectroscopy

Fig. 13.— Percentage of starburst contribution to the bolometric luminosity versus column density in logarithmic scale. Downward arrows represent the 90% upper limits to NiHntr, whenever the 90% lower limit encompassed zero. Red circles, green squares and blue triangles denote broad-line AGN, narrow emission line and absorption line galaxies respectively.
claim that the star formation in XQSOs appears significantly weaker from what we would expect if starburst luminosity increased with accretion luminosity.
8. THE RELATIONSHIP BETWEEN ABSORPTION AND STAR FORMATION
In previous studies a connection has been made between X-ray absorption and star formation in AGN (e.g. Page et al. 2004), though this remains controversial (e.g. Lutz et al. 2010; Shao et al. 2010). To test for whether any correlation exists between NiHntr and star formation in our sample, we must use statistical analysis that can account for upper limits. We examine log NiHntr vs. log SFR and also vs. starburst fraction FS for the 524 of our 1242 objects for which FS> 5%. When the 90% lower limit to NiHntr from our X-ray spectral ﬁts is consistent with zero, we assign its 90% upper limit value as the upper limit for the correlation tests. We test for significance using the Cox Proportional Hazard, Kendall’s τ and Spearman’s ρ tests, as implemented in the ASURV (Survival Analysis for Astronomy) package (Lavalley et al. 1992). Between log NiHntr and the log SFR, we ﬁnd that the correlation is signiﬁcant (i.e., the null hypothesis of no correlation is rejected) at the 0.1% level in the Spearman’s ρ test. However, the Cox and Kendall’s τ test show P 19% and 13%, respectively, which indicates no signiﬁcant correlation. The lack of a signiﬁcant relation with star formation rate SFR is perhaps not so surprising; since SFR is essentially a luminosity, a strong distance eﬀect is encoded therein, which may mask an intrinsic physical relationship. When we test the correlation between log NiHntrand the star formation fraction FS (Figures 12 and 13), we ﬁnd P ≤ 0.1 for all 3 tests; the correlation is highly signiﬁcant. The slope of the best-ﬁt linear regression, however, is rather ﬂat: FS = 0.0122±0.0016 logNiHntr+ 19.84 with a standard deviation of 0.724 from the Buckley-James algorithm. There are a number of reasons why this treatment may not be ideal. First, we lump all source types together

(BLAGN, NELG, ALG) which may be inappropriate to the actual physics in question. Second, there is no a priori reason why we should consider the logarithm of NiHntr vs. FS, except that the distribution is more regular. Also, we exclude objects with FS< 5%, which could be treated similarly as upper limits. However, the number of limits would thereby greatly exceed the number of detections of a starburst component. These would be all piled up at FS=0, and would strongly bias our regression ﬁts. Perhaps more importantly, we note that our X-ray spectral ﬁts do not include (nor in general have suﬃcient S/N to warrant) an emission model component appropriate to strong starburst activity. X-ray emission from star formation regions would generally be rather soft due to thermal emission, making the soft X-ray absorption features even more diﬃcult to detect.
A more credible test may be to examine only the X-ray Seyferts, the subsample of objects with 1042 < L2−10 keV < 1044 erg s−1. Although the obscuration of some AGN is a consequence simply of the geometry of the surrounding material and our line of sight to the nucleus (Antonucci 1993), the prevalence of X-ray absorption in star-forming AGN could imply an alternative source of absorbing material, perhaps related to the gas that is fuelling the star formation or to outﬂowing material from the early stages of AGN feedback. In order to test this hypothesis we restrict our sample to the 430 X-ray Seyferts among which 273 objects have only upper limits to NiHntr. First we perform two-sample tests for a diﬀerence in log NiHntr between the 263 objects with FS≥5% (167 NiHntrlimits), and the 167 with FS<5% (106 NiHntr limits). The mean log NiHntr values are indistinguishable for the two sub-samples at 21.0±0.1, and their distributions using Wilcoxon and LogRank tests are also indistinguishable (P > 88%). We also searched for correlations between star formation and absorption amongst only those 263 X-ray Seyferts with FS¿5%, to avoid being dominated entirely by FS non-detections. Among this subsample, there are 96 detections of NiHntr, but we ﬁnd no evidence for a signiﬁcant correlation either between log NiHntr and log SFR, or between log NiHntr and FS.
9. X-RAY BRIGHT OPTICALLY INACTIVE GALAXIES (XBONG)
Following the deﬁnition of an XBONG, ALGs with LX(2−10 keV )>1.5×1042 erg s−1 (Comastri et al. 2002), we have identiﬁed a total of 81 XBONGs within our spectroscopic sample. However, as can be seen from Figure 7 a large number of ALGs appear to occupy the same parameter space as BLAGN in the fX / fr plane. This might indicate the presence of AGN activity that has been missed due to the shallow optical spectroscopy. In order to address this issue we further restrict our sample by looking for XBONGs in the K-band selected ALG sample. K-band detections come from UKIDSS DR4. We have identiﬁed a population of 25 XBONG within our K-band selected sample in the redshift range 0.035<z<0.948, 20% of the total K-band ALG selected sample. Eleven of the sources appear to be associated with AGN as their X-ray spectrum is described by a steep photon index that ranges between 1.4<Γ<1.9. We ﬁnd evidence for signiﬁcant X-ray absorbing columns in 7 of our sources - those that have NH >1022. Figure 14

14 Trichas et al.

Fig. 14.— Rest-frame 2-10 keV logarithmic X-ray luminosity versus logarithmic K-band luminosity for all ChaMP spectroscopically identiﬁed absorption line galaxies with K-band detections. Red stars is the population of 25 XBONGs, ALGs with LX(2−10 keV )>1.5×1042 erg s−1. Open triangles are radio loud sources. Open squares are sources with log NiHntr > 22.
shows the X-ray vs. K-band luminosity of all the K-band detected ALG sources within the ChaMP spectroscopic sample. Four possible explanations have been proposed for the nature of these objects (Green et al. 2004): a
buried AGN (Comastri et al. 2002), a low luminosity AGN (Severgnini et al. 2003), a BL Lac object (Yuan & Narayan 2004) and galactic scale obscuration (Rigby et al. 2006; Civano et al. 2007).
Green et al. (2004) deﬁned a buried AGN as an object that has either no, or only narrow emission lines in its optical spectrum, strong evidence for NH >1022 in the rest frame and LX(2−10 keV )>1043 erg s−1 without absorption correction. Among our 22 objects there are 4 objects that fulﬁll all of the above criteria and are probably Type-2 QSOs. Our SED ﬁtting suggests that only one of the objects is consistent with an elliptical like broadband spectrum. The remaining three are all ﬁtted with a combination of a Type-2 Seyfert and a starburst template consistent with a buried AGN. In two of the latter, the starburst contribution dominates the bolometric emission at the 95% level. There are additional 6 XBONGs in our sample that have LX(2−10 keV )>1043 erg s−1, no signs of broad optical emission lines in their spectra and soft X-ray spectra which are most likely buried Type2 AGN. Our SED ﬁtting has identiﬁed half of them as ellipticals, 2 as Type-1 QSOs with some < 35% star formation contribution and one Type-2 Seyfert with 10% star formation contribution. There are only 2 XBONGs in our sample that exhibit strong radio emission. Both of them have LX(2−10 keV )>1042 with NH <1021 and are ﬁtted with an elliptical template with no evidence of star formation. These can both be BL Lac candidates but the lack of high S/N optical spectra that would allow us to measure the 4000 ˚A break does not permit us to verify their BL Lac status. All the above suggest that the XBONGs found in our sample comprise a mixed bag of objects primarily including normal elliptical galaxies, Type-1 AGN and most importantly Type-2 QSOs that need further investigation.

10. HIGH-REDSHIFT X-RAY QSOS
There are a total of 78 z > 3 X-ray objects in our spectroscopic catalogue, 70 from SDSS and 8 from our own follow-up campaigns. The latter 8 spectra are presented in Figure 15. 76 are broad line AGN, one narrow emission line galaxy at z = 3.417 and one absorption line galaxy at z = 3.32. There are also two X-ray QSOs at z > 5 whose SDSS spectra are shown in Figure 16. All of our high-z sources have 0.5 − 2 keV detections and 76 have also 2 − 8 keV band detections. 7 sources have UV, all of them have ugriz, 18 have JHK, 22 have WISE and 13 have radio detections. According to our SED ﬁtting method, 76 are ﬁtted with an Type-1 AGN template that in 22 cases requires a signiﬁcant starburst contribution that ranges between 10% and 70% of the bolometric luminosity. The two non-broad line high redshift objects are both ﬁtted with a starburst template, suggesting that these might be high-z Type-2 AGN shrouded in a powerful starburst. The high-z sources in our sample have a relatively high number of detected counts, 31 is the median value, with respect to the depth of the X-ray observations. There are 15 sources that have more than 100 counts. In this count regime, we can assume that the extracted spectral ﬁt results are reliable enough to be used for column density estimations. 45 of our sources have NH >22 suggesting that these sources are obscured.
Our sample represents the largest spectroscopically selected sample of z>3 X-ray sources and the second largest compared to samples with available photometric redshifts (Civano et al. 2011). Our sample has almost doubled the number of spectroscopically identiﬁed z>5 Xray QSOs by adding two more sources (Figure 16) to the three previously known at z=5.19 (Barger et al. 2005), z=5.3 (Civano et al. 2011) and z=5.4 (Steﬀen et al. 2004). Here we report the identiﬁcation of the highest redshift X-ray QSO with optical spectroscopy ever found at z=5.4135 (Figure 16).
11. CONCLUSIONS
We present the complete optical spectroscopic follow-up of ChaMP sources. We utilize a large suite of multi-slit and multi-ﬁber instruments on FLWO, SAAO, WIYN, CTIO, KPNO, MMT, Magellan and Gemini to identify both bright and faint serendipitous X-ray sources as well as archival SDSS optical spectra. These observations resulted in a total of 1569 spectroscopic identiﬁcations of X-ray sources. Among the latter, there are 1242 extragalactic sources, half of which are broad-line QSOs. For these sources we have collected an extensive library of ancillary multi-wavelength data including X-ray, UV, optical, near-IR, mid-IR and radio data from our own photometric follow-ups as well as various public catalogues including GALEX, 2MASS, UKIDSS, WISE, NVSS and FIRST. Multi-wavelength photometry in combination with available optical spectroscopy has allowed us to distinguish among diﬀerent populations, study the X-ray-to-radio SEDs in order to estimate luminosities and assess the level of AGN and star formation contribution, estimate column densities via X-ray spectral ﬁtting and estimate black hole masses and star formation rates.

ChaMP Optical Spectroscopy

Fig. 15.— ChaMP z > 3 objects obtained using CTIO, FAST, WIYN and Magellan telescopes. Spectra are not ﬂux calibrated. CHANDRAOBSID, SPECOBJID, REDSHIFT and CLASS are given in the top of each plot.

Fig. 16.— SDSS optical spectra of the two highest redshift objects found in our sample. They both are broad-line X-ray QSOs at z > 5.

Based on our observations, although X-ray Seyferts

L2−10 keV ∼1044 erg s−1 at 1<z<3 are at the peak of their accretion rates. Therefore, the higher fraction of

appear to be hosted in galaxies with powerful star formation events, when accretion onto the SMBH reaches its peak, as indicated from both hard X-ray luminosity

X-ray Seyferts with star formation compared to the X-ray QSOs with star formation, imply that the most prodigious episodes of star formation are common in

and AGN contribution to the bolometric luminosity, the host galaxies of 1< z < 3 AGN, but avoid powerful

star formation is quenched, resulting in only a small AGN in which accretion is at its peak. This systematic

percentage of X-ray QSOs showing prevalent starburst separation of the peak periods of star formation and

events. According to Ebrero et al. (2009), objects with accretion implies a palpable interaction between the

16 Trichas et al.

two processes, and provides a powerful discriminator for the form of AGN feedback which is responsible for terminating star formation in the host galaxy.
In “QSO mode” feedback, a luminous AGN generates a powerful wind which terminates star formation by driving the interstellar medium from the surrounding host galaxy. In “radio-mode” feedback, star formation is suppressed because collimated jets of relativistic particles emitted by a radiatively-ineﬃcient AGN prevent gas in the surrounding hot halo from cooling, thereby starving the galaxy of cool gas from which to form stars. “Radio-mode” feedback is commonly invoked in semi-analytical models to limit galaxy masses and luminosities (Croton et al. 2006). In these models, black holes grow through luminous accretion episodes and black hole mergers. The correlation between black hole and bulge mass comes from assuming that a ﬁxed fraction of the gas is accreted by the nucleus during each star forming episode that results from a galaxy merger or disc instability, and hence star formation and accretion rate should be correlated over the full range of luminosity.
Our observations are therefore globally inconsistent with models such as Croton et al. (2006) in which AGN inﬂuence their host galaxies only through radio mode feedback. In contrast, models of galaxy formation in which quasar-mode feedback is responsible for terminating the star formation (Hopkins et al. 2006) predict that the AGN luminosity peaks later than the star formation rate, and thus are consistent with our observations that show that star formation not only occurs less often but is also weaker in X-ray QSOs compared to X-ray Seyferts. These models also predict that residual star formation, at the level of a few tens of per cent of the peak, will continue during the period in which the AGN luminosity is at its maximum, consistent with our results which show that some of the X-ray QSOs are still forming stars. Finally, while the observations presented

here provide strong evidence for the violent quenching of star formation as AGN reach peak luminosity, they do not rule out radio-mode feedback as the agent by which galaxy growth is subsequently suppressed. Further observations and/or studies with far-infrared/submm data are essential in order to verify our last ﬁnding and to reduce any ambiguity based on template ﬁtting results.
Our ﬁndings regarding the relationship between Xray column density and starburst contribution and star formation rate further support the prediction that AGN obscuration is a consequence simply of the geometry of the surrounding material and our line of sight to the nucleus (Antonucci 1993) rather than a common material feeding both mechanisms. In this work, we have shown that obscuration does not seem to be associated to star formation either in the general population or the population of star forming X-ray AGNs.
Finally we report the identiﬁcation of 25 K-band selected XBONGs. Among the latter, 10 appear to be Type-2 QSOs with an AGN buried in active starburst events. We have also identiﬁed a signiﬁcant population (78) of z > 3 objects. There are two non-broad line objects in this sample that are quite probably high-z Type-2 AGN. 45 of the high-z objects in our sample appear to be highly obscured. We ﬁnally report here the identiﬁcation of two z > 5 X-ray QSOs who are among the highest spectroscopic redshift X-ray selected QSOs ever observed. Acknowledgements: The authors would like to thank Francesca Civano and Hagai Netzer for their useful comments. Support for this work was provided by the National Aeronautics and Space Administration through Chandra Award Numbers AR9-0020X and AR1-12016X, issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of the National Aeronautics Space Administration under contract NAS8-03060.

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