Radio galaxy host properties spanning three dex in radio luminosity

Radio galaxy host properties spanning three dex in radio luminosity

New Astronomy Reviews 47 (2003) 187–191 www.elsevier.com / locate / newastrev Radio galaxy host properties spanning three dex in radio luminosity Chr...

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New Astronomy Reviews 47 (2003) 187–191 www.elsevier.com / locate / newastrev

Radio galaxy host properties spanning three dex in radio luminosity Chris J. Willott a , *, Ross J. McLure b , Matt J. Jarvis d , Steve Rawlings c , Gary J. Hill e , Ewan Mitchell c , James S. Dunlop b a

Herzberg Institute of Astrophysics, National Research Council, 5071 West Saanich Road, Victoria, B.C. V9 E 2 E7, Canada b IfA, Edinburgh, UK c Oxford Astrophysics, Keble Road, Oxford, OX1 3 RH, UK d Sterrewacht Leiden, Postbus 9513, 2300 RA Leiden, The Netherlands e McDonald Observatory, University of Texas at Austin, Austin, TX, USA

Abstract We describe a major study of radio source host galaxies being carried out with the HST and ground-based facilities. Our sample is selected from 4 complete samples with different radio flux-density limits, giving a range of three orders of magnitude in radio luminosity at a fixed epoch (z 5 0.5). High-resolution HST WFPC2 imaging shows that all 44 radio galaxies have flux distributions well fit by an r 1 / 4 law and lying on the Kormendy relation defined by lower redshift ellipticals with a shift in the zero-point to account for passive evolution. Spectroscopic follow-up enables stellar velocity dispersions to be determined and black hole masses estimated. The clustering environments of the radio galaxies are being probed via multi-colour wide-field imaging. Together, these data allow a detailed investigation of how factors such as clustering environment, close interactions and star-formation history affect the accretion rate, ionizing luminosity and jet production from supermassive black holes.  2003 Elsevier B.V. All rights reserved. Keywords: Galaxies: active; Galaxies: fundamental parameters; Radio continuum: galaxies

1. Introduction The tight correlation exhibited between galaxy bulge masses, their stellar velocity dispersions and their central black holes (Magorrian et al., 1998; Ferrarese and Merritt, 2000; Gebhardt et al., 2000) provides compelling evidence that galaxy formation and evolution at high redshift was strongly dependent upon AGN (accretion) activity. This could have come about by quasar outflows limiting black hole masses, dependent upon the depth of the potential *Corresponding author. Fax: 11250-363-0045. E-mail address: [email protected] (C.J. Willott).

wells of dark matter halos (Silk and Rees, 1998). Subsequent merging events expected in the hierarchical galaxy formation scenario would need to continue some level of gas accretion to maintain these relationships. The host galaxies of powerful 3C radio sources at redshift z | 1 have luminosities and surface brightness profiles consistent with giant elliptical galaxies (Best et al., 1997, 1998). At low redshifts (z , 0.3) 3C radio galaxies are also massive ellipticals with scalelengths similar to those at z | 1 (Owen and Laing, 1989; McLure et al., 1999). The tight relation between the K-band magnitudes and redshifts of 3C radio galaxies (Lilly and Longair, 1984) is consistent

1387-6473 / 03 / $ – see front matter  2003 Elsevier B.V. All rights reserved. doi:10.1016 / S1387-6473(03)00023-X

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with a scenario in which the radio galaxies have a small spread in masses, formed at high redshifts and have evolved passively since at least z | 1. These facts have been used to suggest that there is very little evolution in 3C radio galaxies from z | 1 to the present day. These results agree with a picture where the most massive galaxies at any epoch have the highest radio luminosities. The lower radio luminosities at lower redshifts simply reflect a decrease in the available fuel for accretion due to virialization of galaxies and clusters (Rees, 1990) and not differences in the host galaxies or black hole masses. Therefore, studies of the 3C sample alone (which contains the most radio-luminous sources at any epoch) cannot constrain the physical reasons for different radio luminosities at a fixed epoch. The only way of determining this is to observe radio galaxies over a wide range of radio luminosities at a constant redshift.

2. HST observations of a complete sample of z 5 0.5 radio galaxies To get a large spread in luminosity at a fixed redshift one needs several different samples selected at successively lower flux-density limits. We used 44 orbits with the Hubble Space Telescope in Cycle 10

to obtain WFPC2 imaging in the F785LP filter of a large sample of radio galaxies selected from four complete samples selected at low radio frequencies (178 or 151 MHz) with differing flux limits. The samples used are 3CRR (Laing et al., 1983), 6CE (Rawlings et al., 2001), 7CRS (Willott et al., 2003; Lacy et al., 1999) and TOOT (Hill and Rawlings, 2003). These radio galaxies all lie within the redshift range 0.4 , z , 0.6 and span a range of a thousand in radio luminosity. This redshift range was chosen because by z 5 0.5 there is a large observable volume and the evolution in the radio luminosity function means that the radio luminosities of sources from these four samples at z 5 0.5 range from below the FR I / FR II boundary up to some of the most luminous sources known. Additional factors in the redshift choice are that HST optical filters can probe ˚ radiation and reach emission line-free, l . 4000 A the required sensitivity in reasonably short integrations (1 orbit per target). The aim of our HST programme is to examine how radio luminosity is dependent upon properties of the host galaxies such as morphologies, luminosities and size scales. The HST images have been reduced and 2-dimensional modeling as in McLure et al. (2000) has given accurate surface brightness distributions and scalelengths for our sample of 44 radio galaxies (e.g. Fig. 1). Full details of the reduction, analysis and results obtained from the HST imaging is presented in

Fig. 1. Central region (13 3 13 arcsec) of the HST WFPC2 F785LP image of the z 5 0.46 radio galaxy TOOT130913359 (left), the best-fitting model to the galaxy flux distribution (middle) and the residual after subtraction of this model (right).

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McLure et al. (2003). Here we briefly review some of our findings. • All the galaxies are well fit by an elliptical r 1 / 4 law. None of the galaxies are fit better by an exponential disk. • The z 5 0.5 radio galaxies follow the Kormendy relation between surface brightness and scalelength defined by low-redshift (z , 0.1) radio galaxies (Fig. 2) and inactive ellipticals (Kormendy, 1977). There is an offset in the zero-point of the Kormendy relation at z 5 0.5 of 0.46 magnitudes which is fully consistent with passive evolution of stellar populations which were formed at high redshifts. There is no difference in the scatter about the best fit Kormendy relation compared to radio galaxies at z , 0.1 (Bettoni et al., 2001). • For the 3CRR, 6CE and 7CRS samples there is a

Fig. 2. The Kormendy relation between surface brightness and effective radius for the z 5 0.5 radio galaxies from the 3CRR, 6CE, 7CRS and TOOT samples. The solid line is the best fit to these data. The low-z radio galaxies from Bettoni et al. (2001) are shown as dots and fit with the dashed line. The offset between these lines of 0.46 mags is consistent with passive evolution of a stellar population formed at high redshift.

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correlation between host galaxy absolute magnitude and radio luminosity. However, at the faintest radio luminosities (TOOT) the galaxies tend to be brighter and somewhat larger than those in 7CRS. This effect can also be seen in Fig. 2 where the 3CRR and 6CE galaxies are scattered about the z 5 0.5 Kormendy relation but the 7CRS galaxies are mostly on the faint side of the line and the TOOT galaxies on the bright side. Further discussion can be found in McLure et al. (2003).

3. Ground-based follow-up observations In addition to the high spatial resolution HST imaging, we are observing sources from this sample with ground-based radio and optical telescopes to determine further information. Combining all these different datasets will allow us to build up a detailed picture of the relationships between the properties of the radio emission and the host galaxies and larger scale environments. We have observed all the sources from the 6CE, 7CRS and TOOT samples with the Very Large Array (3CRR sources have data in the VLA archive). Most sources have extensive multi-frequency and multiconfiguration data with which to probe their structures on all scales. These data allow sources to be classified into types FR I and FR II (the traditional dividing luminosity between these groups is around the luminosity of the z 5 0.5 TOOT galaxies). The VLA data also allow asymmetries in structure and spectral index to probe environmental asymmetries. The 1.4 GHz data is obtained in wide-field mode allowing an investigation of other AGN and starbursts in companion galaxies and clusters. Full details of the radio observations will be presented in Mitchell et al. (2003). From the HST imaging analysis one can use the determined galaxy bulge luminosities to estimate the masses of the supermassive black holes in these galaxies assuming that the local correlations extend to higher redshifts, e.g. Magorrian et al. (1998), Merritt and Ferrarese (2001). Modeling the evolution of radio sources shows that the radio luminosity Lrad is roughly proportional to the power in the jets Q,

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which in turn has a linear dependence upon the ionizing continuum luminosity Lion , as evidenced by radio–optical correlations (Willott et al., 1999). Lion (and therefore Q and Lrad ) is largely determined by two main factors. The first is the black hole mass MBH , since assuming the Eddington limit cannot be exceeded the maximum luminosity attainable is directly proportional to MBH . The second parameter is the accretion rate relative to the Eddington limit (Lion /LEdd ). The size of this parameter most likely reflects the amount of fuel available in the host galaxy for accretion. By estimating MBH for sources over a large range of luminosity, we can determine whether the primary dependence of radio luminosity is on MBH or Lion /LEdd . It has been shown that, at low redshift, stellar velocity dispersions provide more accurate estimates of the black hole mass than bulge luminosities [MBH ~ s 4c , Ferrarese and Merritt (2000), Gebhardt et al. (2000)]. Evolution in stellar luminosity between z 5 0 and z 5 0.5 provides a further source of uncertainty when using the bulge luminosities to estimate MBH at z 5 0.5. Therefore we have been pursuing a follow-up program of medium resolution spectroscopy of the radio galaxies with the ISIS spectrograph at the William Herschel Telescope with the primary goal of determining their velocity dispersions. Despite many nights lost to bad weather, we have spectra for almost all the 0.4 , z , 0.5 radio galaxies. We have developed a routine for determining velocity dispersions from the ISIS spectra by fitting to broadened stellar templates. An example of the fitting process is shown in Fig. 3. The best fitting

stellar templates are mostly of spectral type K0 or K1. The acquisition of velocity dispersions allows us to plot the Fundamental Plane, rather than just the Kormendy relation, enabling the determination of stellar mass-to-light ratios by giving a better estimate of the galaxy mass than can be achieved from the Kormendy relation alone. These spectra are also useful for investigating the stellar populations in these radio galaxies, since they ˚ break as well as the G-band and cover the 4000 A Mg I absorption features. Initial results from spectral analysis indicate that the optical spectra of almost all the radio galaxies are dominated by old, evolved stellar populations in line with the amount of passive evolution inferred from the Kormendy relation. Another finding is an anti-correlation between the ˚ break and the emission line strength of the 4000 A luminosity indicative of an extra continuum com˚ which correlates with the ponent at l , 4000 A power of the AGN. This vindicates our HST filter selection which was designed to be redward of the ˚ break and minimize emission line contami4000 A nation. Wide-field optical imaging of the sample is being carried out with the Wide-Field Camera on the Isaac Newton Telescope. Using observations in the gri bands we are able to eliminate foreground and background contamination in order to search for groups and clusters associated with the radio galaxies. The principal aim of this study is to determine if there is a correlation between the clustering environment and radio luminosity. It has been proposed that radio sources could be triggered by cluster–cluster mergers (Roettiger et al., 1999), so the 3D structures

Fig. 3. Example of the velocity dispersion fitting from WHT ISIS spectra. The upper spectrum is that of the galaxy overlaid with best fit broadened stellar template. Below is shown the residual from the fit and the 62s noise level. Greyed out regions are dominated by night sky or object emission lines or atmospheric absorption and excluded from the fitting.

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of the clusters are important. Clusters discovered in the imaging are being followed up with multi-object spectroscopy to determine cluster velocity dispersions and hence masses. Combining the data from these different facilities will allow a detailed investigation of how factors such as clustering environment, close interactions and star-formation history affect the accretion rate, ionizing luminosity and jet production from supermassive black holes.

References ¨ Best, P.N., Longair, M.S., Rottgering, H.J.A., 1997. MNRAS 292, 758. ¨ Best, P.N., Longair, M.S., Rottgering, H.J.A., 1998. MNRAS 295, 549. Bettoni, D., Falomo, R., Fasano, G., Govoni, F., Salvo, M., Scarpa, R., 2001. A&A 380, 471. Ferrarese, L., Merritt, D., 2000. ApJ 539, L9. Gebhardt, K. et al., 2000. ApJ 539, 13.

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Hill, G.J., Rawlings, S., 2003. NewAR 47, this issue. Kormendy, J., 1977. ApJ 218, 333. Lacy, M., Rawlings, S., Hill, G.J., Bunker, A.J., Ridgway, S.E., Stern, D., 1999. MNRAS 308, 1096. Laing, R.A., Riley, J.M., Longair, M.S., 1983. MNRAS 204, 151. Lilly, S.J., Longair, M.S., 1984. MNRAS 211, 833. Magorrian, J. et al., 1998. AJ 115, 2285. McLure, R.J., Kukula, M.J., Dunlop, J.S., Baum, S.A., O’Dea, C.P., Hughes, D.H., 1999. MNRAS 308, 377. McLure, R.J., Dunlop, J.S., Kukula, M.J., 2000. MNRAS 318, 693. McLure, R.J., Willott, C.J., Jarvis, M.J., Rawlings, S., Hill, G.J., Mitchell, E.K., Dunlop, J.S., 2003. MNRAS, submitted Merritt, D., Ferrarese, L., 2001. MNRAS 320, L30. Mitchell, E. et al., in preparation Owen, F.N., Laing, R.A., 1989. MNRAS 238, 357. Rawlings, S., Eales, S., Lacy, M., 2001. MNRAS 322, 523. Rees, M.J., 1990. Science 247, 817. Roettiger, K., Burns, J.O., Stone, J.M., 1999. ApJ 518, 603. Silk, J., Rees, M.J., 1998. A&A 331, L4. Willott, C.J., Rawlings, S., Blundell, K.M., Lacy, M., 1999. MNRAS 309, 1017. Willott, C.J., Rawlings, S., Jarvis, M.J., Blundell, K.M., 2003. MNRAS 339, 173.