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Star formation in 3CR radio galaxies and quasars at z<1

Using the Herschel Space Observatory we have observed a representative sample of 87 powerful 3CR sources at redshift z<1. The far-infrared (FIR, 70-500 micron) photometry is combined with mid-infrared (MIR) photometry from the Wide-Field Infrared Survey Explorer (WISE) and catalogued data to analyse the complete spectral energy distributions (SEDs) of each object from optical to radio wavelength. To disentangle the contributions of different components, the SEDs are fitted with a set of templates to derive the luminosities of host galaxy starlight, dust torus emission powered by active galactic nuclei (AGN) and cool dust heated by stars. The level of emission from relativistic jets is also estimated, in order to isolate the thermal host galaxy contribution. The new data are in line with the orientation-based unification of high-excitation radio-loud AGN, in that the dust torus becomes optically thin longwards of 30 micron. The low excitation radio galaxies and the MIR weak sources represent MIR- and FIR-faint AGN population different from the high-excitation MIR-bright objects; it remains an open question whether they are at a later evolutionary state or an intrinsically different population. The derived luminosities for host starlight and dust heated by star formation are converted to stellar masses and star formation rates (SFR). The host-normalized SFR of the bulk of the 3CR sources is low when compared to other galaxy populations at the same epoch. Estimates of the dust mass yield a 1--100 times lower dust/stellar mass ratio than for the Milky Way, indicating that these 3CR hosts have very low levels of interstellar matter explaining the low level of star formation. Less than 10% of the 3CR sources show levels of star formation above those of the main sequence of star forming galaxies.


Introduction
In the current paradigm of AGN evolution, galaxy collisions and mergers lead to the genesis of powerful radio sources (Heckman et al. 1986). Based on FIR studies with the Infrared Astronomical Satellite (IRAS) in the 1980s, the Palomar-Green (PG) quasars appear to be preceded or accompanied by violent dust-enshrouded starburst activity (Sanders et al. 1988(Sanders et al. , 1989Rowan-Robinson 1995). Refined Infrared Space Observatory (ISO) photometry in the 1990s indicates a potential evolution from FIR-bright to FIR-faint AGN states (see Haas et al. 2003).
Searching for the unbeamed counterparts of the quasar population in the medium-redshift (0.5 < z < 1) sample from the Revised Third Cambridge Catalogue of Radio Sources (3CR), Barthel (1989Barthel ( , 1994 proposed the orientation-based unification scheme of quasars and high-excitation radio galaxies (HERGs). Consensus is growing that this scheme is basically valid for sources with high radio power (P 178 MHz > 10 28 W Hz −1 ).
The sample is subdivided by the classification criteria based on radio and optical properties. In compact steep spectrum (CSS) sources the radio emission is restricted to regions of less than 20kpc. Fanaroff-Riley Class I (FRI) sources show edgedimmed radio lobes, while in FRII sources the lobes are more bright at the edge. The type-1 sources have optical bright continua and broad emission lines and are called Broad-Line Radio Galaxies (BLRG) at low luminosity. The high luminosity Flat-Spectrum-Quasars (FSQs) show flat radio spectra in F ν in contrast to Steep-Spectrum-Quasars (SSQs) with the dividing spectral index α = 0.5 measured at a few GHz. The 3CR radio sources can be sub-divided into many different classes (e.g. quasars and radiogalaxies), and it has early been questioned by demographic arguments that every edge-brightened double-lobe FR II radio galaxy is a misaligned hidden quasar. At low-redshift (z < 0.5) where the radio power of the 3CR sample reaches down to P 178 MHz ≈ 10 26 W Hz −1 , narrow-line radio galaxies outnumber the quasars and broad-line radio galaxies (BLRGs), mainly due to the contribution of low-excitation radio galaxies (LERGs) (Laing et al. 1983;Singal 1993).
Based on mid-infrared (MIR) observations, with VISIR, ISOCAM (van der Wolk et al. 2010; Siebenmorgen et al. 2004) and Spitzer (Ogle et al. 2006), the LERGs and a few HERGs are MIRweak, indicating that they either do not possess high accretion power comparable to the MIRstrong HERGs and quasars/BLRGs or that they are more strongly extincted. FIR observations may be able to discriminate between the two scenarios, but in view of the expected faintness such observations have not been performed so far; only a few dozen bright HERGs and quasars/BLRGs, have been detected in the FIR with ISO 1 as compiled by Haas et al. (2004).
We here present sensitive Herschel PACS/SPIRE 70-500 µm photometry of the representative 3CR sample at low and medium-redshift. The FIR properties of this 3CR sample were already measured with the previous IR satellites (IRAS: Heckman et al. 1992Heckman et al. , 1994Hes et al. 1995;Hoekstra et al. 1997;ISO: van Bemmel et al. 2000;Fanti et al. 2000;Polletta et al. 2000;Meisenheimer et al. 2001;Andreani et al. 2002;Haas et al. 2004 and the Spitzer Space Telescope: Haas et al. 2005;Ogle et al. 2006;Cleary et al. 2007). The new FIR observations with Herschel benefit from the higher spatial resolution and sensitivity of the instruments.
We here analyse the full optical to radio SEDs, also combined with WISE 3-22 µm photometry. The purpose is to explore dust emission in the FIR for the most powerful radio-loud AGN, to provide constraints on the star forming activity and to investigate the evolutionary status of their host galaxies.

Sample
2.1. Medium-redshift sample 0.5 < z < 1 The sample properties for 3CR-sources at medium-redshifts, which were observed by Herschel in the two open time programs from the OT1 mhaas 2 and OT1 jstevens 1 proposals, are given in Table 1. From the 48 sources at 0.5 < z < 1 in the 3CR catalogue a representative subset of 39 was observed. The sources are selected to be brighter than 10 Jy at a frequency of 178 MHz (Laing et al. 1983). The sources that were not observed with Herschel don't bias the remaining subsample because their types are well represented. For the observed sources MIR photometry and/or spectroscopy from the Spitzer Space Telescope can be found in Ogle et al. 2006 andCleary et al. 2007. Sources in the 3CR catalogue but not observed by Spitzer are 2 FSQs (3C 345, 3C 454.3), 1 SSQ (3C 275.1), 4 HERGs (3C 34, 3C 217, 3C 247, 3C 277.2) and 1 LERG (3C 41). Two HERGs, 3C 175.1 and 3C 220.3, have been removed from the analysis. The former has insufficient ancillary data in the literature, and the latter acts as gravitational lens for a submillimetre galaxy at z = 2.2 (Haas et al. 2014).
2.2. Low-redshift sample z < 0.5 The 3CR sample properties at low-redshifts are shown in Table 2. It contains 48 sources at z < 0.5, of which 40 sources are included in the 3CR catalog (Laing et al. 1983). From the Spinrad et al. 1985 version of 3CR-sources, which extends to lower declinations, 4 additional sources belong to this sample. Mainly taken from the OT1 mhaas 2 proposal, the whole Herschel Science Archive (HSA) was searched for 3Csources and the complete Herschel-observed list was collected, which were observed also in the OT1 pogle01 1, OT1 rmushotz 1, OT1 lho 1 and OT1 dfarrah 1 proposals.
For all of them Spitzer MIR data are available. 23 sources were observed in the flux limited sample of Ogle et al. (2006) with S 178 MHz > 15Jy. Four remaining sources from the Ogle sample were planned but not observed with Herschel. The rest of 25 sources were selected from samples already seen with Spitzer by Haas et al. (2005) (also observed by the ISO satellite), by Cleary et al. (2007) and Hardcastle et al. (2009) (X-ray selection).

Data
For some objects of the medium-redshift sample a revision of the coordinates given in NED was necessary. We checked the positions given by Laing et al. (1983) and inspected WISE images. Positions from high resolution radio maps (Mullin et al. 2006;Haas et al. 2014) or positions seen with Chandra at 2-8keV were taken whenever available. For the low-redshift sample the coordinates were revised to match Willot's positions 2 . Core positions from high resolution radio maps from VLA observation by Gilbert et al. (2004) were taken whenever available. The revised coordinates are indicated by footnotes in Tables 1 and 2. Also the classifications for 3C 343 and 3C 455 from NED were altered from QSR to HERG based on classification given by Véron-Cetty and Véron (2010).

Herschel PACS and SPIRE
The data were downloaded from the Herschel Science Archive (HSA) within the framework of the Herschel Interactive Processing Environment (HIPE version 11.1.0, Ott 2010). For source extraction the tool SourceExtractor from Bertin and Arnouts (1996) was used and additional routines were developed in the Interactive Data Language (IDL) using the IDL Astronomy Library (Landsman 1993).

Observations
For the Photoconducter Array Camera and Spectrometer (PACS) (Poglitsch et al. 2010) the Scan-Map observational mode was chosen to observe the sources photometrically at 70/100/160 µm (blue/green/red). In a single-scan two filters (blue-red or green-red) were observed simultaneously. Often a cross-scan was done, with two consecutive single-scans with different scan directions. With the first scan in blue-red and the second in green-red combination the whole spectral range of PACS is covered, and the double scan in  the red filter was combined afterwards to reach a higher sensitivity. For some sources deeper imaging was achieved by the combination of multiple cross-scans. The Spectral and Photometric Imaging Receiver (SPIRE) (Griffin et al. 2010) observes in three bands at 250/350/500 µm (short/mid/long) at once. The Small-Scan-Map observational mode was chosen. For the medium-redshift sample the OBSIDs for the 98 PACS scans and 12 SPIRE scan-maps are shown in Table 1. The low-redshift sample was observed in 118 PACS scans and 23 SPIRE maps, OBSIDs are given in Table 2.

PACS-Reduction
The reduction of the PACS scan-maps was done in two steps, as bright sources have to be masked during the high-pass filtering (see Popesso et al. 2012). In the first step a preliminary image is generated, which is then used to determine the positions for masking with SourceExtractor (only detections with 9 pixels above a 3σ threshold are masked).
To minimize correlated noise and to get a good signal-to-noise ratio a pixel fraction of 0.6 and pixel sizes of 1.1 ′′ , 1.4 ′′ and 2.1 ′′ for the 70 µm, 100 µm and 160 µm band was chosen. Additionally the high-pass filter radius was set to 10, 15 and 20 readouts. The multiple scans were then combined with the mosaic task in HIPE.
The aperture corrected flux was determined for the pointlike sources in the frame. The target source was assumed to be that closest to and within 7 ′′ of the known source position (as listed in Tables 1 and 2). Images of size 2 ′ ×2 ′ are shown in Appendix A.2.
We derived the photometric uncertainty as follows: Every frame comes with a coverage map which was used to generate 500 random positions on the map, where the coverage is greater than 75% of its maximum. At these positions the HIPE routine annularSkyApertureP hotometry was used to perform aperture photometry with the background calculated in an annulus. Values for aperture and annulus radii (recommended for fluxes < 500mJy) given in Table 3 follow the Herschel Webinar for "PACS Point Source Photome-try" by Paladini 3 . The Gaussian dispersion of the 500 aperture-corrected fluxes was adopted as the 1σ uncertainty for each map (see also Leipski et al. 2013), and is listed in Tables 4 and 5. Where no sources could be detected a 3σ upper limit is given.

SPIRE-Reduction
For the photometry of the SPIRE observations we followed the steps of the "Recipe for SPIRE Photometry" 4 . The recommended algorithm for point source photometry is the time-line-fitter, sourceExtractorTimeline in HIPE. To determine the positions of sources in the SPIRE maps, we used the level2 products of the observations in the HSA. A source list was generated within HIPE by sourceExtractorSussextractor. The coordinates of these sources were then used to perform the fitting in the timeline data on the level1 products in the HSA. The nearest source within 30 ′′ to the coordinates given in Table 1 and 2 was identified as the 3CR target.
As for the uncertainty determination for the PACS observations, we used 500 randomly generated positions on the SPIRE maps, centered within 23 pixels of the center (138 ′′ /230 ′′ /322 ′′ for 250 µm/350 µm/500 µm). At these positions the photometry was carried out in the same manner as for the sources. The dispersion of the distribution again gave the 1σ uncertainty or 3σ upper limits, which are given in Tables 4 and 5. Images of size 4 ′ × 4 ′ are shown in Appendix A.2.

ISOCAM and Spitzer
We combined the SEDs in the MIR with data from the Infrared Space Observatory (Kessler et al. 1996) and Spitzer Space Telescope (Werner et al. 2004). We used photometric imaging observations with ISOCAM (Cesarsky et al. 1996) by Siebenmorgen et al. (2004) and spectra taken with the Infrared Spectrograph (IRS, Houck et al. 2004) from 5.2 to 38 µm, which were extracted by the CASSIS (Lebouteiller et al. 2011) and newly stitched and scaled by the IDEOS project (Spoon 2012). From previous analysis of the spectra (Ogle et al. 2006) flux densities at 7 and 15 µm restframe are included. Also photometric Spitzer data from the Multiband Imaging Photometer (MIPS, Rieke et al. 2004) at 24 µm are used (Shi et al. 2005;Cleary et al. 2007;Hardcastle et al. 2009;Fu and Stockton 2009;Dicken et al. 2010;Shang et al. 2011).

2MASS and WISE
We queried the wise allwise p3as psd data release from the Wide-field Infrared Survey Explorer (WISE, Wright et al. 2010) with the IDL query irsa cat routine around 4" of the estimated positions for the 3CR sources. The allwise query delivers point source photometry in the 4 WISE bands (W 1/W 2/W 3/W 4 at 3.4/4.6/12/22 µm) and also the point source photometry from the 2MASS catalogue for J, H and K filters at 1.235, 1.662 and 2.159 µm.
Among the low-redshift sample six sources are extended, therefore PSF photometry was replaced by extended apertures 5 for 3C 31, 3C 35, 3C 98, 3C 120, 3C 236 and 3C 390. 2MASS photometry for extended sources 6 was delivered by querying fp xsc catalogue with the IDL query irsa cat routine.

Visible wavelengths
A query on the SDSS catalogue (V/139/sdds9) with the IDL query vizier routine was performed.

Spectral Energy Distributions
Figures 1 to 7 show the rest-frame SEDs for the sample at 0.5 < z < 1, separated for the AGN types with flat and steep radio spectrum (FSQ and SSQ), HERGs with strong, medium and faint MIR emission, one LERG and the 2 sources omitted from the analysis. Figures 8 to 15 show the rest frame SEDs, separated for the FSQ and SSQ sources, BLRGs, HERGs and LERGs, that are seen at redshifts z < 0.5. The striking feature of the Herschel PACS/SPIRE data is that they nicely bridge the former gap between the radio and MIR SEDs. Also the WISE data points expand the previous ISOCAM and Spitzer IRS/MIPS24 SED coverage. A steep radio spectrum source is roughly constant in a νF ν diagram, while a flat radio source rises towards shorter wavelengths. For the host galaxy a synthetic stellar population from Bruzual and Charlot (2003) is used. The MIR emission is fitted with models for clumpy tori from Hönig and Kishimoto (2010). For the FIR a modified blackbody (Eq. 5) with emissivity index β = 1.5 is used.

SEDs at medium-redshifts
The quasar SEDs differ in their radio properties. 7 FSQs show a rise in their GHz spectra (e.g. 3C 207, Fig. 1), while the 7 SSQs have GHz spectra which are constant in νF ν (e.g. 3C 175, Fig. 2). A strong curvature is found in the MHz to GHz spectra of some CSS quasars and radio galaxies, (e.g. We group 3C 147 in the FSQs because of its SED rise between 90 GHz and 230 GHz (Steppe et al. 1995). The CSS 3C 455 and 3C 343 are sometimes classified as QSRs but they have neither a prominent 5 GHz core nor broad emission lines and therefore are treated here as HERGs (Figs. 3, 4).
The SSQs show a 1.5 dex thermal bump in MIR-FIR (Fig. 2). However, the FSQs show a 0.5 dex MIR-FIR emission bump above the extrapolated rising GHz spectrum. The FSQs most likely have a strong synchrotron contribution to their IR emission.
At optical wavelengths the quasars (FSQ and SSQ) show a strong power-law component rising towards shorter wavelengths. This component and the hot dust emission at about 1 µm outshine the host galaxy. To estimate the host contribution in the SEDs we include the disentangled host galaxy magnitude from HST imaging by Lehnert et al. (1999) to guide a fit for the host galaxy.
Similarly to the SSQs, the HERGs (except 3C 268.1, Fig 5) show a clear MIR-FIR emission component above the extrapolation of the radio spectrum to shorter wavelengths. However, there is a large diversity in the MIR. Figures 3 through 5 show the HERGs with strong, medium and weak MIR emission relative to the host galaxy.
While in both SSQs and HERGs the MIR SED is well determined, the detection rate in the FIR (at rest frame 60-100 µm) is 17 detections out of a sample of 28 sources. The sources with FIR detections are also bright in the MIR, and the SED declines longward of 40 µm. Examples are 3C 147 in Fig. 1, 3C 263 in Fig. 2, and 3C 226 in Fig. 3. The only exception with a good detected FIR plateau beyond 40 µm is 3C 55 in Fig. 3. The MIR-bright sources with FIR upper limits mostly show the SED decline longward of 40 µm, e.g., 3C 254 in The SED of the LERG 3C 427.1 shows faint MIR (and FIR) emission ( Fig. 6), corroborating the idea that LERGs are AGN with low accretion activity (Ogle et al. 2006).

SEDs at low-redshift
The quasar/BLRG SEDs differ in their radio properties. Four flat spectrum sources show a rise in their GHz spectra (Fig. 8), while the 10 steep spectrum sources have GHz spectra which are constant in νF ν (Figs. 9 and 10). A strong curvature is found in the MHz to GHz spectra of two CSS quasars and BLRGs, (3C 48 in Fig 9, and 3C 268.3 in Fig. 10).
The steep spectrum sources show a clear MIR-FIR emission component above the extrapolation of the radio spectrum to shorter wavelengths ( Fig. 9). In contrast, the flat spectrum sources show a relatively modest MIR-FIR emission bump above the extrapolated rising GHz spectrum. They most likely have a strong synchrotron contribution to their IR SED. At optical wavelengths the quasars (2 of the 4 FSQs and 3 of the 4 SSQs) show a strong power-law component rising towards shorter wavelengths.
Similarly to the SSQs, the HERGs show a clear MIR-FIR emission component above the extrapolation of the radio spectrum to shorter wavelengths. However, there is a large diversity in the MIR. Figures 11 to 13 show the HERGs with strong, medium and weak MIR emission relative to the host galaxy.
While in both SSQs and HERGs the MIR SED is well determined, the detection rate in the FIR (at rest frame 60-100 µm) is 38/48. For the HERGs with strong and medium MIR emission the SED declines longward of about 30-40 µm. where the GHz respectively cm spectrum rises towards shorter wavelengths in νF ν scaling. Filled black circles with error bars denote detections, 3σ upper limits are marked by arrows. The Herschel PACS and SPIRE band ranges are shadowed in red, the 2MASS and WISE ranges in green, the optical (SDSS) range in blue. Red and blue diamonds are optical photometry values from Véron-Cetty and Véron (2010) and from Laing et al. (1983)), respectively. "+" symbols are detections (with arrows: upper limits) collected via NED. Disentangled host flux from Lehnert et al. (1999) is shown with a star symbol. Black open squares mark photometry with Spitzer/MIPS at 24 µm or Spitzer/IRS; IRS spectra are plotted as blue lines and the position of the 9.7 µm silicate absorption is indicated by the black vertical dash-dotted line. SCUBA 450/850 µm and IRAM 1.2 mm data points by Haas et al. (2004) are marked with black dots. Large blue dots mark median data points at 30 GHz and 178 MHz restframe. Big blue, green and red dots at IR-wavelengths mark interpolated flux levels at 30, 60 and 100 µm, respectively. Models of the host galaxy, the AGN heated warm dust and the SF heated cool dust are shown as dashed lines.  -Spectral energy distributions of high excitation radio galaxies (HERGs) at 0.5 < z < 1, with bright MIR emission, up to a factor ten above the host galaxy level. Note the deep 9.7 µm silicate absorption in the CSS 3C 49 and in 3C 55, 3C 226 and 3C 343. Notation as in Fig.1.

Median SEDs of Quasars and Radio-Galaxies
The SEDs of all sources were scaled to νL ν with their luminosity distance D L given in Tables 1 and 2. The median SEDs were built for the classes FSQ, SSQ, BLRG, HERG and LERG for each redshift sample as given in Tables 7 and 8. The individual SEDs were first normalized to their 178 MHz rest frame flux density, which is interpolated and tabulated in Tables 16 and 17 and then scaled to the median luminosity of the sub-sample at 178 MHz. The scaled SEDs were combined in continuous bins of 100 consecutive data points. In each bin the median wavelength, luminosity and standard deviation in logarithmic space was calculated and plotted in Figure 16. The templates are tabulated in Table 6.
The 178 MHz restframe flux normalization was chosen because orientation effects can be excluded. Even so, the radio-lobe power may be influenced by the environment of the 3C sources. As shown in Section 5.3 there is a trend of the ratio of radio-to-MIR luminosities changes with redshift, which can be interpreted as a denser environment at earlier ages. Therefore separate templates are provided for a range of source types and redshift ranges.
While for HERGs, LERGs and also for BLRGs, the stellar component of the SEDs is visible and can be fitted well, for the SSQs and FSQs the strong power-law shaped AGN continuum in the optical and ultra-violet has to be taken into account. Because that was not possible in a consistent manner, the host galaxy fits and the derived stellar masses have to be seen as upper limits for the quasars (Section 4.4).
In the νL ν scaling both quasar types, FSQ and SSQ, show a flat, nearly identical distribution in the range from 0.1 µm λ 20 µm, justifying the assumption that the two classes are intrinsically similar objects. At wavelengths beyond 20 µm the median SED of FSQs and SSQs diverges with a flux higher in the FSQs. This was interpreted in the past as a jet component (Cleary et al. 2007) which is relativistically beamed towards us. Now with the new Herschel data included, the jet en-hancement can be traced to FIR wavelengths for the FSQs, which also shows up in the non-thermal shape of the SED. FIR-inferred SFR rates have therefore only are upper limits for the FSQs (Section 4.4).
The HERGs and LERGs median SEDs appear quite differently at IR wavelength. On average the HERGs are one dex more luminous in the MIR than the LERGs. The weak MIR activity of LERGs was interpreted as low accretion activity (Ogle et al. 2006). For both types the MIR shows absorption features from silicate at 9.7 µm absent in all quasar (FSQ, SSQ, BLRG) median SEDs. LERGs have a relatively weaker dust to starlight continuum ratio than HERGs. For LERGs the peak in the FIR is more distinguished and shifted to longer wavelengths, suggesting cooler dust compared to HERGs.

Decomposition into Host, AGN Torus and Star formation
The components and structure of the galaxy (gas dust, stars, radio-jets and lobes) are reflected in the SEDs and can be disentagled from it. The stellar emission of the host galaxy peaks, depending on the stellar population, between NIR and UV wavelength (Fioc and Rocca-Volmerange 1997;Bruzual and Charlot 2003;De Breuck et al. 2010) In the orientation-based unified scheme of powerful FRII radio galaxies and quasars (Barthel 1989;Antonucci 1993) the optical and UV emission of the central engine is blocked in some directions by anisotropically distributed dust. The heating by the AGN causes the warm dust emission to peak at restframe MIR (10-40 µm) wavelength (Rowan-Robinson 1995), which has been observed for most of the 3C sources (e.g., Siebenmorgen et al. 2004;Ogle et al. 2006;Hardcastle et al. 2009). A torodial and clumpy configuration in the so called dust torus is a widely accepted hypothesis for the dust configuration (Nenkova et al. 2002;Hönig et al. 2006;Siebenmorgen et al. 2015).
The dust-enshrouded formation of stars causes the stellar light to be reprocessed by the dust. Corresponding to the cool temperature the reemission peaks at ∼ 100µm (Schweitzer et al. 2006;Netzer et al. 2007;Veilleux et al. 2009). Table 6: Median spectral templates for different galaxy types separated for low-(z < 0.5) and mediumredshift (0.5 < z < 1).
The aim of the analysis is to quantify host galaxy stellar mass and star formation rates in the environment of the strong AGN emission, which can contribute at all wavelength ranges. Also the question of the unification of radio galaxies and quasars shall be answered at the FIR wavelengths, where the opacity is low. From the SEDs are extracted: a) L Host , the luminosity of the stars in the host galaxy, by integration over fitted synthetic stellar population models by Bruzual and Charlot (2003) (libraries available from Mariska Kriek 7 ). From the synthetic stellar population templates the luminosity of the stars in the host galaxy L Host (Eq. 2) was derived. With the inherent mass-to-light ratio M L BC03 of the templates, stellar masses M ⋆ can then be calculated (Eq. 3). Values for both samples are given in Tables 10 and 11. The templates were calculated with an exponentially declining star formation history (with time scale υ [log yr]), metallicities Z ranging from sub-to super-solar, and a Chabrier IMF. Free parameters in the fitting routine were υ, Z, and the age of the stellar population. The synthesized flux-densities F 0 λ were attenuated for the extinction in the interstellar medium with the dust-attenuation k(λ) and R V = 4.05 (Calzetti et al. 2000, see Eq. 1). The dependence of the derived stellar masses on the extinction coefficient A V is weak for a sample of early type galaxies (see Swindle et al. 2011). Therefore the median A V = 0.1 found for the Swindle et al. (2011) sample was applied here.
b) L AGN , the luminosity of the AGN powered dust (torus), by integration over fitted torus models by Hönig and Kishimoto 2010. The MIR emission was fitted using a template library 8 . Parameters of the best fitting template with the derived total luminosity L AGN (Eq. 4) are given in Tables  12 and 13. Parameters used for the fitting process were: The index a of the power law for radial dust cloud distribution, the number N of clouds along the equatorial line of sight, the half opening angle θ, the optical depth τ and the inclination to the observer i.
(4) c) L FIR , the luminosity of cool FIR emitting dust, by integration of a modified blackbody at 20-50 K (β = 1.5), which is given by and The FIR emission can be attributed to dust heated by stars. The integrated luminosity L FIR was used to estimate the SFR by applying Eq. 7 (taken from Kennicutt 1998 Eq. (4)), which is valid for starbursts with an age less than 10 8 years. Values are given in Tables 14 and 15. SFR d) Monochromatic luminosities at rest frame νL 30 GHz ν , νL 178 MHz ν were used to trace synchrotron contribution from radio jets and inclination effects in the IR at νL 30 µm ν , νL 60 µm ν , νL 100 µm ν from interpolated fluxes (Tables 16 and  17).
Present AGN torus models often require an ad hoc T = 1300 K (Leipski et al. 2013;Podigachoski et al. 2015a) dust component in quasars to fit the nearinfrared (NIR) bump around 3 µm. In addition, new AGN torus models (Siebenmorgen et al. 2015) invoke fluffy dust particles and are able to fit the AGN SEDs to longer wavelengths compared to the HK models, with SED peak beyond ∼ 80 µm. This increases the ambiguity of AGN-SF model fitting and star formation may be even lower than indicated by our analysis here.

Bayesian SED fitting
The fitting of all components was achieved by the application of a Metropolis-Hastings algorithm The prior P rior(p) of a single model parameter p in the range of the maximum and minimum allowed values p max and p min is given by the probability density of the uniform distribution (Eq. 9).
Then the prior P rior(M ) of the whole model can be written in logarithmic space as Eq. 10.
The likelihood Like(d|m) of single model point m fitting a data point d with mean value µ and standard deviation σ is given by the probability density of the normal distribution (Eq. 11).
The likelihood Like(D|M ) of the whole model M fitting the data D can then be written like Eq. 12.
With this nomenclature, a constant P rior(D) and using the logarithmic metric the posterior probability is calculated like Eq. 13. Modelling parameters and ranges for host, torus and FIR templates are given in Table 9. The Metropolis-Hastings Monte-Carlo chain starts for each source with an individual set of scaling factors for host-, torus-and FIR-template, while M etal start = 0.5, υ start = 10 7 , Age start = 10 9.5 for the host N start = 5.0, a start = −1, θ start = 32.5 and τ start = 35 for the torus were selected equally for all sources. The start value for inclination was set to 5 • for type 1 sources and 45 • for type 2 sources. The start value for T FIR was also selected individually for each source. The Metropolis-Hastings algorithm proceeds by randomizing the model parameters M i of the preceding iteration with a proposal function M i+1 = f unc proposal(M i ) which was tuned to allow the chain values to vary in suitable steps for each model parameter. Then the posterior probability of the preceding model set P ost(M i |D) was compared and normalized to the new proposed model set P ost(M i+1 |D) and the probability of an improvement was computed via Eq. 14 The computed value of P rob(M i |M i+1 |D) was compared to a uniformally distributed random number between 0 and 1. If P rob(M i |M i+1 |D) was greater than this random number the proposed model set M i+1 was included in the Monte-Carlo chain and chosen as new start value for the next iteration step. This procedure allows the chain to evolve to better models while also models which don't seem to be an actual improvement retain a small chance to enter the chain. By this behaviour the Metropolis-Hastings algorithm is able to leave local maxima in the posterior space and search for the global one. For each model 10000 chain values were calculated and the last 5000 iterations were used for the analysis via histograms for each model parameter (see Figures 17, 18 and  19).

MIR-weak sources
Based on 15 µm luminosity measured in the Spitzer IRS spectra, Ogle et al. (2006) defined MIR-weak sources by an absolute monochromatic threshold, νL 15 µm ν < 8 · 10 43 erg/s (roughly corresponding to the integrated luminosity of the torus model fit of L MIR = 2 · 10 10 L ⊙ ). While successfully identifying MIR-weak sources at lowredshift, potential analogs at higher redshift may be missed because they fall below the detection limit, and a more flexible definition is desiredalso because F 15 µm ν is not available for all of our sources. The torus and host template fits are able to measure the entire integrated MIR luminosity as well as the host luminosity. Therefore we define MIR-weak sources relative to the host galaxy: L MIR /L Host < 1 (Fig. 20).By this threshold all galaxies classified as LERGs are included in the MIR-weak definition, as well as some sources classified by their optical spectra as HERGs. Also two MIR-weak BLRGs, 3C 219 and 3C 382 are found according to this definition.
For 3C 219 (see Fig. 10) the MIR-weakness can be verified from the SED, where the fits of host and torus agree well with the observed data. For the flat-spectrum BLRG 3C 382, the host luminosity cannot be independently estimated, and the model fit is most likely an over-estimate as contamination from the AGN could not be disentangled. A weaker ratio of L MIR /L Host < 1 3 is also indicated in Fig. 20 which would exclude the two BLRGs but also two LERGs and several HERGs from the MIR-weak definition.
The definition is motivated by the relation of black-hole and bulge masses ( (Häring and Rix 2004)), thus more massive galaxies can reach a larger accretion luminosity. To check the consistency of the inferred host masses and MIR luminosities, the black hole masses M BH have been calculated with Eq. 15 taken from Häring and Rix (2004) with stellar mass estimates M ⋆ derived from the host luminosities L Host as input (see Tables 10 and 11). We find black hole masses in the range of ≈ 10 6 − 10 9 M ⊙ consistent with the range found for example by Tremaine et al. (2002) log(M BH /M ⊙ ) = (8.2 ± 0.1) + (1.12 ± 0.06) (15) × log(M Bulge /10 11 M ⊙ ) With the derived black hole masses M BH we are able to calculate the limiting Eddington luminosity L Edd as Eq. 16. The ratio of AGN luminosity in the MIR and Eddington luminosity L AGN /L Edd is given in Tables 12 and 13. The comparison shows an average ratio of a few percent with none of the sources exceeding the Eddington limit.
The definition of MIR-weak sources relative to the hosts has the advantage that it is independent of absolute luminosities and thus may allow us to identify MIR-weak sources also at higher redshift. (In fact, we find MIR-weak sources which exceed Ogle et al.'s absolute luminosity limit by about a factor of ten). In the plots, MIR-weak sources are marked with a superposed "x".
Beyond z > 0.5, the 3C-sample contains 5 MIR-weak HERGs but only one LERG 3C 427.1 (L MIR upper limit, Fig. 20). The lack of LERGs raises the question whether (some) MIR-weak HERGS were misclassified and actually belong to the LERG class. We checked the classification into low-and high-excitation emission line sources based on the ratio of  Jackson and Rawlings (1997) and Grimes et al. (2004) Grimes et al. (2004) have been extrapolated from Jackson and Rawlings (1997) [O II] fluxes using an average HERG line ratio. Therefore misclassification among the MIR-weak HERGs of the medium-redshift sample cannot be excluded. We find two MIR-weak BLRGs (3C 219 and 3C 382); they could be the broad-line counterparts of the otherwise type-2 dominated MIRweak class. This finding is remarkable because type-1 AGN are typically brighter in the MIR than type-2 AGN, and the type-1 hosts are more difficult to measure. Nevertheless, the number ra-tio of the type-1 / type-2 MIR-weak is small and a large dust covering angle would be required to reach consistency with orientation based unification schemes.
In the orientation-based AGN unification, MIRweak sources either have less dust, a dust torus with a small covering angle or low accretion power. To distinguish between these scenarios is a particular challenge. MIR-weak sources are found among both HERGs and LERGs, indicating a potential smooth transition and arguing against sharply distinguished, fundamentally different mechanisms like "radiation dominated" vs. "advection dominated" accretion (Ogle et al. 2006).

Comparison of MIR to radio-lobe and [O III] luminosities
Three luminosities in MIR, radio-lobe and [O III] luminosities are expected to be tracers of the intrinsic AGN accretion power and therefore should be correlated. Fig. 21 (right) shows the ratio L MIR /L O III , which appears similar over four orders of magnitude for all three classes QSRs, HERGs and LERGs. The relation was fitted for all classes (see Eq. 17) and for the LERGs separately (see Eq. 18). There is a trend that LERGs have about a factor 3 higher L O III compared to QSRs and HERGs of the same L MIR (all LERGs except 3C 236 lie on the right side of the median relationship in Fig. 21,(right)). This trend can be explained by differences in the dust torus or intrinsic difference in the AGN-SED of high-and low-excitation sources. A smaller torus covering angle and less extinction of the inner NLR might be the cause. Also a central engine with a lower production rate of ionizing photons is thinkable. Best-fit relations are: In Fig. 21 (left) the monochromatic radio-lobe luminosity is plotted versus the MIR luminosity. The distributions for the different classes of QSRs, HERGs and LERGs show a clear overall trend. The correlations for QSRs, HERGs and LERGs are fitted separately (see Eq. 19 -21). At νL 178 MHz ν = 5 · 10 9 L ⊙ the low from the mediumredshift sample are separated; there are only three low-z exceptions (3C 47, 3C 48 and 3C 123) exceeding that radio luminosity threshold. slope. The torus models do not properly account for the hot (∼1000 K) dust emission in type-1 sources. This was already noted by Leipski et al. (2013) and Podigachoski et al. (2015a) for the high-z quasars. Thus the integrated luminosity L MIR from the fitted torus models is underestimating the MIR luminosities of the bright quasars. Independent of the slopes, the MIR/radio ratio of QSRs exceeds that of the HERGs by a factor of 5-10. This can be explaind by orientation-dependent extinction even at MIR wavelengths (e.g. Haas et al. 2008;Leipski et al. 2010;Podigachoski et al. 2015b).
Likewise, both LERGs and MIR-weak HERGs show a 2-20 times weaker L MIR /νL 178 MHz ν ratio than the MIR-strong HERGs which is rather caused by decreased MIR than increased radio luminosity. Differences in the central engine can cause different AGN SEDs or low dust content may be the reason for MIR weakness; for example a binary black hole or differences in the black hole spin could lead to strong jet development on lower accretion rates.

Beamed IR contribution in FSQs
At medium redshifts the SSQs 3C 334 and 3C 336 (and also some HERGs) have such low 1.2 mm fluxes observed (Haas et al. 2004) that there is no room for a beamed synchrotron component (with reasonable spectral slope α) to contribute to the MIR and FIR (Fig. 2). This is comparable to radio-quiet quasars as seen by Chini et al. (1989). The other 6 SSQs do not have 1.2 mm measurements, but the same picture can be assumed for them.
In contrast the 7 FSQs have a rising GHz spectrum and beamed emission may contribute to the FIR and MIR (Fig. 1)  ∼ 20 µm can be identified in most sources, except 3C 207 and 3C 216. Also the NIR 3-4 µm bump is discernible (e.g., 3C 147). This suggests that the NIR-MIR SED is dominated by dust emission and that any beamed contribution to the MIR and NIR is weaker than in the FIR. The same picture can been seen at lower redshifts for the FSQs in Fig. 8, where the non-thermal contribution can be traced to the FIR for 3C 111, 3C 120, 3C 273 and 3C 382. The SSQs and BLRGs plots show ( Fig. 9 and 10) that the FIR is dominated by dust emission.
Following the concept introduced by Meisenheimer et al. (2001), we determined the dustto-radio ratio R DR = νF IR ν /νF 178 MHz ν at 30 and 100 µm. To quantify the dependence of L IR at 30 and 100 µm on the radio slope, we consider R DR versus R GM = νL 30 GHz ν /νL 178 MHz nu (Fig. 22). R GM clearly separates FSQs from SSQs, with a dividing ratio R GM = 5. Fig. 22 shows on the vertical axes the R DR distributions at 30, and 100 µm for the different AGN types. The large crosses mark the averages (in log space) and the dex range for the different AGN types: • yellow/black: LERGs, excluding FR I and 3C 236 as outlier = 40 for the medium-redshift sample separate sources with an exceptional high FIR luminosity like 3C 321 or the CSS 3C 48; the curved radio spectrum of the CSS leads to an even lower 178 MHz flux. This check reveals that statistically L FIR is higher by a factor of 2-3 in the FSQs. In contrast the MIR luminosity is similar (except 3C 120), which can be explained by a wavelengthindependent constant contribution of non-thermal radiation, which is more dominant in the sources with weaker (about 3 times) IR emission. Fig. 22 shows a remarkable R 30 µm DR and R 100 µm DR difference between the low and medium redshift samples of SSQs and MIR-strong HERGs. For the medium-z sample, on average, R DR is about a factor 5-10 lower than for the low-z sample. This indicates that at a given MIR AGN power the radio lobes are much fainter in the local universe compared to the earlier epoch. Thus, the lobe production via working surface of the jet with the ambient medium is less efficient. Notably, R DR of the local MIR-weak HERGs matches that of the distant MIR-strong HERGs and the local LERGs have the lowest R DR . This may indicate that their circumgalactic medium is denser, perhaps due to cluster environment (further discussed in Sect. 5.5).

SSQ / MIR-strong HERG unification
Both the radio-lobe luminosity νL 178 MHz ν and the dust luminosity L FIR are assumed to be isotropic. In the orientation-based unified scheme, their distributions should be indistinguishable for steep spectrum quasars (SSQs) and highexcitation radio galaxies (HERGs). The same should hold for ratios of isotropic observables. If the distributions differ, then either the observables are not isotropic or the sources have intrinsic differences. For the low-redshift sample the HERGs (with the MIR-weak ones excluded) and SSQs sub-samples show a nearly perfect match in logarithmic average and range (Fig. 22). FRI and CSS sources were excluded from the average for both classes.
For the medium-redshift sample the SSQs show a R DR ratio at 30 µm that is on average a factor of two higher than the HERGs, but the samples match in their average R DR at 60 µm and even better at 100 µm. This can be interpreted by a dust torus that is optically thick at 30 µm and emits isotropically at 100 µm. Also the FSQs match with SSQs in the unification framework by synchrotron contribution from beamed jet emission in FIR and MIR. The match at 100 µm may be favoured by the fact that the averages are dominated by the match of the upper limits. Again MIR-weak and CSS sources were excluded.
These results support the orientation-based unified scheme for MIR-strong HERGs and SSQs. However, the relationship to LERGs and MIRweak HERGs might not be explained simply by orientation effects, as discussed in Sect. 5.5.

Star formation
To estimate the star forming luminosity L FIR we assume that the FIR emission fitted by the ∼30 K modified blackbody is entirely powered by stars. However, the AGN may heat dust at lower temperatures than accounted for by the torus models of Hönig et al. (2010); in cases of different chemical dust composition and grain geometries the AGN create larger emission at longer wavelengths (Siebenmorgen et al. 2015). Therefore L FIR and the SFR derived from our SED fits may be overestimated and the actual SFR may be smaller. Therefore we treat our estimates as maximum possible SFR. Other star formation indicators, e.g., via optical Balmer or [O II] lines, may suffer even more from AGN contamination than the FIR. In fact there is evidence (Hes et al. 1993) that isotropic [O II] emission from the narrow-line region is playing in important role in quasars and radio galaxies.
To provide a tentative cross check, we have converted both L FIR and L O II into star formation rates SFR FIR and SFR O II using the scaling relations (Eq. 7 and 22, Kennicutt 1998 The SFRs derived from both indicators match within an order of magnitude (Fig. 23). There is no correlation between SFR O II and SFR FIR in the medium-redshift sample, where a higher AGNtriggered [O II] emission has to be taken into account. For the low-redshift sample we find correlation but SFR O II is larger than SFR FIR . Because we have not subtracted AGN contributions from L O II we suggest that SFR O II is overestimated as well.
For most 3CR sources the ratio L FIR /L Host < 1 is below that of the Milky Way. This suggests that the bulk of the sources contains a small amount of interstellar matter, which serves as a gas reservoir for star formation. To estimate the dust mass M D from L 100 µm ν and the dust temperature T D , we used with dust opacity κ 100 µm = 27 cm 2 /g (Draine 2003;Siebenmorgen et al. 2014). The dust masses are listed in Tables 14 and 15. For all but a handful starbursting 3CRs (identified below), the dust-tostellar mass ratio lies in the range 10 −3 − 10 −5 . That is about a factor 1-100 lower than for the Milky Way, i.e. more reminiscent of dust-poor elliptical galaxies. Despite large uncertainties in the dust mass estimates (M D is especially sensitive to T D ), this strongly suggests that the bulk of the 3CRs contains only a relatively small dust mass (and gas mass as well). If the dust mass is widely distributed across the host galaxy, this results in a low dust column density, and one may expect only a modest amount of overall optical extinction. This may explain the rough agreement between SFR O II and SFR FIR . In the following we use SFR FIR . For comparison with other galaxy types and across cosmic time, the derived SFR has to be placed in the context of the already existing stellar mass M Host , derived from the host luminosity via the intrinsic mass-to-light ratio of the synthetic stellar population fits of the SEDs (Table 10). For FSQs L FIR might be overestimated due to synchrotron contamination and SFR upper limits are plotted. For type-2 AGN and steep-spectrum BLRGs, M Host and SFR are not affected this way.
For QSRs (SSQs and FSQs) the host luminosity is likely overestimated, and we therefore plot upper limits for M Host of these sources. We find some sources in the medium redshift sample, e.g. 3C 343 or 3C 6.1, with stellar masses up to ≈ 10 12 M ⊙ , which are rare in the local universe (z < 0.3), but also have been reported recently for quasar host galaxies at redshifts < 1 (see Fig. 7 of Matsuoka et al. (2015)). For three sources (3C 6.1, 3C 184 and 3C 280) there is no optical data available. In these sources the host fit is based on the WISE measurements where confusion within the WISE beam can not be excluded. Thus the host luminosity and derived stellar masses are treated as upper limits.
For the low-redshift sample the stellar masses lie in the range of 10 10 up to 10 12 M ⊙ , and the FIR luminosities are about 10 10 L ⊙ (Tables 11 and  15). In Figure 24 Jackson and Rawlings (1997) and L FIR from our modified blackbody fit. The lines are not a fit; they illustrate the overall agreement with slope unity (solid) and a factor 10 above/below unity (dotted). Notation as in Fig. 20.
gether with a comparison sample of SDSS galaxies in the redshift range 0.015 < z < 0.1 investigated by Brinchmann et al. (2004) and Kauffmann et al. (2003). The relation between SFR and mass for the SDSS galaxies is: For the medium-redshift sample the range of L FIR lies around 10 11 L ⊙ (Fig. 24 right, Table 14), i.e. ,that of IR luminous SF galaxies (LIRGs) with a few sources above 10 12 L ⊙ in the regime of ULIRGs. Derived host masses lie in the range of 10 11 -10 12 M ⊙ , hence in the range of the most massive galaxies. For comparison a selection of star forming galaxies from the GOODS fields (Elbaz et al. 2007) with 10 9 M ⊙ < M ⋆ < 10 12 M ⊙ , 1 M ⊙ yr −1 < SFR < 300 M ⊙ yr −1 ), 0.8 < z < 1. The clouds of small grey and yellow dots indicate the main sequence of star forming galaxies and AGN, respectively, at low-redshift (0.015 < z < 0.1) from Brinchmann et al. (2004) and Kauffmann et al. (2003)) with the thin blue line representing the average relation of the star forming galaxies (Elbaz et al. 2007). The thick black line flanked by the black dotted lines shows the average relation and 1σ of the 0.8 < z < 1.2 GOODS star forming galaxies from Elbaz et al. (2007) . The location of the main sequence of star forming galaxies shifts up with increasing redshift Noeske et al. (2007). Notation as in Fig. 20. For the HERG, LERG and BLRG class, both stellar masses and star formation rates establish that the 3Cs at z < 1 belong to the most massive galaxies of their epoch, but most have low specific star forming activity. This is remarkably different from the results for 3CR sources at 1 < z < 2 (Podigachoski et al. 2015a), where ≈40% show ULIRG-like SFRs (200-2000 M ⊙ /yr) at similar host masses (10 11 -10 12 M ⊙ ). This comparison suggests that many of the 3CRs at z < 1 are in a late evolutionary state. Alternatively, if their nuclear activity is triggered by galaxy interactions/mergers, these could be dry mergers, i.e., the collision of two ISM-poor ellipticals. Strikingly, the MIR-weak sources and LERGs populate the lowest end of the specific SFR distributions.

Evolution from HERGs over MIRweak to LERGs?
The possibility that MIR-weak sources and LERGs may be considered as classically accreting AGN in which the dust torus has a small covering angle, and where a low extinction enables bright [O II] emission, and where the environment favours a high radio lobe luminosity is raised in Sec. 5.1 and 5.2. MIR-weak sources and LERGs populate the low end of the FIR R DR distributions (Fig. 22). The overall trends in Fig. 22 make an evolutionary HERG-to-LERG scenario attractiv, in which MIR-strong HERGs evolve to MIR-weak HERGs and then further to LERGs. In this picture both the AGN accretion luminosity as traced by the dust torus and the SF luminosity (and the dust and gas mass) are high for young sources and decline with increasing age. However, there are several open issues with such a picture, as already discussed by Ogle et al. (2006), who suggested that the LERGs are jet-dominated sources with low, if any, accretion power. Here we can add more pieces to the puzzle: a) In the low-z sample the LERGs and MIRweak HERGs populate the same host and radio lobe luminosity ranges as the MIR strong HERGs and QSRs (Figs. 20 and 21). The same holds for the lobe extent. If accretion plays a substantial role in creating the radio power, one would have to postulate that with declining accretion during the HERG-to-LERG transition another power source grows, in order to keep the lobe power similar for LERGs and HERGs. If accretion plays a subordinate role, then the jet power may be provided by other processes such as a spinning or a binary black hole in the nucleus. b) If the evolutionary HERG-LERG scenario is valid, one may expect that it holds also at higher luminosities/redshifts. In the medium-z sample, however, MIR-weak sources (and LERGs) are rare, even with our new definition of MIRweakness, and despite the denser circumgalactic medium compared to the local universe. The five MIR-weak sources have the lowest lobe power among the medium-z sample (Fig. 21). This suggests that the MIR-weak successors of MIR-strong HERGs at 0.5 < z < 1 decline in lobe luminosity, so that they fall below the 178 MHz flux limit of the 3CR sample. The time scales of radio loudness are in the order of several 10 7 years, much shorter than the age range of the sample. Thus, any LERG-successors of MIR-strong HERGs of the 0.5 < z < 1 3CR sample cannot have moved out of that redshift range. For example t(z = 0.55) − t(z = 0.53) ≈ 1.5 · 10 8 yr (Wright 2006). c) Another possibility is that MIR-weak sources and LERGs do not exist in the early, say z > 0.75 universe and have recently evolved. This may be related to the findings based on the Molonglo 2 Jy radio galaxies that LERGs are more frequently found in clusters than QSRs/BLRGs or HERGs (Ramos Almeida et al. 2013). Then the intra-cluster gas may enhance the radio lobes, as found for Cygnus A by Barthel & Arnaud (1996). Because the time scale for cluster formation is much higher than the radio-loud phase, a MIRstrong HERG in the field cannot evolve in several 10 7 years into a LERG surrounded by a cluster.
To summarize, there are several arguments against a simple evolutionary HERG-to-LERG scenario, and much future work is required to solve the puzzle on the relation between the MIR-weak and MIR-strong sources.

Summary and conclusions
a) The z < 0.5 sample contains many LERGs, the medium-redshift sample many FSQs and in general more powerful RGs/QSRs. Complete photometry from diverse catalogues was collected for all sources to cover the SEDs continuously from optical to radio wavelengths.
b) The new SEDs were used to measure host, AGN and star forming luminosities by fitting appropriate templates with a Metropolis-Hastings algorithm, based on maximizing the Bayesian posterior probability. Also model-independent luminosities were derived at selected wavelength, to quantify opacity effects and non-thermal contributions from synchrotron emission.
c) The class of MIR-weak sources was investigated. A new flux-ratio-dependent definition of MIR-weakness is given, which avoids an absolute threshold. Compared to the previous definition, now MIR-weak sources can clearly be separated also at higher luminosities. Possible explanations of the MIR weakness are either an extreme cool and thin dust torus or a lane seen directly from the edge. The MIR-weak sources can also represent an intrinsically different class of gas-and dustpoor AGN. Such a class may have suffered from evolutionary depletion by an early strong merger history in a more clustered environment.
d) The dust-to-radio-lobe luminosity ratios were calculated in the range of 30 − 100 µm. This results in confirmation of the unification hypothesis of HERGs and QSRs.
e) The sample reveals a decline of the radiolobe-to-dust luminosity ratio with increasing redshift. This indicates a decline of the efficiency to create radio lobes from early epochs up to today. We suggest that this is caused by the dilution of the cirumgalactic medium during cosmic evolution.
f ) For the whole sample, stellar masses and star formation rates were presented. This allows us to put the host galaxies of radio-loud AGN into context with non-AGN and radio-quiet AGN at the same epoch. The analysis shows that radioloud AGN are associated with the most-massive galaxies (10 10 M ⋆ 10 12 ). In the majority of these galaxies new stars are formed only at a low level. The SFR may even be smaller if the AGN-heated dust torus contributes more at longer wavelength than indicated by currently available models.
Altogether, the present Herschel observations of the 3CRs at z < 1 do not support the hypothesis that every radio-loud quasar is accompanied by a high specific star forming activity. Our analysis suggests that, if radio-loud AGN are triggered by galaxy interactions (Heckmann et al. 1986, Stock-ton et al. 1986, in most cases these are probably dry mergers with little dust and gas mass. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration.
This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation.
Funding for the creation and distribution of the SDSS Archive has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Aeronautics and Space Administration, the National Science Foundation, the U.S. Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society. The SDSS Web site is http://www.sdss.org/.
The SDSS is managed by the Astrophysical Research Consortium (ARC) for the Participating Institutions. The Participating Institutions are The University of Chicago, Fermilab, the Institute for Advanced Study, the Japan Participation Group, The Johns Hopkins University, the Korean Scientist Group, Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington.
This research has made use of NASA's Astrophysics Data System. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France. The original description of the VizieR service was published in Ochsenbein et al. 2000. This work is supported by the Nordrhein-Westfälische Akademie der Wissenschaften und der Künste in the framework of the academy program of the Federal Republic of Germany and the state Nordrhein-Westfalen, and by Deutsches Zentrum für Luft-und Raumfahrt (DLR 50 OR 1106).
CW thanks BJW, JK and SPW for their hospitality during his 4 weeks visit at the CfA, kindly granted by the Smithsonian Institution and Henrik Spoon for providing the IRS spectra.
We thank the referee for constructive comments.