STAR FORMATION IN 3CR RADIO GALAXIES AND QUASARS AT 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 $0.5\lt z\lt 1$ in the 3CR catalog, 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 do not 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) and Cleary et al. (2007). Two FSQs (3C 345, 3C 454.3), one SSQ (3C 275.1), four HERGs (3C 34, 3C 217, 3C 247, 3C 277.2), and one LERG (3C 41) are in the 3CR catalog but not observed by Spitzer. Two HERGs, 3C 175.1 and 3C 220.3, were removed from the analysis. The former has insufficient ancillary data in the literature, and the latter acts as gravitational lens for a submillimeter galaxy at z = 2.2 (Haas et al. 2014).

Table 1.  3CR Sources $0.5\lt z\lt 1$ Observed with Herschel

Name	R.A. [J2000]	Decl. [J2000]	Redshift	${D}_{{\rm{L}}}$ (Mpc)	Type	Proposal-IDa	PACS-OBSID	SPIRE-OBSID
3C006.1	00 16 31.1	+79 16 50	0.8404	5193	HERG	1	1342262061/62	⋯
3C022.0	00 50 56.3	+51 12 03	0.9360	5935	BLRG	2	1342237866/67	⋯
3C049.0	01 41 09.1	+13 53 28	0.6207	3568	HERGb	1	1342261865/66	⋯
3C055.0	01 57 10.5	+28 51 38	0.7348	4392	HERG	1	1342261794/95	1342261703
3C138.0	05 21 09.9	+16 38 22	0.7590	4578	QSRb	1	1342267270/71	1342268340
3C147.0	05 42 36.1	+49 51 07	0.5450	3048	QSRb	1	1342268972/73	⋯
3C172.0	07 02 08.3	+25 13 53c	0.5191	2876	HERG	1	1342268994/95	⋯
3C175.0	07 13 02.4	+11 46 15	0.7700	4665	QSR	1	1342269004/05	⋯
3C175.1	07 14 04.7	+14 36 22	0.9200	5820	HERG	2	1342242694/95	1342230780
3C184.0	07 39 24.2	+70 23 11c	0.9940	6406	HERG	2	1342243742/43	1342229126
3C196.0	08 13 36.0	+48 13 03	0.8710	5436	QSR	1	1342254180/81	⋯
3C207.0	08 40 47.6	+13 12 24	0.6806	4009	QSR	1	1342254575/76	⋯
3C216.0	09 09 33.5	+42 53 46	0.6699	3929	QSRb	1	1342254561/62	1342255115
3C220.1	09 32 39.6	+79 06 32	0.6100	3498	HERG	1	1342254194-96	⋯
3C220.3	09 39 23.8	+83 15 26c	0.6800	3997	LENS	1	1342221818/19	1342254521
3C226.0	09 44 16.5	+09 46 17c	0.8177	5030	HERG	1	1342255958/59	1342255165
3C228.0	09 50 10.8	+14 20 01	0.5524	3106	HERG	1	1342255462-64	⋯
3C254.0	11 14 38.7	+40 37 20	0.7366	4418	QSR	1	1342255900/01	⋯
3C263.0	11 39 57.0	+65 47 49	0.6460	3755	QSR	1	1342255428-30	⋯
3C263.1	11 43 25.1	+22 06 56	0.8240	5078	HERG	1	1342255685-87	⋯
3C265.0	11 45 29.0	+31 33 47c	0.8110	4978	HERG	1	1342255485/86	⋯
3C268.1	12 00 24.5	+73 00 46c	0.9700	6214	HERG	2	1342245706/07	1342229628
	⋯	⋯	⋯	⋯	⋯	⋯	1342247316/17	⋯
3C280.0	12 56 57.8	+47 20 20c	0.9960	6426	HERG	2	1342233434/35	1342232704
3C286.0	13 31 08.3	+30 30 33	0.8499	5275	QSRb	1	1342259326/27	1342259451
3C289.0	13 45 26.4	+49 46 33	0.9674	6196	HERG	2	1342233495/96	1342232711
3C292.0	13 50 41.9	+64 29 36c	0.7100	4218	HERG	1	1342257595-97	⋯
3C309.1	14 59 07.6	+71 40 20	0.9050	5698	QSRb	1	1342259354-57	⋯
3C330.0	16 09 34.9	+65 56 38c	0.5500	3082	HERG	1	1342261369/70	⋯
3C334.0	16 20 21.8	+17 36 24	0.5551	3118	QSR	1	1342261319/20	1342263861
3C336.0	16 24 39.1	+23 45 12	0.9265	5868	QSR	1	1342261324-27	⋯
3C337.0	16 28 52.5	+44 19 07c	0.6350	3674	HERG	1	1342261350-53	⋯
3C340.0	16 29 36.6	+23 20 13c	0.7754	4702	HERG	1	1342261321-23	⋯
3C343.0	16 34 33.8	+62 45 36	0.9880	6356	HERGb,c	2	1342234218/19	⋯
3C343.1	16 38 28.2	+62 34 44	0.7500	4511	HERGb	1	1342261364-66	⋯
3C352.0	17 10 44.1	+46 01 29	0.8067	4937	HERG	1	1342256219-21	⋯
3C380.0	18 29 31.8	+48 44 46	0.6920	4081	QSRb	1	1342257947/48	⋯
3C427.1	21 04 06.8	+76 33 11	0.5720	3230	LERG	1	1342261377/78	⋯
3C441.0	22 06 04.9	+29 29 20	0.7080	4193	HERG	1	1342221833-36	⋯
3C455.0	22 55 03.9	+13 13 34	0.5430	3026	HERGb,c	1	1342258014-17	⋯

Notes.

^a1 = OT1_mhaas_2, 2 = OT1_jstevens_1. ^bCSS. ^cCoordinates/classifiaction revised.

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Thus a sample of 37 representative sources was analyzed: seven FSQs (six of them CSS), seven SSQs (one BLRG), twenty-two HERGs (four CSS), and one LERG.

The 3CR sample properties at low redshifts are shown in Table 2. It contains 48 sources at $z\lt 0.5$, 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 3C-sources and the complete Herschel-observed list was collected, which was also observed in the OT1_pogle01_1, OT1_rmushotz_1, OT1_lho_1 and OT1_dfarrah_1 proposals.

Table 2.  3CR Sources $z\lt 0.5$ Observed with Herschel

Name	R.A. [J2000]	Decl. [J2000]	Redshift	${D}_{{\rm{L}}}$ (Mpc)	Type	Proposal-IDa	PACS-OBSID	SPIRE-OBSID
3C020.0	00 43 09.2	+52 03 36b	0.1740	804	HERG	1	⋯	1342265338
3C031.0	01 07 24.9	+32 24 45	0.0170	66	LERGc	3	1342224218/19	1342236245
3C033.0	01 08 52.9	+13 20 14b	0.0597	252	HERG	1	1342261863/64	⋯
3C033.1	01 09 44.3	+73 11 57b	0.1810	842	BLRG	1	1342261944-46	⋯
3C035.0	01 12 02.3	+49 28 36b	0.0670	286	HERG	1	1342261413-16	⋯
3C047.0	01 36 24.4	+20 57 28b	0.4250	2252	QSR	1	⋯	1342261707
3C048.0	01 37 41.3	+33 09 35	0.3670	1892	QSRd	1	⋯	1342261702
3C079.0	03 10 00.1	+17 05 59b	0.2559	1244	HERG	1	1342262229/30	⋯
3C098.0	03 58 54.4	+10 26 03	0.0305	126	HERG	1	1342267198/99	⋯
3C109.0	04 13 40.4	+11 12 15b	0.3056	1529	BLRG	1	1342267272/73	1342266668
3C111.0	04 18 21.3	+38 01 36	0.0485	205	BLRG	4	1342239439/40	1342229105
3C120.0	04 33 11.1	+05 21 16	0.0330	138	BLRG	4	1342241955/56	1342239936
3C123.0	04 37 04.4	+29 40 14	0.2177	1037	LERG	1	1342267256-59	⋯
3C153.0	06 09 32.5	+48 04 15	0.2769	1367	LERG	1	1342267224-27	⋯
3C171.0	06 55 14.8	+54 08 57b	0.2384	1152	HERG	1	1342267228/29	⋯
3C173.1	07 09 18.2	+74 49 32b	0.2921	1453	LERG	1	1342265540/41	⋯
3C192.0	08 05 35.0	+24 09 50	0.0597	260	HERG	1	1342254172/73	⋯
3C200.0	08 27 25.4	+29 18 45	0.4580	2475	LERG	1	1342254174-77	⋯
3C219.0	09 21 08.6	+45 38 57	0.1747	815	BLRG	1	1342254559/60	⋯
3C234.0	10 01 49.5	+28 47 09	0.1849	870	HERG	1	1342255459	1342255182
3C236.0	10 06 01.8	+34 54 10b	0.1005	449	LERG	3	1342246697/98	1342246613
	⋯	⋯	⋯	⋯	⋯	1	1342270912/13	⋯
3C249.1	11 04 13.9	+76 58 58b	0.3115	1566	QSR	5	1342221763-66	1342229630
3C268.3	12 06 24.7	+64 13 37	0.3717	1928	BLRGd	1	1342255424/25	⋯
3C273.0	12 29 06.7	+02 03 09	0.1583	734	QSR	6	⋯	1342234882
3C274.1	12 35 26.7	+21 20 35	0.4220	2246	HERG	1	1342258032-35	⋯
3C285.0	13 21 17.9	+42 35 15	0.0794	349	HERG	1	1342258514/15	1342256880
3C300.0	14 22 59.8	+19 35 37b	0.2700	1331	HERG	1	1342262509-12	⋯
3C305.0	14 49 21.6	+63 16 14	0.0416	177	HERGc	3	1342223959/60	1342234915
3C310.0	15 04 57.1	+26 00 58b	0.0538	233	LERGc	3	1342235116/17	1342234778
3C315.0	15 13 40.1	+26 07 31	0.1083	484	HERGc	3	1342224636/37	1342234777
3C319.0	15 24 04.9	+54 28 06b	0.1920	903	LERG	1	1342231879-82	⋯
3C321.0	15 31 43.5	+24 04 19	0.0961	426	HERG	1	⋯	1342261679
3C326.0	15 52 09.1	+20 05 24b	0.0895	395	LERG	3	1342248732/33	1342238327
3C341.0	16 28 04.0	+27 41 39b	0.4480	2406	HERG	1	1342261328/29	⋯
3C349.0	16 59 28.9	+47 02 55b	0.2050	970	HERG	1	1342261354/55	⋯
3C351.0	17 04 41.4	+60 44 30b	0.3719	1927	QSR	5	1342232428-31	1342229147
3C381.0	18 33 46.3	+47 27 03	0.1605	737	BLRG	1	1342261360/61	⋯
3C382.0	18 35 03.4	+32 41 47	0.0579	246	BLRG	1	1342256206/07	⋯
3C386.0	18 38 26.2	+17 11 50b	0.0169	68	LERGc	3	1342231672/73	1342239789
3C388.0	18 44 02.4	+45 33 30	0.0917	401	LERG	1	1342261356-59	⋯
3C390.3	18 42 08.9	+79 46 17b	0.0561	239	BLRG	1	1342221871/72	⋯
3C401.0	19 40 25.0	+60 41 36b	0.2011	947	LERG	1	1342256194-97	⋯
3C424.0	20 48 12.0	+07 01 17	0.1270	567	LERG	3	1342233349/50	1342244149
3C433.0	21 23 44.5	+25 04 28b	0.1016	445	HERGc	1	1342219391/92	⋯
	⋯	⋯	⋯	⋯	⋯	3	1342232731/32	1342234675
3C436.0	21 44 11.7	+28 10 19	0.2145	1016	HERG	3	1342235316/17	1342234676
	⋯	⋯	⋯	⋯	⋯	1	1342257734-37	⋯
3C438.0	21 55 52.3	+38 00 28b	0.2900	1435	LERG	1	1342259246-49	⋯
3C452.0	22 45 48.8	+39 41 16	0.0811	349	HERG	1	1342259368/69	⋯
3C459.0	23 16 35.2	+04 05 18	0.2201	1045	BLRG	3	1342237979/80	1342234756

Notes.

^a1 = OT1_mhaas_2, 2 = OT1_jstevens_1, 3 = OT1_pogle01_1, 4 = OT1_rmushotz_1, 5 = OT1_lho_1, 6 = OT1_dfarrah_1. ^bcoordinates revised. ^cFR I. ^dCSS.

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Spitzer MIR data are available for all sources. Twenty-three sources were observed in the flux limited sample of Ogle et al. (2006) with ${S}_{178\mathrm{MHz}}\gt 15\;\mathrm{Jy}$. Four remaining sources from the Ogle sample were planned but not observed with Herschel. The rest of the sources were selected from samples already seen with Spitzer by Haas et al. (2005; also observed by the ISO satellite), Cleary et al. (2007), and Hardcastle et al. (2009; X-ray selection).

For the analysis the sample is subdivided into four FSQs (thereof three BLRGs), ten SSQs (thereof six BLRGs), nineteen HERGs, and fifteen LERGs. All but six sources (three HERGs and three LERGs) in this sample are morphologically classified as FR II sources (Fanaroff & Riley 1974).

The data were downloaded from the 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 & Arnouts (1996) was used and additional routines were developed in the Interactive Data Language (IDL) using the IDL Astronomy Library (Landsman 1993).

3.1.1. Observations

3.1.2. PACS-Reduction

3.1.3. SPIRE-Reduction

For the photometry of the SPIRE observations, we followed the steps of the "Recipe for SPIRE Photometry."¹⁰ The recommended algorithm for point source photometry is the timeline-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 $30^{\prime\prime}$ to the coordinates given in Tables 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 ($138^{\prime\prime}$/$230^{\prime\prime}$/$322^{\prime\prime}$ for $250\;\mu {\rm{m}}$/$350\;\mu {\rm{m}}$/$500\;\mu {\rm{m}}$). At these positions, the photometry was carried out in the same manner as for the sources. The dispersion of the distribution gave the 1σ uncertainty or 3σ upper limits, which are given in Tables 4 and 5. Images of size $4^{\prime} \times 4^{\prime}$ are shown in Appendix A.2.

Table 5.  3CR Sources $z\lt 0.5$ PACS and SPIRE Flux Densities

Name	Figure	F70 (mJy)	F100 (mJy)	F160 (mJy)	F250 (mJy)	F350 (mJy)	F500 (mJy)
3C020.0	Figure 11	⋯	⋯	⋯	58(19)	50(16)	<50
3C031.0	Figure 15	⋯	867(3)	1347(11)	955(16)	408(20)	169(20)
3C033.0	Figure 11	161(4)	194(4)	179(8)	⋯	⋯	⋯
3C033.1	Figure 10	38(4)	31(3)	<39	⋯	⋯	⋯
3C035.0	Figure 13	<6	16(3)	<23	⋯	⋯	⋯
3C047.0	Figure 9	⋯	⋯	⋯	<41	<40	<23
3C048.0	Figure 9	⋯	⋯	⋯	311(10)	137(13)	62(10)
3C079.0	Figure 11	65(4)	49(5)	37(10)	⋯	⋯	⋯
3C098.0	Figure 12	41(5)	49(4)	<37	⋯	⋯	⋯
3C109.0	Figure 10	158(4)	106(4)	62(9)	<37	<46	<46
3C111.0	Figure 8	242(6)	⋯	461(24)	577(27)	741(26)	876(31)
3C120.0	Figure 8	783(8)	⋯	1145(20)	634(9)	465(13)	439(16)
3C123.0	Figure 14	22(2)	10(3)	<32	⋯	⋯	⋯
3C153.0	Figure 14	<8	<10	<20	⋯	⋯	⋯
3C171.0	Figure 11	13(4)	<15	<34	⋯	⋯	⋯
3C173.1	Figure 14	<10	13(4)	<30	⋯	⋯	⋯
3C192.0	Figure 13	28(4)	33(4)	<24	⋯	⋯	⋯
3C200.0	Figure 14	<7	12(3)	<18	⋯	⋯	⋯
3C219.0	Figure 10	<11	<12	<29	⋯	⋯	⋯
3C234.0	Figure 11	⋯	87(4)	46(13)	<40	<47	<38
3C236.0	Figure 15	55(5)	90(2)	120(9)	92(13)	81(15)	78(14)
3C249.1	Figure 9	64(3)	62(3)	45(6)	<39	<46	<31
3C268.3	Figure 10	22(3)	32(4)	<26	⋯	⋯	⋯
3C273.0	Figure 8	⋯	⋯	⋯	475(16)	683(11)	1062(20)
3C274.1	Figure 13	<6	<10	<19	⋯	⋯	⋯
3C285.0	Figure 12	222(4)	292(5)	307(11)	180(20)	74(13)	<44
3C300.0	Figure 13	<6	<8	<19	⋯	⋯	⋯
3C305.0	Figure 12	⋯	381(4)	502(9)	254(22)	118(17)	<64
3C310.0	Figure 15	⋯	23(1)	38(3)	<30	<43	<41
3C315.0	Figure 13	⋯	31(3)	36(9)	<24	<27	<27
3C319.0	Figure 14	<7	<11	31(8)	⋯	⋯	⋯
3C321.0	Figure 11	⋯	⋯	⋯	287(16)	108(13)	<40
3C326.0	Figure 15	6(2)	15(1)	19(4)	<30	<20	<23
3C341.0	Figure 11	28(3)	<11	<23	⋯	⋯	⋯
3C349.0	Figure 12	<11	<12	<23	⋯	⋯	⋯
3C351.0	Figure 9	172(3)	156(4)	89(10)	<60	<81	<34
3C381.0	Figure 10	35(4)	34(5)	39(10)	⋯	⋯	⋯
3C382.0	Figure 8	76(4)	96(4)	97(11)	⋯	⋯	⋯
3C386.0	Figure 15	⋯	66(3)	81(9)	<90	<43	<43
3C388.0	Figure 15	<7	<9	<16	⋯	⋯	⋯
3C390.3	Figure 10	157(4)	110(4)	51(8)	⋯	⋯	⋯
3C401.0	Figure 14	<8	<9	<18	⋯	⋯	⋯
3C424.0	Figure 14	⋯	7(1)	<13	<22	<39	<28
3C433.0	Figure 11	294(4)	288(2)	226(6)	120(22)	<51	<46
3C436.0	Figure 13	16(3)	30(2)	37(5)	<51	<30	<40
3C438.0	Figure 14	<7	<11	<42	⋯	⋯	⋯
3C452.0	Figure 12	38(4)	36(5)	27(8)	⋯	⋯	⋯
3C459.0	Figure 10	⋯	584(4)	549(11)	284(15)	115(11)	54(16)

Note.  1σ-errors are given in brackets; upper limits are 3σ.

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Table 6.  Median Spectral Templates for Different Galaxy Types Separated for Low- (z < 0.5) and Medium-redshift (0.5 $\lt \quad z\quad \lt$ 1)

	HERG-low-z	HERG-med-z	LERG	BLRG	FSQ-low-z	FSQ-med-z	SSQ-low-z	SSQ-med-z
$\mathrm{log}({\lambda }_{\mathrm{Rest}})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$	$\mathrm{log}(\nu {L}_{\nu }^{})$
(μm)	$({L}_{\odot })$	$({L}_{\odot })$	$({L}_{\odot })$	$({L}_{\odot })$	$({L}_{\odot })$	$({L}_{\odot })$	$({L}_{\odot })$	$({L}_{\odot })$
−0.4	10.4 ± 0.7	10.7 ± 0.4	⋯	⋯	⋯	11.8 ± 0.3	⋯	12.0 ± 0.6
−0.3	10.7 ± 0.7	11.0 ± 0.3	10.6 ± 1.0	10.7 ± 0.5	11.0 ± 0.4	11.8 ± 0.2	11.6 ± 1.0	12.0 ± 0.6
−0.2	11.0 ± 0.7	11.1 ± 0.3	10.8 ± 0.9	10.9 ± 0.5	10.9 ± 0.3	11.8 ± 0.2	11.6 ± 1.0	12.0 ± 0.6
−0.1	10.9 ± 0.7	11.1 ± 0.3	11.0 ± 0.9	11.0 ± 0.4	10.9 ± 0.3	11.8 ± 0.2	11.6 ± 1.1	12.0 ± 0.4
−0.0	11.0 ± 0.6	11.1 ± 0.2	11.0 ± 0.9	11.0 ± 0.4	10.9 ± 0.3	11.8 ± 0.2	11.6 ± 1.2	12.0 ± 0.4
0.1	11.1 ± 0.5	11.1 ± 0.2	11.2 ± 0.9	11.0 ± 0.3	10.8 ± 0.4	11.8 ± 0.2	11.7 ± 1.2	12.0 ± 0.4
0.2	11.0 ± 0.5	11.1 ± 0.2	11.1 ± 0.9	11.1 ± 0.3	10.9 ± 0.5	11.8 ± 0.2	11.7 ± 1.2	12.0 ± 0.4
0.3	10.9 ± 0.5	11.1 ± 0.2	11.1 ± 1.0	11.1 ± 0.3	11.0 ± 0.4	11.8 ± 0.2	11.7 ± 1.0	12.0 ± 0.4
0.4	10.9 ± 0.5	11.2 ± 0.2	10.5 ± 1.2	11.1 ± 0.3	11.0 ± 0.5	11.8 ± 0.2	11.7 ± 1.0	12.0 ± 0.3
0.5	10.7 ± 0.5	11.3 ± 0.3	10.3 ± 1.3	11.1 ± 0.4	11.0 ± 0.4	11.9 ± 0.2	11.7 ± 1.0	12.2 ± 0.3
0.6	10.6 ± 0.5	11.4 ± 0.3	9.9 ± 1.3	11.1 ± 0.4	10.9 ± 0.4	11.9 ± 0.2	11.7 ± 0.2	12.0 ± 0.2
0.7	10.6 ± 0.5	11.3 ± 0.3	9.5 ± 0.9	11.0 ± 0.5	10.9 ± 0.4	11.9 ± 0.2	11.8 ± 0.2	12.2 ± 0.3
0.8	10.7 ± 0.6	11.5 ± 0.3	9.6 ± 0.9	11.3 ± 0.5	11.0 ± 0.4	12.0 ± 0.2	11.9 ± 0.2	12.1 ± 0.3
0.9	10.7 ± 0.7	11.4 ± 0.3	9.4 ± 0.8	11.0 ± 0.5	10.9 ± 0.4	12.0 ± 0.2	11.9 ± 1.6	12.0 ± 0.3
1.0	10.8 ± 0.7	11.3 ± 0.3	9.4 ± 0.7	11.3 ± 0.5	10.9 ± 0.4	12.0 ± 0.2	12.0 ± 1.5	12.1 ± 0.3
1.1	10.8 ± 0.7	11.3 ± 0.3	9.6 ± 0.7	11.5 ± 0.5	10.8 ± 0.5	12.1 ± 0.2	11.7 ± 0.2	12.1 ± 0.4
1.2	10.9 ± 0.7	11.4 ± 0.4	9.8 ± 0.6	11.5 ± 0.4	10.7 ± 0.5	12.1 ± 0.2	12.1 ± 0.2	12.2 ± 0.4
1.3	10.9 ± 0.7	11.4 ± 0.3	9.8 ± 0.5	11.5 ± 0.5	10.7 ± 0.5	12.0 ± 0.2	12.1 ± 0.3	12.4 ± 0.3
1.4	10.8 ± 0.7	11.3 ± 0.5	9.5 ± 0.5	11.4 ± 0.5	10.6 ± 0.6	12.0 ± 0.2	12.2 ± 0.4	12.5 ± 0.5
1.5	10.8 ± 0.7	11.3 ± 0.5	10.6 ± 0.8	11.3 ± 0.5	10.5 ± 0.7	11.9 ± 0.2	12.1 ± 0.4	12.5 ± 0.5
1.6	10.8 ± 0.7	11.3 ± 0.5	10.7 ± 0.9	11.3 ± 0.5	10.4 ± 0.8	11.9 ± 0.3	12.1 ± 0.4	12.2 ± 0.7
1.7	10.8 ± 0.7	11.2 ± 0.6	10.6 ± 0.9	11.3 ± 0.5	10.3 ± 0.8	11.8 ± 0.3	11.9 ± 0.6	11.6 ± 0.8
1.8	10.5 ± 0.7	11.0 ± 0.7	10.4 ± 0.9	11.2 ± 0.7	10.2 ± 0.8	11.8 ± 0.3	11.8 ± 0.9	11.4 ± 0.8
1.9	10.3 ± 0.8	11.0 ± 0.7	10.0 ± 0.9	11.0 ± 0.8	10.3 ± 0.8	11.7 ± 0.3	11.7 ± 1.0	11.3 ± 0.8
2.0	10.2 ± 0.9	10.9 ± 0.7	9.8 ± 0.9	10.7 ± 0.9	10.3 ± 0.8	11.7 ± 0.3	11.6 ± 1.0	10.9 ± 0.8
2.1	10.1 ± 1.0	10.8 ± 0.6	9.7 ± 0.9	10.5 ± 0.9	10.2 ± 0.7	11.6 ± 0.3	11.3 ± 1.0	10.9 ± 0.8
2.2	9.9 ± 1.0	10.8 ± 0.6	9.5 ± 1.0	10.1 ± 0.8	10.2 ± 0.7	11.6 ± 0.3	11.1 ± 1.0	10.9 ± 0.8
2.3	9.7 ± 1.0	10.8 ± 0.6	9.5 ± 0.9	9.9 ± 0.8	10.2 ± 0.7	11.6 ± 0.3	11.0 ± 1.0	10.9 ± 0.8
2.4	9.6 ± 0.9	10.8 ± 0.6	9.3 ± 0.9	9.8 ± 0.8	10.2 ± 0.7	11.6 ± 0.3	10.9 ± 1.0	10.9 ± 0.8
2.5	9.5 ± 0.9	10.8 ± 0.6	9.2 ± 0.9	9.8 ± 0.8	10.2 ± 0.6	11.6 ± 0.3	10.7 ± 1.0	10.9 ± 0.8
3.0	9.4 ± 0.9	10.6 ± 0.6	9.2 ± 0.9	9.8 ± 0.8	10.1 ± 0.6	11.6 ± 0.3	10.3 ± 1.0	10.9 ± 0.8
3.4	9.4 ± 0.9	10.6 ± 0.6	9.2 ± 0.9	9.8 ± 0.8	10.0 ± 0.5	11.4 ± 0.2	10.3 ± 1.0	10.8 ± 0.8
3.8	9.3 ± 0.7	10.6 ± 0.6	9.2 ± 0.9	9.8 ± 0.8	9.8 ± 0.4	11.2 ± 0.3	10.3 ± 1.0	10.7 ± 0.8
4.2	9.1 ± 0.6	10.4 ± 0.6	9.2 ± 0.8	9.7 ± 0.7	9.6 ± 0.4	11.1 ± 0.3	10.3 ± 0.9	10.6 ± 0.7
4.6	9.0 ± 0.4	10.4 ± 0.3	9.1 ± 0.4	9.6 ± 0.3	9.3 ± 0.5	11.0 ± 0.3	10.2 ± 0.8	10.6 ± 0.2
5.0	9.0 ± 0.1	10.4 ± 0.3	9.1 ± 0.3	9.4 ± 0.1	8.8 ± 0.5	10.8 ± 0.3	⋯	10.5 ± 0.2
5.4	9.0 ± 0.2	10.3 ± 0.2	9.0 ± 0.1	9.4 ± 0.1	8.4 ± 0.4	10.5 ± 0.2	⋯	10.4 ± 0.1
5.8	8.9 ± 0.2	10.2 ± 0.2	8.9 ± 0.2	9.3 ± 0.1	⋯	10.4 ± 0.2	⋯	10.4 ± 0.1
6.2	8.8 ± 0.1	10.1 ± 0.1	8.8 ± 0.1	9.2 ± 0.2	⋯	10.2 ± 0.2	⋯	10.4 ± 0.1
6.6	8.7 ± 0.1	10.0 ± 0.2	8.7 ± 0.1	9.1 ± 0.1	⋯	⋯	⋯	10.3 ± 0.1

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We combined the SEDs in the MIR with data from the ISO (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 $38\;\mu {\rm{m}}$, 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 the 7 and $15\;\mu {\rm{m}}$ rest frame are included. Photometric Spitzer data from the Multiband Imaging Photometer (MIPS; Rieke et al. 2004) at $24\;\mu {\rm{m}}$ are also used (Shi et al. 2005; Cleary et al. 2007; Hardcastle et al. 2009; Fu & Stockton 2009; Dicken et al. 2010; Shang et al. 2011).

We queried the wise_allwise_p 3as_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 four WISE bands ($W1/W2/W3/W4$ at $3.4/4.6/12/22\;\mu {\rm{m}}$) and the point source photometry from the 2MASS catalog for $J,H$, and K filters at 1.235, 1.662, and $2.159\;\mu {\rm{m}}$, respectively.

Among the low-redshift sample, six sources are extended, therefore PSF photometry was replaced by extended apertures¹¹ for 3C 31, 3C 35, 3C 98, 3C 120, 3C 236, and 3C 390. 2MASS photometry for extended sources¹² was delivered by querying fp_xsc catalog with the IDL query_irsa_cat routine.

A query on the SDSS catalog (V/139/sdds9) with the IDL query_vizier routine was performed. Because not all sources were observed in SDSS, we complete the SEDs with data from Laing et al. (1983) and Véron-Cetty & Véron (2010). From the Hubble Space Telescope (HST) snapshot survey, the host contribution in the visible was estimated by taking encircled energy diagrams (EEDs) from Lehnert et al. (1999). Emission line data for [O ii] and [O iii] were collected from Grimes et al. (2004) and Jackson & Rawlings (1997). For the medium-redshift sample, [O iii] was measured for only five objects (3C 207, 3C 254, 3C 263, 3C 265, and 3C 334).

At radio wavelengths the data were collected from NED, which gives reference to the following papers: Pilkington & Scott (1965), Pauliny-Toth et al. (1966), Gower et al. (1967), Aslanian et al. (1968), Kellermann et al. (1969), Colla et al. (1970), Stull (1971), Colla et al. (1972), Kellermann & Pauliny-Toth (1973), Fanti et al. (1974), Laing & Peacock (1980), Kuehr et al. (1981), Large et al. (1981), Geldzahler & Kuhr (1983), Ficarra et al. (1985), Baldwin et al. (1985), Hales et al. (1988), Hales et al. (1990), Becker et al. (1991), Gregory & Condon (1991), Hales et al. (1991), Becker et al. (1995), Waldram et al. (1996), Wiren et al. (1992), Hales et al. (1993), Gear et al. (1994), Hales et al. (1995), Griffith et al. (1995), Klein et al. (1996), Rengelink et al. (1997), Condon et al. (1998), Bennett et al. (2003), Gilbert et al. (2004), Mack et al. (2005), Kassim et al. (2007), Cohen et al. (2007), Mantovani et al. (2009), Wright et al. (2009), Chen & Wright (2009), Chynoweth et al. (2009), Jenness et al. (2010), Agudo et al. (2010), Richards et al. (2011), Gold et al. (2011), Algaba et al. (2011), and Lister et al. (2011).

The quasar SEDs differ in their radio properties. Seven FSQs show a rise in their GHz spectra (e.g., 3C 207, Figure 1), while the seven SSQs have GHz spectra that are constant in $\nu {F}_{\nu }$ (e.g., 3C 175, Figure 2). A strong curvature is found in the MHz to GHz spectra of some CSS quasars and radio galaxies, (e.g., 3C 147 in Figure 1, 3C 343 in Figure 3, and 3C 343.1 in Figure 4); some CSS with modest curvature are 3C 196 in Figure 2, 3C 49 in Figure 3, and 3C 455 in Figure 4.

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We group 3C 147 in the FSQs because of its SED rise between 90 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 (Figures 3, 4).

The SSQs show a 1.5 dex thermal bump in MIR–FIR (Figure 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 toward 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, Figure 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.

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While the MIR SED is well determined in both SSQs and HERGs, the detection rate in the FIR (at rest frame $60\mbox{--}100\;\mu {\rm{m}}$) 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 $40\;\mu {\rm{m}}$. Examples are 3C 147 in Figure 1, 3C 263 in Figure 2, and 3C 226 in Figure 3. The only exception with a good detected FIR plateau beyond $40\;\mu {\rm{m}}$ is 3C 55 in Figure 3. The MIR-bright sources with FIR upper limits mostly show the SED decline longward of $40\;\mu {\rm{m}}$ (e.g., 3C 254 in Figure 2, 3C 22 in Figure 2, and 3C 280 in Figure 3). The remaining sources with FIR upper limits often allow for an SED plateau beyond $40\;\mu {\rm{m}}$ (Figures 4 and 5).

The SED of the LERG 3C 427.1 shows faint MIR (and FIR) emission (Figure 6), corroborating the idea that LERGs are AGN with low accretion activity (Ogle et al. 2006).

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The quasar/BLRG SEDs differ in their radio properties. Four flat-spectrum sources show a rise in their GHz spectra (Figure 8), while the 10 steep-spectrum sources have GHz spectra that are constant in $\nu {F}_{\nu }$ (Figures 9 and 10). A strong curvature is found in the MHz to GHz spectra of two CSS quasars and BLRGs (3C 48 in Figure 9 and 3C 268.3 in Figure 10).

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The steep-spectrum sources show a clear MIR–FIR emission component above the extrapolation of the radio spectrum to shorter wavelengths (Figure 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 (two of the four FSQs and three of the four SSQs) show a strong power law component rising toward 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.

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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 HERGs with strong and medium MIR emission, the SED declines longward of about 30–40 μm.

The SEDs of HERGs with weak MIR emission and of LERGs, show faint MIR emission but mostly a rise toward the FIR (Figures 13–15).

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The SEDs of all sources were scaled to $\nu {L}_{\nu }$ with their luminosity distance ${D}_{{\rm{L}}}$ 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 subsample 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.

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The 178 MHz rest frame 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 changing 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 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 ultraviolet 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 $\nu {L}_{\nu }$ scaling, both quasar types, FSQ and SSQ, show a flat, nearly identical distribution in the range from $0.1\;\mu {\rm{m}}\lesssim \lambda \lesssim 20\;\mu {\rm{m}}$, justifying the assumption that the two classes are intrinsically similar objects. At wavelengths beyond $20\;\mu {\rm{m}}$, the median SED of FSQs and SSQs diverge with a flux higher in the FSQs. This was interpreted in the past as a jet component (Cleary et al. 2007) that is relativistically beamed toward us. Now, with the new Herschel data included, the jet enhancement can be traced to FIR wavelengths for the FSQs, which also shows up in the nonthermal shape of the SED. FIR-inferred star-formation rate (SFR) rates are therefore only 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 a low accretion activity (Ogle et al. 2006). For both types, the MIR shows absorption features from silicate at $9.7\;\mu {\rm{m}}$ that are 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.

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 & Rocca-Volmerange 1997; Bruzual & 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. Heating by the AGN causes the warm dust emission to peak at rest frame 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 re-emission peaks at $\sim 100\;\mu {\rm{m}}$ (Schweitzer et al. 2006; Netzer et al. 2007; Veilleux et al. 2009).

The aim of the analysis is to quantify host galaxy stellar mass and SFRs in the environment of the strong AGN emission, which can contribute at all wavelength ranges. In addition, the question of the unification of radio galaxies and quasars shall be answered at FIR wavelengths where the opacity is low. From the SEDs the following are extracted:

(a) ${L}_{\mathrm{Host}}$, the luminosity of the stars in the host galaxy by integration over fitted synthetic stellar population models by Bruzual & Charlot (2003) (libraries available from Mariska Kriek¹³ ). The luminosity of the stars in the host galaxy ${L}_{{\rm{Host}}}$ (Equation (2)) was derived from the synthetic stellar population templates. With the inherent mass-to-light ratio ${\left(\tfrac{M}{L}\right)}_{\mathrm{BC}03}$ of the templates, stellar masses ${M}_{\star }$ can then be calculated (Equation (3)). Values for both samples are given in Tables 10 and 11. The templates were calculated with an exponentially declining star-formation history (with timescale $\upsilon$ [log years]), metallicities $Z$ ranging from sub- to super-solar, and a Chabrier IMF. Free parameters in the fitting routine were $\upsilon ,Z$, and the age of the stellar population. The synthesized flux densities ${F}_{\lambda }^{0}$ were attenuated for extinction in the interstellar medium, with the dust-attenuation $k(\lambda )$ and ${R}_{{\rm{V}}}\;=$ 4.05 (Calzetti et al. 2000, see Equation (1)). The dependence of the derived stellar masses on the extinction coefficient ${A}_{{\rm{V}}}$ is weak for a sample of early type galaxies (see Swindle et al. 2011); therefore, the median ${A}_{{\rm{V}}}\;=$ 0.1 found for the Swindle et al. (2011) sample was applied here.

$$\begin{eqnarray}&&{F}_{\lambda }^{\mathrm{att}}={F}_{\lambda }^{0}\cdot {10}^{-0.4{A}_{{\rm{V}}}k(\lambda )/{R}_{{\rm{V}}}}\end{eqnarray} \tag{ 1 }$$

$$\begin{eqnarray}&&{L}_{\mathrm{Host}}=4\pi {D}_{{\rm{L}}}^{2}\int {F}_{\nu }^{\mathrm{BC}03}d\nu \end{eqnarray} \tag{ 2 }$$

$$\begin{eqnarray}&&{M}_{\star }={\left(\displaystyle \frac{M}{L}\right)}_{\mathrm{BC}03}\times {L}_{\mathrm{Host}}.\end{eqnarray} \tag{ 3 }$$

(b) ${L}_{\mathrm{AGN}}$, the luminosity of the AGN powered dust (torus) by integration over fitted torus models by Hönig & Kishimoto (2010). The MIR emission was fitted using a template library.¹⁴ Parameters of the best fitting template with the derived total luminosity ${L}_{{\rm{AGN}}}$ (Equation (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 $\theta$, the optical depth $\tau$, and the inclination to the observer $i$.

$$\begin{eqnarray}&&{L}_{\mathrm{AGN}}=4\pi {D}_{{\rm{L}}}^{2}\int {F}_{\nu }^{\mathrm{HK}10}d\nu .\end{eqnarray} \tag{ 4 }$$

(c) ${L}_{\mathrm{FIR}}$, the luminosity of cool FIR emitting dust, by integration of a modified blackbody at 20–50 K ($\beta$ = 1.5), which is given by

$$\begin{eqnarray}&&{F}_{\nu }^{\mathrm{MBB}}\propto {\nu }^{\beta }\ {B}_{\nu }({T}_{{\rm{D}}})\end{eqnarray} \tag{ 5 }$$

and

$$\begin{eqnarray}&&{L}_{\mathrm{FIR}}=4\pi {D}_{{\rm{L}}}^{2}\int {F}_{\nu }^{\mathrm{MBB}}d\nu .\end{eqnarray} \tag{ 6 }$$

The FIR emission can be attributed to dust heated by stars. The integrated luminosity ${L}_{\mathrm{FIR}}$ was used to estimate the SFR by applying Equation (7) (taken from Kennicutt (1998) Equation (4)), which is valid for starbursts with an age less than ${10}^{8}$ years. Values are given in Tables 14 and 15.

$$\begin{eqnarray}&&{\rm{SFR}}\left[\displaystyle \frac{{M}_{\odot }}{{\rm{yr}}}\right]=4.5\times {10}^{-44}{L}_{\mathrm{FIR}}\left[\displaystyle \frac{{\rm{erg}}}{{\rm{s}}}\right].\end{eqnarray} \tag{ 7 }$$

(d) Monochromatic luminosities at rest frame $\nu {L}_{\nu }^{30\;{\rm{GHz}}},\nu {L}_{\nu }^{178\;{\rm{MHz}}}$ were used to trace synchrotron contribution from radio jets and inclination effects in the IR at $\nu {L}_{\nu }^{30\;\mu {\rm{m}}},\nu {L}_{\nu }^{60\;\mu {\rm{m}}},\nu {L}_{\nu }^{100\;\mu {\rm{m}}}$ from interpolated fluxes (Tables 16 and 17).

Present AGN torus models often require an ad hoc $T=1300\quad {\rm{K}}$ (Leipski et al. 2013; Podigachoski et al. 2015b) dust component in quasars to fit the near-infrared (NIR) bump around $3\;\mu {\rm{m}}$. 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 an SED peak beyond $\sim 80\;\mu {\rm{m}}$. This increases the ambiguity of AGN-SF model fitting, and star formation may be even lower than indicated by our analysis here.

The fitting of all components was achieved by the application of a Metropolis–Hastings algorithm under the investigation of the posterior probability $\mathrm{Post}(M| D)$ of the model $M$ fitting the data $D$, which can be written after Baye's theorem (Equation (8)) with the prior of the model $\mathrm{Prior}(M)$ and data $\mathrm{Prior}(D)$, and the likelihood of the data given the model $\mathrm{Like}(D| M)$.

$$\begin{eqnarray}&&\mathrm{Post}(M| D)=\displaystyle \frac{\mathrm{Like}(D| M)\mathrm{Prior}(M)}{\mathrm{Prior}(D)}\end{eqnarray} \tag{ 8 }$$

The prior $\mathrm{Prior}(p)$ of a single model parameter $p$ in the range of the maximum and minimum allowed values ${p}_{\mathrm{max}}$ and ${p}_{\mathrm{min}}$ is given by the probability density of the uniform distribution (Equation (9)).

$$\begin{eqnarray}&&\mathrm{Prior}(p)=\displaystyle \frac{1}{{p}_{\mathrm{max}}-{p}_{\mathrm{min}}}.\end{eqnarray} \tag{ 9 }$$

Then the prior $\mathrm{Prior}(M)$ of the whole model can be written in logarithmic space as Equation (10).

$$\begin{eqnarray}&&\mathrm{Prior}(M)=\sum _{i}\mathrm{lnPrior}({p}_{i}).\end{eqnarray} \tag{ 10 }$$

The likelihood $\mathrm{Like}(d| m)$ of the single model point $m$ fitting a data point $d$ with mean value $\mu$ and standard deviation $\sigma$ is given by the probability density of the normal distribution (Equation (11)).

$$\begin{eqnarray}&&\mathrm{Like}(d| m)=\displaystyle \frac{1}{\sqrt{2\pi }\sigma }{e}^{\displaystyle \frac{-{(m-\mu )}^{2}}{2{\sigma }^{2}}}.\end{eqnarray} \tag{ 11 }$$

The likelihood $\mathrm{Like}(D| M)$ of the whole model $M$ fitting the data $D$ can then be written like Equation (12).

$$\begin{eqnarray}&&\mathrm{Like}(D| M)=\sum _{i}\mathrm{lnLike}({d}_{i}| {m}_{i}).\end{eqnarray} \tag{ 12 }$$

With this nomenclature, a constant $\mathrm{Prior}(D)$, and using the logarithmic metric, the posterior probability is calculated like Equation (13).

$$\begin{eqnarray}&&\mathrm{Post}(M| D)=\mathrm{Like}(D| M)+\mathrm{Prior}(M)\end{eqnarray} \tag{ 13 }$$

Modeling 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 the host-, torus-, and FIR-template, while ${\mathrm{Metal}}_{\mathrm{start}}=0.5$, ${\upsilon }_{\mathrm{start}}={10}^{7},{\mathrm{Age}}_{\mathrm{start}}={10}^{9.5}$ for the host ${N}_{\mathrm{start}}=5.0,{a}_{\mathrm{start}}=-1,{\theta }_{{\rm{start}}}=32.5$ and ${\tau }_{\mathrm{start}}=35$ for the torus were selected equally for all sources. The start value for the inclination was set to $5^\circ$ for type-1 sources and $45^\circ$ for type-2 sources. The start value for ${T}_{\mathrm{FIR}}$ 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 ${M}_{i+1}={func}\_{proposal}({M}_{i})$ that 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 $\mathrm{Post}({M}_{i}| D)$ was compared and normalized to the new proposed model set $\mathrm{Post}({M}_{i+1}| D)$ and the probability of an improvement was computed via Equation (14)

$$\begin{eqnarray}&&\mathrm{Prob}({M}_{i}| {M}_{i+1}| D)={e}^{\mathrm{Post}({M}_{i+1}| D)-\mathrm{Post}({M}_{i}| D)}.\end{eqnarray} \tag{ 14 }$$

The computed value of $\mathrm{Prob}({M}_{i}| {M}_{i+1}| D)$ was compared to a uniformally distributed random number between 0 and 1. If $\mathrm{Prob}({M}_{i}| {M}_{i+1}| D)$ 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 models that do not seem to be an actual improvement retain a small chance to enter the chain. By this behavior, the Metropolis–Hastings algorithm is able to leave local maxima in the posterior space and search for the global one. For each model, 10,000 chain values were calculated and the last 5000 iterations were used for the analysis via histograms for each model parameter (see Figures 17–19).

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Based on $15\;\mu {\rm{m}}$ luminosity measured in the Spitzer IRS spectra, Ogle et al. (2006) defined MIR-weak sources by an absolute monochromatic threshold, $\nu {L}_{\nu }^{15\;\mu {\rm{m}}}\lt 8\cdot {10}^{43}\;\mathrm{erg}\;{{\rm{s}}}^{-1}$ (roughly corresponding to the integrated luminosity of the torus model fit of ${L}_{\mathrm{MIR}}=2\cdot {10}^{10}\;{L}_{\odot }$). While successfully identifying MIR-weak sources at low redshift, potential analogs at higher redshift may be missed because they fall below the detection limit, thus a more flexible definition is desired (${F}_{\nu }^{15\;\mu {\rm{m}}}$ is also 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: ${L}_{{\rm{MIR}}}/{L}_{{\rm{Host}}}\;\lt$ 1 (Figure 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. In addition, two MIR-weak BLRGs (3C 219 and 3C 382) are found according to this definition.

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For 3C 219 (see Figure 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 ${L}_{{\rm{MIR}}}{/L}_{{\rm{Host}}}\lt \tfrac{1}{3}$ is also indicated in Figure 20, which would exclude the two BLRGs, as well as two LERGs and several HERGs from the MIR-weak definition.

The definition is motivated by the relation of black hole and bulge masses (Häring & 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 ${M}_{{\rm{BH}}}$ were calculated with Equation (15), taken from Häring & Rix (2004) with stellar mass estimates ${M}_{\star }$ derived from the host luminosities ${L}_{{\rm{Host}}}$ as input (see Tables 10 and 11). We find black hole masses in the range of $\approx {10}^{6}\mbox{--}{10}^{9}\;{M}_{\odot }$, which is consistent with the range found for example by Tremaine et al. (2002).

$$\begin{eqnarray}\mathrm{log}({M}_{{\rm{BH}}}/{M}_{\odot }) & = & (8.2\pm 0.1)+(1.12\pm 0.06)\\ & & \times \quad \mathrm{log}({M}_{{\rm{Bulge}}}/{10}^{11}\;{M}_{\odot })\end{eqnarray} \tag{ 15 }$$

With the derived black hole masses ${M}_{{\rm{BH}}}$, we are able to calculate the limiting Eddington luminosity ${L}_{{\rm{Edd}}}$ as Equation (16). The ratio of AGN luminosity in the MIR and Eddington luminosity ${L}_{\mathrm{AGN}}/{L}_{\mathrm{Edd}}$ 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.

$$\begin{eqnarray}&&{L}_{{\rm{Edd}}}\approx 3.2\times {10}^{4}\left(\displaystyle \frac{{M}_{{\rm{BH}}}}{{M}_{\odot }}\right)\;{L}_{\odot }\end{eqnarray} \tag{ 16 }$$

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 at higher redshift. (In fact, we find MIR-weak sources that exceed Ogle et al.'s absolute luminosity limit by about a factor of 10). In the plots, MIR-weak sources are marked with a superposed "x."

Beyond $z\gt 0.5$, the 3C-sample contains five MIR-weak HERGs, but only one LERG 3C 427.1 (${L}_{\mathrm{MIR}}$ upper limit, Figure 20). The lack of LERGs raises the question of 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 [O ii]/[O iii] > 1 (LERG) and [O ii]/[O iii] < 1 (HERG), using the spectroscopic data from Jackson & Rawlings (1997) and Grimes et al. (2004). Due to the shift of the [O iii] line from the rest frame wavelength of 5007 Å to infrared wavelengths, only seven sources of the medium-redshift sample (3C 207, 3C 220.1, 3C 254, 3C 263, 3C 265, 3C 280 and 3C 334) have measured [O iii] fluxes. The other [O iii] fluxes given by Grimes et al. (2004) have been extrapolated from Jackson & 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.

For the low-redshift sample, the coverage of tabulated emission line data in [O ii] and [O iii] is better and consistent with the HERG classifications (except for the starburst galaxy 3C 459), but the classification could only be confirmed for one LERG (3C 236); the others have no emission line data available.

We find two MIR-weak BLRGs (3C 219 and 3C 382), which could be the broad-line counterparts of the otherwise type-2 dominated MIR-weak 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 ratio 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, MIR-weak 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" versus "advection dominated" accretion (Ogle et al. 2006).

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. Figure 21 (right) shows the ratio ${L}_{\mathrm{MIR}}/{L}_{{\rm{O}}{\rm{III}}}$, which appears similar over four orders of magnitude for all three classes: QSRs, HERGs, and LERGs. The relation was fitted for all classes (see Equation (17)) and for the LERGs separately (see Equation (18)). There is a trend that LERGs have about a factor 3 higher ${L}_{{\rm{O}}{\rm{III}}}$ compared to QSRs and HERGs of the same ${L}_{\mathrm{MIR}}$ (all LERGs except 3C 236 lie on the right side of the median relationship in Figure 21, right). This trend can be explained by differences in the dust torus or an 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. In addition, a central engine with a lower production rate of ionizing photons is thinkable. Best-fit relations are:

$$\begin{eqnarray}\mathrm{log}({L}_{\mathrm{MIR}}^{\mathrm{All}}/{L}_{\odot }) & = & (2.4\pm 0.8)+(1.0\pm 0.1)\\ & & \times \quad \mathrm{log}({L}_{{\rm{O}}{\rm{III}}}/{L}_{\odot })\end{eqnarray} \tag{ 17 }$$

$$\begin{eqnarray}\mathrm{log}({L}_{\mathrm{MIR}}^{{\rm{LERG}}}/{L}_{\odot }) & = & (1.9\pm 0.7)+(1.0\pm 0.1)\\ & & \times \quad \mathrm{log}({L}_{{\rm{O}}{\rm{III}}}/{L}_{\odot })\end{eqnarray} \tag{ 18 }$$

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In Figure 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 Equations (19)–(21)). At $\nu {L}_{\nu }^{178\;{\rm{MHz}}}=5\cdot {10}^{9}\;{L}_{\odot }$ the low from the medium-redshift sample are separated; there are only three low-$z$ exceptions (3C 47, 3C 48, and 3C 123) exceeding that radio luminosity threshold.

$$\begin{eqnarray}\mathrm{log}({L}_{\mathrm{MIR}}^{{\rm{QSR}}}/{L}_{\odot }) & = & (6.3\pm 0.6)+(0.61\pm 0.07)\\ & & \times \quad \mathrm{log}({L}_{\nu }^{178\;{\rm{MHz}}}/{L}_{\odot })\end{eqnarray} \tag{ 19 }$$

$$\begin{eqnarray}\mathrm{log}({L}_{\mathrm{MIR}}^{{\rm{HERG}}}/{L}_{\odot }) & = & (4.0\pm 0.9)+(0.8\pm 0.1)\\ & & \times \quad \mathrm{log}({L}_{\nu }^{178\;{\rm{MHz}}}/{L}_{\odot })\end{eqnarray} \tag{ 20 }$$

$$\begin{eqnarray}\mathrm{log}({L}_{\mathrm{MIR}}^{{\rm{LERG}}}/{L}_{\odot }) & = & (3.3\pm 1.1)+(0.8\pm 0.1)\\ & & \times \quad \mathrm{log}({L}_{\nu }^{178\;{\rm{MHz}}}/{L}_{\odot }).\end{eqnarray} \tag{ 21 }$$

The HERGs and LERGs show a remarkably similar ${L}_{{\rm{MIR}}}/{L}_{\nu }^{178\;{\rm{MHz}}}$ slope, apart from the offset, while the quasars show a flatter ${L}_{{\rm{MIR}}}/{L}_{\nu }^{178\;{\rm{MHz}}}$ 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. (2015b) for the high-z quasars. Thus the integrated luminosity ${L}_{{\rm{MIR}}}$ 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. 2015a).

Likewise, both LERGs and MIR-weak HERGs show a 2–20 times weaker ${L}_{\mathrm{MIR}}/\nu {L}_{\nu }^{178\;{\rm{MHz}}}$ ratio than the MIR-strong HERGs, which is caused by decreased MIR rather than increased radio luminosity. Differences in the central engine can cause different AGN SEDs or the 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.

5.3.1. 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 $\alpha$) to contribute to the MIR and FIR (Figure 2). This is comparable to radio-quiet quasars as seen by Chini et al. (1989). The other six SSQs do not have 1.2 mm measurements, but the same picture can be assumed for them.

In contrast, the seven FSQs have a rising GHz spectrum and beamed emission may contribute to the FIR and MIR (Figure 1). A strong FIR contribution is immediately obvious for 3C 138, 3C 216, and 3C 286. In the MIR, however, a sharp bump at $\sim 20\;\mu {\rm{m}}$ can be identified in most sources except 3C 207 and 3C 216. The NIR 3–4 $\mu {\rm{m}}$ bump is also 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 Figure 8, where the nonthermal contribution can be traced to the FIR for 3C 111, 3C 120, 3C 273, and 3C 382. The SSQs and BLRGs plots show (Figures 9 and 10) that the FIR is dominated by dust emission.

Following the concept introduced by Meisenheimer et al. (2001), we determined the dust-to-radio ratio ${R}_{\mathrm{DR}}=\nu {F}_{\nu }^{\mathrm{IR}}/\nu {F}_{\nu }^{178\;{\rm{MHz}}}$ at 30 and $100\;\mu {\rm{m}}$. To quantify the dependence of ${L}_{\mathrm{IR}}$ at 30 and 100 $\mu {\rm{m}}$ on the radio slope, we consider ${R}_{\mathrm{DR}}$ versus ${R}_{\mathrm{GM}}=\nu {L}_{\nu }^{30\;{\rm{GHz}}}/\nu {L}_{{nu}}^{178\;{\rm{MHz}}}$ (Figure 22). ${R}_{\mathrm{GM}}$ clearly separates FSQs from SSQs, with a dividing ratio ${R}_{\mathrm{GM}}\;=$ 5. On the vertical axes, figure 22 shows the ${R}_{\mathrm{DR}}$ distributions at 30 and 100 $\mu {\rm{m}}$ for the different AGN types. The large crosses mark the averages (in log space) and the dex range for the different AGN types:

• 1.  
  yellow/black: LERGs, excluding FR I and 3C 236 as outlier
• 2.  
  red: HERGs, excluding CSS, FR I, and MIR-weak sources
• 3.  
  blue: SSQs (i.e., steep-spectrum QSRs and BLRGs excluding CSS)
• 4.  
  green: FSQs (i.e., flat-spectrum QSRs and BLRGs).

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5.3.2. Cosmological Evolution of Radio Activity

5.3.3. SSQ/MIR-strong HERG Unification

To estimate the star-forming luminosity ${L}_{\mathrm{FIR}}$, 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 & Kishimoto (2010); in cases of different chemical dust composition and grain geometries, the AGNs create larger emission at longer wavelengths (Siebenmorgen et al. 2015). Therefore the ${L}_{\mathrm{FIR}}$ and SFR derived from our SED fits may be overestimated and the actual SFR may be smaller, so we treat our estimates as maximum possible SFR. Other star-formation indicators (e.g., via optical Blmer 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 an important role in quasars and radio galaxies.

To provide a tentative cross check, we converted both ${L}_{\mathrm{FIR}}$ and ${L}_{{\rm{O}}{\rm{II}}}$ into SFRs ${{\rm{SFR}}}_{\mathrm{FIR}}$ and ${{\rm{SFR}}}_{{\rm{O}}{\rm{II}}}$ using the scaling relations (Equations (7) and (22); Kennicutt 1998).

$$\begin{eqnarray}&&{\rm{SFR}}\left[\displaystyle \frac{{M}_{\odot }}{{\rm{yr}}}\right]=(1.4\pm 0.4)\times {10}^{-41}{L}_{{\rm{O}}{\rm{II}}}\left[\displaystyle \frac{{\rm{erg}}}{{\rm{s}}}\right]\end{eqnarray} \tag{ 22 }$$

The SFRs derived from both indicators match within an order of magnitude (Figure 23). There is no correlation between ${{\rm{SFR}}}_{{\rm{O}}{\rm{II}}}$ and ${{\rm{SFR}}}_{\mathrm{FIR}}$ in the medium-redshift sample, where a higher AGN-triggered [O ii] emission has to be taken into account. We find a correlation for the low-redshift sample, but ${{\rm{SFR}}}_{{\rm{O}}{\rm{II}}}$ is larger than ${{\rm{SFR}}}_{\mathrm{FIR}}$. Because we have not subtracted AGN contributions from ${L}_{{\rm{O}}{\rm{II}}}$, we suggest that ${{\rm{SFR}}}_{{\rm{O}}{\rm{II}}}$ is overestimated as well.

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For most 3CR sources, the ratio ${L}_{\mathrm{FIR}}/{L}_{\mathrm{Host}}\lt 1$ 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 ${M}_{{\rm{D}}}$ from ${L}_{\nu }^{100\;\mu {\rm{m}}}$ and the dust temperature ${T}_{{\rm{D}}}$, we used

$$\begin{eqnarray}&&{M}_{{\rm{D}}}=\displaystyle \frac{{D}_{{\rm{L}}}^{2}{F}_{\nu }}{{\kappa }_{\nu }{B}_{\nu }({T}_{{\rm{D}}})}\end{eqnarray} \tag{ 23 }$$

with dust opacity ${\kappa }_{100\mu {\rm{m}}}=27\;{{\rm{cm}}}^{2}\;{g}^{-1}$ (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-to-stellar mass ratio lies in the range ${10}^{-3}\mbox{--}{10}^{-5}$. 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 (${M}_{{\rm{D}}}$ is especially sensitive to ${T}_{{\rm{D}}}$), 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 ${{\rm{SFR}}}_{{\rm{O}}{\rm{II}}}$ and ${{\rm{SFR}}}_{\mathrm{FIR}}$.

In the following, we use ${{\rm{SFR}}}_{\mathrm{FIR}}$. 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 ${M}_{\mathrm{Host}}$, which was 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, ${L}_{\mathrm{FIR}}$ might be overestimated due to synchrotron contamination and SFR upper limits are plotted. Conversely, for type-2 AGN and steep-spectrum BLRGs, ${M}_{\mathrm{Host}}$ 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 ${M}_{\mathrm{Host}}$ 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 $\approx {10}^{12}\;{M}_{\odot }$, which are rare in the local universe ($z\lt 0.3$), but also have been reported recently for quasar host galaxies at redshifts <1 (see Figure 7 of Matsuoka et al. 2015). For three sources (3C 6.1, 3C 184, and 3C 280) no optical data are available. In these sources, the host fit is based on the WISE measurements where confusion within the WISE beam cannot 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 ${10}^{12}\;{M}_{\odot }$, and the FIR luminosities are about ${10}^{10}\;{L}_{\odot }$ (Tables 11 and 15). In Figure 24 (left) the results are plotted together with a comparison sample of SDSS galaxies in the redshift range 0.015 $\lt \;z\;\lt$ 0.1 investigated by Brinchmann et al. (2004) and Kauffmann et al. (2003). The relation between the SFR and mass for the SDSS galaxies is:

$$\begin{eqnarray}&&{{\rm{SFR}}}_{{\rm{SDSS}}}\left[\displaystyle \frac{{M}_{\odot }}{{\rm{yr}}}\right]=8.7[-3.7,+7.4]\times {\left[\displaystyle \frac{{M}_{\star }}{{10}^{11}{M}_{\odot }}\right]}^{0.77}.\end{eqnarray} \tag{ 24 }$$

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For the medium-redshift sample, the range of ${L}_{\mathrm{FIR}}$ lies around ${10}^{11}\;{L}_{\odot }$ (Figure 24 right, Table 14; i.e., that of IR luminous SF galaxies (LIRGs) with a few sources above ${10}^{12}\;{L}_{\odot }$ in the regime of ULIRGs). Derived host masses lie in the range of ${10}^{11}\mbox{--}{10}^{12}\;{M}_{\odot }$, which means they're 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 ${10}^{9}\;{M}_{\odot }\lt {M}_{\star }\lt {10}^{12}\;{M}_{\odot },1\quad {M}_{\odot }{{\rm{yr}}}^{-1}\lt {\rm{SFR}}\lt 300\quad {M}_{\odot }{{\rm{yr}}}^{-1}$), 0.8 $\lt \;z\;\lt$ 1.2 has:

$$\begin{eqnarray}&&{{\rm{SFR}}}_{\mathrm{GOODS}}\left[\displaystyle \frac{{M}_{\odot }}{{\rm{yr}}}\right]=7.2[-3.6,+7.2]\times {\left[\displaystyle \frac{{M}_{\star }}{{10}^{10}{M}_{\odot }}\right]}^{0.9}.\end{eqnarray} \tag{ 25 }$$

To provide a panoptic view, the whole investigated 3CR sample is shown together with the appropriate comparison samples in Figure 24. The bulk of 3CR galaxies show only a small specific SFR for their epoch. The few exceptions are 3C 49, 3C 55, and 3C 343 for the medium-redshift sample and 3C 48, 3C 321, and 3C 459 for the low-redshift sample.

For the HERG, LERG, and BLRG class, both stellar masses and SFRs establish that the 3Cs at z < 1 belong to the most massive galaxies of their epoch, but most have a low specific star-forming activity. This is remarkably different from the results for 3CR sources at 1 $\lt \;z\;\lt$ 2 (Podigachoski et al. 2015b), where ≈40% show ULIRG-like SFRs (200–2000 ${M}_{\odot }$ yr⁻¹) at similar host masses (${10}^{11}\mbox{--}{10}^{12}\quad {M}_{\odot }$). 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.

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, where a low extinction enables bright [O ii] emission; where the environment favors a high radio lobe luminosity is raised in Sections 5.1 and 5.2. MIR-weak sources and LERGs populate the low end of the FIR ${R}_{\mathrm{DR}}$ distributions (Figure 22). The overall trends in Figure 22 make an evolutionary HERG-to-LERG scenario attractive, 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 MIR-weak HERGs populate the same host and radio lobe luminosity ranges as the MIR-strong HERGs and QSRs (Figures 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 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 and redshifts. In the medium-$z$ sample, however, MIR-weak sources (and LERGs) are rare, even with our new definition of MIR weakness 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 (Figure 21). This suggests that the MIR-weak successors of MIR-strong HERGs at $0.5\lt z\lt 1$ decline in lobe luminosity, so that they fall below the 178 MHz flux limit of the 3CR sample. The timescales of radio loudness are in the order of several ${10}^{7}$ years, which is much shorter than the age range of the sample. Thus, any LERG-successors of MIR-strong HERGs of the $0.5\lt z\lt 1$ 3CR sample cannot have moved out of that redshift range. For example $t(z=0.55)-t(z=0.53)\approx 1.5\cdot {10}^{8}\;{\rm{years}}$ (Wright 2006).

(c) Another possibility is that MIR-weak sources and LERGs do not exist in the early, say $z\gt 0.75$ 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 intracluster gas may enhance the radio lobes, as found for Cygnus A by Barthel & Arnaud (1996). Because the timescale for cluster formation is much higher than the radio-loud phase, an MIR-strong 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 future work is required to solve the puzzle on the relation between the MIR-weak and MIR-strong sources.

This Appendix contains Tables 7–17, which show the compositions of the median SEDs, the model parameters of all SED fits and derived quantities.

Table 9.  Model Parameters

Host				Torus						FIR
${A}_{\mathrm{Host}}$	Metal.	$\upsilon$	Age	${A}_{\mathrm{AGN}}$	i	N	a	θ	τ	${A}_{\mathrm{FIR}}$	${T}_{\mathrm{FIR}}$
(W m−2)		(logyears)	(logyears)	(W m−2)	(deg)			(deg)		(W m−2)	(K)
var.a	0–1b	6.5–11	9–10.2	var.a	0–90c	2.5–10d	−2–0e	5–60f	30–80g	var.a	var.a

Notes.

^aVaries in the range of 200% to one 50% of individual start value. ^bThe interval of [0, 1] corresponds to metallicities of Z = [0.004, 0.008, 0.02, 0.05]. ^cSteps of 15°. ^dSteps of 2.5. ^eSteps of 0.5. ^fSteps of [5, 30, 45, 60]. ^gSteps [30, 50, 80].

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Table 10.  Host Fit Parameters for the 3Cs at 0.5 $\lt \;z\;\lt$ 1.0

Name	${A}_{\mathrm{Host}}\left[\mathrm{log}\left(\tfrac{{\rm{W}}}{{{\rm{m}}}^{2}}\right)\right]$	Z	$\upsilon$ [log(years)]	Age [log(years)]	${M}_{\star }[{10}^{11}\quad {M}_{\odot }]$	${L}_{\mathrm{Host}}[{10}^{11}\;{L}_{\odot }]$	${M}_{\mathrm{BH}}[{10}^{7}\;{M}_{\odot }]$
3C006.1	$-{15.18}_{-0.11}^{+0.10}$	0.008	${9.0}_{-0.9}^{+0.9}$	${9.90}_{-0.16}^{+0.13}$	${10.0}_{-3.9}^{+3.8}$	${8.2}_{-2.1}^{+3.1}$	${208.9}_{-123.3}^{+232.7}$
3C022.0	$-{15.18}_{-0.19}^{+0.10}$	0.02	${10.0}_{-0.6}^{+0.3}$	${9.50}_{-0.12}^{+0.09}$	${7.1}_{-3.3}^{+3.7}$	${11.0}_{-4.1}^{+3.1}$	${142.4}_{-90.5}^{+188.3}$
3C049.0	$-{15.40}_{-0.14}^{+0.14}$	0.008	${7.6}_{-0.7}^{+0.8}$	${9.30}_{-0.06}^{+0.12}$	${1.1}_{-0.4}^{+0.6}$	${2.5}_{-0.7}^{+0.9}$	${17.6}_{-9.0}^{+18.9}$
3C055.0	$-{15.21}_{-0.19}^{+0.18}$	0.004	${8.1}_{-1.2}^{+1.6}$	${9.50}_{-0.07}^{+0.07}$	${2.7}_{-1.5}^{+1.9}$	${6.0}_{-2.3}^{+3.1}$	${48.2}_{-32.9}^{+72.6}$
3C138.0	$-{15.24}_{-0.22}^{+0.10}$	0.02	${7.3}_{-0.4}^{+0.8}$	${9.20}_{-0.16}^{+0.07}$	${2.5}_{-1.0}^{+1.0}$	${5.7}_{-2.3}^{+1.4}$	${44.2}_{-24.6}^{+42.1}$
3C147.0	$-{14.92}_{-0.09}^{+0.04}$	0.02	${6.9}_{-0.3}^{+0.6}$	${9.30}_{-0.05}^{+0.16}$	${3.0}_{-0.8}^{+1.0}$	${5.4}_{-1.0}^{+0.5}$	${54.2}_{-24.6}^{+48.2}$
3C172.0	$-{15.21}_{-0.05}^{+0.04}$	0.05	${8.3}_{-1.1}^{+0.6}$	${9.60}_{-0.09}^{+0.18}$	${2.1}_{-0.4}^{+0.6}$	${2.2}_{-0.2}^{+0.2}$	${36.4}_{-14.6}^{+29.2}$
3C175.0	$-{14.54}_{-0.15}^{+0.09}$	0.05	${8.1}_{-0.5}^{+0.6}$	${9.30}_{-0.07}^{+0.25}$	${18.0}_{-5.3}^{+3.7}$	${28.0}_{-8.5}^{+7.8}$	${403.6}_{-217.3}^{+349.8}$
3C175.1	$-{15.13}_{-0.14}^{+0.27}$	0.05	${8.7}_{-1.4}^{+1.8}$	${10.00}_{-0.13}^{+0.08}$	${19.0}_{-7.2}^{+19.0}$	${9.8}_{-2.7}^{+8.4}$	${428.7}_{-256.5}^{+1030.6}$
3C184.0	$-{15.64}_{-0.12}^{+0.11}$	0.02	${8.9}_{-0.8}^{+1.7}$	${9.90}_{-0.17}^{+0.30}$	${4.2}_{-1.3}^{+1.8}$	${4.2}_{-1.2}^{+2.3}$	${79.1}_{-40.2}^{+86.2}$
3C196.0	$-{14.96}_{-0.09}^{+0.07}$	0.004	${7.5}_{-0.6}^{+0.8}$	${9.40}_{-0.26}^{+0.07}$	${7.5}_{-3.3}^{+2.3}$	${15.0}_{-3.3}^{+2.8}$	${151.4}_{-93.8}^{+143.5}$
3C207.0	$-{15.10}_{-0.12}^{+0.06}$	0.05	${7.5}_{-0.7}^{+0.7}$	${9.30}_{-0.20}^{+0.13}$	${3.1}_{-1.0}^{+1.0}$	${5.7}_{-1.3}^{+0.9}$	${56.3}_{-28.6}^{+48.3}$
3C216.0	$-{15.15}_{-0.22}^{+0.16}$	0.05	${7.5}_{-0.9}^{+1.1}$	${9.30}_{-0.08}^{+0.18}$	${2.5}_{-1.2}^{+1.6}$	${5.2}_{-2.3}^{+2.2}$	${44.2}_{-27.6}^{+61.2}$
3C220.1	$-{15.36}_{-0.10}^{+0.10}$	0.05	${7.5}_{-0.7}^{+2.2}$	${9.40}_{-0.27}^{+0.28}$	${1.3}_{-0.6}^{+0.7}$	${2.4}_{-0.5}^{+0.7}$	${21.3}_{-12.8}^{+23.1}$
3C220.3	$-{15.17}_{-0.20}^{+0.18}$	0.008	${7.9}_{-1.1}^{+0.9}$	${9.60}_{-0.14}^{+0.13}$	${3.7}_{-1.8}^{+2.5}$	${5.2}_{-2.0}^{+2.5}$	${68.6}_{-43.8}^{+103.2}$
3C226.0	$-{15.23}_{-0.23}^{+0.15}$	0.05	${7.6}_{-0.7}^{+1.0}$	${9.70}_{-0.10}^{+0.17}$	${7.6}_{-3.3}^{+3.1}$	${6.0}_{-2.4}^{+2.4}$	${153.6}_{-94.6}^{+173.5}$
3C228.0	$-{15.39}_{-0.05}^{+0.04}$	0.02	${9.2}_{-2.0}^{+1.4}$	${10.00}_{-0.11}^{+0.07}$	${3.5}_{-0.8}^{+0.6}$	${1.7}_{-0.2}^{+0.2}$	${64.5}_{-28.8}^{+41.6}$
3C254.0	$-{15.06}_{-0.06}^{+0.03}$	0.008	${8.2}_{-0.6}^{+0.9}$	${9.80}_{-0.16}^{+0.10}$	${8.5}_{-2.2}^{+2.4}$	${7.5}_{-1.1}^{+0.8}$	${174.2}_{-85.6}^{+160.2}$
3C263.0	$-{14.42}_{-0.09}^{+0.07}$	0.05	${7.0}_{-0.4}^{+0.6}$	${9.20}_{-0.10}^{+0.06}$	${12.0}_{-2.4}^{+2.7}$	${24.0}_{-4.8}^{+4.2}$	${256.3}_{-117.8}^{+219.5}$
3C263.1	$-{15.57}_{-0.12}^{+0.10}$	0.004	${8.9}_{-1.9}^{+1.5}$	${10.00}_{-0.14}^{+0.08}$	${4.8}_{-1.6}^{+1.6}$	${3.2}_{-0.8}^{+0.8}$	${91.8}_{-48.6}^{+86.5}$
3C265.0	$-{15.32}_{-0.22}^{+0.15}$	0.05	${7.7}_{-0.6}^{+0.4}$	${9.60}_{-0.13}^{+0.14}$	${4.5}_{-1.7}^{+2.5}$	${4.8}_{-1.9}^{+2.1}$	${85.4}_{-47.9}^{+112.8}$
3C268.1	$-{15.62}_{-0.07}^{+0.10}$	0.02	${9.3}_{-0.9}^{+0.9}$	${10.00}_{-0.14}^{+0.09}$	${7.3}_{-2.4}^{+2.0}$	${4.0}_{-0.8}^{+1.3}$	${146.9}_{-79.0}^{+130.3}$
3C280.0	$-{15.59}_{-0.21}^{+0.12}$	0.004	${8.4}_{-1.2}^{+1.1}$	${10.00}_{-0.21}^{+0.09}$	${6.7}_{-2.8}^{+3.4}$	${4.9}_{-1.9}^{+1.7}$	${133.4}_{-80.1}^{+172.1}$
3C286.0	$-{14.89}_{-0.15}^{+0.11}$	0.008	${7.6}_{-0.9}^{+1.5}$	${9.60}_{-0.09}^{+0.25}$	${15.0}_{-5.1}^{+5.3}$	${18.0}_{-5.5}^{+4.7}$	${329.0}_{-186.0}^{+367.4}$
3C289.0	$-{15.60}_{-0.09}^{+0.09}$	0.02	${8.2}_{-0.6}^{+0.4}$	${9.40}_{-0.07}^{+0.11}$	${3.0}_{-0.6}^{+1.1}$	${4.4}_{-0.8}^{+1.1}$	${54.2}_{-22.8}^{+51.2}$
3C292.0	$-{15.46}_{-0.06}^{+0.04}$	0.008	${7.6}_{-0.7}^{+0.8}$	${9.60}_{-0.30}^{+0.25}$	${2.7}_{-1.2}^{+1.1}$	${2.9}_{-0.3}^{+0.3}$	${48.2}_{-28.9}^{+48.2}$
3C309.1	$-{14.80}_{-0.15}^{+0.09}$	0.02	${7.7}_{-0.6}^{+0.4}$	${9.10}_{-0.05}^{+0.05}$	${7.6}_{-2.4}^{+2.3}$	${26.0}_{-7.6}^{+6.6}$	${153.6}_{-81.4}^{+144.8}$
3C330.0	$-{15.27}_{-0.08}^{+0.07}$	0.02	${7.5}_{-0.5}^{+0.6}$	${9.60}_{-0.27}^{+0.28}$	${2.0}_{-0.8}^{+1.5}$	${2.1}_{-0.4}^{+0.4}$	${34.4}_{-19.0}^{+53.1}$
3C334.0	$-{14.62}_{-0.16}^{+0.12}$	0.004	${7.4}_{-0.5}^{+0.7}$	${9.50}_{-0.15}^{+0.09}$	${7.6}_{-2.6}^{+3.3}$	${11.0}_{-3.5}^{+3.3}$	${153.6}_{-84.3}^{+180.7}$
3C336.0	$-{15.17}_{-0.10}^{+0.09}$	0.008	${7.6}_{-0.7}^{+0.6}$	${9.10}_{-0.05}^{+0.03}$	${3.0}_{-0.7}^{+0.7}$	${12.0}_{-2.4}^{+2.5}$	${54.2}_{-23.5}^{+38.0}$
3C337.0	$-{15.39}_{-0.12}^{+0.10}$	0.05	${8.8}_{-0.5}^{+1.6}$	${9.80}_{-0.12}^{+0.18}$	${2.8}_{-1.0}^{+1.1}$	${2.4}_{-0.6}^{+0.6}$	${50.2}_{-26.3}^{+49.2}$
3C340.0	$-{15.68}_{-0.11}^{+0.12}$	0.004	${6.9}_{-0.3}^{+0.5}$	${9.10}_{-0.05}^{+0.15}$	${0.7}_{-0.2}^{+0.2}$	${2.2}_{-0.5}^{+0.7}$	${10.1}_{-4.5}^{+8.0}$
3C343.0	$-{15.46}_{-0.15}^{+0.14}$	0.004	${8.7}_{-1.4}^{+2.0}$	${10.00}_{-0.12}^{+0.09}$	${10.0}_{-3.0}^{+4.6}$	${6.5}_{-2.0}^{+2.3}$	${208.9}_{-109.9}^{+263.1}$
3C343.1	$-{15.54}_{-0.07}^{+0.07}$	0.05	${7.7}_{-0.8}^{+1.1}$	${9.40}_{-0.10}^{+0.09}$	${1.7}_{-0.4}^{+0.5}$	${2.9}_{-0.5}^{+0.6}$	${28.7}_{-12.5}^{+21.6}$
3C352.0	$-{15.37}_{-0.03}^{+0.03}$	0.05	${7.9}_{-0.9}^{+0.6}$	${10.00}_{-0.14}^{+0.06}$	${9.1}_{-1.7}^{+1.4}$	${4.0}_{-0.3}^{+0.3}$	${188.0}_{-82.9}^{+131.9}$
3C380.0	$-{15.21}_{-0.19}^{+0.08}$	0.004	${7.6}_{-0.9}^{+0.4}$	${9.30}_{-0.15}^{+0.06}$	${2.0}_{-0.8}^{+0.9}$	${4.9}_{-1.7}^{+1.1}$	${34.4}_{-18.6}^{+35.1}$
3C427.1	$-{15.52}_{-0.06}^{+0.05}$	0.05	${7.6}_{-0.8}^{+0.9}$	${10.00}_{-0.06}^{+0.03}$	${3.0}_{-0.5}^{+0.5}$	${1.2}_{-0.2}^{+0.2}$	${54.2}_{-21.1}^{+32.4}$
3C441.0	$-{15.37}_{-0.07}^{+0.05}$	0.05	${7.5}_{-0.6}^{+0.8}$	${9.80}_{-0.11}^{+0.12}$	${3.8}_{-0.7}^{+1.0}$	${3.1}_{-0.4}^{+0.3}$	${70.7}_{-29.4}^{+55.1}$
3C455.0	$-{15.72}_{-0.22}^{+0.14}$	0.008	${7.0}_{-0.4}^{+0.5}$	${9.10}_{-0.04}^{+0.06}$	${0.3}_{-0.1}^{+0.1}$	${0.9}_{-0.3}^{+0.3}$	${3.8}_{-1.9}^{+2.6}$

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Table 11.  Host Fit Parameters for the 3Cs at z < 0.5

Name	${A}_{\mathrm{Host}}\left[\mathrm{log}\left(\tfrac{{\rm{W}}}{{{\rm{m}}}^{2}}\right)\right]$	Z	$\upsilon$ [log(years)]	Age [log(years)]	${M}_{\star }[{10}^{10}\;{M}_{\odot }]$	${L}_{\mathrm{Host}}[{10}^{10}\;{L}_{\odot }]$	${M}_{\mathrm{BH}}[{10}^{7}\;{M}_{\odot }]$
3C020.0	$-{14.89}_{-0.15}^{+0.12}$	0.008	${7.1}_{-0.4}^{+0.4}$	${9.90}_{-0.08}^{+0.06}$	${5.2}_{-1.5}^{+1.6}$	${3.6}_{-1.1}^{+1.2}$	${7.6}_{-3.2}^{+5.0}$
3C031.0	$-{12.21}_{-0.03}^{+0.04}$	0.02	${6.6}_{-0.1}^{+0.2}$	${9.50}_{-0.02}^{+0.01}$	${10.0}_{-0.9}^{+0.3}$	${13.0}_{-0.8}^{+1.1}$	${15.8}_{-4.5}^{+4.8}$
3C033.0	$-{13.57}_{-0.02}^{+0.01}$	0.02	${8.0}_{-0.4}^{+0.3}$	${9.60}_{-0.11}^{+0.12}$	${7.7}_{-1.5}^{+1.7}$	${7.8}_{-0.3}^{+0.2}$	${11.8}_{-4.2}^{+6.7}$
3C033.1	$-{14.82}_{-0.16}^{+0.11}$	0.004	${7.8}_{-0.5}^{+0.3}$	${9.10}_{-0.08}^{+0.08}$	${1.6}_{-0.6}^{+0.6}$	${5.3}_{-1.6}^{+1.7}$	${2.0}_{-0.9}^{+1.4}$
3C035.0	$-{13.57}_{-0.02}^{+0.01}$	0.05	${7.0}_{-0.4}^{+0.3}$	${9.30}_{-0.22}^{+0.10}$	${5.7}_{-1.6}^{+0.9}$	${9.5}_{-0.4}^{+0.4}$	${8.4}_{-3.6}^{+3.7}$
3C047.0	$-{14.85}_{-0.19}^{+0.15}$	0.05	${7.2}_{-0.5}^{+0.6}$	${9.90}_{-0.15}^{+0.08}$	${48.0}_{-19.0}^{+19.0}$	${29.0}_{-9.8}^{+12.0}$	${91.8}_{-52.9}^{+96.4}$
3C048.0	$-{14.14}_{-0.15}^{+0.12}$	0.004	${8.8}_{-1.2}^{+1.4}$	${9.50}_{-0.09}^{+0.12}$	${72.0}_{-38.0}^{+39.0}$	${130.0}_{-41.0}^{+47.0}$	${144.6}_{-98.5}^{+197.0}$
3C079.0	$-{14.68}_{-0.15}^{+0.10}$	0.008	${8.6}_{-0.4}^{+0.5}$	${9.60}_{-0.06}^{+0.07}$	${10.0}_{-4.2}^{+3.9}$	${17.0}_{-4.8}^{+5.4}$	${15.8}_{-8.8}^{+13.6}$
3C098.0	$-{13.19}_{-0.01}^{+0.01}$	0.05	${7.5}_{-0.6}^{+0.8}$	${9.50}_{-0.03}^{+0.08}$	${3.5}_{-0.2}^{+0.2}$	${4.3}_{-0.1}^{+0.1}$	${4.9}_{-1.0}^{+1.4}$
3C109.0	$-{14.22}_{-0.23}^{+0.16}$	0.008	${10.0}_{-0.6}^{+0.5}$	${9.80}_{-0.06}^{+0.03}$	${67.0}_{-43.0}^{+31.0}$	${64.0}_{-24.0}^{+37.0}$	${133.4}_{-101.6}^{+161.5}$
3C111.0	$-{14.59}_{-0.24}^{+0.14}$	0.008	${7.3}_{-0.5}^{+0.2}$	${9.50}_{-0.06}^{+0.20}$	${0.4}_{-0.2}^{+0.1}$	${0.5}_{-0.2}^{+0.2}$	${0.4}_{-0.2}^{+0.2}$
3C120.0	$-{13.60}_{-0.20}^{+0.05}$	0.02	${6.7}_{-0.2}^{+0.5}$	${9.50}_{-0.10}^{+0.04}$	${1.6}_{-0.6}^{+0.2}$	${2.2}_{-0.8}^{+0.3}$	${2.0}_{-1.0}^{+0.7}$
3C123.0	$-{14.92}_{-0.09}^{+0.06}$	0.05	${7.8}_{-0.9}^{+1.2}$	${10.00}_{-0.18}^{+0.07}$	${10.0}_{-3.3}^{+2.8}$	${4.9}_{-1.0}^{+0.8}$	${15.8}_{-7.6}^{+10.9}$
3C153.0	$-{14.82}_{-0.04}^{+0.04}$	0.008	${8.5}_{-1.5}^{+0.8}$	${9.30}_{-0.19}^{+0.19}$	${5.9}_{-1.6}^{+1.2}$	${15.0}_{-1.7}^{+4.8}$	${8.8}_{-3.6}^{+4.5}$
3C171.0	$-{14.92}_{-0.04}^{+0.03}$	0.008	${9.3}_{-1.6}^{+1.0}$	${9.90}_{-0.21}^{+0.20}$	${10.0}_{-2.9}^{+3.5}$	${7.1}_{-0.7}^{+0.9}$	${15.8}_{-7.1}^{+12.6}$
3C173.1	$-{14.43}_{-0.03}^{+0.03}$	0.02	${10.0}_{-1.2}^{+0.4}$	${10.00}_{-0.11}^{+0.07}$	${61.0}_{-12.0}^{+11.0}$	${33.0}_{-2.4}^{+2.3}$	${120.1}_{-52.2}^{+84.8}$
3C192.0	$-{13.64}_{-0.01}^{+0.01}$	0.05	${6.8}_{-0.2}^{+0.2}$	${9.40}_{-0.05}^{+0.04}$	${4.7}_{-0.3}^{+0.3}$	${6.4}_{-0.2}^{+0.1}$	${6.8}_{-1.6}^{+2.0}$
3C200.0	$-{15.11}_{-0.03}^{+0.03}$	0.02	${7.4}_{-0.6}^{+0.7}$	${9.50}_{-0.19}^{+0.10}$	${17.0}_{-4.9}^{+4.7}$	${22.0}_{-1.6}^{+1.3}$	${28.7}_{-13.3}^{+21.1}$
3C219.0	$-{14.20}_{-0.02}^{+0.02}$	0.05	${7.7}_{-1.0}^{+0.6}$	${9.40}_{-0.07}^{+0.11}$	${12.0}_{-1.3}^{+1.3}$	${18.0}_{-0.8}^{+0.7}$	${19.4}_{-5.9}^{+8.5}$
3C234.0	$-{14.57}_{-0.23}^{+0.13}$	0.008	${8.7}_{-0.5}^{+0.4}$	${9.40}_{-0.11}^{+0.09}$	${5.1}_{-2.9}^{+1.9}$	${11.0}_{-4.1}^{+3.6}$	${7.5}_{-4.9}^{+5.6}$
3C236.0	$-{13.70}_{-0.02}^{+0.02}$	0.008	${8.4}_{-0.9}^{+0.6}$	${10.00}_{-0.11}^{+0.16}$	${27.0}_{-5.7}^{+9.6}$	${18.0}_{-1.0}^{+1.0}$	${48.2}_{-20.1}^{+44.0}$
3C249.1	$-{14.14}_{-0.09}^{+0.09}$	0.004	${8.1}_{-0.7}^{+1.0}$	${9.10}_{-0.08}^{+0.30}$	${24.0}_{-5.0}^{+8.6}$	${91.0}_{-18.0}^{+31.0}$	${42.3}_{-17.4}^{+38.2}$
3C268.3	$-{15.07}_{-0.17}^{+0.17}$	0.05	${7.8}_{-0.9}^{+0.9}$	${9.70}_{-0.24}^{+0.07}$	${14.0}_{-6.2}^{+8.9}$	${14.0}_{-4.4}^{+5.6}$	${23.1}_{-13.4}^{+29.9}$
3C273.0	$-{13.27}_{-0.08}^{+0.03}$	0.02	${7.1}_{-0.2}^{+0.2}$	${9.20}_{-0.04}^{+0.03}$	${62.0}_{-13.0}^{+9.6}$	${140.0}_{-25.0}^{+8.2}$	${122.3}_{-54.5}^{+81.3}$
3C274.1	$-{15.09}_{-0.11}^{+0.12}$	0.02	${7.6}_{-0.2}^{+0.8}$	${9.50}_{-0.08}^{+0.03}$	${14.0}_{-4.3}^{+3.9}$	${19.0}_{-4.0}^{+6.7}$	${23.1}_{-10.9}^{+16.6}$
3C285.0	$-{13.82}_{-0.02}^{+0.02}$	0.008	${7.7}_{-0.6}^{+0.4}$	${9.50}_{-0.05}^{+0.04}$	${5.8}_{-0.6}^{+0.6}$	${8.5}_{-0.4}^{+0.3}$	${8.6}_{-2.3}^{+3.2}$
3C300.0	$-{14.96}_{-0.03}^{+0.03}$	0.004	${7.2}_{-0.5}^{+1.4}$	${9.60}_{-0.05}^{+0.06}$	${8.2}_{-1.9}^{+1.1}$	${9.5}_{-0.6}^{+0.6}$	${12.7}_{-5.0}^{+5.6}$
3C305.0	$-{13.04}_{-0.01}^{+0.01}$	0.02	${7.8}_{-0.8}^{+0.8}$	${9.80}_{-0.04}^{+0.04}$	${17.0}_{-1.1}^{+0.8}$	${13.0}_{-0.2}^{+0.2}$	${28.7}_{-8.1}^{+10.8}$
3C310.0	$-{13.59}_{-0.03}^{+0.02}$	0.004	${7.5}_{-0.8}^{+0.4}$	${9.50}_{-0.08}^{+0.29}$	${5.1}_{-1.2}^{+2.0}$	${6.5}_{-0.4}^{+0.3}$	${7.5}_{-2.8}^{+5.9}$
3C315.0	$-{14.23}_{-0.01}^{+0.01}$	0.05	${8.8}_{-0.6}^{+0.2}$	${9.80}_{-0.04}^{+0.04}$	${6.3}_{-0.5}^{+0.7}$	${5.7}_{-0.1}^{+0.2}$	${9.4}_{-2.4}^{+3.7}$
3C319.0	$-{15.00}_{-0.04}^{+0.02}$	0.02	${7.6}_{-0.5}^{+0.3}$	${9.60}_{-0.05}^{+0.06}$	${3.3}_{-0.4}^{+0.5}$	${3.8}_{-0.2}^{+0.2}$	${4.6}_{-1.2}^{+1.8}$
3C321.0	$-{13.74}_{-0.08}^{+0.06}$	0.05	${8.1}_{-1.2}^{+0.9}$	${9.60}_{-0.09}^{+0.14}$	${13.0}_{-2.9}^{+4.9}$	${14.0}_{-2.6}^{+2.4}$	${21.3}_{-8.5}^{+18.4}$
3C326.0	$-{14.14}_{-0.01}^{+0.01}$	0.05	${7.5}_{-0.4}^{+0.3}$	${9.50}_{-0.05}^{+0.04}$	${3.9}_{-0.3}^{+0.3}$	${4.6}_{-0.1}^{+0.1}$	${5.5}_{-1.2}^{+1.6}$
3C341.0	$-{15.14}_{-0.20}^{+0.17}$	0.05	${8.6}_{-0.8}^{+0.4}$	${9.80}_{-0.08}^{+0.12}$	${21.0}_{-7.1}^{+12.0}$	${20.0}_{-7.8}^{+8.4}$	${36.4}_{-18.5}^{+45.2}$
3C349.0	$-{14.85}_{-0.03}^{+0.02}$	0.02	${7.0}_{-0.4}^{+0.4}$	${9.10}_{-0.05}^{+0.08}$	${2.6}_{-0.3}^{+0.5}$	${6.4}_{-0.4}^{+0.4}$	${3.5}_{-0.8}^{+1.5}$
3C351.0	$-{14.00}_{-0.11}^{+0.10}$	0.004	${8.4}_{-1.5}^{+1.8}$	${9.90}_{-0.16}^{+0.07}$	${210.0}_{-65.0}^{+70.0}$	${170.0}_{-44.0}^{+59.0}$	${479.6}_{-265.3}^{+538.2}$
3C381.0	$-{14.36}_{-0.05}^{+0.05}$	0.02	${11.0}_{-0.3}^{+0.2}$	${9.40}_{-0.05}^{+0.05}$	${7.7}_{-1.3}^{+1.3}$	${11.0}_{-1.5}^{+1.4}$	${11.8}_{-4.0}^{+5.8}$
3C382.0	$-{13.09}_{-0.04}^{+0.03}$	0.05	${7.3}_{-0.5}^{+0.5}$	${9.60}_{-0.06}^{+0.10}$	${18.0}_{-1.8}^{+1.8}$	${20.0}_{-1.8}^{+1.7}$	${30.6}_{-9.6}^{+14.1}$
3C386.0	$-{12.96}_{-0.03}^{+0.03}$	0.05	${7.4}_{-0.5}^{+0.6}$	${9.20}_{-0.09}^{+0.05}$	${1.0}_{-0.2}^{+0.1}$	${2.4}_{-0.2}^{+0.2}$	${1.2}_{-0.3}^{+0.4}$
3C388.0	$-{13.80}_{-0.03}^{+0.02}$	0.02	${7.5}_{-0.7}^{+0.8}$	${9.40}_{-0.08}^{+0.05}$	${8.8}_{-1.1}^{+0.8}$	${12.0}_{-0.7}^{+0.7}$	${13.7}_{-4.2}^{+5.3}$
3C390.3	$-{13.51}_{-0.10}^{+0.06}$	0.05	${7.1}_{-0.3}^{+1.4}$	${9.60}_{-0.04}^{+0.03}$	${6.9}_{-1.5}^{+1.3}$	${7.4}_{-1.6}^{+1.5}$	${10.5}_{-3.9}^{+5.3}$
3C401.0	$-{14.80}_{-0.03}^{+0.02}$	0.008	${7.9}_{-0.9}^{+0.6}$	${9.80}_{-0.10}^{+0.17}$	${7.1}_{-1.0}^{+2.0}$	${6.4}_{-0.3}^{+0.3}$	${10.8}_{-3.3}^{+7.1}$
3C424.0	$-{14.72}_{-0.06}^{+0.05}$	0.02	${8.2}_{-0.6}^{+2.1}$	${9.60}_{-0.04}^{+0.04}$	${2.3}_{-0.4}^{+0.4}$	${2.9}_{-0.4}^{+0.5}$	${3.1}_{-0.9}^{+1.1}$
3C433.0	$-{13.80}_{-0.12}^{+0.09}$	0.008	${7.3}_{-0.6}^{+0.7}$	${9.10}_{-0.06}^{+0.14}$	${6.2}_{-2.1}^{+2.6}$	${16.0}_{-3.9}^{+3.6}$	${9.3}_{-4.4}^{+7.9}$
3C436.0	$-{14.55}_{-0.04}^{+0.02}$	0.05	${7.4}_{-0.7}^{+1.0}$	${9.60}_{-0.14}^{+0.10}$	${11.0}_{-1.8}^{+2.8}$	${12.0}_{-0.7}^{+0.6}$	${17.6}_{-6.1}^{+11.5}$
3C438.0	$-{14.44}_{-0.03}^{+0.03}$	0.05	${7.3}_{-0.5}^{+0.5}$	${10.00}_{-0.13}^{+0.13}$	${57.0}_{-12.0}^{+13.0}$	${29.0}_{-2.1}^{+1.9}$	${111.3}_{-49.3}^{+86.9}$
3C452.0	$-{13.77}_{-0.03}^{+0.02}$	0.05	${8.6}_{-0.7}^{+0.6}$	${9.90}_{-0.05}^{+0.07}$	${12.0}_{-1.7}^{+2.2}$	${8.5}_{-0.6}^{+1.0}$	${19.4}_{-6.4}^{+10.7}$
3C459.0	$-{14.59}_{-0.08}^{+0.07}$	0.008	${7.5}_{-0.6}^{+0.7}$	${9.20}_{-0.17}^{+0.08}$	${5.0}_{-1.3}^{+1.5}$	${14.0}_{-2.4}^{+2.7}$	${7.3}_{-2.9}^{+4.7}$

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