1. The Evolution of AGN over Cosmic Time Current Status and Future Prospects Matt Jarvis University of Hertfordshire What have we learnt from radio surveys so far? What have we learnt from current multi-wavelength surveys? What will future surveys tell us?

2. Radio selection Free from dust obscuration 1.4GHz may not be the best frequency to search for HzRGs as they have steep spectra (optically thin lobe emission). High frequency surveys at high flux density dominated by flat- spectrum quasars Most searches for HzRGs have been conducted at low frequency (<400 MHz)

3. Evolution of the high-luminosity population Need COMPLETE radio samples – in the past this meant spectroscopic completeness and using the K-z diagram Integrate under the LF to measure the space density of the radio sources as a function of cosmic epoch Dunlop & Peacock 1990 The first to find a “redshift cut- off” in the flat-spectrum radio source population

4. Shaver et al. (1996) followed this up with a larger and more complete data set of flat-spectrum quasars. Again found a sharp decline at the high redshifts Evolution of the high-luminosity population

5. Issues with spectral shapes A selection of Shaver et al.’s FLAT-SPECTRUM objects!

6. Jarvis & Rawlings 2000 But steep spectrum sources fall out of flux-limited surveys more quicky than flat- spectrum sources. Issues with Spectral Index Means that if HzRGs have steep spectra then you need to observe them at low frequency

7. Jarvis & Rawlings 2000 But steep spectrum sources fall out of flux-limited surveys more quicky than flat- spectrum sources. Issues with Spectral Index Means that if HzRGs have steep spectra then you need to observe them at low frequency

8. Jarvis & Rawlings 2000 Profound effect on the interpretation of a redshift cut-off Issues with Spectral Index

9. Flat-spectrum population of Shaver et al. was reanalysed fully by Wall et al. (2005). Now a ~4sigma decline is found. But still restricted to the bright, flat-spectrum quasars – which again may not be fair to do and enforces small number statistics. Evolution of the high-luminosity population

10. So measuring the high-redshift evolution of AGN is a tricky business

11. What can we do?

12. The problem For the FIRST survey at 1mJy (1.4GHz)… ~83 sources per sq.degree ~6 local(ish) starburst galaxies ~77 AGN (6 FRIIs where we should detect emission lines) Splitting in redshift… 57 AGN at z<2 (2 FRIIs) 67 AGN at z<3 (4 FRIIs) 73 AGN at z<4 (6 FRIIs)

13. Past searches for HzRGs… Many have utilized the properties of the radio sources themselves to filter out the low-z contaminant sources. Steep spectral index De Breuck et al. 2000 Blundell et al. 1999

14. Past searches for HzRGs… Jarvis et al. 2001

15. The “lack” of a redshift cut-off in the steep-spectrum population Jarvis et al. 2001

16. The “lack” of a redshift cut-off in the steep-spectrum population Jarvis et al. 2001 But remember steep-spectrum selection reduces the accessible volume

17. The “lack” of a redshift cut-off in the steep-spectrum population Jarvis et al. 2001 Not much progress since!

18. The “lack” of a redshift cut-off in the steep-spectrum population Jarvis et al. 2001 Not much progress since! But see later

19. Can turn around the way we use radio surveys

20. eMerlin LOFAR eVLA KAT/ASKAP SKA 201120202010 Spitzer SCUBA2 Herschel WISE ALMA Now20092010 UKIDSS VISTA JWST ELT Now200920132020 Near-IR Mid/Far-IR Radio    2010  SDSS1-2 Pan-STARRS SDSS-3 DES Now20092010  Optical  2012  2011

21. Combine existing survey data to infer the properties of AGN Clewley & Jarvis 2004 Evolution of the low-power radio sources (not necessarily FRIs)

22. Combine existing survey data to infer the properties of AGN Sadler et al. 2007 Clewley & Jarvis 2004 Evolution of the low-power radio sources (not necessarily FRIs)

23. Combine existing survey data to infer the properties of AGN Rigby, Best & Snellen 2008 Morphologically classified FRIs at L(1.4)>10 25 W/Hz

24. Combine existing survey data to infer the properties of AGN Rigby, Best & Snellen 2008 Morphologically classified FRIs at L(1.4)>10 25 W/Hz As well as all of the good work we’ve heard about this morning

25. So what now?

26. First go back to the high-luminosity sources…

27. Use the host galaxies K-band samples the old stellar population – so bulk of the stellar mass

28. Going back to the K-z relation… Jarvis et al. 2001; Willott et al. 2003

29. Going back to the K-z relation… Jarvis et al. 2001; Willott et al. 2003

30. Going back to the K-z relation… Jarvis et al. 2001; Willott et al. 2003

31. Use this information at other wavelengths to eliminate low-z contaminants Jarvis et al. 2004

32. deg 2 K lim Large Area Survey (LAS) 4000 18.4 Galactic Plane Survey (GPS) 1800 19.0 Galactic Clusters Survey (GCS) 1400 18.7 ()Deep eXtragalactic Survey (DXS) 3521.0 (UDS)UltraDeep Survey (UDS) 0.8 23.0 Declination Right Ascension UKIDSS

33. Finding the highest-redshift radio galaxies (similar strategy to CENSORS – Best et al. (2003), Brookes et al. (2006,2008) Use UKIDSS-DXS + Spitzer-SWIRE and a variety of radio surveys (e,g. FIRST). Try and get spectra for all of the objects undetected in the near-IR PhD student Hanifa Teimourian In 10 sq. degrees to 10mJy at 1.4GHz LOFAR Surveys KSP will need to adopt such a strategy to be most efficient. Pan-STARRS/UKIDSS/VISTA/WISE Jarvis, Simpson, Teimourian, Smith & Rawlings

34. A demonstration of combining radio surveys with multi-wavelength data… A typical HzRG at z=4.88 Log(L(1.4))=26.5W/Hz/sr  =0.75 Jarvis et al. 2009

35. A demonstration of combining radio surveys with multi-wavelength data… Teimourian et al. 2010 α=0.9

36. What does this mean? But this survey is only sensitive to the most powerful sources. Due to the need to obtain spectroscopic redshifts and the need for accurate positions from the radio survey. To understand the whole radio source population at all luminosities (from SFGs to powerful FRII radio galaxies) we need exquisite multi-wavelength data and deep radio data. Teimourian et al. in prep.

37. LOFAR Surveys Huub Rottgering (Chair), Peter Barthel, Philip Best, Marcus Brueggen, Matt Jarvis, George Miley, Raffaella Morganti, Ignas Snellen All Sky Survey 20,000 sq.degree survey at 15, 30, 60, 120MHz to 15, 5, 1.7 and 0.1mJy (rare objects + unknown) 1000 sq.degree survey at 200MHz to 0.07mJy (Cluster relics/haloes, starburst galaxies…) Deep Survey 1200 sq.deg at 30 & 60MHz to 0.9 & 0.2mJy 220 sq.deg at 120MHz to 0.025mJy 80 sq.deg.at 200MHz to 0.018mJy (distant starbursts, AGN, clusters…) Ultra-Deep Survey 1-2 pointings (4-8sq.deg) at 200MHz to 0.006mJy (confusion limited at sub- arcsec resolution) very high-z starbursts, RQ-AGN, …

38. Comparison of WENSS, FIRST, NVSS and LOFAR for detecting HzRGs (FRIIs with  =0.8)

39. Radio galaxies at z>7 in Surveys More than 100 sufficiently powerful sources at z>7 predicted in 2π survey. LOFAR’s wide area survey multi-frequency capabilities are essential. Isolate using ultra-steep radio spectrum, plus optically blank in deepest images (eg. PanSTARRS/VISTA/UKIDSS) Ultra-deep images would also detect any clustered starforming galaxies around radio source (would need high dynamic range though).

40. What the future has in store… Survey speed >3x faster than WFCAM and better sensitivity in the Z,Y,J wavebands VISTA

41. The VIDEO Survey (PI Jarvis) FilterTime (per source) Time (full survey) 5  AB5  Vega UKIDSS -DXS Seei ng Moon Z17.5 hours456 hours25.725.2-0.8D Y6.7 hours175 hours24.624.0-0.8G J8.0 hours209 hours24.523.722.30.8G H8.0 hours221 hours24.022.7220.8B KsKs 6.7 hours180 hours23.521.720.80.8B

42. VIDEO+SERVs+DES++ Elais-S1 XMM-LSS CDF-S Spitzer Representative Volume Survey (SERVS) approved to cover VIDEO survey regions + LH and Elais-N1 1400 hours allocated – PI Mark Lacy Management: Matt Jarvis, Seb Oliver and Duncan Farrah Will provide 3.6 and 4.5um data to slightly deeper levels than the VIDEO depths (L* at z>5) VIDEO entering data sharing agreement with the Dark Energy Survey. DES will have grizy photometry over VIDEO regions to depths of AB~27 (5sigma) Concentrating on SNe science initially. Will be covered by Herschel-HerMES survey (100-500um) Partly covered by SCUBA2

43. What can we learn about AGN? Z-Y vs Y-J very efficient at selection z>6.5 QSOs. VIDEO+SERVs crucially allows us to find the reddened high-z QSOs Depending on the QSO LF slope expect 10-30 z>6.5 QSOs in VIDEO L- and T-dwarfs z=6 z=6.5 z=7

44. Summary Radio surveys allow is a relatively unbiased view of this activity Past surveys have enabled us to put some constraints on the high- redshift evolution, but much is still uncertain The way in which we carry out such studies in the future (and now) will change. We must use the multi-wavelength data already in place and move away from “follow-up” of radio surveys Initial results with such a strategy has allowed us to find the most distant radio galaxy thus far in a far more efficient way than any previous studies The prospects for this strategy in the future only get better with the deep optical/IR datasets, combined with the SKA precursor telescopes such as LOFAR, ASKAP and MeerKAT.