1 / 19

The luminosity-dependent evolution of the radio luminosity function

The luminosity-dependent evolution of the radio luminosity function. Emma Rigby University of Nottingham Collaborators: P. Best, M. Brookes, J. Dunlop, J. Peacock, L. Ker, H. Rottgering, J. Wall. Model of a radio-loud AGN (Urry & Padovani). Why study radio galaxy evolution?.

trapper
Download Presentation

The luminosity-dependent evolution of the radio luminosity function

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The luminosity-dependent evolution of the radio luminosity function Emma Rigby University of Nottingham Collaborators: P. Best, M. Brookes, J. Dunlop, J. Peacock, L. Ker, H. Rottgering, J. Wall

  2. Model of a radio-loud AGN (Urry & Padovani) Why study radio galaxy evolution? • Important for galaxy evolution models via feedback • Radio-loud AGN powered by most massive black holes so provide information on upper end of black hole mass function

  3. The evolving radio luminosity function (RLF) • Comoving space density of radio galaxies increases to z ~2 (Dunlop & Peacock 1990), with indications of a decline at higher redshift • Previous work lacked depth & volume necessary to probe high-z behavior • Motivated development of CENSORS - a faint radio source sample (S1.4GHz > 7.2 mJy) • 73% spectroscopically complete (Brookes et al. 2008) • Investigate using a grid-based modelling technique with no assumptions made about the RLF behavior

  4. RLF Modelling: input data • 5 input radio source samples • Wall & Peacock 1985, • Parkes selected regions, (Downes et al 1986), • CENSORS (Best et al. 2003) • Hercules, (Waddington et al. 2001) • VLA-COSMOS, (Smolcic et al. 2008) • Local radio luminosity functions covering ~20 < Log P1.4GHz < 27 (Best et al., 2010; Sadler et al., 2002; Mauch et al., 2007) • Integrated source counts covering 0.05 mJy to 94 Jy (Bondi et al. 2008; Seymour et al. 2004; Windhorst et al. 1984; White et al. 1997; Kellermann & Wall 1987) The radio-power - redshift plane covered by the 5 samples

  5. RLF Modelling: input data • 5 input radio source samples • Wall & Peacock 1985, • Parkes selected regions, (Downes et al 1986), • CENSORS (Best et al. 2003) • Hercules, (Waddington et al. 2001) • VLA-COSMOS, (Smolcic et al. 2008) • Local radio luminosity functions covering ~20 < Log P1.4GHz < 27 (Best et al., 2010; Sadler et al., 2002; Mauch et al., 2007) • Integrated source counts covering 0.05 mJy to 94 Jy (Bondi et al. 2008; Seymour et al. 2004; Windhorst et al. 1984; White et al. 1997; Kellermann & Wall 1987) The CENSORS redshift distribution

  6. Modelling Technique RLF Cosmic evolution Radio Power Space densities Redshift

  7. Modelling Technique 3 input radio-luminosity - redshift (P,z) density grids: 21 points in log P (19.25 < Log P < 29.25) and 8 points in z (0.1 < z < 6) Steep spectrum grid Flat spectrum grid Starforming grid Created by evolving the local starforming galaxy luminosity function Starting estimate created by evolving the local AGN RLF by (1+z)3 Taken as the median of the evolutionary models of Dunlop & Peacock 1990

  8. Modelling Technique 3 input radio-luminosity - redshift (P,z) density grids Steep spectrum grid Flat spectrum grid Starforming grid Amoeba minimisation - varies steep grid only Integrate to form 3 flux-density - redshift (S,z) grids containing source numbers Compare to input datasets

  9. Modelling Technique 3 input radio-luminosity - redshift (P,z) density grids Steep spectrum grid Flat spectrum grid Starforming grid Assuming  = 0.83+0.4log(1+z) for steep;  = 0.8 for starforming &  = 0 for flat grids Amoeba minimisation - varies steep grid only Integrate to form 3 flux-density - redshift (S,z) grids containing source numbers Marginalised errors calculated from a Hessian matrix Compare to input datasets

  10. Results: dataset comparison Radio source samples Integrated source counts Model good fit to input data Local radio luminosity function

  11. Results: model luminosity functions Dashed line: median of Dunlop & Peacock (1990) results

  12. Results: model luminosity functions

  13. Results: model luminosity functions Blue: lack of coverage in local RLF Green: Incomplete coverage of radio power - redshift plane

  14. Robustness testing Varying the spectral index used to calculate the steep source number grid Randomly moving the redshift limits to higher values Redshift cutoffs still present

  15. The high redshift cutoff • High redshift cutoffs seen across the radio power range • Cutoffs still present when model parameters are varied • Need ~5 extra sources in CENSORS sample to reduce the cutoff strength to <3 for 27 < log P < 28 • Position of cutoff appears to be radio luminosity -dependent

  16. Starforming galaxies FRIs FRIIs The future… • Larger radio source samples will mean RLF evolution of different populations can be studied individually • e.g. FRI vs FRII or Low vs High excitation sources Predictions for the LOFAR-deep survey [dashed line - FRIs, solid line - starforming galaxies, dot-dashed line - radio quiet quasars, dotted line - FRIIs]

  17. The future… • Luminosity dependence seen for cutoff needs to be incorporated into SKA population models Red dashed line computed from S3 SKADS simulations (Wilman et al. 2008)

  18. Conclusions • Using our new grid-based modelling have found clear high-redshift cutoff in the RLF • Cutoff appears to move to higher redshift at higher radio power • Results still limited by uncertain redshifts & small radio samples

More Related