ISSUES ABOUT WHICH IS THE MOST FUNDAMENTAL RELATION, IF IT IS A 3-VARIABLE ONE, ETC…

1. ISSUES ABOUT WHICH IS THE MOST FUNDAMENTAL RELATION, IF IT IS A 3-VARIABLE ONE, ETC… WE FIND THE MBH-σRELATION TO BE THE TIGHEST ~0.18 dex FS, L. Ferrarese 2009

2. SO FAR WE HAVE CONSIDERED MODELS WITH CONSTANT EDDINGTON RATIO DISTRIBUTIONS WE NOW ALLOW FOR THE ACCRETION RATES  TO DEPEND ON REDSHIFT (INCREASE/DECREASE WITH z) AND, AT FIXED TIME, TO DEPEND ON BLACK HOLE MASS (INCREASE/DECREASE WITH MBH)

3. Broad Distributions III: The Obscured Fraction MBH-α MBH-α

4. Broad Distributions III: The Obscured Fraction MBH-α Babic et al.; Tozzi et al.; Alexander et al. Hasinger; Akylas et al. FS, D. Weinberg, J. Miralda-Escude’ 2009a

5. Do The Relations Evolve with Redshift? FS, Bernardi, Haiman 2008

6. CONSTRAINING BLACK HOLE AND GALAXY EVOLUTION Francesco Shankar Kunming 27/02/09

7. SAMs are working hard to understand what is going on… Malbon et al. Fontanot et al. ``our knowledge on the physics of accretion onto BHs and their interaction with galaxies is still poor to draw firm conclusions’’

8. GOAL: • EMPIRICALLY CONSTRAIN BLACK HOLE EVOLUTION IN A STATISTICAL SENSE • WE USE: -LOCAL BH MASS FUNCTION -AGN BOL. LUM. FUNCTION - AGN CLUSTERING - OBSERVED DUTY CYCLE TOOLS:

9. INPUT/CONSTRAINTS FOR MODELS AGN LUMINOSITYFUNCTION LOCAL BH MASS FUNCTION

10. L=LEdd (MBH ) LEdd=1.3e38x(MBH/Msun) erg/s tef  / FS, D. Weinberg, J. Miralda-Escude’ 2008

11. Duty cycles: U(Mbh,z)=Ф(L,z)/n(Mbh[L],z) Mean Mass Accretion Histories: Evidence for downsizing

12. Broad Eddington ratio Distributions I FS, D. Weinberg, J. Miralda-Escude’ 2009a

13. …Same DOWNSIZING….

14. Broad Eddington ratio Distributions II Very Narrow p() Very Broad p()

15. Broad Eddington ratio Distributions III Very Broad p() Very Broad p()+f(z)

16. SPECIAL MODELS: -dependent Bolometric Correction Vasudevan & Fabian 2007

17. Low Radiative Efficiency+Low Eddington ratios Similar Downsizing Harder to match the local BHMF: <0.1; <0.06

18. The Effect of SMBH Merging… Negligible effect on accretion histories and duty cycles:

19. How to link Clustering to Accretion b n Ф Mhalo Mhalo L From matching the bias in output duty cycle fAGN Rule of thumb: at fixed scatter, high duty cycle massive halos low numbers Martini & Weinberg 2001; Haiman & Hui 2001

20. An Application: The SDSS z~1.5 quasar clustering Coupling with duty cycle from Continuity Equation breaks some degeneracies! First Results: large scatter! FS, Shen, Weinberg, et al. 2009

21. Duty cycle~1 Another Application: The SDSS z>3 Quasar Clustering n(Mbh=L/)~Ф(L)/P0 FS, M. Crocce, J. Miralda-Escude’, P. Fosalba, D. Weinberg 2008

22. Seeding Central and Satellite Halos with BHs N(Mh) n n Mh Mhalo Mbh Pc(Mbh) Nc[Mh(Mbh)]/Ntot+ Ps(Mbh) Ns[Mh(Mbh)]/Ntot=U(Mbh,z) Q=Ps/Pc Mmin FS, D. Weinberg, J. Miralda-Escude’ 2009b

23. SO…WHAT DID WE LEARN ABOUTHOW BHs EVOLVE? • ACCRETION: can reproduce the local BH mass function; preferred parameters are 0.5<<1 and 0.07<<0.1. Multi Edd. Ratios do not change Accreted BHMF. • The Quasar clustering, independent constraints on duty cycle, mean L-Mhalo relation, and scatter, small-scales constraints on the BH triggering mechanisms • Constraints are independent of specific models and can then be used in SAMs

24. FS, D. Weinberg, J. Miralda-Escude’ 2009b

25. fs= fraction of AGNs which are satellites Eastman et al.; Martini et al.; Sivakoff et al.

26. Low-z Clustering: RESULTS Coil et al.; Croom et al.; da Angela et al.; Francke et al.; Hennawi et al; Mountrichas et al.; Myers et al.; Padmanabhan et al.; Plionis et al; Porciani et al.; Shen et al.

27. Varying the Reference Model… L~MBH

28. L=LEdd (MBH ) LEdd=1.3e38x(MBH/1e8) erg/s tef  / P0=Ф(L)/n(Mbh=L/) FS, D. Weinberg, J. Miralda-Escude’ 2008

29. CONCLUDING on THE LMF 0.06<<0.11 Merging More Massive+Sub-Edd Less Massive+Edd dm/dt~0.5

30. An Example of applying inputs from Accretion+Clustering into SAMs for Co-evolution Outputs of Granato et al. model Within each virialized DM halo negligble post-peak accretion as demography assumptions Clumpy GAS at Tvir Radiative cooling COLD GAS Radiation drag (SFR) SCUBA tvis tdelay Passive Evolution RESERVOIR (low J) Stellar evolution QSO phase Collapse QSO outflows SNae & QSO feedback STARS Viscous accretion IGM SMBH-QSO Granato et al. 2004, 2006, FS et al. 2006 • Integrating the duty cycles in time: • estimate of the mean lifetime of quasars • of a given final mass

31. FOR THE FUTURE: Study of the Black Holes in MPA SAM: -link light-curve to energy self-regulation -compute the number of BH pairs and make predictions for LISA -compute the statistics of radio sources -probe more triggers for BH accretion

32. Massive Dark Objects observed in all bulged-galaxies •  strong link with the host spheroid M/n/ =kVc + VC+DM profile  VVIR(zvir=0)(Mvir )1/3 Dunlop & McLure; Ferrarese et al.; Gebhardt et al.; Graham et al.; Haring & Rix; Lauer et al.; Magorrian et al.; Marconi & Hunt; FS & L. Ferrarese 2009a,b What are MDOs? How and why are they connected with spheroids and DM? What is their role in shaping galaxies?

33. But if Galaxies merge…what happens to SMBHs? FS, F. Marulli, M. Bernardi, et al. 2009

34. SO…WHAT DID WE LEARN ON HOW BHs EVOLVE? • Single- models can reproduce the local BH mass function; preferred parameters are 0.5<<1 and 0.07<<0.1. • Broad p() distributions yield similar BH growth histories if  is independent of BH mass. • The high-z clustering, especially at z=4 measured in SDSS, requires very high host halo masses and matching the AGN luminosity function requires 0.4</<1, i.e., >0.2 if >0.5! • If the Eddington ratio decreases with BH mass and z: -match to the AGN fraction in the field and clusters -match to small-scale clustering -match to the obscured fraction

35. MODELING THE low-z QUASAR CLUSTERING 1-The previous method breaks down at low-z: multiple quasars in halos! 2-We return to our previous accretion modeling tied to the observed AGN Luminosity Function: BH mass function predicted from continuity equation 3-We add the assumption that BH mass is a monotonic function (with scatter) of halo mass or the maximum mass of the subhalo 4-Scatter between L and MHALO can come either from scatter in MBH-MHALO or from a broad p(,z) distribution 5-Add new physical parameter Q=Ps/Pc! Small difference at large scales, significant at small ones

36. AN EXAMPLE OF BASIC CO-EVOLUTION MODEL FOR BHs AND GALAXIES Outputs of Granato et al. model Within each virialized DM halo negligble post-peak accretion as demography assumptions Clumpy GAS at Tvir Radiative cooling COLD GAS Radiation drag (SFR) SCUBA tvis tdelay Passive Evolution • slightly redshift depend. Eddington accretion RESERVOIR (low J) Stellar evolution QSO phase Collapse QSO outflows SNae & QSO feedback STARS Viscous accretion IGM SMBH-QSO Granato et al. 2004, 2006, FS et al. 2006 • Sheth & Tormen positive derivative • cut-off at 31011 M MVIR 21013 M and zvir1.5 • Bardeen power spectrum with baryons and 8=0.84 • scatter in the MBH-MVIR relation of ~0.3 dex

37. Another Application: The SDSS z>3 Quasar Clustering FS, M. Crocce, J. Miralda-Escude’, P. Fosalba, D. Weinberg 2008

38. MBH -  () First Step:How many SMBH?How Massive? MBH - Lbulge For all relations used I convolve with a Gaussian weightto account for intrinsic scatter ! Φ(L)→Φ(Lbulge) Ф(MBH)

39. Results: systematic uncertainties!

40. THE ACTIVE EVOLUTION OF BLACK HOLES: THE AGN LUMINOSITY FUNCTION

41. independent ofcosm. par. but very dependent on the Kbol/ε ratio! SMBH from Merging/Dark Accretion or through Visible Accretion detected in the AGN luminosity Functions? Soltan argument

42. Do BHs grow faster than Galaxies? The ratio <MBH/MSTAR> probably was nearly constant at all times at least up to z~1.5-2 FS, M. Bernardi, Z. Haiman 2008

43. Low-z Clustering: RESULTS Coil et al.; Croom et al.; da Angela et al.; Francke et al.; Hennawi et al; Mountrichas et al.; Myers et al.; Padmanabhan et al.; Plionis et al; Porciani et al.; Shen et al.

44. Another Application: The SDSS z>3 Quasar Clustering FS, M. Crocce, J. Miralda-Escude’, P. Fosalba, D. Weinberg 2008

45. Good constraints from the small scales….

46. What do we learn from high-z clustering? 1-DIFFICULT: high bias rare BHs, high duty cycles! 2-Reproducing the LF requires high  and/or low : 0.4</<1; Shen et al. --> >0.5 --> >0.2 3-High halo mass and the limit duty cycle ≤ 1 leads to very rapid drop of quasar number counts at z>6 FS, M. Crocce, J. Miralda-Escude’, P. Fosalba, D. Weinberg 2008

47. Towards a successful Model: • We already saw in PART I: mass dependence • can match the obscured fraction -A reasonable match to duty cycles and low-z clustering can be found if: 1-MBH-1/3 2- f(z)=[1-exp(z/2)] 3-Q=0.5-1 4-Scatter in MBH-Mhalo ~0.3-0.5 dex

48. fs= fraction of AGNs which are satellites Eastman et al.; Martini et al.; Sivakoff et al.

49. Towards a successful Model II:

50. TO GET FINAL ANSWERS: FROM OBSERVATIONS: • Resolve systematics in the AGN LF knee and bright end • Understand biases in the -distributions • Systematics in the mean bias values FROM THEORY: • Convolve continuity Equation with BH merger rates • Get final BH mass function at all z consistent with ALL observables • Predict the BH mass function from SAM