1. Massive galaxies in massive datasets M. Bernardi, J. Hyde and E. Tundo M. Bernardi, J. Hyde and E. Tundo University of Pennsylvania

2. Importance of Early-Type Galaxies –Stellar masses & Black Holes The Hierarchical formation picture –Down-sizing and Dry mergers Testing Dry mergers using scaling relations –Luminosities, Sizes, Velocity dispersions, Colors Selection bias in the M bh – L –  relations OUTLINE

3. Early-types don’t dominate number, but they do dominate stellar mass 57% 17% 43% 83% Renzini 2006

4. The most massive galaxies are red and dead

5. Super Massive Black Holes Gebhardt et al. 2000 Connection with “AGN feedback”!! Ferrarese & Merritt 2000

6. We need to find out when …. stars were formed stars were formed the galaxy was assembled the galaxy was assembled

7. Downsizing Star formation only in smaller systems at late times Environmental dependence important, but controversial ( Thomas et al. 2005; but see Bernardi et al. 2006a; Bundy et al. 2006 )

8. Old stellar population (OK for everybody!!) ?? When were galaxies assembled ?? Population of massive red galaxies seen even at z~1.5 (K20 Survey, VVDS) Consistent with passive evolution (e.g. Cimatti et al. 2006, Consistent with passive evolution (e.g. Cimatti et al. 2006, Bundy et al. 2006, Brown et al. 2006) OR Still assembling at low z (e.g. ? Still assembling at low z (e.g. Faber et al. 2006)? In the hierarchical formation picture ….. the problem is to form stars, and assemble them into a single massive system, in a relatively short time (in this respect, LCDM is friendlier than SCDM) the problem is to form stars, and assemble them into a single massive system, in a relatively short time (in this respect, LCDM is friendlier than SCDM) How to do this?

9. Importance of Early-Type Galaxies –Stellar masses & Black Holes The Hierarchical formation picture –Down-sizing and Dry mergers Testing Dry mergers using scaling relations –Luminosities, Sizes, Velocity dispersions, Colors Selection bias in the M bh – L –  relations OUTLINE

10. New models match K-band luminosity function at z~0 Main change is to include AGN related effects No AGN feedback AGN feedback Croton et al. 2006 (Munich) Bower et al. 2006 (Durham)

11. Massive Redheads? Latest generation of semi-analytic models, calibrated to z=0, able to match K-band luminosity function at z~1.5 Main change is to include AGN related effects  BCG Dry mergers common Bower et al. 2006 (Durham) Passive evolution + Dry mergers

12. Bimodality Models now produce reasonable color- magnitude relations BCGs bluer? Bower et al. 2006 (Durham) BCGs Satellite galaxies (not BCGs) Croton et al. 2006 (Munich) BCGs

13. Importance of Early-Type Galaxies –Stellar masses & Black Holes The Hierarchical formation picture –Down-sizing and Dry mergers Testing Dry mergers using scaling relations –Luminosities, Sizes, Velocity dispersions, Colors OUTLINE Selection bias in the Mbh – L –  relations Selection bias in the Mbh – L –  relations

14. Brightest Cluster Galaxies Standard candles/rods, visible far away Giant elliptical + extended faint envelope Down-sizing: massive, but old stars Red … when did they form? stellar population AND assembling stellar population AND assembling If formation by ‘dry’ mergers, no dissipation  larger sizes? no dissipation  larger sizes?

15. Brightest Cluster Galaxies C4 cluster catalog Uses both position and color info Miller et al. 2005

17. Properties of early-type galaxies Pairwise scaling relations –Faber-Jackson: L-  –Kormendy: I e -R e –L-R e – Color - L Inclusion of third parameter –The Fundamental Plane: I e -R e -  Are they the same for BCGs????

18. BCGs show deviation from Kormendy relation Oegerle & Hoessel 1991 BCGs ETGs

19. Luminosity-Size relation Upturn to larger sizes at large luminosities Why? ● BCGs ● High-  Oegerle & Hoessel 1991 R ~ L 0.8 R ~ L 0.6 Dry merging? Bernardi et al. 2007a

20. L-R relation expected to depend on mass ratio and impact parameter of merging spheroids (Robertson et al. 2006)

21. Flattening? Scatter correlates with size: consistent with Virial theorem:  2 ~ M/R Luminosity-  relation ● 2 comp ● deV

22. The Fundamental Plane

23. Deviation from deVaucouleur r 1/4 ? Using Sersic (r 1/n ) instead makes little difference Steeper slope for BCGs; upturn at large L seems to be real

24. Bimodality Models now produce reasonable color- magnitude relations BCGs bluer? Bower et al. 2006 (Durham) BCGs Satellite galaxies (not BCGs)

25. Bower et al. 2006 (Durham) BCGs Color-Magnitude Croton et al. 2006 (Munich)

26. SDSS measurementsOUR measurements B03-Etypes C4-BCGs PL-BCGs

27. Color-Magnitude Models Hyde & Bernardi 2007 OUR-SDSS B03-Etypes C4-BCGs PL-BCGs

28. Another class of massive galaxies? BCGs are most luminous galaxies What about galaxies with largest  : – these host the most massive BHs – constraints on formation mechanism (cooling cutoff) (cooling cutoff) Once again, to select a clean sample must worry about systematics!

29. Expect 1/300 objects to be a superposition Galaxies with the largest velocity dispersion ● Single/Massive  Double ◊ BCG Sheth et al. 2003 Bernardi et al. 2006b

30. ‘Double’ from spectrum and image

31. ‘Double’ from spectrum, not image

32. ‘Single?’

33. HST images: with ACS-HRC SDSS  = 412 ± 27 km/s SDSS J151741.7-004217.6 3” 1’ HST

34. SDSS J204712.0-054336.7  = 404 ± 32 km/s HST SDSS 1’ 3’

35. HST: ACS-HRC 28 single15 multiple  = 369 ± 22  = 383 ± 27  = 385 ± 34  = 385 ± 24  = 395 ± 27  = 402 ± 35  = 404 ± 32  = 407 ± 27  = 408 ± 39  = 413 ± 35 Large  not likely due to projection

36. Luminosity-Size relation ● High-  ● BCGs Oegerle & Hoessel 1991 L ~ R 0.8 L ~ R 0.6 Compared to BCGs, large  sample has smaller sizes Large  from extreme dissipation? Bernardi et al. 2006b

37. Importance of Early-Type Galaxies –Stellar masses & Black Holes The Hierarchical formation picture –Down-sizing and Dry mergers Testing Dry mergers using scaling relations –Luminosities, Sizes, Velocity dispersions, Colors OUTLINE Selection bias in the M bh – L –  relations Selection bias in the M bh – L –  relations

38. Selection bias in the M bh - L -  !

39. From L From  Discrepancy between M bh function from L and  Tundo et al. 2007

40. What is the cause for this discrepancy? Selection bias in the  -L relation!! Bernardi et al. 2007b

41. Simulations …..

42. Conclusions Hierarchical models getting closer to observations … but not there yet BCGs should be good testing ground BCGs appear to be consistent with dry merger formation Large  objects consistent with more dissipation Selection bias in the M bh – L - 