1. massive galaxies at high redshift: models confront observations rachel somerville STScI rachel somerville STScI GIRLS; Leiden, September 2008

2. z=5.7 (t=1.0 Gyr) z=1.4 (t=4.7 Gyr) z=0 (t=13.6 Gyr) Springel et al. 2006 Wechsler et al. 2002  shock heating & radiative cooling  photoionization squelching  merging  star formation (quiescent & burst)  SN heating & SN- driven winds  chemical evolution  stellar populations & dust  shock heating & radiative cooling  photoionization squelching  merging  star formation (quiescent & burst)  SN heating & SN- driven winds  chemical evolution  stellar populations & dust

3. rss, Hopkins, Cox, Robertson & Hernquist 2008, MN in press fairly broad consensus:  SN-driven winds remove baryons in small-mass halos  some process(es) prevent(s) cooling in large-mass halos (radio jets, clumps, conduction, cosmic ray pressure?) fairly broad consensus:  SN-driven winds remove baryons in small-mass halos  some process(es) prevent(s) cooling in large-mass halos (radio jets, clumps, conduction, cosmic ray pressure?)

4. quenching of massive galaxies (note the slope is wrong for low mass galaxies. this is not due to AGN FB, & cannot be easily solved by ‘tweaking’) rss, Hopkins, Cox, Robertson & Hernquist 2008, MN in press SSFR stellar mass

5.  halos with primarily “cold” vs. “hot” flows separated by a critical mass of few x 10 12 M sun at low redshift (e.g. Birnboim & Dekel 2003; Keres et al. 2004);  heating processes only effective when a quasi-static hot gas halo is present (i.e. in large mass halos)  halos with primarily “cold” vs. “hot” flows separated by a critical mass of few x 10 12 M sun at low redshift (e.g. Birnboim & Dekel 2003; Keres et al. 2004);  heating processes only effective when a quasi-static hot gas halo is present (i.e. in large mass halos) hot vs. cold flows simulations: A. Kravtsov

6. M*M* M vir [M ʘ ] all hot 10 14 10 13 10 12 10 1110 10 9 0 1 2 3 4 5 redshift z all cold cold filaments in hot medium M shock M shock >>M * M shock ~M * Dekel, Birnboim, Zinger, Kravtsov dense cold filaments can penetrate the hot medium in large-mass halos at high redshift

7.  associated with optical/X- ray luminous AGN/QSO  triggered/fed by mergers or secular (bar) instabilities  high accretion rates (0.1-1 L Edd ), fueled by cold gas via thin accretion disk  may drive winds that can shut off further accretion onto the BH and sweep the ISM out of the galaxy  associated with optical/X- ray luminous AGN/QSO  triggered/fed by mergers or secular (bar) instabilities  high accretion rates (0.1-1 L Edd ), fueled by cold gas via thin accretion disk  may drive winds that can shut off further accretion onto the BH and sweep the ISM out of the galaxy QSO/bright mode Radio Mode  radio galaxies (classical FR I and FR II type sources); generally no optical emission lines  ‘low accretion state’ (low Eddington ratio, <10 -3 Bondi accretion or ADAF?)  jets may heat gas in a hydrostatic hot halo, offsetting or quenching cooling flow

8. star formation historystellar mass build-up all stars star formation in bursts blue: fiducial model (cLCDM  8 =0.9) red: WMAP3 orange: no cooling if M h <10 11 M sun time-dependent IMF? SFR at high-z overestimated?

9. solid: MORGANA dash: Munich Mill. dot-dash: rss08 stellar mass function evolution “raw” model predictionswith convolved errors Fontanot, de Lucia, Monaco & rss in prep

10. stellar mass assembly without mass errorswith errors (0.25 dex) solid: MORGANA dash: Munich Mill. dot-dash: rss08 data: red: Conselice et al. blue: composite MF Fontanot et al. in prep

11. star formation rate density as function of galaxy mass green: GOODS; blue: Zheng et al. (COMBO-17) red: Conselice et al.; cyan: Mobasher et al. 2008 solid: MORGANA dash: Munich Mill. dot-dash: rss08 Fontanot et al. in prep

12. data: red square: Drory et al. 2008 blue: Bell et al. 2007 cyan: Martin et al. 2007 green: Grazian et al. 2006 magenta: Noeske et al. 2007 red x: Chen et al. 2008 blue diamond: Dunne et al. 2008 evolution of the SF ‘main sequence’ Fontanot et al. in prep

13. archeological downsizing data: Panter et al. 2007data: Gallazzi et al. 2007 Fontanot et al. in prep

14. when did the red sequence emerge?  the red sequence is still clearly identifiable in the field & clusters up to z~1 (Bell et al. 2005; Faber et al. 2007)  recently, a population of massive red galaxies detected in the field at 2<z<3 (Kriek et al. 2008; Taylor et al. 2008)  very red populations discovered in clusters up to z~2, but absent by z~3 (Zirm et al. 2008; Kodama et al. 2008)  the red sequence is still clearly identifiable in the field & clusters up to z~1 (Bell et al. 2005; Faber et al. 2007)  recently, a population of massive red galaxies detected in the field at 2<z<3 (Kriek et al. 2008; Taylor et al. 2008)  very red populations discovered in clusters up to z~2, but absent by z~3 (Zirm et al. 2008; Kodama et al. 2008)

15. Kriek et al. 2008 U-B

16. Zirm et al. 2008 field population

17. color-magnitude relation for coma Trager & rss 2008 black points: SDSS red points: SAM

18. rest-frame u-r for proto-clusters (M>10 14 M sun ) ‘field’ RS from Taylor et al. ECDFS z~0 SDSS RS Millennium z=2 clusters

19. Zirm et al. data H(AB) observed frame J-H for proto-clusters (M>10 14 M sun ) z=2

20. Testing physical parameter extraction from broad-band photometry  created SAM mock catalogs (including dust & IGM) and extracted U-, B-, and V- dropouts using GOODS selection criteria  added photometric errors by bootstrapping from GOODS data  ran a fairly standard BC03-based SED- fitting code on ACS+ISAAC+IRAC photometry (extract stellar mass, stellar population age, and SFR)  created SAM mock catalogs (including dust & IGM) and extracted U-, B-, and V- dropouts using GOODS selection criteria  added photometric errors by bootstrapping from GOODS data  ran a fairly standard BC03-based SED- fitting code on ACS+ISAAC+IRAC photometry (extract stellar mass, stellar population age, and SFR) S. Lee, R. Idzi, H. Ferguson, rss, T. Wikland, M. Giavalisco

21. U-drops (z~3); redshift fixed -19% -65% x2

22. B-drops (z~4); redshift fixed -25% -58% x2

23. B-drops; redshift fit

24. U-drops with largest mass errorsU-drops with smallest mass errors

25. Stringer et al. 2008 z~0.4-1.4 DEEP+Palomar photometry fixed redshift bootstrapped photometric errors Bundy et al. (2006) mass estimation method  no significant offset or mass trend --> scatter ~0.15 dex

26. parameter estimation summary  sources of error:  mismatch between assumed “tau” SFHs and SAM predicted SFH  ‘hiding’ of mass beneath young stellar population  ‘conspiracy’ of overestimated age (--> higher mass estimate) + ‘youth bias’ (lowers mass estimate) actually reduces mass errors  two-component models (with ‘maximally old’ component or secondary burst) produce improved age & SFR estimates, but poorer mass estimates!  sources of error:  mismatch between assumed “tau” SFHs and SAM predicted SFH  ‘hiding’ of mass beneath young stellar population  ‘conspiracy’ of overestimated age (--> higher mass estimate) + ‘youth bias’ (lowers mass estimate) actually reduces mass errors  two-component models (with ‘maximally old’ component or secondary burst) produce improved age & SFR estimates, but poorer mass estimates!

27. summary  differences between observational datasets much larger than differences between models!  number/mass density of massive galaxies is reproduced fairly well by models (when mass errors convolved) to z~2  SFR of massive galaxies at z~1-2 underestimated by factor of ~few in models if observational estimates taken at face value (IMF, AGN contamination, large errors in SED-fit based estimates?)  low mass galaxies form too early in models --> mass assembly “upsizes” rather than “downsizes”  massive galaxies in large mass halos are being quenched too late in models (RS emerges late)  errors in stellar masses, SFR, and ages derived from SED fitting to broad-band photometry at high redshift may be larger than we think...  differences between observational datasets much larger than differences between models!  number/mass density of massive galaxies is reproduced fairly well by models (when mass errors convolved) to z~2  SFR of massive galaxies at z~1-2 underestimated by factor of ~few in models if observational estimates taken at face value (IMF, AGN contamination, large errors in SED-fit based estimates?)  low mass galaxies form too early in models --> mass assembly “upsizes” rather than “downsizes”  massive galaxies in large mass halos are being quenched too late in models (RS emerges late)  errors in stellar masses, SFR, and ages derived from SED fitting to broad-band photometry at high redshift may be larger than we think...

29. bias in line-strength derived ages stellar mass mass weighted age LS derived age for 20 realizations of a Coma-sized halo Trager & rss 2008

30. star formation histories of early type galaxies as a function of stellar mass  SF histories of E’s in hierarchical models show qualitatively correct ‘downsizing’ behavior  but, probably not strong enough (new evidence from  /Fe ratios -- Arrigoni, Trager & rss in prep)  SF histories of E’s in hierarchical models show qualitatively correct ‘downsizing’ behavior  but, probably not strong enough (new evidence from  /Fe ratios -- Arrigoni, Trager & rss in prep)

31. the original downsizing plot Cowie et al. 1996 ~SSFR ~stellar mass

32. the many manifestations of ‘downsizing’  SF history from lookback studies (original Cowie definition): star formation activity shifts to lower mass galaxies over time  mass assembly histories: high mass galaxies assembled early, low mass galaxies assembled later  archeological downsizing: stellar ages are younger in low mass galaxies, indicating a later epoch of SF  chemo-archeological downsizing: higher [  /Fe] ratios in more massive galaxies indicate a shorter epoch of formation  SF history from lookback studies (original Cowie definition): star formation activity shifts to lower mass galaxies over time  mass assembly histories: high mass galaxies assembled early, low mass galaxies assembled later  archeological downsizing: stellar ages are younger in low mass galaxies, indicating a later epoch of SF  chemo-archeological downsizing: higher [  /Fe] ratios in more massive galaxies indicate a shorter epoch of formation