1. Lecture #4 Observational facts Olivier Le Fèvre – LAM Cosmology Summer School 2014

2. Putting it all together  Clear survey strategies  Instrumentation and observing procedures  Selection function estimates measure Let’s measure galaxy evolution !

3. Lecture plan 1. What are the main contenders to drive galaxy SFR and mass growth ? 2. The luminosity function and its evolution 3. The star formation history: luminosity density and SFRD 4. The mass function and the stellar mass density evolution 5. Mass assembly from merging 6. A scenario for galaxy evolution ?

4. What may drive galaxy evolution ?  A rich theory/simulation literature…  Identify key physical processes  When ? On which timescales ? Beware: fashion of the day (e.g. from simulations) may fade quickly… …Stick to facts !

5. Main physical processes driving evolution  Hierarchical assembly by merging  Increases mass “catastrophically”  Gaz accretion  Cold / Hot  Fuels star formation  Increases mass continuously  along the cosmic web  Feedback: sends matter back to the IGM  AGN (jets, …)  Supernovae (explosion)  Star formation and stellar evolution  Luminosity / color, lifetime  Star formation quenching  Environnement, f(density)  Quenching, Harassement, Stripping,… 5

6. Hierarchical merging 6 The basics: hierarchical growth of structures Merging of DM halos Galaxies in DM halos merge by dynamical friction Major mergers can produce spheroids from disks Merging increases star formation (but maybe short lived) Increases mass (minor, major) Merger Rate  (1+z) m

7. Stellar mass growth from star formation and evolution of stellar populations  In-situ gas at halo collapse transforms into stars  Accreted gas along lifetime transforms into stars  Stars evolve (HR diagram)  Luminosity evolution  Color evolution  Stellar population synthesis models: (Bruzual&Charlot, Maraston,…) 7

8.  Along the filaments of the cosmic web  Steady flow for some billion years can accumulate a lot of gas  Gas transforms into stars  Produces important mass growth  From Press-Schechter theory 8 Simulations Dekel et al., 2009 At z~2 Cold gas accretion

9. Feedback  Takes material out of a galaxy back to DM halo  May quench star formation ?  AGN feedback  f =0.05 (thermal coupling efficiency)  r =0.1 (radiative efficiency)  SNe feedback  : instantaneous SFR feedback efficiency V hot =485km/s and  hot =3.2 9

10. Example: combined effect of feedback and cooling on mass function 10

11. A lot of “definitive” theories and simulations Hopkins et al., 2006 White and Rees, 1978 White & Frenk, 1991

12. Dekel, 2013

13. Cool simulations, but… need to measure galaxy evolution ! A short summary of previous lectures…  With deep galaxy surveys  Imaging & Spectroscopy  In large volumes  Minimize cosmic variance  For large numbers  Statistical accuracy  Measure properties at different epochs to trace evolution  Use these measurements to derive a physical scenario 13

14. Main evolution indicators  Luminosity function, luminosity density  Star formation rate density  Stellar mass function  Stellar mass density  Merging  Accretion  …

15. The luminosity function From lecture #1

16. The reference at z~0.1: SDSS Blanton, 2001 10000 galaxies Blanton, 2003 150000 galaxies

18. Galaxy types vs. color

19. Evolution ! Canada-France Redshift Survey back in 1995  600 z spec  First evidence of evolution over ~7 Gyr  M* brightens by ~1 magnitude Global LF Lilly et al., 1995 Le Fèvre et al., 1995 1 mag

20. CFRS: LF evolution per type to z~1  The LF of red galaxies evolves very little since z~1  Red early-type galaxies are already in place at z~1  Consistent with passive evolution (no new star formation)  Strong evolution of the LF for blue star-forming galaxies  Luminosity or number evolution ? Little evolution Strong evolution

21. LF at z~1 from DEEP2 and VVDS

24. A jump to z~2-4: UV LF from LBG samples  Using the LBG samples of Steidel et al.  ~700 galaxies with redshifts  Continued evolution in luminosity L*  Steeper faint end slope  From Reddy et al., 2008

25. Probing the LF to z~4 with the magnitude-selected VVDS  Steep slope for z>1  Continuous evolution in luminosity  Evolution in density before z~2 Cucciati et al. 2012 1 mag 2.5 mag

26. Downsizing  The most massive / luminous galaxies form first, followed by gradually lower mass galaxies  The most massive galaxies stop forming stars first, with lower mass galaxies becoming quiescent later  This is ‘anti-hierarchical’ ! SFR(z) vs. Halo mass De Lucia et al., 2006

27. Quenching  Star formation is stopped  But what produces quenching ?  Merging  Mass-related (feedback ?)  Environment Peng et al., 2010

28. The Star Formation Rate Evolution: the ‘Madau diagram’ back in 1996  Putting together several measurement:  the strong evolution in luminosity density observed by the CFRS from z~0 to z~1  Lower limits on SFRD from LBG samples at z~3  Lower limits on SFRD from HST LBG samples 2.7<z<4  A peak in SFRD at z~1-2 ? From CFRS From Steidel et al. Let’s call it the “et al. diagram”… From HST Hubble Deep Field

29. SFRD from the UV  Direct observation of UV photons produced by young stars  But absorbed by dust: need to estimate dust absorption SFRD from the IR  UV photons produced by young stars are warming-up dust  Dust properties: calibration of UV photons to IR flux

30. Comparing Luminosity density from UV and IR Same shape: transformation is extinction E(B-V)

31. Deriving dust extinction

32. Star formation rate evolution: today Cucciati et al., 2012 SFRD rise to z~2, then flat, then decreases Considerable uncertainties at z>3

33. Stellar mass function evolution  Get stellar mass of galaxies from SED fitting  Uncertainties ~x2 (Initial Mass Function, Star formation history, number of photometric points on the SED, …)  Compute the number of galaxies at a given mass per unit volume

34. Stellar mass function evolution  Use double Schechter function  Because of the different shape of the MF for different galaxy types (next slide)  Massive galaxies are in place at z~1.5  Strong evolution of the low-mass slope  Evolution in number density Redshift

35. MF evolution per type  Star-forming galaxies  Strong evolution in M*  Strong evolution of   Quiescent galaxies  Strong evolution in M* to z~1.5, then no- evolution  Strong evolution in number density Ilbert et al., 2013

36. Mass function: evolution scenario

37. The mass growth of galaxies: stellar mass density * evolution  Integrate the MF  Global and per type  Smooth increase of the global  *  z=1-3: the epoch of formation of quiescent/early-type galaxies  Almost x100 from z~3 to z~1

38. Galaxy mass assembly: Cold gas accretion or merging ?  Cold gas accretion: The main mode of gas/mass assembly ? « This stream- driven scenario for the formation of disks and spheroids is an alternative to the merger picture » (Dekel et al., 2010)  Merging  major merging ?  minor merging ?  Occasional but large mass increase  Over time mergers can accumulate a lot of mass  Need to measure the GMRH since the formation of galaxies  Mergers more/less frequent in the past  Integral mass accrued from mergers 38 ?

39. pairs of galaxies  Method 1, A priori: pairs of galaxies merger remnants, shapes  Method 2, A posteriori: merger remnants, shapes  Both methods require a timescale  Timescale for the pair to merge (vs. mass and separation)  Timescale for features visibility (vs. redshift, type of feature…)  At high redshifts z>1: pairs  Faint tails/wisps lost to (1+z) 4 surface brightness dimming 39 Measuring the evolution of the galaxy merger rate

40. A wide range of measurements …  Different selection functions  Different luminosity/mass  Photometric pair samples  Pairs confused with star-forming regions  Background/foreground correction  Merger remnants  Redshift dependant  Subjective classifications  Different merger timescales 40 Conselice et al., 2008 With F mg ~F 0  (1+z) m m=0 to 6 !

41. Merging rate from pair fraction 41 Merging ratePair count Number density Merger probability in T mg Merging Timescale T mg depends on separation r p and stellar mass Kitzbichler & White 2008 computed timescales ~x2 larger than previously assumed ~1Gy vs. 500My

42. 42 z=0.35 z=0.63 z=0.93 Spectroscopy enables to identify real pairs Both galaxies have a spectroscopic redshift No contamination issue

43. Galaxy Merger Rate History since z~1  Major merger rate depends on luminosity/mass  Higher and faster evolution for low mass mergers  Explains some of the discrepancy between different samples  Minor merger rate has slightly increased since z~1, while major merger rate has strongly decreased  Major mergers more important for the mass growth of ETGs (40%) than LTGs (20%) Major mergers, de Ravel et al. 2009 Minor mergers, Lopez-SanJuan et al. 2010 m=4.7 m=1.5

44. Mergers at z~1.5 from MASSIV survey  80 galaxies selected from VVDS  Observed with SINFONI: 3D velocity fields  Straightforward classification: 1/3 galaxies are mergers 10kpc Mergers at z~1.5 44 Lopez-SanJuan, 2013

45. What about merging at early epochs ? Merging pairs at higher z from VUDS 45 Merging pair at z~2.96 HST/ACS VIMOS spectra Tasca et al, 2013

46. Galaxy Merger Rate History since z~3 from spectroscopic pairs  Peak in major merger rate at z~1.5-2 ?  Integrate the merger rate: >40% of the mass in galaxies has been assembled from merging with >1/10 mass ratio  Merging is an important contributor to mass growth  Other processes at play 46

47. Cold gas accretion ? First evidence in 2013 ?

48. Building a galaxy evolution scenario ?  Several key processes have been identified,  Direct: mergers, stellar evolution  Indirect: accretion, feedback, environment  Properties have been quantified over >12Gyr  Observationnal references exist to confront models  Semi-analytical models  Take the DM halo evolution  Plug-in the physical description of processes  Get simulated galaxy populations  Semi-successful… some lethal failures  Over-production of low-mass/low-z and under-production of high-mass/high-z galaxies  Reproducing low-z LF/MF AND high-z LF/MF  More to be done ! 48

49. Circa 2002

50. Hopkins et al., 2008