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SURVeys : THE mass assembly and star formation history

Lecture #4. SURVeys : THE mass assembly and star formation history. Observational facts. Putting it all together. Clear survey strategies Instrumentation and observing procedures Selection function estimates Let’s measure galaxy evolution !. Lecture plan.

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SURVeys : THE mass assembly and star formation history

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  1. Lecture #4 SURVeys: THE mass assembly and star formation history Observationalfacts Olivier Le Fèvre – LAM CosmologySummerSchool2014

  2. Putting it all together • Clearsurveystrategies • Instrumentation and observingprocedures • Selectionfunctionestimates Let’smeasuregalaxyevolution !

  3. Lecture plan • What are the main contenders to drive galaxy SFR and mass growth ? • The luminosityfunction and itsevolution • The star formation history: luminositydensity and SFRD • The mass function and the stellar mass densityevolution • Mass assemblyfrommerging • A scenario for galaxyevolution ?

  4. Whatmay drive galaxyevolution ? • A richtheory/simulation literature… • Identify key physicalprocesses • When ? On whichtimescales ? Beware: fashion of the day (e.g. from simulations) may fade quickly… …Stick to facts !

  5. Main physicalprocessesdrivingevolution • 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,…

  6. Hierarchicalmerging • The basics: hierarchicalgrowth of structures • Merging of DM halos • Galaxies in DM halos merge by dynamical friction • Major mergerscanproducespheroidsfromdisks • Mergingincreases star formation (but maybe short lived) • Increases mass (minor, major) • Merger Rate  (1+z)m

  7. Stellar mass growthfrom star formation and evolution of stellar populations • In-situ gasat halo collapse transformsinto stars • Accretedgasalonglifetimetransformsinto stars • Stars evolve (HR diagram) • Luminosityevolution • Colorevolution • Stellar population synthesismodels: (Bruzual&Charlot, Maraston,…)

  8. Cold gasaccretion • Along the filaments of the cosmic web • Steady flow for some billion yearscanaccumulate a lot of gas • Gastransformsinto stars • Produces important mass growth • FromPress-Schechtertheory Simulations At z~2 Dekel et al., 2009

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

  10. Example: combinedeffect of feedback and cooling on mass function

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

  12. Dekel, 2013

  13. Cool simulations, but…need to measuregalaxyevolution !A short summary of previouslectures… • Withdeepgalaxysurveys • Imaging & Spectroscopy • In large volumes • Minimizecosmic variance • For large numbers • Statisticalaccuracy • Measurepropertiesatdifferentepochs to trace evolution • Use thesemeasurements to derive a physical scenario

  14. Main evolutionindicators • Luminosityfunction, luminositydensity • Star formation rate density • Stellar mass function • Stellar mass density • Merging • Accretion • …

  15. The luminosityfunction From lecture #1

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

  17. Galaxy types vs. color

  18. Evolution ! Canada-France Redshift Survey back in 1995 • 600 zspec • 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

  19. CFRS: LF evolution per type to z~1 • The LF of red galaxies evolvesverylittlesince z~1 • Redearly-type galaxies are already in place at z~1 • Consistent with passive evolution (no new star formation) • Strongevolution of the LF for blue star-forming galaxies • Luminosity or numberevolution ? Littleevolution Strongevolution

  20. LF at z~1 from DEEP2 and VVDS

  21. A jump to z~2-4: UV LF from LBG samples • Using the LBG samples of Steidel et al. • ~700 galaxies withredshifts • Continuedevolution in luminosity L* • Steeperfaint end slope FromReddy et al., 2008

  22. Probing the LF to z~4 with the magnitude-selected VVDS • Steepslope for z>1 • Continuousevolution in luminosity • Evolution in densitybefore z~2 1 mag 2.5 mag Cucciati et al. 2012

  23. Downsizing SFR(z) vs. Halo mass • 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’ ! De Lucia et al., 2006

  24. Quenching • Star formation isstopped • But whatproducesquenching ? • Merging • Mass-related (feedback ?) • Environment Peng et al., 2010

  25. The Star Formation Rate Evolution: the ‘Madaudiagram’ back in 1996 • Putting togetherseveralmeasurement: • the strongevolution in luminositydensityobserved by the CFRS from z~0 to z~1 • Lowerlimits on SFRD from LBG samplesat z~3 • Lowerlimits on SFRD from HST LBG samples 2.7<z<4 • A peak in SFRD at z~1-2 ? From CFRS From HST Hubble Deep Field FromSteidel et al. Let’s call it the “et al. diagram”…

  26. SFRD from the IR SFRD from the UV • Direct observation of UV photons produced by young stars • But absorbed by dust: need to estimatedust absorption • UV photons produced by young stars are warming-up dust • Dustproperties: calibration of UV photons to IR flux

  27. ComparingLuminositydensityfrom UV and IR Sameshape: transformation is extinction E(B-V)

  28. Derivingdust extinction

  29. Star formation rate evolution: today • SFRD rise to z~2, then flat, thendecreases • Considerableuncertaintiesat z>3 Cucciati et al., 2012

  30. Stellar mass functionevolution • Getstellar 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

  31. Stellar mass functionevolution • Use double Schechterfunction • Because of the differentshape of the MF for differentgalaxy types (nextslide) • Massive galaxies are in place at z~1.5 • Strongevolution of the low-mass slope • Evolution in numberdensity Redshift

  32. MF evolution per type • Star-forming galaxies • Strongevolution in M* • Strongevolution of  • Quiescent galaxies • Strongevolution in M* to z~1.5, then no-evolution • Strongevolution in numberdensity Ilbert et al., 2013

  33. Mass function: evolution scenario

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

  35. Galaxy mass assembly: Cold gasaccretion or merging ? • Cold gasaccretion: The main mode of gas/mass assembly ? « This stream-driven scenario for the formation of disks and spheroidsis an alternative to the mergerpicture » (Dekel et al., 2010) • Merging • major merging ? • minormerging ? • Occasional but large mass increase • Over time mergerscanaccumulate a lot of mass • Need to measure the GMRH since the formation of galaxies • Mergers more/lessfrequent in the past • Integral mass accruedfrommergers ?

  36. Measuring the evolution of the galaxy merger rate • Method 1, A priori: pairs of galaxies • Method 2, A posteriori: mergerremnants, shapes • Bothmethodsrequire a timescale • Timescale for the pair to merge (vs. mass and separation) • Timescale for featuresvisibility (vs. redshift, type of feature…) • At high redshifts z>1: pairs • Fainttails/wispslost to (1+z)4 surface brightnessdimming

  37. 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 Conselice et al., 2008 With Fmg~F0(1+z)m m=0 to 6 !

  38. Merging rate from pair fraction Number density Merging rate Pair count Merger probability in Tmg Merging Timescale Tmg depends on separation rp and stellar mass Kitzbichler & White 2008 computed timescales ~x2 larger than previously assumed ~1Gy vs. 500My

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

  40. Galaxy Merger Rate History since z~1 m=4.7 • 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%) m=1.5 Major mergers, de Ravel et al. 2009 Minor mergers, Lopez-SanJuan et al. 2010

  41. Mergersat z~1.5 from MASSIV survey • 80 galaxies selectedfrom VVDS • Observedwith SINFONI: 3D velocityfields • Straightforward classification: 1/3 galaxies are mergers 10kpc Mergers at z~1.5 Lopez-SanJuan, 2013

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

  43. 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 assembledfrommergingwith >1/10 mass ratio • Mergingis an important contributor to mass growth • Otherprocessesatplay 46

  44. Cold gasaccretion ? First evidence in 2013 ?

  45. Building a galaxyevolution scenario ? • Several key processes have been identified, • Direct: mergers, stellarevolution • Indirect: accretion, feedback, environment • Properties have been quantified over >12Gyr • Observationnalreferencesexist to confrontmodels • Semi-analyticalmodels • Take the DM halo evolution • Plug-in the physical description of processes • Getsimulatedgalaxy populations • Semi-successful… somelethalfailures • Over-production of low-mass/low-z and under-production of high-mass/high-z galaxies • Reproducinglow-z LF/MF AND high-z LF/MF • More to bedone !

  46. Circa 2002

  47. Hopkins et al., 2008

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