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FORMATION AND EVOLUTION OF EARLY TYPE GALAXIES: Hierarchical or Monolithic ?

FORMATION AND EVOLUTION OF EARLY TYPE GALAXIES: Hierarchical or Monolithic ?. C esare Chiosi Department of Physics & Astronomy “Galileo Galilei ” University of Padova , Italy.

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FORMATION AND EVOLUTION OF EARLY TYPE GALAXIES: Hierarchical or Monolithic ?

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  1. FORMATION AND EVOLUTION OF EARLY TYPE GALAXIES:Hierarchical or Monolithic? Cesare Chiosi Department of Physics & Astronomy “Galileo Galilei” University of Padova, Italy Castiglione della Pescaia 16 -20 September, 2013

  2. ….and collaborators Umberto Buonomo Giovanni Carraro LetiziaCassara’ Tommaso Grassi Emiliano Merlin Cesario Lia Stefano Pasetto Lorenzo Piovan Rosaria Tantalo

  3. Setting the scene: Cosmic Proportions In this context: Galaxy Fomation and Evolution are hot topics of modern Astrophysics • Dark Energy 70% • Dark Matter 25% • Baryonic Matter + Neutrinos 5%

  4. Classical Paradigm of Galaxy Formation (ETGs, in particular) • Cosmological Model of the Universe • Dark Energy + Dark Matter + Baryonic Matter (& Neutrinos) • Hierarchical Clustering of Dark Matter • Hierarchical mergers of DM+BM haloes to form “visible” galaxies all over the Hubble time • Massive galaxies are the end product of repeated mergers and are in place only at recent times. But data do not exactly tell this and …..

  5. In brief, the mainquestions are: Ellipticals & Dwarfs Which mechanism(s) can explain the complex SFHs of dwarf galaxies? How did massive ellipticals form? (Mergers vs. Collapse)

  6. Downsizing scenario: at variance with the hierarchical trend of DM halos, more massive galaxies tend to form their stars earlier and in a shorter period than smaller galaxies, which experience more prolonged star formation histories (at odd with ‘naive’ hierarchical models). See e.g. Bundy et al. 2006, Clemens 2006. Recent observations of massive and red spheroids at very high redshift (e.g. Cimatti 2007, 2008) support this scenario. Perez-Gonzalez et al. 2007 Massive ETGs are elusive Galaxies • White 1996, “early” hierarchical model: these galaxies form late (z < 1) by the merging of already assembled discs. Evidence from stellar populations (Matteucci 1996), the tightness of the fundamental plane (Renzini & Ciotti, 1993), the evolution of the color-magnitude relation (Kodama et al., 1998; Blakeslee et al., 2003; Ellis et al. 2006) and the local Mg2- relation (Bernardi et al. 2003) suggested that they formed early (z > 2) in a short burst of star formation. Chiosi & Carraro (2002) and Merlin & Chiosi (2006) showed how this is indeed achievable in numerical simulations, provided that mass, density and energy budgets of protogalactic halos are correctly taken into account. • Bell 2004, De Lucia et al. 2006, “dry mergers” hierarchical model: massive ellipticals could be assembled late by dry mergers of other ellipticals, to preserve the oldness of their stellar populations while producing a low assembly redshift. This possibility is severely constrained by the modest (if any) evolution of the high end of the stellar mass function since z = 1.5 (Bundy et al. 2006; Cimatti et al. 2006): while models predict a doubling of stellar masses (De Lucia & Blaizot, 2007), evidence excludes an evolution larger than 0.2 dex (Monaco et al. 2006).

  7. Dwarf galaxies are elusive as well... • The star formation histories of LG Dwarfs are all different from one another. • Many dIrrs contain significant old populations (RGBs, and/or RR Lyr stars). • The most recent star-formation episodes are relatively short, ranging from 10-500 Myr in duration in both dIrrs and dSphs. Seemingly, long intermediate-age episodes of star formation may actually be made by many short, unresolved, bursts. • Chemical considerations suggest that the oldest populations in these galaxies are younger than the oldest Galactic globular clusters. Anyway, very few single galaxies contain only stars older than 10 Gyr. Some galaxies may contain very few or no stars older than 10 Gyr. Mateo (1998)

  8. So…current scenarios are • Hierarchical: massive ETGs are the end product of subsequentmergers of smallersub-units over time scalesalmostequal to the Hubble time. • Dry Mergers: fusion of gas-free galaxies to avoid star formation. WetMergers: the samebut with some stellar activity. • Monolithic: ETGsform at high redshift by rapidcollapse and undergo a single, prominent star formationepisode, eversincefollowed by quiescence. • RevisedMonolithic: a great deal of the stars in massive ETGs are formedveryearly-on at high redshifts and the remainingonesatlowerredshifts.

  9. Hierarchical or Monolithic? For long time the preferencehasgone to the hierarchicalschemethatwasconsidered the reference frame for anytheory of ETGsformation (the massive ones in particular). The success of thistheoryismainly due to the achievementsobtained in modelling the large scale gravitationalstructures of the Universe (filamentarystructure, galaxygroups and clusters). Howeveritsextensiontoindividualgalaxieshasneverbeenvalidatedbysolidindependentarguments. Because of it, the potentialcapability of the monolithic-like mode hasnotbeenfullyexplored. Weintend to show herethatthislatterschemeworksequallywell, ifnotbetter.

  10. Aims of this Review….. • We concentrate on the models obtained with the Revised Monolithic scheme. • First we highlight the role of the initial density and total mass of the system in determining the kind of star formation that takes place in ETGs. • Second, we shortly report how they are able to reproduce current observational data for ETGs. • Finally, we quickly present galaxy models with DUST in the ISM and the effect of this on SEDs and colors.

  11. Whichkind of Star Formation?… from ObservationalHints (1) • Scale Relations: Faber-Jackson EffectiveRadius- SurfaceBrightness FundamentalPlane& kappa space Diameter (m=20.75 mag/sec^2) - velocity dispersion – surface brigthness SFR - Mass - Luminosity - Redshift

  12. Whichkind of Star Formation?…from ObservationalHints (2) • HR diagrams for nearby dwarf galaxies of the LG. • Integrated spectra, magnitudes, colors, line absortpion indices for galaxies of the local Universe • The same but as a function of the redshift for distant galaxies. • The chemical properties (abundances, abundance ratios, gradients).

  13. Whichkind of Star Formation?…from ObservationalHints (3) • Colour-Magnitude Relation • a-enhancement: [a/Fe] vs [Fe/H]  SFR • The UV excess • Linestrengthindices • Two indices diagnostics …… the list is very long !

  14. It follows that ….. • Over the years, all the topics mentioned above have been extensively investigated to conclude that: • In some way the kind of SF occurring in ETGs depends on their mass and density (which one?). • It is early, short and intense in massive (and high density) ETGs and long, less efficient, and perhaps in bursts, in the low-mass (and low-density) ones.

  15. Wewouldlike to address and answer the followingquestions… • Under whichphysicalconditionseither a single prominentepisode or severalepisodes of star formations do occur? • Which model best explains the whole pattern of observational data for ETGs? The hierarchical or the monolithic ? Or a complexcombination of the two? • Standard semi-analytical galaxy models are not suited to the aim, because they already contain the answer built in. • The numerical NB-TSPH simulations are the right tool provided they include accurate treatments of important physical processes such as SF, heating by energy deposit, cooling by radiative processes, and chemical enrichment, … suitable initial conditions..

  16. Simulating the formation of cosmic structures: Ingredients and recipes • Interactions • Gravity • Hydrodynamics • “Specials” • Cosmological • View • Matter • Dark Matter • Gas • Stars • Temporal evolution

  17. Matter • Dark Matter • Gas • Stars “Particles” (“bodies”) with different properties, moving in the phase space • Interactions • Gravity • Hydrodynamics • “Specials” Newton’s law Tree structure (N logN) Particle-particle (N²) • Cosmological framework • Temporal evolution Simulating the formation of cosmic structures: requirements of a NB-TSPH code (Dark Matter)

  18. Matter • Dark Matter • Gas • Stars “Particles” (“bodies”) with different properties, moving in the phase space Conservation laws • Interactions • Gravity • Hydrodynamics • “Specials” Smoothed Particle Hydrodynamics (Only for gas particles) • Cosmological framework • Temporal evolution Simulating the formation of cosmic structures: Requirements of a NB-TSPH code (Gas)

  19. “Particles” (“bodies”) with different properties, freely moving in the phase space • Matter • Dark Matter • Gas • Stars • Energy sinks and sources: • Cooling (radiative cooling, inverse Compton effect) • Heating (Stellar feedback, UV cosmic background, • “exotic” sources) • Chemical composition and enrichment • Star formation • ... • Interactions • Gravity • Hydrodynamics • “Specials” • Cosmological framework • Cosmological expansion of the Universe • Appropriate boundary conditions • Temporal evolution Simulating the formation of cosmic structures: Requirements of a NB-TSPH code (Stars)

  20. Simulating the formation of cosmic structures Extremely large ranges in physical values - mass: 106 ---> 1014 Mo (8 orders of magnitudes) - temperature: 10 ---> 108 K (7 orders of magnitudes) - distances: 1 ---> 107 pc (7 orders of magnitudes) - times: 1 ---> 1010 years (10 orders of magnitudes) - density: 10-33 ---> 10-18 g/cm3 (25 orders of magnitudes) Very large numbers of particles are (would be…) needed Baryonic mass of a typical galaxy: 1011 Mo Mass of a typical small structure: 106 Mo Particles to resolve small structures: from 102---> 107 particles (without considering outskirts...) – feasible ? ---> often lower resolution Extremely violent phenomena Supernova explosions Supersonic turbulence and shocks AGN feedbacks

  21. RealisticModels of Galaxiesrequire accurate Input Physics & precise NumericalAlgorithms 1. Parallel code: Evol 2. Initial conditions: start at very early epochs 3. Cooling and Heating 4. Feed back by SN & SW, Chemical enrichment 5. Interstellar Medium (presence of dust) 6. Star Formation (prescriptions)

  22. 7. Gravitational pot 8. Formation Histories (mass and densities) 9. Mass assembling and 3D structure 10. Stars after assembling 11. Surface and volume mass densities 12. Ages and metals of stars 13. Galactic winds 14. Dust in ISM and photometry 15. Scale Relationships

  23. 1. The Parallel NB-TSPH Code: EvoL No details are given here………..

  24. LCDM Cosmology H0=70.1 km/s/Mpc Flat Geometry ΩL=0.721 σ8=0.817 Baryonic Fraction ≃ 0.1656

  25. 2. Initial Conditions from CosmologicalSimulations Start from a simulation for a given model of the Universe (SCDM orLCDM ) Fully cosmological initial conditions in LCDM concordance cosmology Ho = 70.1 km/s/Mpc,WL=0.721,Wb=0.046,baryon ratio 0.1656, s8=0.817, n=0.96. Large scale simulations calculated with COSMIC (Bertschinger 1995) COSMIC returns the initial comoving positions and initial peculiar velocities of all particles at the time the highest density perturbation in the field exits the linear regime. Therefore, the kind of DM proto-haloes that are in place at each redshift are known. 25

  26. Lukic et al. (2007) Plane • Numberdensity of haloes per Mpc3as a function of the mass and redshift. • The underlying IMF is from Warren (2003), seealso Press & Schechter and others. • Scale factor is needed to the volume coverd by typicalsurveys. Therefore haloes as massive as 1011 to 1012 Mo (and somewhat larger) have some probability of being already in place at redshifts larger than 5 (before the GDFs start decreasing by mergers). We estimate that 5 × 106 is a reasonable choice. Take the numer of ETGs in SDSS (about 60,000) and compare it with the total number of galaxies (over one million). Since the total volume covered by SDSS is about 108 Mpc3, the above estimate for the number ETGs corresponds to about 5% of the total volume. Therefore the scale is C ≃ 0.05 × 108.

  27. InitialConditions • Instead of searching inside a large scale simulation, the perturbation (proto-halo) best suited to our proposes, we simply suppose that a perturbation of this type is there and derive with COSMIC the position and velocities of the DM+BM particles from a smaller area of the large scale field around the perturbation we are interested in. • The box has a size of l=9.2 comovingMpc, and is described by grid of 463 particles; impose a constrained density peak to induce a virialized structure at the center of box; impose a gaussian spherical overdensity with average linear density contrastdr/r = b(withb=3, 5, 10) smoothed over a region of 3.5 comovingMpc; COSMICS returns the initial comoving positions and peculiar velocities at the moment in which the particle with the highest density is exiting the linear regime.

  28. Initial conditions • Cut off a sphere of radius l/2 change the comoving coordinates to physical values (by dividing the comoving value by the expansion parameter a=1/z-1 with z the initial redshift) and add a radial outward velocity to each particle, proportional to the radial position and initial redshift thus mimicking the outward Hubble flow • Where H(z) is need cosmological model • Add a minimum value of solid-boy rotation with spin parameterl=0.02 • Gas particles have mass mgas=01.656 mo, DM particles have mass MDM = (1-0.1656) mo • Total number of MD and gas particles 2 x 58000.

  29. Set of Model Galaxies Initial parameters of model galaxies (Merlin et al. 2012) These initial conditions are similar to those adopted by Merlin & Chiosi (2006, 2007)

  30. 6. Stirring in the GravitationalPot • Duty cicle: …stars – energy generation - gas heating – gas enriching – gas cooling – stars…. • The pot: the gravitationalpotentialwell • Therefore: totalgalaxy mass & initialdensity are the keyparameters It follows that….. For all details see Chiosi & Carraro (2002), Merlin et al (2010, 2011, 2012)

  31. 7. Star FormationHistories: Sameinitial over-densitybutdifferentmasses Chiosi & Carraro (2002 MNRAS, 335, 335) predictedthat SFR changes from monolithic to bursting mode atdecreasing mass and anticipated downsizing and time delay.

  32. KeyResult for the SFR:Same mass butdifferentinitialover-density Thisbasicdependence of the SFR on the total galaxy mass and initial over-density (environment) hasbeenamplyconfirmed over the years by manyobservational and theoreticalstudies. It is worth noting here that this is possible only in the monolithic-like scenarios. Chiosi & Carraro (2002, MNRAS, 335, 335) predictedthat SFR changes from monolithic to bursting mode at decreasing overdensity (environment) and fixed mass.

  33. The same from indices Later re-proposed by Thomas et al (2005) analysing the line strength indices for a sample of nearby galaxies. Picture from Thomas et al. (2005) & Renzini (2006, ARAA)

  34. Predicting future observationalconfirmation: Goods From Chiosi & Carraro (2002) see also Giavalisco et al (2006)

  35. SFH: oldresultsfullyconfirmed Merlin et al 2012 High Mass HM Medium Mass MM Low Mass LM Density High Medium Low Very Low

  36. 8. Assembling the Stellar Mass • Top Panel: percentage of assembled mass at given redshift with respect to the star mass at z=1. • Color code: red z=10, blue z=5, green z=2, black z=1.5 • Bottom Panel: redshift at which a given percentage p of the total stellar mass at z=1 is assembled • Color code: red p=50%, black p=99% I, J: I for density, J for mass

  37. 9. Stellar Content afterAssembly Density HD MD LD VLD Mass (MO) HM 1.7x1013 MM 2.7x1011 LM 4.2x109 Redshift HDHM 0.27 MDHM 0.56 LDHM 0.49 VLDHM 1.0 HDMM 1.0 MDMM 0.88 LDMM 0.6 VLDMM 0.15 HDLM 0.73 MDLM 0.79 LDLM 0.25 VLDLM 0.51

  38. 10. Surface Mass Density Profiles Density HD MD LD VLD Mass HM MM LM Z = 1 Log s [g/cm2] Where m=4 for HM-, m=1.5 for IM-, and m=2.5 for LM- galaxies in partial agreement with the empirical luminosity – index relationship by Caon et al (1993). In any case mHM > mIM + LM . Log r [kpc] Black Diamonds: Reff

  39. Mass Density Profiles Density HD MD LD VLD Mass HM MM LM Z = 1 Log r [g/cm3] Log r [kpc] 62

  40. 11. Ages of Stellar Populations Density HD MD LD VLD Mass HM MM LM Redshift HDHM 0.27 MDHM 0.56 LDHM 0.49 VLDHM 1.0 HDMM 1.0 MDMM 0.88 LDMM 0.6 VLDMM 0.15 HDLM 0.73 MDLM 0.79 LDLM 0.25 VLDLM 0.51 Virial radius is equal to rmax in the abscsissa

  41. Metallicitiesof Stellar Populations Density HD MD LD VLD Mass HM MM LM Redshift HDHM 0.27 MDHM 0.56 LDHM 0.49 VLDHM 1.0 HDMM 1.0 MDMM 0.88 LDMM 0.6 VLDMM 0.15 HDLM 0.73 MDLM 0.79 LDLM 0.25 VLDLM 0.51 64 Virial radius is equal to rmax in the abscsissa

  42. Predicted vs observed mass-metallicity relationship It flattens out !!! From old NB-TSPH models SLOAN DATA Tremonti et al (2004 ApJ 613, 898) Chiosi & Carraro (2002)

  43. Mean Metallicity vs Mass 5 SFR is implicit ! 10 99% 50% Merlin et al (2012)

  44. Adding the SFR:Metallicity – Mass – SFR Mannucci, Cresci et al (2010), Cresci et al (2011)

  45. Metallicity-SFR-outflow-infall Relationship • Various physical causes at work. • From the chemical point of view, NB-TSPH models grossly obey the scheme :infall (early) + outflow (late). • With infall the metallicity tends to the yield, with outflow the metallicity tends to freeze out. • Mass-SFR relation: in massive galaxies the SFR is early and intense. This cuses early outflows and freezing out of metallicity. • All this in agreement with the alpha-enhancement problem.

  46. Gradients in Metallicity Chiosi & Carraro (2002) Confirmed by the observational study of Forbes et al (2005) Confirmed by Merlin et al (2012, MNRAS, 427, 1530)

  47. Gradients in Metallicity Left to right, top to bottom: HDHM, LDHM, HDLM, LDLM at their last computed age

  48. Gradients in MeanMetallicity Merlin et al (2012)

  49. 12. GalacticWinds Galactic winds occur but not according to the Larson (1974) model, thus ruling out a point of severe contradiction

  50. More on Galactic Winds Model LDLM Model HDHM Z= 2.2 Z= 1.0 Z= 0.05 Z= 4.4 Z= 1.0 Z= 0.2

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