Semianalytics and mock catalogues as tools to observe

Semi-analytics and mock catalogues as tools to observe ideas I. Semi-analytic modelling of galaxy formation The long way from first principles to the distribution of galaxy properties II. Mocking the Universe Construction, limitations and examples of mock catalogues Cargèse - August 2006

Semi-analytic modelling of galaxy formation “Y a des progrès à faire du côté de la gastrophysique” … F. R. Bouchet Jérémy Blaizot (MPA) Cargèse - August 2006

Large-scale surveys To what extent are galaxies tracers of DM Physical “sampling” (bias) + observational selection Colless et al. , 2001 Cargèse - August 2006

From low to high redshifts Galaxies @ z = 0. 4 SAMs and mocks provide a means to connect populations of galaxies selected in different ways at different redshifts (e. g. LBGs/BXs/etc. from Steidel’s group) Galaxies @ z = 2. 6 Driver et al. 1998 Cargèse - August 2006

Observations at different wavelengths SAMs and mocks help establish the connection between populations of galaxies selected at different wavelengths HST O S I Sources 15 mm Sources 6. 7 mm The ISO-HDF Project (Mann et al. ) Cargèse - August 2006

Last but not least … On top of these motivations, there is the increasing need to produce “realistic” catalogues that can be used: - to prepare forthcoming observations - to validate analysis techniques used on real obs. - to check/understand biases & uncertainties (e. g. cosmic variance) Cargèse - August 2006

Structure formation Dark matter hierarchical structure formation Given initial conditions and a cosmological model, we know how to describe the formation of dark matter structures with N-body simulations. Cargèse - August 2006

Structure formation : N-body simulations Cargèse - August 2006

It all happens in haloes… Semi-analytics neglect the impact of baryons on the formation of large scale structures, and can thus be described a posteriori within the hierarchy of haloes and their evolution. The hybrid approach exploits our best way to describe structure formation : N-body simulations. Cargèse - August 2006

Galaxy formation : relevant processes Cooling (metallicity, structure, …) Star formation (threshold, efficiency, IMF, …) AGNs (BH growth, feedback, …) Dust (formation, distribution, heating & cooling, …) Galaxy formation & evolution Galaxy interactions (morphological transformations, starburs intracluster stars, … Winds (IGM heating, enrichment, SN feedback, etc…) Stellar evolution (spectrophotometric evolution, yields, SN I/II rates, …) Cargèse - August 2006

Layout I. Implementation of the “hybrid” approach II. Limitations of SAMs III. Example : Brightest cluster galaxies Cargèse - August 2006

Layout I. Implementation of the “hybrid” approach II. Limitations of SAMs III. Example : Brightest cluster galaxies Cargèse - August 2006

From particles to haloes From particles to « haloes » z=3 Halo identification (FOF) and characterisation (Mass, Spin, Energies, etc. ) z=1 z=0 Cargèse - August 2006

(Sub-)Halo finders … Identification of substructures from the density field (only) SUBFIND (Springel et al. 2001) ADAPTAHOP (Aubert et al. 2004) Cargèse - August 2006

From particles to halo merger trees From particles to « haloes » z=3 Halo identification (FOF) and characterisation (Mass, Spin, Energies, etc. ) From density evolution to merger trees z=1 Construction of a full merger tree (mergers, accretion, z=0 fragmentation, evaporation) Cargèse - August 2006

Example of a Cluster’s tree Tidal stipping Cargèse - August 2006

Semi-analytics Hot gas (Tvir) Feedback Metal enrichment (ICM & IGM) Galaxy mergers Spin (l) cooling Disc formation Star formation Stellar evolution Metal enrichment (ISM) + model of simple stellar population evolution (w/ dust) Cargèse - August 2006

Cooling (source term…) Assume hydrostatic equilibrium (+ isothermal) : temperature and density profile. Cooling time (function of radius) : White & Rees (1978) Binney (1977), Silk (1977) Mass of gas that actually cools : Free-fall radius Note : cooling rates are sensitive to the heavy elements content of the gas (Z). Cargèse - August 2006

Cooling (source term…) “cold accretion” (rapid cooling) Quasi-static contraction (inefficient cooling) Transition at ~ 1012 Msun (with some redshift dependency) Kravtsov et al. Cargèse - August 2006

Star formation & feedbacks Star formation rate : (highl redshifts ? ) SSFR Supernovae feedback : (highly uncertain) or not … Kennicutt (1998) Metal enrichment : (hyper-highly uncertain) Sgas Fixed yield ? Instantaneous recycling ? Instantaneous mixing ? Cargèse - August 2006

Galaxy mergers - galaxy morphologies Galaxies spiral down haloes’ potential wells due to dynamical friction. When they reach the center they merge with the central galaxy. Bulge formation 100 % Disrupted disk (m 1 = m 2) Major mergers 50 % Fraction of progenitor disk mass tranfered to descendent’s bulge. Minor mergers 0% 0 m 2 / m 1 No bulge (m 1 >> m 2) 1 Cargèse - August 2006

Spectral energy distributions Final SED is the sum of SEDs of stars formed all along the hierarchical history … - stellar evolutionary tracks (Padova tracks, Genova, aenhancement ? ) - stellar spectra library - IMF … (Chabrier, Kennicutt, Salpeter …) - Extinction/emission by dust. Cargèse - August 2006

THE result … spirals ellipticals Stellar mass SFR Gas+stars Cargèse - August 2006

THE result … Cargèse - August 2006

Frequently asked questions - Do you “resolve” galaxies ? NO ! Galaxies in a SAM are “vectors” : {Mstar, etc, …} - How many parameters do you fit ? I wish I knew… Lucky we don’t “fit” … - What do you get that you didn’t put in by hand ? A quantitative estimate of the coupled evolution of a set of processes (each “put by hand”) within a complex system of boundary conditions (merger trees). Cargèse - August 2006

SAM Cinema … Semi-analytic galaxies D. M. density John Helly (Durham : http: //www. virgo. dur. ac. uk/) Cargèse - August 2006

Layout I. Implementation of the “hybrid” approach II. Limitations of SAMs III. Example : Brightest cluster galaxies Cargèse - August 2006

Chosing a simulation Trade-off between : - Mass resolution (ability to describe history + faint objects) - Volume (ability to describe rare objects) Cargèse - August 2006

Effects of mass resolution (1/3) • completeness limit galaxies in small mass haloes are missing. galics 3 galics 1 2 d. F Halo mass resolution “Galics 1” : 1. 6 1011 Msun “Galics 3” : 2. 8 109 Msun Cargèse - August 2006

Effects of mass resolution (2/3) • completeness limit galaxies in small mass haloes are missing. • redshift limit beyond zlim, there are no resolved haloes. 1010 MO 1011 MO 1012 MO 1013 MO Cargèse - August 2006

Effects of mass resolution (3/3) • completeness limit galaxies in small mass haloes are missing. galics 3 Mh = 3 109 Msun • redshift limit beyond zlim, there are no resolved haloes. • history resolution properties of new galaxies are not realistic galics 1 Mh = 2 1011 Msun Cargèse - August 2006

Other limitations … Each step of the post-processing involve approximations that do not disapear even if the results fit the observations ! - halo finder : N-body describes exactly the (non-linear) evolution of a density field … haloes are not so exact… - halo merger trees : following sub-structures is a delicate business … - galaxy mergers : largely unknown … (both when & how) - metals : production, transport … - SEDs : if you don’t believe in BC 03 or Chabrier’s IMF … Cargèse - August 2006

Layout I. Implementation of the “hybrid” approach II. Limitations of SAMs III. Example : Brightest cluster galaxies Cargèse - August 2006

Brightest Cluster Galaxies (BCGs) Brightest (and central) galaxies of the most massive haloes of the Universe (typically Mhalo ~ 1015 Msun) Selection of clusters (e. g. with LX), so far possible up to z ~ 1 BCGs are the galaxies with the richest merger trees Cargèse - August 2006

Brightest Cluster Galaxies (BCGs) De Lucia & Blaizot (2006) Cargèse - August 2006

Brightest Cluster Galaxies (BCGs) De Lucia & Blaizot (2006) Cargèse - August 2006

Brightest Cluster Galaxies (BCGs) : 2 x 2 Mpc (comoving) Cargèse - August 2006

Brightest Cluster Galaxies (BCGs) Mass growth ~ 3 since z=1 (along the “main branch”) Infered mass growth ~ 3 since z=1 (“total”) High-z BCGs are do not end up in local BCGs… Cargèse - August 2006

Brightest Cluster Galaxies (BCGs) The monolithic approximation (isolated evolution or “one-branch tree”) is wrong in general and should not be used to try to assess evolutionary links between galaxy populations observed at different redshifts. The proper way to go is to reproduce observational selections on the model galaxies, using mock catalogues, and then go back to the model to understand the (hierarchical) links between galaxies selected in different ways. Cargèse - August 2006

SAMs & mock catalogues for interpreting observations Jérémy Blaizot (MPA) Cargèse - August 2006

Selections … To what extent are galaxies tracers of DM Physical “sampling” (bias) + observational selection Colless et al. , 2001 Cargèse - August 2006

Selections, selections … SAMs + Mocks help establish the connection between populations of galaxies selected at different wavelengths HST O S I Sources 15 mm Sources 6. 7 mm The ISO-HDF Project (Mann et al. ) Cargèse - August 2006

Selections, selections, hierarchical evolution … Galaxies @ z = 0. 4 SAMs and mocks provide a means to connect (statistically) populations of galaxies selected in different ways at different redshifts (e. g. LBGs/BXs/etc. from Steidel’s group) Galaxies @ z = 2. 6 Cargèse - August 2006

General framework Theoretical Framework Observations Physical model (“ingredients” & “Recipes”) Surveys Galaxy samples @ diff. z & l Hybrid implementation Some comparison to obs. Mock Catalogues Cargèse - August 2006

Layout I. Construction of mock catalogues II. Limitations of mock catalogues III. Example 2 : Lyman Break Galaxies IV. Just do it … Cargèse - August 2006

Layout I. Construction of mock catalogues II. Limitations of mock catalogues III. Example 2 : Lyman Break Galaxies IV. Just do it … Cargèse - August 2006

Inputs for mock catalogues Series of napshots at zsnap = zi (i = 1, …, N) - Observer-frame (zsnap) absolute magnitudes and their derivative : - positions / velocities - size(s), inclination - IDs Cargèse - August 2006

Tiling boxes … basics Cargèse - August 2006

dec. Tiling boxes … replications r. a. Cargèse - August 2006

Tiling boxes … random tiling Supresses replication effects … and some of the signal (see later) dec. “Random tiling” r. a. Cargèse - August 2006

Example 1 : mock SDSS stripe 21 < r < 22 20 < r < 21 19 < r < 20 18 < r < 19 Cargèse - August 2006

Example 2 : mock V-band deep field 6 arcmin HDF 3 arcmin Johnson V filter Cargèse - August 2006

Sky. Maker (E. Bertin) Cargèse - August 2006

Layout I. Construction of mock catalogues II. Limitations of mock catalogues III. Example 2 : Lyman Break Galaxies IV. Just do it … Cargèse - August 2006

Correlation functions Excess probability of finding a pair of galaxies at a given separation, relative to a random distribution. Data-Data Random-Random Field-to-field variance (in counts) ~ average of x over field-size Cargèse - August 2006

Random tiling bias Negative bias typically peaking around r 0, with amplitude : Random pairs Cargèse - August 2006

Random tiling bias 100 Mpc/h 12 Mpc/h R. T. bias present around r 0, but well understood. Finite volume effects (integral constraint) comes in at larger scales… R. T. bias Finite Volum e Analytic estimate Cargèse - August 2006

Finite-volume effects & correlation function 100 Mpc/h A simulation does not contain fluctuations (clustering) on scales larger than Lbox 20 Mpc/h Cargèse - August 2006

Finite-volume effect & cosmic variance Simulation volume should be >> light-cone volume … Cargèse - August 2006

Layout I. Construction of mock catalogues II. Limitations of mock catalogues III. Example 2 : Lyman Break Galaxies IV. Just do it … Cargèse - August 2006

LBG selection (at z=3) (e. g. ) Adelberger et al. (1998) : Pure photometric selection : good test for the model and mock-catalogue methodology Blaizot et al. (2004) Cargèse - August 2006

LBG counts and cosmic variance 0 Gyr 1. 1 Gyr 1. 3 Gyr galics 3 Clustering of LBGs dominates cosmic variance up to (at least) 1 deg Cargèse - August 2006

LBGs : physical properties C’est « ca va » ! Steidel’s team 30% of LBGs’ intense SF is triggered by mergers Cargèse - August 2006

Link to local galaxies (1/2) The Epoch of Galaxy Formation, Baugh et al. 1998 LBGs z z Cargèse - August 2006

Link to local galaxies (2/2) z=3 z=0 77% of z=3 LBGs end up in E or S 0 at z = 0 35% of local E or S 0 have a LBG progenitor at z = 3 LBGs at z=3 E + S 0 with LBG prog. at z=3 Other E + S 0 Sp with LBG prog. at z=3 Cargèse - August 2006

Layout I. Construction of mock catalogues II. Limitations of mock catalogues III. Example 2 : Lyman Break Galaxies IV. Just do it … Cargèse - August 2006

Online stuff … box halo galaxy Cosmological quantities at each snapshot (e. g. redshift, number of halos, mass of stars) Physical props. Hierarchical links, Spatial information. Rest-frame magnitudes. cone Mock Images Observer-frame spectra Spatial information, Apparent magnitudes. Rest-frame spectra Cargèse - August 2006

Online stuff … http: //www. g-vo. org/Millennium/ (Gerard Lemson) Cargèse - August 2006