Formation hirarchique des structures grande chelle de lUnivers:

Les observations face aux modles

Sophie Maurogordato

En collaboration avec:M. Arnaud, E. Belsole, F. Bernardeau, M.Lachize-Rey, J.L. Sauvageot, R.Schaeffer, R. Teyssier (CEA-CEN Saclay)

F. Bouchet (IAP)

C. Benoist, A. Bijaoui, H. Bourdin, C.Ferrari, E. Slezak (OCA)

C. Balkowski, V. Cayatte, P. Felenbok, D. Proust (Obs. Paris- Meudon)

R. Pello, J.P. Kneib (OMP, Toulouse)

A.Cappi, P. Vettolani, L. Feretti (Obs. & CNR Bologna, I)

M. Plionis, S. Basilakos (Obs. Athenes, Gr)

D. Batuski, C. Miller, T. Beers, J. Kriessler (USA)

The ESP team

CfA2SSRS29325 galaxiesmB

General Framework Big Bang theory General Relativity Cosmological Principle

Primordial fluctuations (infinitesimal)

Growth by gravitational instability

Large scale structure of the Universe observed today

Cosmological ScenarioDensity parameters: Wm + WL + Wk = 1 (Einstein equations)

Wm: total matterWL: dark energyWk: curvatureWb: baryonic matter

Hubble constant : H0 = 100 h km/sec/Mpc

Normalization: s8 mass fluctuations in 8h-1 Mpc spheres

+ Nature of dark matter

Cosmological parameters from observations

Statistical Analysis of galaxy and cluster distribution 2-pt indicatorsESPGalaxy/matter Bias Luminosity segregationSSRS, SSRS2, ESPHigh order Moments of galaxies and clusters

How to constrain P(k) from LSS ? Primordial P(k) matter Theoretical Predictions Nature of density fluctuations (gaussian, non gaussian) Mechanism (inflation, texture, cosmic strings)

Linear evolution Evolved P(k) matterbias : relation galaxies/matter distributionlinear bias approximation: dr/r g = dr/r m

Evolved P(k)galaxies in real space

modelling the clustering distortion redshift space/real space

Evolved P(k)galaxies in redshift space Observations

Modelling P(k)

P(k) = B k (1+{ak+(bk)3/2+(ck)2}n)2/n

a,b,c functions of G = W h(Bond and Efstathiou 1984)

CMBNormalisation : BLSS via s8 and model of bias(variance in spheres of 8h-1 Mpc)and linear evolution

Coherence of large and small scales normalisation bias

Shape : characteristical of the nature and amount of dark matter

Standard CDM : G = W h = 0.5

The evolution of the clustering pattern with z for different cosmological scenarios

2nd order statistics on galaxy catalogs2D APM:Shape of w(q) and P(k) disagrees with SCDM (G=0.5)3D catalogs: Large uncertainty on normalisation (bias)Problem of Fair SampleFrom Maddox et al. 1990From Efstathiou et al. 1992

The ESO Slice ProjectEuropean Project (Vettolani et al. 1998) at the ES0 3.6m telescope

Slice of 23 square degrees near SGPbJ < 19.4

3342 redshifts

Large structure :50 x 100 h-1 Mpc @z=0.1From Vettolani et al. 1998

3D correlation function in 2000sThe power excess at large scales detected by the 2D APM is confirmed

SCDM with G=0.5 ruled out. Best agreement G = 0.2-0.3From Guzzo et al. 1999

Scaling relations in the galaxy/matter distribution Observations: The distribution of galaxies today is highly non gaussian.Hierarchical relation between correlation functions which can be modelized by:

Hierarchical modelSchaeffer 1984, Fry 1984Sum over graphes Sum over labelling of graphesMore generally: Scale invariant models (Balian and Schaeffer 1989)SJ are independent of scale

Predictions for the matter distribution:

SJs:Mildly non linear regime: Perturbation theory (Juskiewicz, Bouchet and Colombi 1993, Bernardeau 1994)

Case of power laws: SJ are constants

Highly non linear regime: numerical simulations (Baugh, Gaztanaga and Efstathiou 1995)

Scale invariance of the Void Probability function:SJ = f(g1,,gJ-1)

Scaling relations in 3D galaxy catalogsVoid probability functionCounts probabilities Maurogordato, Schaeffer and da Costa 1992Correlation functionsBenoist et al. 1999SSRSSSRSSSRS2

Galaxy/Mass distributionsDoes light trace mass ?

Linear bias hypothesis: dr/r g = b dr/r m

Biased galaxy Formation (Kaiser 1984, Bardeen et al. 1986)galaxies form at the location of high density peaks in an initial gaussian random field:d > ns x(r) > ns = A x(r) A = k n2/s2

more massive objects more clustered

Bias relation at small scales: more complicated (gaz cooling, supernovaefeedback, galaxy fusions within halos)

Distribution of galaxies within the halos: Semi-analytical models (Mo and White 1996, Benson et al. 2000, )

Luminosity bias in the SSRS2From Benoist et al. 1996Strong enhancement of correlation amplitude for very bright galaxies:M > -20.0

Luminosity bias in the ESPredshift space Real space (projected)From Guzzo et al. 1999

The next generation catalogs:Colless et al. 2002106688 galaxies 2dF Galaxy Redshift Survey

Luminosity bias in 3D galaxy catalogs in the 2000sFrom Norberg et al. 2001

Test of the linear bias hypothesisdg(x)= bg dm(x) xgJ(r)=bgJxmJ(r) SgJ = SmJ bgJ-2

Expected from luminosity segregation on x(r) ObservedInconsistence between 2nd order and high order moments results for linear bias hypothesis at small scales.From Benoist et al. 1999Second-order term for high luminosities

Cluster clustering3D x(r)ACO North and South with bII > 40z

AQUARIUS SUPERCLUSTERAmerican-French programPercolation on the ACO catalog: dcc < 25 h-1 Mpc supercluster candidates From Batuski et al. 1999Aquarius supercluster: Exceptionally dense and extended ! n=8 over 110 h-1 Mpcn=150 in the core (6 clusters)

110 h-1 Mpc

ConclusionsGalaxy distribution: hierarchical relations of high order correlations (cumulants, VPF, count probabilities)

Predicted in the frame of models with hierarchical formation of structures

Success of gravity to form the structure pattern observed today from initial gaussian fluctuations

Luminosity bias constant with scale (analysis of SSRS, SSRS2 and ESP, confirmed now by 2dFGRS and SDSS)

Problems with the linear bias hypothesis at small scales from the combined analysis of cumulants/ 2pt correlation function (galaxy and cluster distribution)

Today: multiple evidences for a concordant LCDM hierarchical model:Wm = 1 WL = 0.3, Wb=0.02, h=0.70, n=1.Combining CMB and LSS analysis gives a better determination of the parametersFrom Lahav et al. 2002New generation of 3D surveys (SDSS, 2dFGRS, ) + CMB experiments at different angular scales (COBE, Boomerang, WMAP, Planck,)

Soon : good knowledge of cosmological parametersBut still need to improve our understanding of the bias relation and physics of galaxy formation

Analysis of currently forming clusters In the hierarchical model, galaxy clusters form by merging of smaller mass units

Irregular, morphologically complex clusters are still forming.

Insights on the formation process before virialisation

Cosmological interest: n(z) is W dependant

Combined X-Ray/ Optical analysis allows to follow separately the distribution of gas and of galaxies.

Evolution with time of the density and velocity distribution of galaxies during the merger eventFrom Schindler and Bohringer 1993

Evolution of the density and temperature of the gas with time during the merging eventFrom Takizawa 1999

Abell 521: a cluster forming at the crossing of LSS filaments? - Severe gas-galaxy segregation- X-Ray: well fitted by a 2-component b-model: cluster + group- Privilegiated axes- Huge velocity dispersion: 1450 km/s (40 z)- BCG offset from the main cluster, in the group regionFrom Arnaud, Maurogordato, Slezak and Rho, 2000WW N

The Brightest Cluster GalaxyExtremely bright: L = 13 L*Arc structure embedding knots at z clusterLocated near the X-Ray group centerProfile: de Vaucouleurs without the cD tailBCG in formation within a group, by cannibalism of merging galaxies

From Maurogordato et al. 2000

Dynamical AnalysisNew observational data:150 zVariation of v and s along the general axis of the cluster:

In the central ridge: very high velocity dispersion, low mean velocity. Signatures of an old collision.

In the X-Ray group: low velocity dispersion, higher mean velocity. Probably infalling group towards the main cluster.Velocity distribution: non gaussian.Well fitted by a mixture of three gaussian distributions. From Ferrari et al. 2003s

v

Witnessing the collision of the Northern group with the main clusterCompression of the gas by the colliding group: Increase of Temperature in between the colliding units (detected by Chandra)Triggering of star-formation (excess of younger population in the compression region) From Ferrari et al. 2003From Arnaud et al. 2003

MUSIC: the programMUlti-wavelength Sample of Interacting Clusters

S. Maurogordato, C. Ferrari, C.Benoist, E. Slezak, H. Bourdin, A. Bijaoui (OCA)J.L. Sauvageot, E. Belsole, R. Teyssier, M. Arnaud (CEA-CEN Saclay)L.Feretti, G.Giovannini (IRA Bologne)

10 clusters at different stages of the merging process, 0.05 < z < 0.1

X-Ray: XMM/EPIC

Optical: 3-bands (V,R,I) wide-field imaging (ESO: Wfi@2.2m, CFHT: Cfh12K@3.6m) Multi-Object Spectroscopy (ESO: Efosc2@3.6m, next VIMOS@UT2, CFHT: MOS@3.6m)

Radio: VLA

MUSIC: Scientific Objectives

Characterize the merging process: velocity field and mass ratio of the components, axis and epoch of collision. Reconstruction of the merging scenario by numerical simulation.

Compare the respective distribution of galaxies, gas and dark matter according to the dynamical stage of the merging process.

Test for correlation between Star Formation Rate and gas compression

Large scale environnement. Do merging clusters preferentially occur at the crossing of filaments as predicted by hierarchical scenarios of structure formation ?

MUSIC: the targetsA 2933PreA 2440PreA 1750PreXMM/ESOA 3921MidXMM/ESOA 2384MidA 2142PostXMM/CFHA 2065PostXMM/CFHA 4038Post

Alignments effects in galaxy clustersPAI Platon: OCA (S.Maurogordato), NOA (M. Plionis)300 Abell clustersStrong alignment effect for clusters within superclusters:BCG / cluster10 brightest galaxies / cluster

The case of Abell 521Strong alignment of groups with the main orientation of the cluster

The fundamental plane of galaxy clusters: another evidence for hierarchical clusteringFrom Schaeffer, Maurogordato, Cappi and Bernardeau 1993Galaxy clusters

Elliptical galaxies

Dwarfs galaxies

Globular clustersGalaxy clusters:L = K Ra s2ba= 0.89, b=0.64

Future: Analysis of the cluster distribution in the CFHTLSGalaxy catalogCluster catalog by identification of the Red Sequence of ellipticals

Constraining the hierarchical model: I: Evolution of cluster counts with redshift: From Evrard et al. 2003Slice of 10x10

II- Evolution of correlation length with richness From Colberg et al. 2000

CONCLUSIONSMultiple evidences for the hierarchical model:

Scale invariance in the galaxy and cluster distribution,Fundamental plane for structures of very different masses,Properties of merging clusters.

Concordant model : LCDM with Wm=0.3, WL=0.7 agrees with most results of observational cosmology but still room for other alternatives

Next future:

Theory + Numerical simulations + Observations:

Which hierarchical model ?Better understanding of the bias relationNature of primordial fluctuationsTest of the Cosmological Principle