1. Merging clusters of galaxies: an optical view Sophie Maurogordato CNRS Laboratoire CASSIOPEE Observatoire de la Cote d’Azur, Nice

2. In collaboration with: M. Arnaud, J.L. Sauvageot (SAP, CEA-CEN Saclay) C.Benoist, A. Bijaoui, G.Mars,E. Slezak (Cassiopee, Nice) G. Soucail (OMP, Toulouse) A.Cappi, L. Feretti (Obs. & CNR Bologna) C.Ferrari, S. Schindler (Univ. Innsbruck) H. Bourdin (Univ. Roma) E. Belsole (IAO, Cambridge) G. Pratt (Max Planck Institute, Garching) B. Vandame (ESO, Garching) M. Plionis (IOA, Athens) R. Hunstead (Univ. Sydney)

3. Clusters in the process of merging In the hierarchical model, galaxy clusters form by merging of smaller mass units Irregular, morphologically complex clusters are seen in the process of formation. Key issue on the mass assembly of the universe at the scale of several Mpc. Combined X-Ray/ Optical analysis allows to follow separately the distribution of gas and of galaxies.

4. Evolution with time of the density and velocity distribution of galaxies during the merger event Schindler and Bohringer 1993

5. Evolution of the density and temperature of the gas with time during the merging event Takizawa 1999

6. MUltiwavelength Sample of Interacting Clusters Scientific goals:  Caracterize the merging scenario:  Comparison of density distributions (galaxies/gas/dark matter)  Velocity distribution, mass ratios of the sub-clusters  Signatures in the TX maps optical + X-Ray observations + Numerical simulations axis and date of collision  Test for the impact of the merging process on galaxy properties: Star formation ? Luminosity functions? SFR properties: optical (colors+ H  + spectra) + IR + radio

7. MUltiwavelength Sample of Interacting Clusters Optical: S.Maurogordato, C.Benoist, G.Mars, E. Slezak CASSIOPEE/OCA C.Ferrari, Univ. Innsbruck, A A.Cappi, Oss. Bologna, I M.Plionis, Athens, Gr X: J.L. Sauvageot, M. Arnaud, SAp, CEA-Saclay E. Belsole, Univ. Bristol, UK. H. Bourdin, Univ. Roma, I G.Pratt, Max Planck Institute, Garching Radio: C.Ferrari, S. Schinder, Univ. Innsbruck, L. Feretti, IRA Bologna R.Hunstead, Univ. Sydney IR C. Ferrari, Univ. Innsbruck,A P.A. Duc, D.Elbaz, Sap/CEA Saclay S.Maurogordato, C.Benoist, CASSIOPEE Optical BRI H  imaging: ESO (wfi@2.2m), CFHT (CfH12K)wfi@2.2m Multi-object spectroscopy R~600 ESO(EFOSC2@3.6m)EFOSC2@3.6m CFHT (MOS@3.6m)MOS@3.6m 2dF(AAT) X-Ray: Spectro-imaging: XMM, Chandra Radio: VLA, ATCA IR Proposal Spitzer submitted

8. MUltiwavelength Sample of Interacting Clusters Optical: S.Maurogordato, C.Benoist, A. Bijaoui,G.Mars, E. Slezak,CASSIOPEE/OCA C.Ferrari, Univ. Innsbruck, A A.Cappi, Oss. Bologna, I B.Vandame, ESO Garching M.Plionis, Athens, Gr X: J.L. Sauvageot, M. Arnaud, SAp, CEA-Saclay E. Belsole, IAO, Cambridgel, UK. H. Bourdin, Univ. Roma, I G.Pratt, Max Planck Institute, Garching Radio: C.Ferrari, S. Schindler, Univ. Innsbruck, L. Feretti, IRA Bologna R.Hunstead, Univ. Sydney IR C. Ferrari, Univ. Innsbruck,A P.A. Duc, D.Elbaz, Sap/CEA Saclay S.Maurogordato, C.Benoist, CASSIOPEE

9. MUSIC: Sample Selection Small sample: 10 clusters merger candidates with systematic X- Ray/Optical observations X-Ray bright clusters: First targets from XMM GT program Sauvageot et al. Low redshift: z ≈ 0.08-0.1  Spatial coverage: 30’ FOV (XMM, WFI) ≈ 2 h -1 Mpc  Spectral resolution (R ≈ 600) on a 3.6m telescope  High S/N Temperature maps Sample different stages of the merging process (pre/mid/post) from gas/galaxy segregation (Kolokotronis et al. 2000) 6 clusters fully observed: All are mergers !

10. A 2933 A 2440 A 1750 A 3921 A 2384 A 2142 A 2065 A 4038

11. How to characterize the mergers ? Optical: Analysis of the galaxy distribution Density distribution (2D)  Mapping: Dressler 1980, adaptative kernel (Kriessler and Beers 1997), multiscale analysis (Slezak et al. 1990, Escalera et al 1994)  Detection of sub-clusters & significance  Partitioning: best fit and reconstruction ! Projection effects : decontamination of background/foreground Red Sequence, Photometric redshifts

12. Multiscale analysis of A2163 Reconstruction of the Density field with different wavelets planes

13. Velocity distribution (1D) Departure from gaussianity:  skewness, kurtosis, tail and asymetry indexes Multiple tests (Beers et al. 1990, Pinkney et al. ) Partitioning ( KMM: McLachlan & Basford 1988)

14. Systems with high velocity dispersion: requires good sampling for testing if real ! CBI= 74018 ± 125 km/s  SBI = 1325 ± 145 km/s (125 members) -strong departure from gaussianity -well fitted by KMM 3-partition Central: CBI = 74249 ± 90 km/s, SBI= 879 ± 55 km/s Ferrari et al., 2003 CBI = 60000 ± 100 km/s SBI = 1451 ± 120 km/s (205 members) - Not significantly deviant from gaussianity - slight bimodality, just after the collision ? - Very massive system S. Maurogordato,. A. Cappi, C. Ferrari, G. Soucail et al., 2006 Abell 2163 Abell 521

15. Velocity offset of the sub-clusters A 1750: sub-clusters distinct in velocity space Pre-merger A2933: the subclusters are less clearly separated: the interaction has begun

16. Abell 2163: bimodality in the core region: West and East sub-clusters mixed Undergoing merger Maurogordato,. Cappi, Ferrari, Soucail et al., 2006

17. Subclustering in both density/velocity space Dressler and Schectman 1988, Girardi et al. 1997, KMM 3D, h-tree (Serna & Gerbal 1996), DEDICA (Pisani et al. 1998), Tomography (Ferrari et al. 2003)

19. Comparison galaxies/gas density field A2933: a pre-merger 2 sub-clusters in X-Ray and optical, spatially coincident

20. Abell 521: a multiple merger Ferrari et al. 2003, Arnaud et al. 2000, Maurogordato et al. 2000

21. A2163: a pre and post-merger Main component: segregation gas/galaxies post-merger Northern component: gas/galaxies coincident pre-merger Arnaud, Sauvageot, Pratt, Bourdin et al. 2006

22. Properties of BCGs -No unicity (as in relaxed clusters) -Spatial offset from the centroid of the cluster -Often spatially associated to sub-clusters -Alignment of the PA with that of the cluster (or subcluster) -Frequent multi-nuclei structure -Velocity offset from the mean velocity of the cluster (and of the sub-clusters) -Offsets : signature of the dynamical stage

23. A 521A 2933 N A2933 SA2163

24. Alignment effects  PA gas density distribution  PA galaxy density distribution  PA of dominant galaxies  sub-clumps/ general axis Plionis et al. 2003

25. Strong signatures in the Tx maps Sauvageot et al. 2005 Belsole et al. 2003, 2004 Bourdin et al. 2004

26. Evolution in galaxy clusters Observational evidences SF lower in clusters/field -lower percentage of star-forming objects// field -HI deficiency in clusters SF in clusters depends on: Density (MD relation) redshift (Butcher-Oemler effect) Mass (downsizing effect) dynamical state ?

27. Which is (are) the culprit(s)? Infall of galaxy in the IGM > gas stripping (Gunn & Gott 1972) Ram pressure: High IGM density + relative velocity galaxy-galaxy interations : Strong: galaxy mergers (low relative velocities) Herquist & Barnes 1991 Weak: tidal effects (« harassment » Moore et al. 1998 Strangulation (gas halo removed, Bower & Balogh 2004)… Probably a mix of different mechanisms + increase of SFR in field galaxies and of infall rate of galaxies on clusters with z

28. How does merging affect SF in clusters ?  Induce starbursts: Time-dependent gravitational field (Bekki 1999) Combination of previous effects (Gnedin 1999, Moore 1999)  Observational evidence Distribution of SB, PSB galaxies in Coma Caldwell et al. 1993, Poggianti et al. 2004, in A521 and A3921 Ferrari et al. 2005 Existence of a burst of SF before truncation

29. Poggianti et al. 2004 Ferrari, Benoist et al. 2005 Ferrari,Maurogordato et al. 2003

30. Reconstructing the SF history in A2163 Coll. J. Brinchmann (Porto Univ. ) & S. Charlot (IAP) in progress High spectral resolution R=2500, S/N > 10, VIMOS/VLT spectra (300/205 cluster members) 400-520 nm Lick indexes, Dn(4000), EW ([OII], [OIII], Balmer lines) Test for recent (< 2 Gyr) star formation bursts Detection of k, k+a, e(a), e(b), e(c) population and localisation as respect to the signature of merging events

31. Summary  Generic properties of merging clusters as predicted by numerical simulations  Irregularities in the density distribution (sub-clusters, isophote twisting, ventroid offsets) Gas/galaxy segregation Offset of brightest members (z, spatial) Strong signatures in X-Ray T maps Departure from gaussianity in the velocity distribution Strong alignments effects  Careful comparison to simulations to modelize the merger history X-Ray + optical data  Is star formation affected by the merging process and how?  Higher fraction of SB/PSB galaxies/ regular low z clusters Cases of spatial correlation with the merger, to be extended to larger sample Multiwavelength data ( cf talk Chiara Ferrari: Abell 3921) Numerical simulations with SF