BEFORE I START MY TALK…… a few recent results from the environment of the HIPASS HI gals

MORPOLOGICAL & DYNAMICAL PARAMETERS OF HALOS IN VOIDS Manolis Plionis (NOA-Greece & INAOE-Mexico) Cinthia Ragone-Figueroa (IATE – Cordoba- Argentina) Amsterdam-Holland, December 2006 Extension of work taking gas into account is under-way using the HR Mare-Nostrum ΛCDM Simulations Gustavo Yepes (Univ. Autonoma de Madrid – Spain)Gustavo Yepes (Univ. Autonoma de Madrid – Spain) Stefan Gottlober (Potsdam Univ. – Germany)Stefan Gottlober (Potsdam Univ. – Germany) Dante Paz (IATE – Argentina)Dante Paz (IATE – Argentina) Nestor Espino Biriones (INAOE, Mexico)Nestor Espino Biriones (INAOE, Mexico) See talks by Porciani et al. and Aragon-Calvo et al.

What does structure formation paradigm tell us: CDM-like Power Spectra of initial perturbations predict a bottom-up scenario but with roughly simultaneous formation of structure at large-scales. Structures form by gravitational instability which as soon as it switches on creates anisotropic structures (filaments, walls). Galaxies & Clusters form in high-density regions (inside filaments & walls) by anisotropic accretion and merging of smaller mass units. Roughly simultaneous formation of structure at different scales creates “cross-talk” and thus correlated phenomena between these scales: k 3/2 δ k Log(M/M  ) Kaufmann et al 1999 From West 1994

What does formation paradigm tell us: Clusters form by merging accreting matter along preferred directions (filaments)  generic in all hierarchical clustering models, like CDM (cf. Bardeen et al. 1986; Van Haarlem & Van der Weygaert 1993, Tormen 1997; Knebe et al. 2004), irrespective of the density parameter for as long as the spectral index is n<-1. Knebe et al 2004 van Haarlem & van de Weygaert 1993, West 1994 GADGET Simulations from Yepes, Gottlober, et al.

0a. Our simulation, Halo Identification Procedure & Void definition ΛCDM simulation Size: L=500 h -1 Mpc with DM particles (m p = 7.7 x10 10 h -1 M o ) FoF: Halo Identification with linking length l=0.17 inter-particle separation Number: haloes with n m >130 (M>10 13 h -1 M o ), 1593 with M>2 x h -1 M o. Note that we do not identify independently sub-haloes, that belong to large haloes (as do for example, Avila-Reese et al. 2005) Environment Definitions For all Group-size Halos with <M<2x10 14 M o we find the nearest neighbour distance, R nn Void Haloes: Using as neighbours all haloes with M>10 13 M o we identify R nn as the Isolation Radius (R isolation ) and which defines the “Void” Radius. Haloes near Clusters: Using as neighbours only Cluster haloes with M>2 x10 14 M o ) we identify R nn as the call R cluster Radius.

0b. Halo Parameter Estimation Halo density and velocity ellipsoid shapes are determined by diagonalizing the corresponding moments of Inertia tensor: Alignment between any two vectors defined as: Halo Dynamical state: Dressler & Shectman (1998) substructure Δ-deviation statistic:

0c. Halo Parameter Error Estimation Resolution effects can introduce significant uncertainties in the derived parameters. Therefore, we estimate such uncertainties by selecting the most massive haloes and degrading them randomly to 130 particles/halo Systematic errors due to Resolution effects are also present:

R isolation >12 h -1 Mpc R cluster < 4h -1 Mpc Interesting: There are high-mass Group-size halos which are completely isolated (R isolation >12h -1 Mpc), corresponding to -0.7<δρ/ρ< Halo Mass Function in Voids & High-density Regions

2. Morphology of Void & High-Density region Group-size Haloes Shape parameters for Haloes in Voids (R isolation >12 h -1 Mpc) and around high density regions (R cluster < 4h -1 Mpc). The deeper the Void the flatter and the more prolate the Haloes are. Simulation ΛCDM Haloes show Mass-flattening relation (Jing & Suto 2002; Allgood et al 2005, Kasun & Evrard 2005, etc) IMPORTANT: This relation corresponds to an overall anticorrelation between Mass and c/a of R=-0.12 with a random probability of Environmental Dependence of the Correlation between Halo Mass and Shape. Void Halos are FLATTER & more PROLATE and there is smooth transition as a function of decreasing δρ/ρ.

2. Morphology of Void & High-Density region Group-size Haloes Dividing haloes in those with high and low Δ-deviation index The fact that Void haloes with substructure are more elongated and prolate than corresponding haloes in high-density regions, imply that accretion by anisotropic merging is much more directional and coherent in Voids.

3. Dynamical Characteristics of Void & High-Density region Group-size Haloes The observed correlation around massive haloes is not due to σ-Μ virial correlation. The σ-Μ virial correlation is respected in Voids. Ragone-Figueroa et al 2004: Halo velocity dispersion dependence on distance from massive host. The Halo σ is lower in Voids (R isolation >12 h -1 Mpc) with respect to high density regions (R cluster < 4h -1 Mpc) for equal mass haloes (<4 x Mo). The angular momentum is larger in high-density regions, independent of halo mass. The Virial correlation (M-σ) is respected in Voids but NOT near Clusters. This implies that the measured velocity dispersion of observed groups in the vicinity of Clusters is an unreliable measure of there Mass.

3. Dynamical Characteristics of Void & High-Density region Group-size Haloes Dividing haloes in those with high and low Δ-deviation index The fact that the substructured Haloes are those for which the M-σ correlation breaks near Clusters implies that the cause is probably contamination of σ by bulk (infall) motions of sub-haloes

4. Alignments of Void & High-Density region Group-size Haloes Alignments of nearest-neighbour cluster & group size haloes is well known (eg. Splinter et al. 1997, Onuora & Thomas 2000, Faltenbacher et al. 2002, Kasun & Evrard 2005, Hopkins et al. 2005, Basilakos et al. 2006). Void Haloes are more aligned with their nearest neighbour, with respect to haloes in high-density regions. The coherence of the Void Halo alignment extends to large distances. This again supports that accretion by anisotropic merging is much more directional and coherent in Voids.

4. Alignments of Void & High-Density region Group-size Haloes Dividing haloes in those with high and low Δ-deviation index

5. Clustering of Halos as a function of level of substructure 2-p spatial correlation analysis shows that dynamically young Halos are more clustered than virialized ones; ie., they are found in high-density regions. Espino-Briones, Plionis & Ragone-Figueroa, 2007APM clusters (Plionis & Basilakos 2002) Dynamically young (high Δ) Halos are more clustered (found in high-density environments! (as expected from mass function of different Δ άλος depending on environment

Conclusions 1. There are high-mass Group-size halos which are completely isolated (R isolation >12h - 1 Mpc), corresponding to -0.7<δρ/ρ< Environmental Dependence of the correlation between group-size Halo Mass and Shape. (a) Void Halos are more ELONGATED & more PROLATE, and there is smooth transition as a function of decreasing δρ/ρ. (b) Substructured Void haloes are more elongated and more prolate than corresponding haloes in high-density regions, which imply that accretion by anisotropic merging is much more directional and coherent in Voids. 3. Void Haloes are more aligned with their nearest neighbour, with respect to haloes in high-density regions. The coherence of the Void Halo alignment extends to large distances. This again supports that accretion by anisotropic merging is much more directional and coherent in Voids. 4. The Virial correlation (M-σ) is respected for Halos in Voids but NOT near Clusters. (a) This implies that the measured velocity dispersion of observed groups in the vicinity of Clusters is an unreliable measure of their Mass (CAUTION OBSERVERS !), (b) The fact that the substructured Haloes are those for which the M-σ correlation breaks near Clusters implies that the cause is probably contamination of σ by bulk (infall) motions. RELATED TALKS by C. PORCIANI et al. & M. ARAGON-CALVO et al.