The Topological Non-connectivity Threshold and magnetic phase transitions in classical anisotropic long-range interacting spin system

We analyze from the dynamical point of view the classical characteristics of the Topological Non-connectivity Threshold (TNT), recently introduced in F.Borgonovi, G.L.Celardo, M.Maianti, E.Pedersoli, J.Stat.Phys.,116,516(2004). This shows interesting connections among Topology, Dynamics, and Thermo-Statistics of ferro/paramagnetic phase transition in classical spin systems, due to the combined effect of anisotropy and long-range interactions.Comment: 6 revtex pages, 4 .eps figures Contribution presented at the 3rd Conference NEXT-Sigma-Phi News, Expectations, and Trends in Statistical Physics, August 13-18 2005, Kolymbari, Crete. For related results see also cond-mat/0402270 cond-mat/0410119 cond-mat/0505209 cond-mat/0506233 cond-mat/051007

A global descriptor of spatial pattern interaction in the galaxy distribution

We present the function J as a morphological descriptor for point patterns formed by the distribution of galaxies in the Universe. This function was recently introduced in the field of spatial statistics, and is based on the nearest neighbor distribution and the void probability function. The J descriptor allows to distinguish clustered (i.e. correlated) from ``regular'' (i.e. anti-correlated) point distributions. We outline the theoretical foundations of the method, perform tests with a Matern cluster process as an idealised model of galaxy clustering, and apply the descriptor to galaxies and loose groups in the Perseus-Pisces Survey. A comparison with mock-samples extracted from a mixed dark matter simulation shows that the J descriptor can be profitably used to constrain (in this case reject) viable models of cosmic structure formation.Comment: Significantly enhanced version, 14 pages, LaTeX using epsf, aaspp4, 7 eps-figures, accepted for publication in the Astrophysical Journa

Clustering of loose groups and galaxies from the Perseus--Pisces Survey

We investigate the clustering properties of loose groups in the Perseus--Pisces redshift Survey (PPS). Previous analyses based on CfA and SSRS surveys led to apparently contradictory results. We investigate the source of such discrepancies, finding satisfactory explanations for them. Furthermore, we find a definite signal of group clustering, whose amplitude $A_G$ exceeds the amplitude $A_g$ of galaxy clustering ($A_G=14.5^{+3.8}_{-3.0}$, $A_g=7.42^{+0.20}_{-0.19}$ for the most significant case; distances are measured in \hMpc). Groups are identified with the adaptive Friends--Of--Friends (FOF) algorithms HG (Huchra \& Geller 1982) and NW (Nolthenius \& White 1987), systematically varying all search parameters. Correlation strenght is especially sensitive to the sky--link $D_L$ (increasing for stricter normalization $D_0$), and to the (depth \mlim of the) galaxy data. It is only moderately dependent on the galaxy luminosity function $\phi(L)$, while it is almost insensitive to the redshift--link $V_L$ (both to the normalization $V_0$ and to the scaling recipes HG or NW).Comment: 28 pages (LaTeX aasms4 style) + 5 Postscript figures ; ApJ submitted on May 4th, 1996; group catalogs available upon request ([email protected]

A global descriptor of spatial pattern interaction in the galaxy distribution

We present the function J as a morphological descriptor for point patterns formed by the distribution of galaxies in the Universe. This function was recently introduced in the field of spatial statistics, and is based on the nearest neighbor distribution and the void probability function. The J descriptor allows to distinguish clustered (i.e. correlated) from “regular ” (i.e. anti–correlated) point distributions. We outline the theoretical foundations of the method, perform tests with a Matérn cluster process as an idealised model of galaxy clustering, and apply the descriptor to galaxies and loose groups in the Perseus–Pisces Survey. A comparison with mock–samples extracted from a mixed dark matter simulation shows that the J descriptor can be profitably used to constrain (in this case reject) viable models of cosmic structure formation