Local Rigidity in Sandpile Models

We address the problem of the role of the concept of local rigidity in the family of sandpile systems. We define rigidity as the ratio between the critical energy and the amplitude of the external perturbation and we show, in the framework of the Dynamically Driven Renormalization Group (DDRG), that any finite value of the rigidity in a generalized sandpile model renormalizes to an infinite value at the fixed point, i.e. on a large scale. The fixed point value of the rigidity allows then for a non ambiguous distinction between sandpile-like systems and diffusive systems. Numerical simulations support our analytical results.Comment: to be published in Phys. Rev.

Multi-layer model for the web graph

This paper studies stochastic graph models of the WebGraph. We present a new model that describes the WebGraph as an ensemble of different regions generated by independent stochastic processes (in the spirit of a recent paper by Dill et al. [VLDB 2001]). Models such as the Copying Model [17] and Evolving Networks Model [3] are simulated and compared on several relevant measures such as degree and clique distribution

Quantitative description and modeling of real networks

In this letter we present data analysis and modeling of two particular cases of study in the field of growing networks. We analyze WWW data set and authorship collaboration networks in order to check the presence of correlation in the data. The results are reproduced with a pretty good agreement through a suitable modification of the standard AB model of network growth. In particular, intrinsic relevance of sites plays a role in determining the future degree of the vertex.Comment: 4 pages, 3 figure

The extremal limit of D-dimensional black holes

The extreme limit of a class of D-dimensional black holes is revisited. In the static limit, it is shown that well defined extremal limiting procedure exists and it leads to new solutions of the type AdS2 times constant curvature symmetric spaces.Comment: 8 pages, proceedings of Londrina Conference, April 2000, Londrina, Brazi

A perturbative approach to the Bak-Sneppen Model

We study the Bak-Sneppen model in the probabilistic framework of the Run Time Statistics (RTS). This model has attracted a large interest for its simplicity being a prototype for the whole class of models showing Self-Organized Criticality. The dynamics is characterized by a self-organization of almost all the species fitnesses above a non-trivial threshold value, and by a lack of spatial and temporal characteristic scales. This results in {\em avalanches} of activity power law distributed. In this letter we use the RTS approach to compute the value of $x_c$, the value of the avalanche exponent $\tau$ and the asymptotic distribution of minimal fitnesses.Comment: 4 pages, 3 figures, to be published on Physical Review Letter

Supersymmetric gyratons in five dimensions

We obtain the gravitational and electromagnetic field of a spinning radiation beam-pulse (a gyraton) in minimal five-dimensional gauged supergravity and show under which conditions the solution preserves part of the supersymmetry. The configurations represent generalizations of Lobatchevski waves on AdS with nonzero angular momentum, and possess a Siklos-Virasoro reparametrization invariance. We compute the holographic stress-energy tensor of the solutions and show that it transforms without anomaly under these reparametrizations. Furthermore, we present supersymmetric gyratons both in gauged and ungauged five-dimensional supergravity coupled to an arbitrary number of vector supermultiplets, which include gyratons on domain walls.Comment: 25 pages, no figures, uses JHEP3.cls. Final version to appear in CQ

Models and Algorithms for Graph Watermarking

We introduce models and algorithmic foundations for graph watermarking. Our frameworks include security definitions and proofs, as well as characterizations when graph watermarking is algorithmically feasible, in spite of the fact that the general problem is NP-complete by simple reductions from the subgraph isomorphism or graph edit distance problems. In the digital watermarking of many types of files, an implicit step in the recovery of a watermark is the mapping of individual pieces of data, such as image pixels or movie frames, from one object to another. In graphs, this step corresponds to approximately matching vertices of one graph to another based on graph invariants such as vertex degree. Our approach is based on characterizing the feasibility of graph watermarking in terms of keygen, marking, and identification functions defined over graph families with known distributions. We demonstrate the strength of this approach with exemplary watermarking schemes for two random graph models, the classic Erd\H{o}s-R\'{e}nyi model and a random power-law graph model, both of which are used to model real-world networks

Dynamics of Fractures in Quenched Disordered Media

We introduce a model for fractures in quenched disordered media. This model has a deterministic extremal dynamics, driven by the energy function of a network of springs (Born Hamiltonian). The breakdown is the result of the cooperation between the external field and the quenched disorder. This model can be considered as describing the low temperature limit for crack propagation in solids. To describe the memory effects in this dynamics, and then to study the resistance properties of the system we realized some numerical simulations of the model. The model exhibits interesting geometric and dynamical properties, with a strong reduction of the fractal dimension of the clusters and of their backbone, with respect to the case in which thermal fluctuations dominate. This result can be explained by a recently introduced theoretical tool as a screening enhancement due to memory effects induced by the quenched disorder.Comment: 7 pages, 9 Postscript figures, uses revtex psfig.sty, to be published on Phys. Rev.

Bayesian Networks Analysis of Malocclusion Data

In this paper we use Bayesian networks to determine and visualise the interactions among various Class III malocclusion maxillofacial features during growth and treatment. We start from a sample of 143 patients characterised through a series of a maximum of 21 different craniofacial features. We estimate a network model from these data and we test its consistency by verifying some commonly accepted hypotheses on the evolution of these disharmonies by means of Bayesian statistics. We show that untreated subjects develop different Class III craniofacial growth patterns as compared to patients submitted to orthodontic treatment with rapid maxillary expansion and facemask therapy. Among treated patients the CoA segment (the maxillary length) and the ANB angle (the antero-posterior relation of the maxilla to the mandible) seem to be the skeletal subspaces that receive the main effect of the treatment