arXiv subjects

Vittorio Loreto

Publications and source records attributed to Vittorio Loreto.

89 records · Page 5Linked to original sources

arXiv2006

Measuring complexity with zippers

Physics concepts have often been borrowed and independently developed by other fields of science. In this perspective a significant example is that of entropy in Information Theory. The aim of this paper is to provide a short and pedagogical introduction to the use of data compression techniques for the estimate of entropy and other relevant quantities in Information Theory and Algorithmic Information Theory. We consider in particular the LZ77 algorithm as case study and discuss how a zipper can be used for information extraction.

physics.ed-ph↗

arXiv2006

Agreement dynamics on small-world networks

In this paper we analyze the effect of a non-trivial topology on the dynamics of the so-called Naming Game, a recently introduced model which addresses the issue of how shared conventions emerge spontaneously in a population of agents. We consider in particular the small-world topology and study the convergence towards the global agreement as a function of the population size $N$ as well as of the parameter $p$ which sets the rate of rewiring leading to the small-world network. As long as $p \gg 1/N$ there exists a crossover time scaling as $N/p^2$ which separates an early one-dimensional-like dynamics from a late stage mean-field-like behavior. At the beginning of the process, the local quasi one-dimensional topology induces a coarsening dynamics which allows for a minimization of the cognitive effort (memory) required to the agents. In the late stages, on the other hand, the mean-field like topology leads to a speed up of the convergence process with respect to the one-dimensional case.

cond-mat.stat-mech↗

arXiv2006

Ring structures and mean first passage time in networks

In this paper we address the problem of the calculation of the mean first passage time (MFPT) on generic graphs. We focus in particular on the mean first passage time on a node 's' for a random walker starting from a generic, unknown, node 'x'. We introduce an approximate scheme of calculation which maps the original process in a Markov process in the space of the so-called rings, described by a transition matrix of size O(ln N / ln X ln N / ln ), where N is the size of the graph and the average degree in the graph. In this way one has a drastic reduction of degrees of freedom with respect to the size N of the transition matrix of the original process, corresponding to an extremely-low computational cost. We first apply the method to the Erdos-Renyi random graph for which the method allows for almost perfect agreement with numerical simulations. Then we extend the approach to the Barabasi-Albert graph, as an example of scale-free graph, for which one obtains excellent results. Finally we test the method with two real world graphs, Internet and a network of the brain, for which we obtain accurate results.

cond-mat.stat-mech↗

arXiv2006

Artificial Sequences and Complexity Measures

In this paper we exploit concepts of information theory to address the fundamental problem of identifying and defining the most suitable tools to extract, in a automatic and agnostic way, information from a generic string of characters. We introduce in particular a class of methods which use in a crucial way data compression techniques in order to define a measure of remoteness and distance between pairs of sequences of characters (e.g. texts) based on their relative information content. We also discuss in detail how specific features of data compression techniques could be used to introduce the notion of dictionary of a given sequence and of Artificial Text and we show how these new tools can be used for information extraction purposes. We point out the versatility and generality of our method that applies to any kind of corpora of character strings independently of the type of coding behind them. We consider as a case study linguistic motivated problems and we present results for automatic language recognition, authorship attribution and self consistent-classification.

cond-mat.stat-mech↗

arXiv2005

Strategies for fast convergence in semiotic dynamics

Semiotic dynamics is a novel field that studies how semiotic conventions spread and stabilize in a population of agents. This is a central issue both for theoretical and technological reasons since large system made up of communicating agents, like web communities or artificial embodied agents teams, are getting widespread. In this paper we discuss a recently introduced simple multi-agent model which is able to account for the emergence of a shared vocabulary in a population of agents. In particular we introduce a new deterministic agents' playing strategy that strongly improves the performance of the game in terms of faster convergence and reduced cognitive effort for the agents.

physics.soc-ph↗

arXiv2005

Comparison of voter and Glauber ordering dynamics on networks

We study numerically the ordering process of two very simple dynamical models for a two-state variable on several topologies with increasing levels of heterogeneity in the degree distribution. We find that the zero-temperature Glauber dynamics for the Ising model may get trapped in sets of partially ordered metastable states even for finite system size, and this becomes more probable as the size increases. Voter dynamics instead always converges to full order on finite networks, even if this does not occur via coherent growth of domains. The time needed for order to be reached diverges with the system size. In both cases the ordering process is rather insensitive to the variation of the degreee distribution from sharply peaked to scale-free.

cond-mat.stat-mech↗

arXiv2004

Influence length and space-time correlation between earthquakes

Short and long range interactions between earthquakes are attracting increasing interest. Scale invariant properties of seismicity in time, space and energy argue for the presence of complex triggering mechanisms where, like a cascade process, each event produces aftershocks. A definitive method to assess any connection between two earthquakes separated in time and distance does not exist. Here we propose a novel method of data analysis that, based on the space-time combined generalization of the correlation integral leads to a self-consistent visualization and analysis of both spatial and temporal correlations. When analyzing global seismicity we discovered a universal relation linking the spatial Influence Length of a given earthquake to the time elapsed from the event itself. Following an event, time correlations (i.e. causality effects) exist in a region that shrinks over time, suggesting a long-range dissipating stress transfer. A different process is acting in the short-range where events are randomly set, evidencing a sub-diffusive growth of the seismogenic zone.

physics.geo-ph↗

arXiv2004

Defining and identifying communities in networks

The investigation of community structures in networks is an important issue in many domains and disciplines. This problem is relevant for social tasks (objective analysis of relationships on the web), biological inquiries (functional studies in metabolic, cellular or protein networks) or technological problems (optimization of large infrastructures). Several types of algorithm exist for revealing the community structure in networks, but a general and quantitative definition of community is still lacking, leading to an intrinsic difficulty in the interpretation of the results of the algorithms without any additional non-topological information. In this paper we face this problem by introducing two quantitative definitions of community and by showing how they are implemented in practice in the existing algorithms. In this way the algorithms for the identification of the community structure become fully self-contained. Furthermore, we propose a new local algorithm to detect communities which outperforms the existing algorithms with respect to the computational cost, keeping the same level of reliability. The new algorithm is tested on artificial and real-world graphs. In particular we show the application of the new algorithm to a network of scientific collaborations, which, for its size, can not be attacked with the usual methods. This new class of local algorithms could open the way to applications to large-scale technological and biological applications.

cond-mat.stat-mech↗

arXiv2003

Temperature probes in binary granular gases

We investigate the validity of Fluctuation-Dissipation (FD) relations for a mixture of two granular gases with different physical properties (restitution coefficients or masses) subject to stochastic driving. It is well known that the partial granular temperatures T_1 and T_2 of the two components are different, i.e. energy equipartition is broken. We observe, with numerical simulations of inelastic hard disks in homogeneous and non-homogeneous situations, that the classical equilibrium Green-Kubo relations are satisfied separately for each component of the gas, the role of the equilibrium temperature being played by the granular temperature of each component. Of particular interest is the limit in which one of the two components consists of only one particle, representing a non-perturbing thermometer. In this case it turns out that such a thermometer is measuring its own temperature and not that of the surrounding granular media, which in general will be different.

cond-mat.stat-mech↗

arXiv2002

Fluctuation-Dissipation Ratio for Compacting Granular Media

In this paper we investigate the possibility of a dynamical definition of an effective temperature for compacting granular media in the framework of the Fluctuation-Dissipation (FD) relations. We have studied two paradigmatic models for the compaction of granular media, which consider particles diffusing on a lattice, with either geometrical (Tetris model) or dynamical (Kob-Andersen model) constraints. Idealized compaction without gravity has been implemented for the Tetris model, and compaction with a preferential direction imposed by gravity has been studied for both models. In the ideal case of an homogeneous compaction, the obtained FD ratio is clearly shown to be in agreement with the prediction of Edwards' measure at various densities. Similar results are obtained with gravity only when the homogeneity of the bulk is imposed. In this case the FD ratio obtained dynamically for horizontal displacements and mobility and from Edwards' measure coincide. Finally, we propose experimental tests for the validity of the Edwards' construction through the comparison of various types of dynamical measurements.

cond-mat.stat-mech↗

arXiv2001

Language Trees and Zipping

In this letter we present a very general method to extract information from a generic string of characters, e.g. a text, a DNA sequence or a time series. Based on data-compression techniques, its key point is the computation of a suitable measure of the remoteness of two bodies of knowledge. We present the implementation of the method to linguistic motivated problems, featuring highly accurate results for language recognition, authorship attribution and language classification.

cond-mat.stat-mech↗

arXiv2001

On the definition of temperature in dense granular media

In this Letter we report the measurement of a pseudo-temperature for compacting granular media on the basis of the Fluctuation-Dissipation relations in the aging dynamics of a model system. From the violation of the Fluctuation-Dissipation Theorem an effective temperature emerges (a dynamical temperature T_{dyn}) whose ratio with the equilibrium temperature T_d^{eq} depends on the particle density. We compare the results for the Fluctuation-Dissipation Ratio (FDR) T_{dyn}/T_d^{eq} at several densities with the outcomes of Edwards' approach at the corresponding densities. It turns out that the FDR and the so-called Edwards' ratio coincide at several densities (very different ages of the system), opening in this way the door to experimental checks as well as theoretical constructions.

cond-mat.stat-mech↗

arXiv2000

Edwards' measures: a thermodynamic construction for dense granular media and glasses

We present numerical support for the hypothesis that macroscopic observables of dense granular media can be evaluated from averages over typical blocked configurations: we construct the corresponding measure for a class of finite-dimensional systems and compare its predictions for various observables with the outcome of the out of equilibrium dynamics at large times. We discuss in detail the connection with the effective temperatures that appear in out of equilibrium glass theories, as well as the relation between our computation and those based on `inherent structure' arguments. A short version of this work has appeared in Phys. Rev. Lett. 85, 5034 (2000) (cond-mat/0006140).

cond-mat.stat-mech↗

arXiv1999

Response properties in a model for granular matter

We investigate the response properties of granular media in the framework of the so-called {\em Random Tetris Model}. We monitor, for different driving procedures, several quantities: the evolution of the density and of the density profiles, the ageing properties through the two-times correlation functions and the two-times mean-square distance between the potential energies, the response function defined in terms of the difference in the potential energies of two replica driven in two slightly different ways. We focus in particular on the role played by the spatial inhomogeneities (structures) spontaneously emerging during the compaction process, the history of the sample and the driving procedure. It turns out that none of these ingredients can be neglected for the correct interpretation of the experimental or numerical data. We discuss the problem of the optimization of the compaction process and we comment on the validity of our results for the description of granular materials in a thermodynamic framework.

cond-mat.stat-mech↗

arXiv1999

Bubbling and Large-Scale Structures in Avalanche Dynamics

Using a simple lattice model for granular media, we present a scenario of self-organization that we term self-organized structuring where the steady state has several unusual features: (1) large scale space and/or time inhomogeneities and (2) the occurrence of a non-trivial peaked distribution of large events which propagate like ``bubbles'' and have a well-defined frequency of occurrence. We discuss the applicability of such a scenario for other models introduced in the framework of self-organized criticality.

cond-mat.stat-mech↗

arXiv1996

Renormalization of Systems with Non-equilibrium Critical Stationary States

We introduce the general formulation of a renormalization method suitable to study the critical properties of non-equilibrium systems with steady-states: the Dynamically Driven Renormalization Group. We renormalize the time evolution operator by computing the rescaled time transition rate between coarse grained states. The obtained renormalization equations are coupled to a stationarity condition which provides the approximate non-equilibrium statistical weights of steady-state configurations to be used in the calculations. In this way we are able to write recursion relations for the parameters evolution under scale change, from which we can extract numerical values for the critical exponents. This general framework allows the systematic analysis of several models showing self-organized criticality in terms of usual concepts of phase transitions and critical phenomena.

cond-mat.stat-mech↗

arXiv1996

Dynamically Driven Renormalization Group

We present a detailed discussion of a novel dynamical renormalization group scheme: the Dynamically Driven Renormalization Group (DDRG). This is a general renormalization method developed for dynamical systems with non-equilibrium critical steady-state. The method is based on a real space renormalization scheme driven by a dynamical steady-state condition which acts as a feedback on the transformation equations. This approach has been applied to open non-linear systems such as self-organized critical phenomena, and it allows the analytical evaluation of scaling dimensions and critical exponents. Equilibrium models at the critical point can also be considered. The explicit application to some models and the corresponding results are discussed.

cond-mat↗