Biomedical subjects

Vittorio Loreto

Publications and source records attributed to Vittorio Loreto.

8 recordsLinked to original sources

PubMed2006

Nonequilibrium dynamics of language games on complex networks.

The naming game is a model of nonequilibrium dynamics for the self-organized emergence of a linguistic convention or a communication system in a population of agents with pairwise local interactions. We present an extensive study of its dynamics on complex networks, that can be considered as the most natural topological embedding for agents involved in language games and opinion dynamics. Except for some community structured networks on which metastable phases can be observed, agents playing the naming game always manage to reach a global consensus. This convergence is obtained after a time generically scaling with the population's size N as t(conv) approximately N(1.4+/-0.1), i.e., much faster than for agents embedded on regular lattices. Moreover, the memory capacity required by the system scales only linearly with its size. Particular attention is given to heterogeneous networks, in which the dynamical activity pattern of a node depends on its degree. High-degree nodes have a fundamental role, but require larger memory capacity. They govern the dynamics acting as spreaders of (linguistic) conventions. The effects of other properties, such as the average degree and the clustering, are also discussed.

Journal Article↗

PubMed2006

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 on generic graphs. We focus in particular on the mean first passage time on a node 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 (k) x ln N/ln (k)), where is the size of the graph and (k) the average degree in the graph. In this way one has a drastic reduction of degrees of freedom with respect to the size of the transition matrix of the original process, corresponding to an extremely low computational cost. We first apply the method to the Erdös-Renyi random graphs for which the method allows for almost perfect agreement with numerical simulations. Then we extend the approach to the Barabási-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.

Cell Physiological Phenomena↗

PubMed2006

Topology-induced coarsening in language games.

We investigate how very large populations are able to reach a global consensus, out of local "microscopic" interaction rules, in the framework of a recently introduced class of models of semiotic dynamics, the so-called naming game. We compare in particular the convergence mechanism for interacting agents embedded in a low-dimensional lattice with respect to the mean-field case. We highlight that in low dimensions consensus is reached through a coarsening process that requires less cognitive effort of the agents, with respect to the mean-field case, but takes longer to complete. In one dimension, the dynamics of the boundaries is mapped onto a truncated Markov process from which we analytically computed the diffusion coefficient. More generally we show that the convergence process requires a memory per agent scaling as N and lasts a time N1+2/d in dimension d < or = 4 (the upper critical dimension), while in mean field both memory and time scale as N3/2 , for a population of agents. We present analytical and numerical evidence supporting this picture.

Journal Article↗

PubMed2005

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 degree distribution from sharply peaked to scale free.

Journal Article↗

PubMed2004

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 and protein networks), or technological problems (optimization of large infrastructures). Several types of algorithms exist for revealing the community structure in networks, but a general and quantitative definition of community is not implemented in the algorithms, leading to an intrinsic difficulty in the interpretation of the results without any additional nontopological information. In this article we deal with this problem by showing how quantitative definitions of community 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 local algorithm to detect communities which outperforms the existing algorithms with respect to computational cost, keeping the same level of reliability. The algorithm is tested on artificial and real-world graphs. In particular, we show how the algorithm applies to a network of scientific collaborations, which, for its size, cannot be attacked with the usual methods. This type of local algorithm could open the way to applications to large-scale technological and biological systems.

Algorithms↗

PubMed2002

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.

Journal Article↗

PubMed2002

Definition of temperature in dense granular media.

In this paper we report the measurement of a pseudotemperature 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 emerges an effective temperature (a dynamical temperature T(dyn)) whose value depends on the particle density. We compare the results for T(dyn) at several densities with the values of Edwards' compactivity at the corresponding densities [S. F. Edwards, in Granular Matter: An Interdisciplinary Approach, edited by A. Mehta (Springer-Verlag, New York, 1994) and references therein]. It turns out that the dynamical temperature and Edwards' compactivity coincide on a large range of densities, opening in this way the door to experimental checks as well as theoretical constructions.

Algorithms↗

PubMed2002

Language trees and zipping.

In this Letter we present a very general method for extracting 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.

Algorithms↗