Fenómenos complejos en sistemas extendidos en el espacio

• Main Author: Sánchez de La Lama, Marta
• Other Authors: López Martín, Juan Manuel
• Format: Doctoral Thesis
• Language: English
• Published: Universidad de Cantabria 2009
• Subjects: phase transitions; complex networks; surface growth; non equilibrium systems; transiciones de fase; redes complejas; crecimiento de superficies; física de sistemas fuera de equilibrio; Física Estadística y No Lineal; 53
• Online Access: http://hdl.handle.net/10803/10649; http://nbn-resolving.de/urn:isbn:9788469416778

Uno de los aspectos más fascinantes del mundo que nos rodea es la gran variedad de escalas a las que tienen lugar los diversos fenómenos. En muchos casos esta diversidad pone de manifiesto la estructura fractal de la Naturaleza y podemos hablar entonces de fenómenos complejos, en los que eventos de diferentes magnitudes no pueden analizarse de manera independiente. Dicha complejidad emerge como un fenómeno cooperativo a escalas microscópicas, que produce un complejo comportamiento macroscópico caracterizado por correlaciones de largo alcance e invarianza de escala. Aparecen así conceptos como leyes de escalado, universalidad y renormalización, pilares fundamentales dentro de la Física Estadística.El abanico de fenómenos complejos es muy amplio, y abarca sistemas de muy diversas disciplinas que van desde la Físicamás ortodoxa hasta la Biología, Sociología, Geología e, incluso, Economía. Esta Tesis se centra en fenómenos complejos extendidos en el espacio. En concreto hemos focalizado nuestra labor en tres grandes temas que constituyen importantes focos de interés dentro de la Mecánica Estadística: Crecimiento de Interfases, Sociofísica y Redes Complejas. === The ubiquity of complexity in Nature provides examples of a huge variety of systems to be analyzed by means of Statistical Mechanics and leads to the interconnection among various scientific disciplines. This Thesis focuses on three highlight topics of spatially extended complex systems: Interface Growth,Sociophysics, and Complex Networks. The document has been partitioned in three separated parts according to those topics.The first part deals with far-from-equilibrium growing interfaces. This subject represents one of the main fields in which fractal geometry has been widely applied, and is nowadays of great interest in Condensed Matter Physics. The Chapter 2 provides a brief and basic introduction to interface growth. We introduce some fractal and scaling concepts, as well as the main universality classes in presence of annealed disorder (EW and KPZ) in terms of both growth equations and discrete models. In Chapter 3 we focus on the elastic interface dynamics in disordered media, i.e., in presence of quenched randomness. This Chapter contains original research based on cellular automata simulations. We carry out a novel study of the dynamics by focusing on the discrete activity patterns that the interface sites describe during therelaxation toward the steady state. We analyze the spatio-temporal correlations of such patterns as the temperature is varied. We observe that, for some range of low temperatures, the out-of-equilibrium relaxation can be understood in the context of creep dynamics.The second part of the Thesis focus on Sociophysics. This discipline attends to the social interactions among individuals -most often mapped onto networks to provide them a topological structure- and has recently attracted much interest in the physics community. Social interactions give rise to adaptive systems that exhibit complex features as self-organization and cooperation. Therefore, Statistical Mechanics provides the necessary tools to analyze the behavior of such groups of agentsin a first level of simplification. The topics that Sociophysics deals with are quite a number, and we particularly focus on processes of opinion formation. The Chapter 4 presents a basic classification of the different opinion formation models present in the literature. In Chapter 5 we provide some analytical and numerical own results to describe the effect that the social temperature- understood as a simplified description of the interplay between an agent, its surroundings, and a collective climate parameter- may exert on such opinion formation processes. The thermal effect can be implemented in different ways. In the first part of the Chapter we work on a simple opinion formation model that, according to some procedural rules, reproduces the Sznajd dynamics. We include the thermal effect by means of some probability that the agents adopt the opposite opinion that the one indicated by such rules. In the second part of the Chapterwe consider a system with three different interacting groups of individuals, where the thermal effect is implemented as certain probability of spontaneous changes of the agents opinion. We exploit the van Kampen's expansion approach to analyze the macroscopic behavior of the different supporter group densities as well as the fluctuations around such macroscopic behavior.The third and last part of the document concerns Complex Networks, which have recently prompted the scientific community to investigate the mechanisms that determine their topology and dynamical properties.The rapid development of networks like the Internet and the World-Wide-Web, which represent today the basic substrate for all sort of communications at planetary level, has given rise to a number of interdisciplinary studies with highly technological applications. We first provide an introduction to complex networks in Chapter 6, where we introduce some basic concepts as scale-free graphs, mixing patterns, clustering coefficient, and small-world effect. In Chapter 7 we deal with traffic processes on networks, and specifically we focus on optimization of the routing protocols that define the connecting paths among all the pair of nodes. Such optimization pursues to avoid the traffic jams that emerge for huge quantities of matter or information flowing inthe graph. We propose an optimization algorithm that, in order to avert jamming, minimizes the number of paths that go through the most visited node (maximal betweenness) while keeping the path length as short as possible, i.e., in the proximities of the length distribution of the initial shortest-path protocol.