In the last years several problems been studied at the interface between statistical physics and computer science. The reason being that often these problems can be reinterpreted in the language of physics of disordered systems, where a big number of variables interacts through local fields dependent on the state of the surrounding neighborhood. Among the numerous applications of combinatorial optimisation the optimal routing on communication networks is the subject of the first part of the thesis. We will exploit the cavity method to formulate efficient algorithms of type message-passing and thus solve several variants of the problem through its numerical implementation. At a second stage, we will describe a model to approximate the dynami...
Un grand nombre des problèmes d'optimisation, ainsi que des problèmes inverses, combinatoires ou hor...
This PhD document is devoted to the analyses of large stochastic networks used to study mathematical...
This PhD document is devoted to the analyses of large stochastic networks used to study mathematical...
A large number of optimization, inverse, combinatorial and out-of-equilibrium problems, arising in t...
A large number of optimization, inverse, combinatorial and out-of-equilibrium problems, arising in t...
Dans les dernières années, plusieurs problèmes ont été étudiés à l'interface entre la physique stati...
The scope of these lecture notes is to provide an introduction to modern statistical physics mean-fi...
The scope of these lecture notes is to provide an introduction to modern statistical physics mean-fi...
This thesis deals with some aspects of the physics of disordered systems. It consists of four papers...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
This thesis deals with some aspects of the physics of disordered systems. It consists of four papers...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Un grand nombre des problèmes d'optimisation, ainsi que des problèmes inverses, combinatoires ou hor...
This PhD document is devoted to the analyses of large stochastic networks used to study mathematical...
This PhD document is devoted to the analyses of large stochastic networks used to study mathematical...
A large number of optimization, inverse, combinatorial and out-of-equilibrium problems, arising in t...
A large number of optimization, inverse, combinatorial and out-of-equilibrium problems, arising in t...
Dans les dernières années, plusieurs problèmes ont été étudiés à l'interface entre la physique stati...
The scope of these lecture notes is to provide an introduction to modern statistical physics mean-fi...
The scope of these lecture notes is to provide an introduction to modern statistical physics mean-fi...
This thesis deals with some aspects of the physics of disordered systems. It consists of four papers...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
This thesis deals with some aspects of the physics of disordered systems. It consists of four papers...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Advances in statistical physics relating to our understanding of large-scale complex systems have re...
Un grand nombre des problèmes d'optimisation, ainsi que des problèmes inverses, combinatoires ou hor...
This PhD document is devoted to the analyses of large stochastic networks used to study mathematical...
This PhD document is devoted to the analyses of large stochastic networks used to study mathematical...