Convergence Towards Equilibrium Of Probabilistic Cellular Automata

This book explores Probabilistic Cellular Automata (PCA) from the perspectives of statistical mechanics, probability theory, computational biology and computer science. PCA are extensions of the well-known Cellular Automata models of complex systems, characterized by random updating rules. Thanks to their probabilistic component, PCA offer flexible computing tools for complex numerical constructions, and realistic simulation tools for phenomena driven by interactions among a large number of neighboring structures. PCA are currently being used in various fields, ranging from pure probability to the social sciences and including a wealth of scientific and technological applications. This situation has produced a highly diversified pool of theoreticians, developers and practitioners whose interaction is highly desirable but can be hampered by differences in jargon and focus. This book – just as the workshop on which it is based – is an attempt to overcome these difference and foster interest among newcomers and interaction between practitioners from different fields. It is not intended as a treatise, but rather as a gentle introduction to the role and relevance of PCA technology, illustrated with a number of applications in probability, statistical mechanics, computer science, the natural sciences and dynamical systems. As such, it will be of interest to students and non-specialists looking to enter the field and to explore its challenges and open issues.

Part I, Bertoin, J.: Subordinators: Examples and Applications: Foreword.- Elements on subordinators.- Regenerative property.- Asymptotic behaviour of last passage times.- Rates of growth of local time.- Geometric properties of regenerative sets.- Burgers equation with Brownian initial velocity.- Random covering.- Lévy processes.- Occupation times of a linear Brownian motion.- Part II, Martinelli, F.: Lectures on Glauber Dynamics for Discrete Spin Models: Introduction.- Gibbs Measures of Lattice Spin Models.- The Glauber Dynamics.- One Phase Region.- Boundary Phase Transitions.- Phase Coexistence.- Glauber Dynamics for the Dilute Ising Model.- Part III, Peres, Yu.: Probability on Trees: An Introductory Climb: Preface.- Basic Definitions and a Few Highlights.- Galton-Watson Trees.- General percolation on a connected graph.- The first-Moment method.- Quasi-independent Percolation.- The second Moment Method.- Electrical Networks.- Infinite Networks.- The Method of Random Paths.- Transience of Percolation Clusters.- Subperiodic Trees.- The Random Walks RW (lambda) .- Capacity.-.Intersection-Equivalence.- Reconstruction for the Ising Model on a Tree,- Unpredictable Paths in Z and EIT in Z3.- Tree-Indexed Processes.- Recurrence for Tree-Indexed Markov Chains.- Dynamical Pecsolation.- Stochastic Domination Between Trees.

Fellow Russian mathematicians discuss and extend the works of Dobrushin (1929-95,), who worked in many areas of mathematics, but had deepest influence on mathematical physics and was one of the founders of the rigorous study of statistical physics. The 15 technical papers are flanked by a short biography and recollections by colleagues and students. The topics include the lower spectral branch of the generator of the stochastic dynamics for the classical Heisenberg model, non-symmetric simple random walks along orbits of ergodic automorphisms, the Cramer transform and large deviations on three- dimensional Lobachevsky space, and dynamics of Ising-spin systems at zero temperature. No index is provided. Annotation copyrighted by Book News, Inc., Portland, OR.

No detailed description available for "Probability Theory and Mathematical Statistics".

This book contains the lectures given at the NATO Advanced Study Institute on `Cellular Automata and Cooperative Systems', held at Les Houches, France, from June 22 to July 2, 1992. The book contains contributions by mathematical and theoretical physicists and mathematicians working in the field of local interacting systems, cellular probabilistic automata, statistical physics, and complexity theory, as well as the applications of these fields.

This volume describes the current state of knowledge of random spatial processes, particularly those arising in physics. The emphasis is on survey articles which describe areas of current interest to probabilists and physicists working on the probability theory of phase transition. Special attention is given to topics deserving further research. The principal contributions by leading researchers concern the mathematical theory of random walk, interacting particle systems, percolation, Ising and Potts models, spin glasses, cellular automata, quantum spin systems, and metastability. The level of presentation and review is particularly suitable for postgraduate and postdoctoral workers in mathematics and physics, and for advanced specialists in the probability theory of spatial disorder and phase transition.

The power of modelization in physics and in engineering is not in doubt, while in the biotechnological field many theoretical studies stop at the description level. It is time for theoretical modelization to enter the field of biotechnology, and that needs people with both physical and biological knowledge.This book introduces interested scientists with varied backgrounds to active research in different areas broadly related to what has come to be called ?dynamical modeling in biology?.