



LEADER 
02361nmm a2200277 u 4500 
001 
EB000689325 
003 
EBX01000000000000000542407 
005 
00000000000000.0 
007 
cr 
008 
140122  eng 
020 


a 9783662094440

100 
1 

a Kesten, Harry
e [editor]

245 
0 
0 
a Probability on Discrete Structures
h Elektronische Ressource
c edited by Harry Kesten

250 


a 1st ed. 2004

260 


a Berlin, Heidelberg
b Springer Berlin Heidelberg
c 2004, 2004

300 


a IX, 351 p
b online resource

505 
0 

a The Objective Method: Probabilistic Combinatorial Optimization and Local Weak Convergence  The RandomCluster Model  Models of FirstPassage Percolation  Relaxation Times of Markov Chains in Statistical Mechanics and Combinatorial Structures  Random Walks on Finite Groups

653 


a Probability Theory

653 


a Probabilities

041 
0 
7 
a eng
2 ISO 6392

989 


b SBA
a Springer Book Archives 2004

490 
0 

a Encyclopaedia of Mathematical Sciences

028 
5 
0 
a 10.1007/9783662094440

856 
4 
0 
u https://doi.org/10.1007/9783662094440?nosfx=y
x Verlag
3 Volltext

082 
0 

a 519.2

520 


a Most probability problems involve random variables indexed by space and/or time. These problems almost always have a version in which space and/or time are taken to be discrete. This volume deals with areas in which the discrete version is more natural than the continuous one, perhaps even the only one than can be formulated without complicated constructions and machinery. The 5 papers of this volume discuss problems in which there has been significant progress in the last few years; they are motivated by, or have been developed in parallel with, statistical physics. They include questions about asymptotic shape for stochastic growth models and for random clusters; existence, location and properties of phase transitions; speed of convergence to equilibrium in Markov chains, and in particular for Markov chains based on models with a phase transition; cutoff phenomena for random walks. The articles can be read independently of each other. Their unifying theme is that of models built on discrete spaces or graphs. Such models are often easy to formulate. Correspondingly, the book requires comparatively little previous knowledge of the machinery of probability
