Wolfgang Woess

Bio: Wolfgang Woess is an academic researcher from Graz University of Technology. The author has contributed to research in topics: Random walk & Cayley graph. The author has an hindex of 29, co-authored 133 publications receiving 3775 citations. Previous affiliations of Wolfgang Woess include University of Salzburg & University of Leoben.

Random Walks on Infinite Graphs and Groups

Abstract: Part I. The Type Problem: 1. Basic facts 2. Recurrence and transience of infinite networks 3. Applications to random walks 4. Isoperimetric inequalities 5. Transient subtrees, and the classification of the recurrent quasi transitive graphs 6. More on recurrence Part II. The Spectral Radius: 7. Superharmonic functions and r-recurrence 8. The spectral radius 9. Computing the Green function 10. Spectral radius and strong isoperimetric inequality 11. A lower bound for simple random walk 12. Spectral radius and amenability Part III. The Asymptotic Behaviour of Transition Probabilities: 13. The local central limit theorem on the grid 14. Growth, isoperimetric inequalities, and the asymptotic type of random walk 15. The asymptotic type of random walk on amenable groups 16. Simple random walk on the Sierpinski graphs 17. Local limit theorems on free products 18. Intermezzo 19. Free groups and homogenous trees Part IV. An Introduction to Topological Boundary Theory: 20. Probabilistic approach to the Dirichlet problem, and a class of compactifications 21. Ends of graphs and the Dirichlet problem 22. Hyperbolic groups and graphs 23. The Dirichlet problem for circle packing graphs 24. The construction of the Martin boundary 25. Generalized lattices, Abelian and nilpotent groups, and graphs with polynomial growth 27. The Martin boundary of hyperbolic graphs 28. Cartesian products.

A Survey on Spectra of infinite Graphs

Abstract: Introduction. Operateurs lineaires associes a un graphe. Resultats fondamentaux. Rayon spectral, fonctions generatrices de marche et mesures spectrales. Croissance et nombre isoperimetrique d'un graphe. Fonctions propres positives. Graphes de groupes, arbres et graphes reguliers en distance. Quelques remarques sur les applications en chimie et en physique

Random Walks on Infinite Graphs and Groups — a Survey on Selected topics

Abstract: Contents 1. Introduction 2 2. Basic definitions and preliminaries 3 A. Adaptedness to the graph structure 4 B. Reversible Markov chains 4 C. Random walks on groups 5 D. Group-invariant random walks on graphs 6 E. Harmonic and superharmonic functions 6 3. Spectral radius, amenability and law of large numbers 6 A. Spectral radius, isoperimetric inequalities and growth 6 B. Law of large numbers 9 4. The type problem 11 A. The type problem for random walks on groups 11 B. The type problem for reversible Markov chains 13 C. Nearest neighbour random walks on trees and recurrence criteria 17 D. /^-recurrence 18 5. Periodicity, ratio limit theorems 19 A. The period of a random walk 19 B. Ratio limit theorems 20 6. The asymptotic behaviour of transition probabilities 22 A. Reversible Markov chains and Dirichlet inequalities 23 B. Local limit theorems and growth of groups 24 C. Random walks on free groups and trees 25 D. Random walks on free products 27 E. Cartesian products 30 7. Behaviour at infinity and harmonic functions 30 A. Integer lattices, Abelian and nilpotent groups 32 B. Entropy and the Poisson boundary 34 C. Trees 36 D. Hyperbolic graphs 38 E. Planar graphs 39 F. Ends of graphs and groups 40 G. Cartesian products 43 H. The Martin boundary for recurrent random walks 43 8. Electric networks and harmonic functions with finite Dirichlet sum 45 A. Existence criteria 46 B. Uniqueness of current and harmonic functions 47 9. Random walks and the classification of Riemannian manifolds 50 Index of abbreviations 52 References 53

Isotropic Markov semigroups on ultra-metric spaces

Abstract: Let (X,d) be a locally compact separable ultra-metric space. Given a reference measure \mu\ on X and a step length distribution on the non-negative reals, we construct a symmetric Markov semigroup P^t acting in L^2(X,\mu). We study the corresponding Markov process. We obtain upper and lower bounds of its transition density and its Green function, give a transience criterion, estimate its moments and describe the Markov generator and its spectrum, which is pure point. In the particular case when X is the field of p-adic numbers, our construction recovers fractional derivative and the Taibleson Laplacian (spectral multiplier), and we can also apply our theory to the study of the Vladimirov Laplacian which is closely related to the concept of p-adic Quantum Mechanics. Even in this well established setting, several of our results are new. We also elaborate the relation between our processes and Kigami's jump processes on the boundary of a tree which are induced by a random walk. In conclusion, we provide examples illustrating the interplay between the fractional derivatives and random walks.

Convergence of Probability Measures

Abstract: Convergence of Probability Measures. By P. Billingsley. Chichester, Sussex, Wiley, 1968. xii, 253 p. 9 1/4“. 117s.

Analytic Combinatorics

Abstract: Analytic Combinatorics is a self-contained treatment of the mathematics underlying the analysis of discrete structures, which has emerged over the past several decades as an essential tool in the understanding of properties of computer programs and scientific models with applications in physics, biology and chemistry. Thorough treatment of a large number of classical applications is an essential aspect of the presentation. Written by the leaders in the field of analytic combinatorics, this text is certain to become the definitive reference on the topic. The text is complemented with exercises, examples, appendices and notes to aid understanding therefore, it can be used as the basis for an advanced undergraduate or a graduate course on the subject, or for self-study.

Convergence of probability measures

Abstract: The author's preface gives an outline: "This book is about weakconvergence methods in metric spaces, with applications sufficient to show their power and utility. The Introduction motivates the definitions and indicates how the theory will yield solutions to problems arising outside it. Chapter 1 sets out the basic general theorems, which are then specialized in Chapter 2 to the space C[0, l ] of continuous functions on the unit interval and in Chapter 3 to the space D [0, 1 ] of functions with discontinuities of the first kind. The results of the first three chapters are used in Chapter 4 to derive a variety of limit theorems for dependent sequences of random variables. " The book develops and expands on Donsker's 1951 and 1952 papers on the invariance principle and empirical distributions. The basic random variables remain real-valued although, of course, measures on C[0, l ] and D[0, l ] are vitally used. Within this framework, there are various possibilities for a different and apparently better treatment of the material. More of the general theory of weak convergence of probabilities on separable metric spaces would be useful. Metrizability of the convergence is not brought up until late in the Appendix. The close relation of the Prokhorov metric and a metric for convergence in probability is (hence) not mentioned (see V. Strassen, Ann. Math. Statist. 36 (1965), 423-439; the reviewer, ibid. 39 (1968), 1563-1572). This relation would illuminate and organize such results as Theorems 4.1, 4.2 and 4.4 which give isolated, ad hoc connections between weak convergence of measures and nearness in probability. In the middle of p. 16, it should be noted that C*(S) consists of signed measures which need only be finitely additive if 5 is not compact. On p. 239, where the author twice speaks of separable subsets having nonmeasurable cardinal, he means "discrete" rather than "separable." Theorem 1.4 is Ulam's theorem that a Borel probability on a complete separable metric space is tight. Theorem 1 of Appendix 3 weakens completeness to topological completeness. After mentioning that probabilities on the rationals are tight, the author says it is an

Markov Chains and Mixing Times

Abstract: This book is an introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space. The authors develop the key tools for estimating convergence times, including coupling, strong stationary times, and spectral methods. Whenever possible, probabilistic methods are emphasized. The book includes many examples and provides brief introductions to some central models of statistical mechanics. Also provided are accounts of random walks on networks, including hitting and cover times, and analyses of several methods of shuffling cards. As a prerequisite, the authors assume a modest understanding of probability theory and linear algebra at an undergraduate level. ""Markov Chains and Mixing Times"" is meant to bring the excitement of this active area of research to a wide audience.

THE LAPLACIAN SPECTRUM OF GRAPHS y

Abstract: The paper is essentially a survey of known results about the spectrum of the Laplacian matrix of graphs with special emphasis on the second smallest Lapla- cian eigenvalue 2 and its relation to numerous graph invariants, including connectivity, expanding properties, isoperimetric number, maximum cut, independence number, genus, diameter, mean distance, and bandwidth-type parameters of a graph. Some new results and generalizations are added.