Almost-additive thermodynamic formalism for countable Markov shifts
Creators
- 1. Facultad de Matemáticas, Pontificia Universidad Católica de Chile (PUC), Avenida Vicuña Mackenna 4860, Santiago (Chile)
- 2. Departamento de Ciencias Básicas, Campus Fernando May Avda. Andrés Bello S/N, Universidad del Bío-Bío, Chillán (Chile)
Description
This paper is devoted to extend the thermodynamic formalism theory to almost-additive sequences of continuous functions defined over topologically mixing, non-compact, countable Markov shifts. Difficulties are two fold, on the one hand we have to deal with the lack of compactness of the phase space and on the other with the non-additivity of the sequence potentials. In this context, based on the work of Sarig and also on the work of Barreira, we introduce a definition of pressure. We prove that it satisfies the variational principle and hence it is good definition. Under certain combinatorial assumptions on the shift space (that of being BIP) we prove the existence and uniqueness of Gibbs measures. Applications are given, among others, to the study of maximal Lypaunov exponents of product of matrices and to obtain a formula for the Hausdorff dimension of certain geometrical constructions
Availability note (English)
Available from http://dx.doi.org/10.1088/0951-7715/25/1/165Additional details
Identifiers
- DOI
- 10.1088/0951-7715/25/1/165;
- PII
- S0951-7715(12)02330-4;
Publishing Information
- Journal Title
- Nonlinearity (Print)
- Journal Volume
- 25
- Journal Issue
- 1
- Journal Page Range
- p. 165-191
- ISSN
- 0951-7715
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 45037790
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- DIMENSIONS; LYAPUNOV METHOD; MARKOV PROCESS; MATHEMATICAL SOLUTIONS; MATRICES; PHASE SPACE; POTENTIALS; THERMODYNAMICS; TOPOLOGY; VARIATIONAL METHODS
- Descriptors DEC
- CALCULATION METHODS; MATHEMATICAL SPACE; MATHEMATICS; SPACE; STOCHASTIC PROCESSES