Saved in:
Bibliographic Details
Main Author: Thomas, Alain
Format: Preprint
Published: 2022
Subjects:
Online Access:https://arxiv.org/abs/2205.09044
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916305936842752
author Thomas, Alain
author_facet Thomas, Alain
contents To prove that a measure, linearly representable by means of a finite set of nonnegative matrices $\mathcal M$, has the weak-Gibbs property, one check the uniform convergence (on $\mathcal M^\mathbb N$) of the sequence of vectors $\frac{A_1\cdots A_nc}{\Vert A_1\cdots A_nc\Vert}$ ($c$ positive column-vector). The main theorem gives a sufficient condition for this sequence to converge pointwise. This theorem generalizes the Birkhoff contraction method because it can be used even if the matrices have many zero entries. We also look at the convergence of the sequence of matrices $\frac{A_1\cdots A_n}{\Vert A_1\cdots A_n\Vert}$. The measures defined by Bernoulli convolution are in certain cases linearly representable; we give two example of weak-Gibbs Bernoullt convolutions, by using the Birkhoff contraction coefficient for the first and the theorem for the second. Furthermore we explicit the relationship between the notions of Bernoulli convolution, fundamental curves and lattice two-scale difference equations.
format Preprint
id arxiv_https___arxiv_org_abs_2205_09044
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Normalized image of a vector by an infinite product of nonnegative matrices
Thomas, Alain
Functional Analysis
15B48, 28A12
To prove that a measure, linearly representable by means of a finite set of nonnegative matrices $\mathcal M$, has the weak-Gibbs property, one check the uniform convergence (on $\mathcal M^\mathbb N$) of the sequence of vectors $\frac{A_1\cdots A_nc}{\Vert A_1\cdots A_nc\Vert}$ ($c$ positive column-vector). The main theorem gives a sufficient condition for this sequence to converge pointwise. This theorem generalizes the Birkhoff contraction method because it can be used even if the matrices have many zero entries. We also look at the convergence of the sequence of matrices $\frac{A_1\cdots A_n}{\Vert A_1\cdots A_n\Vert}$. The measures defined by Bernoulli convolution are in certain cases linearly representable; we give two example of weak-Gibbs Bernoullt convolutions, by using the Birkhoff contraction coefficient for the first and the theorem for the second. Furthermore we explicit the relationship between the notions of Bernoulli convolution, fundamental curves and lattice two-scale difference equations.
title Normalized image of a vector by an infinite product of nonnegative matrices
topic Functional Analysis
15B48, 28A12
url https://arxiv.org/abs/2205.09044