Arbitrarily Finely Divisible Matrices

Fuente: arXiv
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Autori principali: Joshi, Priyanka, Šmigoc, Helena
Natura: Preprint
Pubblicazione: 2024
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author Joshi, Priyanka
Šmigoc, Helena
author_facet Joshi, Priyanka
Šmigoc, Helena
contents The class of stochastic matrices that have a stochastic $c$-th root for infinitely many natural numbers $c$ is introduced and studied. Such matrices are called arbitrarily finely divisible, and generalise the class of infinitely divisible matrices. In particular, if $A$ is a transition matrix for a Markov process over some time period, then arbitrarily finely divisibility of $A$ is the necessary and sufficient condition for the existence of transition matrices corresponding to this Markov process over arbitrarily short periods. In this paper, we lay the foundation for research into arbitrarily finely divisible matrices and demonstrate the concepts using specific examples of $2 \times 2$ matrices, $3 \times 3$ circulant matrices, and rank-two matrices.
format Preprint
id arxiv_https___arxiv_org_abs_2409_11125
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Arbitrarily Finely Divisible Matrices
Joshi, Priyanka
Šmigoc, Helena
Probability
Spectral Theory
15A16, 15B51, 60J10
The class of stochastic matrices that have a stochastic $c$-th root for infinitely many natural numbers $c$ is introduced and studied. Such matrices are called arbitrarily finely divisible, and generalise the class of infinitely divisible matrices. In particular, if $A$ is a transition matrix for a Markov process over some time period, then arbitrarily finely divisibility of $A$ is the necessary and sufficient condition for the existence of transition matrices corresponding to this Markov process over arbitrarily short periods. In this paper, we lay the foundation for research into arbitrarily finely divisible matrices and demonstrate the concepts using specific examples of $2 \times 2$ matrices, $3 \times 3$ circulant matrices, and rank-two matrices.
title Arbitrarily Finely Divisible Matrices
topic Probability
Spectral Theory
15A16, 15B51, 60J10
url https://arxiv.org/abs/2409.11125