Poisson representations for tree-indexed Markov chains
Malin Palö Forsström
TL;DR
This work analyzes when tree-indexed Markov chains admit a Poisson representation, extending the class ${\mathcal R}$ from linear graphs to trees. It proves a sharp phase transition on finite trees: for a finite tree with boundary size $k$ and maximum degree $m$, there are thresholds $r_0(k)$ and $r_1(m)$ such that representability depends on both $r$ and the regime of $p$ (near 0 or near 1). It further shows that certain infinite trees, notably octopus trees $T_m$, admit Poisson representations for some parameter ranges, with a $p$-independent threshold $r_2(m)$ and a special case $m=3$ where $r_2(3)=r_1(3)=1/2$, making representability determined by $r$ alone in that case. The paper also strengthens and broadens prior results by providing streamlined proofs, signed-measure extensions, and scaling arguments that connect finite and infinite-tree behavior, clarifying when Ising-like models fail to be Poisson representable and enriching the theory of tree-indexed processes.
Abstract
In~\cite{fgs}, the class of Poisson representable processes was introduced. Several well-known processes were shown not to belong to this class, with examples including both the Curie Weiss model and the Ising model on $ \mathbb{Z}^2 $ for certain choices of parameters. Curiously, it was also shown that all positively associated $ \{ 0,1 \}$-valued Markov chains do belong to this class. In this paper, we interpolate between Markov chains and Ising models by considering tree-indexed Markov chains. In particular, we show that for any finite tree that is not a path, whether or not the corresponding tree-indexed Markov chain is representable always depends on the parameters. Moreover, we give an example of a family of infinite trees such that the corresponding tree-indexed Markov chains are representable for some non-trivial parameters. In addition, we give alternative proofs and arguments and also strengthen several of the results in~\cite{fgs}.
