${\mathrm{ASL}_n}(\mathbb Z)$ invariant random subsets of $\mathbb Z^n$
Miko{\l}aj Fr\k{a}czyk, Simon Machado

TL;DR
This paper classifies affine special linear invariant measures on subsets of integer lattices, revealing a structure built from invariant polynomials and independent sampling, generalizing cut-and-project methods.
Contribution
It introduces a higher-order generalization of the cut-and-project method for classifying invariant measures, connecting polynomial maps, group actions, and point processes.
Findings
Every invariant process is constructed from an invariant polynomial and independent sampling.
When the action is weakly mixing, the measure is a convex combination of Bernoulli shifts.
The classical cut-and-project construction is recovered in the degree-one case.
Abstract
We classify measures on , , the space of subsets of , which are invariant under all affine special linear transformations. In other words, we classify simple point processes on whose law is invariant under affine special linear transformations. We show that every such process is built from a random equivariant polynomial together with independent random sampling, a higher-order generalisation of the cut-and-project method: a random polynomial map is drawn from a distribution invariant under a natural action of , each site is then retained independently with a probability determined by a measurable function of the polynomial's value, and the classical cut-and-project construction is recovered in the degree-one case. As a corollary, when the underlying -action is weakly mixing the…
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