On generalized self-similarities of cut-and-project sets

TL;DR

This paper characterizes linear self-similarities of cut-and-project sets, which are models for quasicrystals, and determines the minimal lattice dimension needed for their construction.

Contribution

It provides a complete characterization of self-similar linear maps for cut-and-project sets and constructs such sets with minimal lattice dimension.

Findings

Characterization of linear self-similarities of cut-and-project sets

Construction method for cut-and-project sets with given self-similarity

Determination of minimal lattice dimension for these constructions

Abstract

Cut-and-project sets $\Sigma\subset\mathbb{R}^n$ represent one of the types of uniformly discrete relatively dense sets. They arise by projection of a section of a higher-dimensional lattice to a suitably oriented subspace. Cut-and-project sets find application in solid state physics as mathematical models of atomic positions in quasicrystals, the description of their symmetries is therefore of high importance. We focus on the question when a linear map $A$ on $\mathbb{R}^n$ is a self-similarity of a cut-and-project set $\Sigma$, i.e.\ satisfies $A\Sigma\subset\Sigma$. We characterize such mappings $A$ and provide a construction of a suitable cut-and-project set $\Sigma$. We determine minimal dimension of a lattice which permits construction of such a set $\Sigma$.