Homometric Point Sets and Inverse Problems

TL;DR

This paper explores the inverse diffraction problem, focusing on homometric point sets and their autocorrelation measures, revealing non-uniqueness issues and constructing examples with fixed diffraction but varying entropy.

Contribution

It analyzes homometry in point sets, connects it to Matheron's covariogram problem, and constructs examples of structures with identical diffraction patterns but different entropies.

Findings

Homometric point sets share the same autocorrelation.

Distinct structures can have identical diffraction images.

Examples of structures with fixed diffraction but varying entropy are constructed.

Abstract

The inverse problem of diffraction theory in essence amounts to the reconstruction of the atomic positions of a solid from its diffraction image. From a mathematical perspective, this is a notoriously difficult problem, even in the idealised situation of perfect diffraction from an infinite structure. Here, the problem is analysed via the autocorrelation measure of the underlying point set, where two point sets are called homometric when they share the same autocorrelation. For the class of mathematical quasicrystals within a given cut and project scheme, the homometry problem becomes equivalent to Matheron's covariogram problem, in the sense of determining the window from its covariogram. Although certain uniqueness results are known for convex windows, interesting examples of distinct homometric model sets already emerge in the plane. The uncertainty level increases in the presence of diffuse scattering. Already in one dimension, a mixed spectrum can be compatible with structures of different entropy. We expand on this example by constructing a family of mixed systems with fixed diffraction image but varying entropy. We also outline how this generalises to higher dimension.