Fast approximation of the affinity dimension for dominated affine iterated function systems

TL;DR

This paper develops a fast method to approximate the affinity dimension of affine iterated function systems, extending previous results to higher dimensions and less restrictive conditions, enabling highly precise calculations.

Contribution

It generalizes earlier work by removing constraints and applying to arbitrary dimensions, allowing for accurate computation of affinity dimensions in complex systems.

Findings

Extended the computation to higher dimensions

Achieved calculations with over 30 decimal places

Relaxed conditions to include dominated affine systems

Abstract

In 1988 K. Falconer introduced a formula which predicts the value of the Hausdorff dimension of the attractor of an affine iterated function system. The value given by this formula -- sometimes referred to as the affinity dimension -- is known to agree with the Hausdorff dimension both generically and in an increasing range of explicit cases. It is however a nontrivial problem to estimate the numerical value of the affinity dimension for specific iterated function systems. In this article we substantially extend an earlier result of M. Pollicott and P. Vytnova on the computation of the affinity dimension. Pollicott and Vytnova's work applies to planar invertible affine contractions with positive linear parts under several additional conditions which among other things constrain the affinity dimension to be between 0 and 1. We extend this result by passing from planar self-affine sets to self-affine sets in arbitrary dimensions, relaxing the positivity hypothesis to a domination condition, and removing all other constraints including that on the range of values of the affinity dimension. We provide some explicit examples of two- and three-dimensional affine iterated function systems for which the affinity dimension can be calculated to more than 30 decimal places.