Improved dimension theory of sofic self-affine fractals
Nima Alibabaei

TL;DR
This paper provides a combinatorial formula for the Hausdorff dimension of self-affine fractals, extending previous work on sofic sets and establishing conditions for dimension equivalence in higher-dimensional Euclidean spaces.
Contribution
It introduces a new combinatorial expression for the Hausdorff dimension of self-affine fractals, including extensions to higher dimensions and conditions for Minkowski and Hausdorff dimension equality.
Findings
Derived a combinatorial formula for Hausdorff dimension of self-affine fractals.
Extended dimension results to certain sofic sets in higher-dimensional spaces.
Established conditions under which Minkowski and Hausdorff dimensions coincide for planar sofic sets.
Abstract
Follow-up comment by the author: Theorem 2.2 in this paper is a special case of Theorems 1.1 and 4.1 in the article "Weighted thermodynamic formalism on subshifts and applications", Asian J. Math. 16 (2012), by J. Barral and D. J. Feng. In addition, Zhou Feng studied the conditions under which general self-affine fractals, including sofic sets, have the same Hausdorff dimension and box dimension in the paper "On the coincidence of the Hausdorff and box dimensions for some affine-invariant sets", arXiv:2405.03213. I would like to thank Dr. Zhou Feng for pointing out these works. The calculation of the exact Hausdorff dimension of sofic sets presented in this article is refined in my subsequent work "Exact Hausdorff dimension of some sofic self-affine fractals", arXiv:2412.05805. Original abstract: We establish a combinatorial expression for the Hausdorff dimension of a given…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical Dynamics and Fractals · Topological and Geometric Data Analysis · advanced mathematical theories
