Projection theorems using effective dimension

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Neil Lutz , D.M. Stull
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引用次数: 0

Abstract

In this paper we use the theory of computing to study fractal dimensions of projections in Euclidean spaces. A fundamental result in fractal geometry is Marstrand's projection theorem, which states that for every analytic set E, for almost every line L, the Hausdorff dimension of the orthogonal projection of E onto L is maximal.

We use Kolmogorov complexity to give two new results on the Hausdorff and packing dimensions of orthogonal projections onto lines. The first shows that the conclusion of Marstrand's theorem holds whenever the Hausdorff and packing dimensions agree on the set E, even if E is not analytic. Our second result gives a lower bound on the packing dimension of projections of arbitrary sets. Finally, we give a new proof of Marstrand's theorem using the theory of computing.

使用有效尺寸的投影定理
在本文中,我们利用计算理论来研究欧几里得空间中投影的分形维度。分形几何的一个基本结果是马斯特兰投影定理,该定理指出,对于每一个解析集合 E,对于几乎每一条直线 L,E 到 L 的正交投影的豪斯多夫维度都是最大的。第一个结果表明,只要集合 E 的 Hausdorff 维度和堆积维度一致,即使 E 不是解析的,马斯特兰定理的结论也成立。第二个结果给出了任意集合投影的堆积维数的下限。最后,我们利用计算理论给出了马斯特兰定理的新证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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