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Bounding the dimension of exceptional sets for orthogonal projections

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arxiv 2411.04959 v3 pith:JILJ5KW6 submitted 2024-11-07 math.CA

classification math.CA
keywords dimensionexceptionalequationestimatesknownmathbborthogonalanalytic
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abstract

It is well known that if $A \subseteq \mathbb{R}^n$ is an analytic set of Hausdorff dimension $a$, then $\dim_H(\pi_VA)=\min\{a,k\}$ for a.e.\ $V\in G(n,k)$, where $G(n,k)$ denotes the set of all $k$-dimensional subspaces of $\mathbb{R}^n$ and $\pi_V$ is the orthogonal projection of $A$ onto $V$. In this paper we study how large the exceptional set \begin{equation*} \{V\in G(n,k) \mid \dim_H(\pi_V A) < s\} \end{equation*} can be for a given $s\le\min\{a,k\}.$ We improve previously known estimates on the dimension of the exceptional set, and we show that our estimates are sharp for $k=1$ and for $k=n-1$. Hence we completely resolve this question for $n=3$.

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  1. Algorithmic Information Bounds for Distances and Orthogonal Projections

    cs.CC 2025-09 conditional novelty 7.0 of 10

    A new proof technique shows distances and orthogonal projections retain at least half of a planar point's Kolmogorov complexity, improving pinned distance dimension bounds to 3/4 s and generalizing Bourgain's theorem.

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