The point-to-set principle characterizes the Hausdorff dimension of a subset $E\subseteq\R^n$ by the effective dimension of its individual points. This characterization has been used to prove several results in classical, i.e., without any computability requirements, analysis. Recent work has shown that algorithmic techniques can be fruitfully applied to Marstrand's projection theorem, a fundamental result in fractal geometry. In this paper, we introduce an extension of point-to-set principle - the notion of optimal oracles for subsets $E\subseteq\R^n$. One of the primary motivations of this definition is that, if $E$ has optimal oracles, then the conclusion of Marstrand's projection theorem holds for $E$. We show that every analytic set has optimal oracles. We also prove that if the Hausdorff and packing dimensions of $E$ agree, then $E$ has optimal oracles. Thus, the existence of optimal oracles subsume the currently known sufficient conditions for Marstrand's theorem to hold. Under certain assumptions, every set has optimal oracles. However, assuming the axiom of choice and the continuum hypothesis, we construct sets which do not have optimal oracles. This construction naturally leads to a new, algorithmic, proof of Davies theorem on projections.
翻译:点定原则将奥斯多夫子集的维度定性为 $E\ subseteq\ R ⁇ n$, 以其各点的有效维度为核心。 这种定性已被用于在古典中证明若干结果, 也就是说, 没有任何可比较性要求, 分析。 最近的工作显示, 算法技术可以有成效地应用到马斯特兰德的投影定理上, 这是分形几何制的一个根本结果 。 在本文中, 我们引入了点到定原则的延伸, 即子集 $E\ subseteqeq\ R ⁇ n$ 的概念。 这个定义的主要动机之一是, 如果美元具有最优或最优的结果, 那么Marstrandds投影的定理将维持在$。 我们显示, 每套解算法都具有最优或最优的定的定局 。 因此, 最优的或最优的定局将保持一个最优的定局 。