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Towards Computational Complexity Theory on Advanced Function Spaces in Analysis

机译:面向分析中高级功能空间的计算复杂性理论

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Pour-El and Richards [PER89], Weihrauch [Weih00], and others have extended Recursive Analysis from real numbers and continuous functions to rather general topological spaces. This has enabled and spurred a series of rigorous investigations on the computability of partial differential equations in appropriate advanced spaces of functions. In order to quantitatively refine such qualitative results with respect to computational efficiency we devise, explore, and compare natural encodings (representations) of compact metric spaces: both as infinite binary sequences (TTE) and more generally as families of Boolean functions via oracle access as introduced by Kawamura and Cook ([KaCo10], Sect. 3.4). Our guide is relativization: Permitting arbitrary oracles on continuous universes reduces computability to topology and computational complexity to metric entropy in the sense of Kolmogorov. This yields a criterion and generic construction of optimal representations in particular of (subsets of) L~p and Sobolev spaces that solutions of partial differential equations naturally live in.
机译:Pour-El和Richards [PER89],Weihrauch [Weih00]等将递归分析从实数和连续函数扩展到相当普遍的拓扑空间。这使得并激发了一系列对偏微分方程在适当的高级函数空间中的可计算性的严格研究。为了从计算效率上定量地改进这些定性结果,我们设计,探索和比较了紧凑度量空间的自然编码(表示形式):既是无限二进制序列(TTE),更一般地是通过oracle访问的布尔函数族,例如由Kawamura和Cook提出([KaCo10],第3.4节)。我们的指南是相对论:在连续宇宙上允许使用任意预言片会降低拓扑结构的可计算性,并降低度量熵的度量复杂度(从Kolmogorov的角度而言)。这产生了最优表示的准则和一般构造,特别是L〜p和Sobolev空间(的子集)的自然表达,其中偏微分方程的解自然存在于其中。

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