路径不可压缩树的生长和不可还原性

IF 0.8 4区计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS

Information and Computation Pub Date : 2024-01-09 DOI:10.1016/j.ic.2024.105136

George Barmpalias, Xiaoyan Zhang

引用次数: 0

摘要

我们研究了路径不可压缩树（即有限随机性缺陷树）的随机性保留变换。我们描述了它们的分支密度，并证明：(a) 稀疏的完美路径不可压缩树可以有效地密集化，这几乎是肯定的；(b) 存在一棵具有无限多条路径的路径不可压缩树，它不能计算任何具有可计算甲骨文使用的完美路径不可压缩树。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Growth and irreducibility in path-incompressible trees

We study randomness-preserving transformations of path-incompressible trees, namely trees of finite randomness deficiency. We characterize their branching density, and show: (a) sparse perfect path-incompressible trees can be effectively densified, almost surely; (b) there exists a path-incompressible tree with infinitely many paths which does not compute any perfect path-incompressible tree with computable oracle-use.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

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