RANDOMNESS AND DIFFERENTIABILITY

被引:22
作者
Brattka, Vasco [1 ,2 ]
Miller, Joseph S. [3 ]
Nies, Andre [4 ]
机构
[1] Univ Bundeswehr Munchen, Fac Comp Sci, D-85577 Neubiberg, Germany
[2] Univ Cape Town, Dept Math & Appl Math, ZA-7701 Rondebosch, South Africa
[3] Univ Wisconsin, Dept Math, Madison, WI 53706 USA
[4] Univ Auckland, Dept Comp Sci, Auckland 1, New Zealand
基金
新加坡国家研究基金会; 美国国家科学基金会;
关键词
Computable analysis; algorithmic randomness; differentiability; monotonic function; bounded variation;
D O I
10.1090/tran/6484
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We characterize some major algorithmic randomness notions via differentiability of effective functions. (1) As the main result we show that a real number z. [0, 1] is computably random if and only if each nondecreasing computable function [0, 1]. R is differentiable at z. (2) We prove that a real number z. [0, 1] is weakly 2- random if and only if each almost everywhere differentiable computable function [0, 1]. R is differentiable at z. (3) Recasting in classical language results dating from 1975 of the constructivist Demuth, we show that a real z is Martin-Lof random if and only if every computable function of bounded variation is differentiable at z, and similarly for absolutely continuous functions. We also use our analytic methods to show that computable randomness of a real is base invariant and to derive other preservation results for randomness notions.
引用
收藏
页码:581 / 605
页数:25
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