Coherent randomness tests and computing the $K$-trivial sets

Bienvenu, Laurent, et al. "Coherent randomness tests and computing the $K$-trivial sets." Journal of the European Mathematical Society 018.4 (2016): 773-812. <http://eudml.org/doc/277230>.

@article{Bienvenu2016,
abstract = {We introduce Oberwolfach randomness, a notion within Demuth’s framework of statistical tests with moving components; here the components’ movement has to be coherent across levels. We show that a ML-random set computes all $K$-trivial sets if and only if it is not Oberwolfach random, and indeed that there is a $K$-trivial set which is not computable from any Oberwolfach random set. We show that Oberwolfach random sets satisfy effective versions of almost-everywhere theorems of analysis, such as the Lebesgue density theorem and Doob’s martingale convergence theorem. We also show that random sets which are not Oberwolfach random satisfy highness properties (such as LR-hardness) which mean they are close to computing the halting problem. A consequence of these results is that a ML-random set failing the effective version of Lebesgue’s density theorem for closed sets must compute all $K$-trivial sets. Combined with a recent result by Day and Miller, this gives a positive solution to the ML-covering problem of algorithmic randomness. On the other hand these results settle stronger variants of the covering problem in the negative: no low ML-random set computes all $K$-trivial sets, and not every $K$-trivial set is computable from both halves of a random set.},
author = {Bienvenu, Laurent, Greenberg, Noam, Kučera, Antonín, Nies, André, Turetsky, Dan},
journal = {Journal of the European Mathematical Society},
keywords = {coherent randomness tests; $K$-trivial sets; coherent randomness tests; -trivial sets},
language = {eng},
number = {4},
pages = {773-812},
publisher = {European Mathematical Society Publishing House},
title = {Coherent randomness tests and computing the $K$-trivial sets},
url = {http://eudml.org/doc/277230},
volume = {018},
year = {2016},
}

TY - JOUR
AU - Bienvenu, Laurent
AU - Greenberg, Noam
AU - Kučera, Antonín
AU - Nies, André
AU - Turetsky, Dan
TI - Coherent randomness tests and computing the $K$-trivial sets
JO - Journal of the European Mathematical Society
PY - 2016
PB - European Mathematical Society Publishing House
VL - 018
IS - 4
SP - 773
EP - 812
AB - We introduce Oberwolfach randomness, a notion within Demuth’s framework of statistical tests with moving components; here the components’ movement has to be coherent across levels. We show that a ML-random set computes all $K$-trivial sets if and only if it is not Oberwolfach random, and indeed that there is a $K$-trivial set which is not computable from any Oberwolfach random set. We show that Oberwolfach random sets satisfy effective versions of almost-everywhere theorems of analysis, such as the Lebesgue density theorem and Doob’s martingale convergence theorem. We also show that random sets which are not Oberwolfach random satisfy highness properties (such as LR-hardness) which mean they are close to computing the halting problem. A consequence of these results is that a ML-random set failing the effective version of Lebesgue’s density theorem for closed sets must compute all $K$-trivial sets. Combined with a recent result by Day and Miller, this gives a positive solution to the ML-covering problem of algorithmic randomness. On the other hand these results settle stronger variants of the covering problem in the negative: no low ML-random set computes all $K$-trivial sets, and not every $K$-trivial set is computable from both halves of a random set.
LA - eng
KW - coherent randomness tests; $K$-trivial sets; coherent randomness tests; -trivial sets
UR - http://eudml.org/doc/277230
ER -