Randomness via infinite computation and effective descriptive set theory
Merlin Carl, Philipp Schlicht

TL;DR
This paper explores randomness notions related to infinite time Turing machines, establishing their properties and differences from classical and hyperarithmetic randomness, and introduces technical results on forcing and admissible sets.
Contribution
It introduces and analyzes randomness notions associated with infinite time Turing machines, showing they share properties with classical randomness and differ from hyperarithmetic cases.
Findings
Randomness notions for infinite time Turing machines have properties similar to classical randomness.
Mutual randoms do not share information and satisfy van Lambalgen's theorem.
If a real is computable relative to all reals in a positive measure set, it is already computable.
Abstract
We study randomness beyond -randomness and its Martin-L\"of type variant, introduced in \cite{MR2340241} and further studied in \cite{Continuous-higher-randomness}. The class given by the infinite time Turing machines (\ITTM s), introduced by Hamkins and Kidder, is strictly between and . We prove that the natural randomness notions associated to this class have several desirable properties resembling those of the classical random notions such as Martin-L\"of randomness, and randomness notions defined via effective descriptive set theory such as -randomness. For instance, mutual randoms do not share information and can be characterized as in van Lambalgen's theorem. We also obtain some differences to the hyperarithmetic setting. Already at the level of , some properties of randomness notions are independent \cite{Infinite-computations}.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
