The interplay of classes of algorithmically random objects

Abstract

We study algorithmically random closed subsets of $\cs$\!, algorithmically random continuous functions from $\cs$ to $\cs$\!, and algorithmically random Borel probability measures on $\cs$, especially the interplay between these three classes of objects. Our main tools are preservation of randomness and its converse, the no randomness ex nihilo principle, which say together that given an almost-everywhere defined computable map between an effectively compact probability space and an effective Polish space, a real is Martin-Löf random for the pushforward measure if and only if its preimage is random with respect to the measure on the domain. These tools allow us to prove new facts, some of which answer previously open questions, and reprove some known results more simply.

Our main results are the following. First we answer an open question in \cite{Barmpalias:2008aa} by showing that $\X\subseteq\cs$\! is a random closed set if and only if it is the set of zeros of a random continuous function on $\cs$\!. As a corollary we obtain the result that the collection of random continuous functions on $\cs$ is not closed under composition. Next, we construct a computable measure $Q$ on the space of measures on $\cs$ such that $\X\subseteq\cs$ is a random closed set if and only if $\X$ is the support of a $Q$-random measure. We also establish a correspondence between random closed sets and the random measures studied in \cite{Culver:2014aa}. Lastly, we study the ranges of random continuous functions, showing that the Lebesgue measure of the range of a random continuous function is always contained in $(0,1)$.