# 2014 seminar talk: Algorithmic Randomness and the Turing Degrees

Talk held by Dan Turetsky (KGRC) at the KGRC seminar on 2014-03-27.

### Abstract

Algorithmic randomness uses the tools of computability theory to analyze the question, "When is an infinite binary sequence random?".  Several different definitions of a random sequence are studied, with the most common being Martin-Löf randomness.

Randomness has a rich interaction with the Turing degrees of more classical computability theory, in particular with the c.e. degrees and the PA degrees. For example, if a random cannot compute $0'$ (or equivalently, cannot compute a PA degree), then every c.e. set which it can compute is $K$-trivial, which means that randomness considers it useless as an oracle; despite being non-computable, it has no derandomization power. The covering problem asks if this can be reversed; is every $K$-trivial computable from a random that does not compute $0'$?

I will review the appropriate definitions and discuss the covering problem and similar questions. I will also discuss the proof of the covering problem, which touches on the interaction of algorithmic randomness and effective analysis.