The existence and utility of Giry algebras in probability theory

TL;DR

This paper explores the existence and properties of Giry algebras in probability theory, showing they form a rich categorical structure under certain set-theoretic assumptions, contrasting with the Giry monad's Kleisli category.

Contribution

It establishes conditions for the existence of Giry algebras and demonstrates their categorical advantages over the Kleisli category in modeling probability.

Findings

Giry algebras exist under specific set-theoretic hypotheses.

The category of Giry algebras is symmetric monoidal closed with all limits and colimits.

This category provides a more comprehensive framework for probability theory than the Kleisli category.

Abstract

Giry algebras are barycenters maps, which are coequalizers of contractible coequalizer pairs (like any algebras), and their existence, in general, requires the measurable space be coseparated by the discrete two point space, and the hypothesis that no measurable cardinals exist. Under that hypothesis, every measurable space which is coseparated has an algebra, and the category of Giry algebras provides a convenient setting for probability theory because it is a symmetric monoidal closed category with all limits and colimits, as well as having a seperator and coseperator. This is in stark contrast to the Kleisi category of the Giry monad, which is often used to model conditional probability, which has a seperator but not much else.