Bimonoidal Structure of Probability Monads

We give a conceptual treatment of the notion of joints, marginals, and independence in the setting of categorical probability. This is achieved by endowing the usual probability monads (like the Giry monad) with a monoidal and an op<PRE_TAG>monoidal structure</POST_TAG>, mutually compatible (i.e. a bi<PRE_TAG>monoidal structure</POST_TAG>). If the underlying monoidal category is cartesian monoidal, a bi<PRE_TAG>monoidal structure</POST_TAG> is given uniquely by a commutative strength. However, if the underlying monoidal category is not cartesian monoidal, a strength is not enough to guarantee all the desired properties of joints and marginals. A bimonoidal structure is then the correct requirement for the more general case. We explain the theory and the operational interpretation, with the help of the graphical calculus for monoidal categories. We give a definition of stochastic independence based on the bi<PRE_TAG>monoidal structure</POST_TAG>, compatible with the intuition and with other approaches in the literature for cartesian monoidal categories. We then show as an example that the Kantorovich monad on the category of complete metric spaces is a bimonoidal monad for a non-cartesian monoidal structure.