Convex Spaces I: Definition and Examples
arXiv:0903.5522
Abstract
We propose an abstract definition of convex spaces as sets where one can take convex combinations in a consistent way. A priori, a convex space is an algebra over a finitary version of the Giry monad. We identify the corresponding Lawvere theory as the category from arXiv:0902.2554 and use the results obtained there to extract a concrete definition of convex space in terms of a family of binary operations satisfying certain compatibility conditions. After giving an extensive list of examples of convex sets as they appear throughout mathematics and theoretical physics, we find that there also exist convex spaces that cannot be embedded into a vector space: semilattices are a class of examples of purely combinatorial type. In an information-theoretic interpretation, convex subsets of vector spaces are probabilistic, while semilattices are possibilistic. Convex spaces unify these two concepts.
24 pages, 4 figures, one of them in color. v3: clarified that this manuscript constitutes a non-original rediscovery of known material
References in corpus (1)
Cited by in corpus (11)
- On the axiomatization of convex subsets of Banach spaces
- A Bayesian Characterization of Relative Entropy
- A presentation of the category of stochastic matrices
- Codensity and the Giry monad
- One simple postulate implies that every polytopic state space is classical
- Category Theory in Machine Learning
- Monads, partial evaluations, and rewriting
- Effectuses in Categorical Quantum Foundations
- (Co)monads in Free Probability Theory
- Healthiness from Duality
- On functors from category of Giry algebras to category of convex spaces