Dilations and information flow axioms in categorical probability

Type: Article

Publication Date: 2023-10-25

Citations: 4

DOI: https://doi.org/10.1017/s0960129523000324

Abstract

Abstract We study the positivity and causality axioms for Markov categories as properties of dilations and information flow and also develop variations thereof for arbitrary semicartesian monoidal categories. These help us show that being a positive Markov category is merely an additional property of a symmetric monoidal category (rather than extra structure). We also characterize the positivity of representable Markov categories and prove that causality implies positivity , but not conversely. Finally, we note that positivity fails for quasi-Borel spaces and interpret this failure as a privacy property of probabilistic name generation.

Locations

  • Mathematical Structures in Computer Science - View
  • arXiv (Cornell University) - View - PDF
  • Radboud Repository (Radboud University) - View - PDF
  • Oxford University Research Archive (ORA) (University of Oxford) - View - PDF

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