Derivatives for Containers in Univalent Foundations
Philipp Joram, Niccol\`o Veltri

TL;DR
This paper extends the concept of derivatives for containers within Univalent Foundations, providing universal properties, laws, and a chain rule, all formalized in Cubical Agda, to enhance the representation of one-hole contexts in type theory.
Contribution
It introduces derivatives for untruncated containers in Univalent Foundations, establishing their universal properties and laws, and formalizes these results in Cubical Agda.
Findings
Derivatives satisfy a universal property in the category of untruncated containers.
A chain rule exists but is generally non-invertible, with restrictions in set-truncated cases.
Derived rules for fixed points and characterized invertibility of derivatives.
Abstract
Containers conveniently represent a wide class of inductive data types. Their derivatives compute representations of types of one-hole contexts, useful for implementing tree-traversal algorithms. In the category of containers and cartesian morphisms, derivatives of discrete containers (whose positions have decidable equality) satisfy a universal property. Working in Univalent Foundations, we extend the derivative operation to untruncated containers (whose shapes and positions are arbitrary types). We prove that this derivative, defined in terms of a set of isolated positions, satisfies an appropriate universal property in the wild category of untruncated containers and cartesian morphisms, as well as basic laws with respect to constants, sums and products. A chain rule exists, but is in general non-invertible. In fact, a globally invertible chain rule is inconsistent in the presence of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLogic, programming, and type systems · Topological and Geometric Data Analysis · Constraint Satisfaction and Optimization
