English

Data Structures for Topologically Sound Higher-Dimensional Diagram Rewriting

Category Theory 2023-08-01 v3 Data Structures and Algorithms Logic in Computer Science

Abstract

We present a computational implementation of diagrammatic sets, a model of higher-dimensional diagram rewriting that is "topologically sound": diagrams admit a functorial interpretation as homotopies in cell complexes. This has potential applications both in the formalisation of higher algebra and category theory and in computational algebraic topology. We describe data structures for well-formed shapes of diagrams of arbitrary dimensions and provide a solution to their isomorphism problem in time O(n^3 log n). On top of this, we define a type theory for rewriting in diagrammatic sets and provide a semantic characterisation of its syntactic category. All data structures and algorithms are implemented in the Python library rewalt, which also supports various visualisations of diagrams.

Keywords

Cite

@article{arxiv.2209.09509,
  title  = {Data Structures for Topologically Sound Higher-Dimensional Diagram Rewriting},
  author = {Amar Hadzihasanovic and Diana Kessler},
  journal= {arXiv preprint arXiv:2209.09509},
  year   = {2023}
}

Comments

In Proceedings ACT 2022, arXiv:2307.15519

R2 v1 2026-06-28T01:42:56.288Z