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.
翻译:我们展示了图表集的计算实施,这是高维图重写模型的模型,它“在地形上健全 ” : 图表中承认一个线性解释是细胞综合体中的同族体。 这在高代数和类别理论的正规化以及计算代数表层中都有潜在应用。 我们描述任意尺寸图的完善形状的数据结构,并及时为它们的无形态问题提供一个解决方案 $O(n ⁇ 3\log n) 。 除此之外, 我们定义了用于重写图表集的理论类型, 并提供了其合成分类的语义特征。 所有数据结构和算法都在 Python 图书馆雷瓦尔特 中实施, 也支持了图表的各种可视化。