We introduce monoidal width as a measure of complexity for morphisms in monoidal categories. Inspired by well-known structural width measures for graphs, like tree width and rank width, monoidal width is based on a notion of syntactic decomposition: a monoidal decomposition of a morphism is an expression in the language of monoidal categories, where operations are monoidal products and compositions, that specifies this morphism. Monoidal width penalises the composition operation along ``big'' objects, while it encourages the use of monoidal products. We show that, by choosing the correct categorical algebra for decomposing graphs, we can capture tree width and rank width. For matrices, monoidal width is related to the rank. These examples suggest monoidal width as a good measure for structural complexity of processes modelled as morphisms in monoidal categories.
翻译:我们引入了单向宽度,作为单向类别形态的复杂度度。 受众所周知的图表结构宽度测量(如树宽度和排位宽度)的启发, 单向宽度基于合成分解的概念: 一种单向变异性是单向类别语言的一种表达方式, 操作是单向产物和构成, 以指定这种形态。 单向宽度惩罚“ bigg” 对象的构成操作, 同时鼓励使用单向产品。 我们通过选择正确的直线代数来分解图形, 我们可以捕捉树宽度和排位宽。 对于矩阵, 单向宽度与等级相关。 这些示例显示单向宽度是作为单向类别形态的流程结构复杂性的良好衡量尺度。