论文标题
用catlab和semanticmodels组成的科学计算
Compositional Scientific Computing with Catlab and SemanticModels
论文作者
论文摘要
科学计算目前是通过编写特定于域的建模框架来解决特殊类数学问题的。由于应用类别理论提供了用于描述和分析数学不同领域的抽象推理机制，因此它是构建用于科学计算的通用和可重复使用的软件组件的自然平台。我们提出catlab.jl，该catlab.jl提供了该项目的类别理论基础架构，以及semanticmodels.jl，它利用该基础架构用于特定的建模任务。这种方法通过将互连系统数学建模的最新进展应用于Cospan代数来增强和自动化科学计算工作流程。
Scientific computing is currently performed by writing domain specific modeling frameworks for solving special classes of mathematical problems. Since applied category theory provides abstract reasoning machinery for describing and analyzing diverse areas of math, it is a natural platform for building generic and reusable software components for scientific computing. We present Catlab.jl, which provides the category-theoretic infrastructure for this project, together with SemanticModels.jl, which leverages this infrastructure for particular modeling tasks. This approach enhances and automates scientific computing workflows by applying recent advances in mathematical modeling of interconnected systems as cospan algebras.
