Learn how category theory can revolutionize scientific workflows and software engineering in this 55-minute seminar talk from the Topos Institute Berkeley series. Explore how computational category theory offers a more robust alternative to ad hoc programming abstractions, with practical examples from scientific modeling and data management. Discover approaches for creating maintainable, scalable abstractions that effectively handle complex scientific models, databases, and simulators. Follow along as Kris Brown demonstrates applications in chemical reaction networks, multiphysics modeling, and agent-based systems, showing how category theory enables seamless model integration, multiplication, and manipulation without extensive coding. Gain insights into using tools like AlgebraicJulia and C-Sets to build more conceptual, interconnected programming solutions that can evolve with changing scientific requirements.
Scientific and Software Engineering Applications of Category Theory
Overview
Syllabus
Abstraction
The status quo
Why Category Theory?
Applied Category Theory?
B. DFT simulations
B.Storing the data of lots of simulations
B. An improvement: databases
B. Another improvement: C-Sets/ACSets
B. Head-to-head comparison
B. Data migration
Models through the eyes of the computer
Models through the eyes of the scientist
C-Set for Chemical Reaction Networks
Colimits of CSets: gluing models together
Limits of CSets: model multiplication
Continuous time simulations
Multiphysics modeling
Agent based models
Merging, deleting, copying, adding... without code
Conclusions
Resources
Taught by
Topos Institute
