Language-based Abstractions for Dynamical Systems

Andrea Vandin
(IMT School for Advanced Studies Lucca)

Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of effectively performing analyses. This has motivated a large body of research, across many disciplines, into abstraction techniques that provide smaller ODE systems while preserving the original dynamics in some appropriate sense. In this paper we give an overview of a recently proposed computer-science perspective to this problem, where ODE reduction is recast to finding an appropriate equivalence relation over ODE variables, akin to classical models of computation based on labelled transition systems.

In Herbert Wiklicky and Erik de Vink: Proceedings 15th Workshop on Quantitative Aspects of Programming Languages and Systems (QAPL 2017), Uppsala, Sweden, 23rd April 2017, Electronic Proceedings in Theoretical Computer Science 250, pp. 15–24.
Published: 12th July 2017.

ArXived at: bibtex PDF
References in reconstructed bibtex, XML and HTML format (approximated).
Comments and questions to:
For website issues: