Optimization of a partial differential equation on a complex network

M Stoll, M Winkler - arXiv preprint arXiv:1907.07806, 2019 - arxiv.org
arXiv preprint arXiv:1907.07806, 2019arxiv.org
Differential equations on metric graphs can describe many phenomena in the physical world
but also the spread of information on social media. To efficiently compute the solution is a
hard task in numerical analysis. Solving a design problem, where the optimal setup for a
desired state is given, is even more challenging. In this work, we focus on the task of solving
an optimization problem subject to a differential equation on a metric graph with the control
defined on a small set of Dirichlet nodes. We discuss the discretization by finite elements …
Differential equations on metric graphs can describe many phenomena in the physical world but also the spread of information on social media. To efficiently compute the solution is a hard task in numerical analysis. Solving a design problem, where the optimal setup for a desired state is given, is even more challenging. In this work, we focus on the task of solving an optimization problem subject to a differential equation on a metric graph with the control defined on a small set of Dirichlet nodes. We discuss the discretization by finite elements and provide rigorous error bounds as well as an efficient preconditioning strategy to deal with the large-scale case. We show in various examples that the method performs very robustly.
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