Global well-posedness for volume-surface reaction-diffusion systems
Jeff Morgan, Bao Quoc Tang

TL;DR
This paper proves the global existence of classical solutions for volume-surface reaction-diffusion systems with mass control, introducing new energy methods and conditions to handle the complex volume-surface coupling.
Contribution
It develops a novel $L^p$-energy approach combined with a duality method to establish global solutions under the intermediate sum condition and quasi-uniform diffusion assumptions.
Findings
Global existence of classical solutions under the intermediate sum condition.
Solutions are uniformly bounded in time for mass-dissipative systems.
Applicable to biological models like membrane protein clustering and cell polarization.
Abstract
We study the global existence of classical solutions to volume-surface reaction-diffusion systems with control of mass. Such systems appear naturally from modeling evolution of concentrations or densities appearing both in a volume domain and its surface, and therefore have attracted considerable attention. Due to the characteristic volume-surface coupling, global existence of solutions to general systems is a challenging issue. In particular, the duality method, which is powerful in dealing with mass conserved systems in domains, is not applicable on its own. In this paper, we introduce a new family of -energy functions and combine them with a suitable duality method for volume-surface systems, to ultimately obtain global existence of classical solutions under a general assumption called the \textit{intermediate sum condition}. For systems that conserve mass, but do not satisfy…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical Biology Tumor Growth · Mathematical and Theoretical Epidemiology and Ecology Models · Stochastic processes and statistical mechanics
