Limits and consistency of non-local and graph approximations to the Eikonal equation - Institut National des Sciences Appliquées de Rouen Accéder directement au contenu
Article Dans Une Revue IMA Journal of Numerical Analysis Année : 2023

Limits and consistency of non-local and graph approximations to the Eikonal equation

Résumé

In this paper, we study a non-local approximation of the time-dependent (local) Eikonal equation with Dirichlet-type boundary conditions, where the kernel in the non-local problem is properly scaled. Based on the theory of viscosity solutions, we prove existence and uniqueness of the viscosity solutions of both the local and non-local problems, as well as regularity properties of these solutions in time and space. We then derive error bounds between the solution to the non-local problem and that of the local one, both in continuous-time and Backward Euler time discretization. We then turn to studying continuum limits of non-local problems defined on random weighted graphs with $n$ vertices. In particular, we establish that if the kernel scale parameter decreases at an appropriate rate as $n$ grows, then almost surely, the solution of the problem on graphs converges uniformly to the viscosity solution of the local problem as the time step vanishes and the number vertices $n$ grows large.
Fichier principal
Vignette du fichier
Paper_finalversion_arxiv.pdf (466.76 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03218100 , version 1 (06-05-2021)
hal-03218100 , version 2 (07-05-2021)
hal-03218100 , version 3 (17-01-2022)
hal-03218100 , version 4 (25-02-2022)
hal-03218100 , version 5 (21-11-2022)

Identifiants

Citer

Jalal M. Fadili, Nicolas Forcadel, Thi Tuyen Nguyen, Rita Zantout. Limits and consistency of non-local and graph approximations to the Eikonal equation. IMA Journal of Numerical Analysis, 2023, 43 (6), pp.3685-3728. ⟨10.1093/imanum/drac082⟩. ⟨hal-03218100v5⟩
164 Consultations
93 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More