Leticia Mattos Da Silva, Oded Stein, Justin Solomon
{"title":"A Framework for Solving Parabolic Partial Differential Equations on Discrete Domains","authors":"Leticia Mattos Da Silva, Oded Stein, Justin Solomon","doi":"arxiv-2312.00327","DOIUrl":null,"url":null,"abstract":"We introduce a framework for solving a class of parabolic partial\ndifferential equations on triangle mesh surfaces, including the Hamilton-Jacobi\nequation and the Fokker-Planck equation. PDE in this class often have nonlinear\nor stiff terms that cannot be resolved with standard methods on curved triangle\nmeshes. To address this challenge, we leverage a splitting integrator combined\nwith a convex optimization step to solve these PDE. Our machinery can be used\nto compute entropic approximation of optimal transport distances on geometric\ndomains, overcoming the numerical limitations of the state-of-the-art method.\nIn addition, we demonstrate the versatility of our method on a number of linear\nand nonlinear PDE that appear in diffusion and front propagation tasks in\ngeometry processing.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"40 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Numerical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2312.00327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We introduce a framework for solving a class of parabolic partial
differential equations on triangle mesh surfaces, including the Hamilton-Jacobi
equation and the Fokker-Planck equation. PDE in this class often have nonlinear
or stiff terms that cannot be resolved with standard methods on curved triangle
meshes. To address this challenge, we leverage a splitting integrator combined
with a convex optimization step to solve these PDE. Our machinery can be used
to compute entropic approximation of optimal transport distances on geometric
domains, overcoming the numerical limitations of the state-of-the-art method.
In addition, we demonstrate the versatility of our method on a number of linear
and nonlinear PDE that appear in diffusion and front propagation tasks in
geometry processing.