Rigorous numerical enclosures for positive solutions of Lane-Emden's equation with sub-square exponents
Kazuaki Tanaka, Michael Plum, Kouta Sekine, Masahide Kashiwagi, and, Shin'ichi Oishi

TL;DR
This paper develops rigorous numerical methods to enclose positive solutions of Lane-Emden's equation with sub-square exponents, overcoming non-Lipschitz challenges and providing explicit error bounds for solutions near numerical approximations.
Contribution
It introduces a novel approach for obtaining explicit enclosures of solutions for nonlinear PDEs with non-Lipschitz nonlinearities, especially in the sub-square exponent case.
Findings
Successfully enclosed solutions for p=3/2 on the unit square
Proved existence of solutions near numerical approximations with explicit bounds
Extended Newton-Kantorovich theorem to non-Lipschitz nonlinearities
Abstract
The purpose of this paper is to obtain rigorous numerical enclosures for solutions of Lane-Emden's equation with homogeneous Dirichlet boundary conditions. We prove the existence of a nondegenerate solution nearby a numerically computed approximation together with an explicit error bound, i.e., a bound for the difference between and . In particular, we focus on the sub-square case in which so that the derivative of the nonlinearity is not Lipschitz continuous. In this case, it is problematic to apply the classical Newton-Kantorovich theorem for obtaining the existence proof, and moreover several difficulties arise in the procedures to obtain numerical integrations rigorously. We design a method for enclosing the required integrations explicitly, proving the existence of a desired solution based on a…
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
TopicsDifferential Equations and Boundary Problems · Numerical methods for differential equations · Differential Equations and Numerical Methods
