Effective maximum principles for spectral methods
Dong Li

TL;DR
This paper develops a new framework called effective maximum principles for spectral methods, allowing controlled deviations from sharp maximum bounds in numerical solutions of PDEs like Allen-Cahn, Burgers, and Navier-Stokes equations.
Contribution
It introduces the concept of effective maximum principles for spectral methods, providing a rigorous analysis that accommodates discretization errors while preserving maximum norm bounds.
Findings
Effective maximum principles are established for Fourier spectral methods.
The framework applies to various PDEs including Allen-Cahn, Burgers, and Navier-Stokes.
The analysis covers different time discretizations like forward Euler and Strang splitting.
Abstract
Many physical problems such as Allen-Cahn flows have natural maximum principles which yield strong point-wise control of the physical solutions in terms of the boundary data, the initial conditions and the operator coefficients. Sharp/strict maximum principles insomuch of fundamental importance for the continuous problem often do not persist under numerical discretization. A lot of past research concentrates on designing fine numerical schemes which preserves the sharp maximum principles especially for nonlinear problems. However these sharp principles not only sometimes introduce unwanted stringent conditions on the numerical schemes but also completely leaves many powerful frequency-based methods unattended and rarely analyzed directly in the sharp maximum norm topology. A prominent example is the spectral methods in the family of weighted residual methods. In this work we introduce…
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Taxonomy
TopicsSolidification and crystal growth phenomena · Advanced Mathematical Modeling in Engineering · Advanced Numerical Methods in Computational Mathematics
