Advancements in Numerical Methods for Partial Differential Equations

The field of numerical methods for partial differential equations is witnessing significant developments, with a focus on improving the accuracy and efficiency of existing methods. Researchers are exploring new approaches to tackle complex problems, such as multiscale parabolic equations, singularly perturbed coupled systems, and relativistic charged-particle dynamics. Noteworthy papers in this area include: A concurrent global-local numerical method for multiscale parabolic equations, which improves macroscopic and microscopic errors. An efficient spline-based scheme on Shishkin-type meshes for solving singularly perturbed coupled systems with Robin boundary conditions, achieving almost second-order convergence. Error and long-term analysis of two-step symmetric methods for relativistic charged-particle dynamics, which preserves energy, mass shell, and phase-space volume. A novel time integration scheme for linear parabolic PDEs, enhancing the Crank-Nicolson method with radial basis function interpolation for higher-order temporal accuracy.

Sources

A concurrent global-local numerical method for multiscale parabolic equations

Curvature-Based Optimal Polynomial Geometric Interpolation of Circular Arcs

An efficient spline-based scheme on Shishkin-type meshes for solving singularly perturbed coupled systems with Robin boundary conditions

Correction of weighted and shifted seven-step BDF for parabolic equations with nonsmooth data

Error and long-term analysis of two-step symmetric methods for relativistic charged-particle dynamics

CAZAC sequence generation of any length with iterative projection onto unit circle: principle and first results

Fractal Based Rational Cubic Trigonometric Zipper Interpolation with Positivity Constraints

A novel time integration scheme for linear parabolic PDEs

Tensor-Train Operator Inference

An Improved Robin-Robin Coupling Method for Parabolic-Parabolic Interface Problems

Restarting the Numerical Flow Iteration through low rank tensor approximations

Built with on top of