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Research Software

SphericalSBPOperators.jl

High-order numerical operators for spherical and curvilinear coordinates, enabling symmetry-reduced simulations with theoretical O(N^2) speedups and memory reductions over full 3D Cartesian discretizations.

Julia Numerical Analysis Performance Optimization

Summary

SphericalSBPOperators.jl develops stable high-order summation-by-parts finite-difference operators for spherical and general curvilinear coordinates, with special attention to coordinate singularities such as the origin. The project provides a framework for constructing discrete operators that preserve continuum energy estimates, reduce symmetry-reduced evolution problems to lower-dimensional domains, and retain high-order accuracy without giving up stability at singular points. In practice, that makes it possible to solve hyperbolic PDEs in geometries that would otherwise require a far more expensive full 3D Cartesian discretization.

Keywords

Julia Numerical Analysis Performance Optimization

Key Insights

Symmetry reduction changes the computational regime

The main payoff is dimensional reduction rather than a marginal constant-factor speedup. By building stable operators directly in spherical and curvilinear coordinates, the project targets problems where symmetry can be exploited without giving up rigorous stability arguments.

The origin is handled through operator design

A central numerical insight is that the r = 0 singularity should be treated as part of the discretization problem itself. The SBP construction is designed to retain discrete energy estimates and high-order accuracy even in the presence of singular coordinate structure.