A Hybrid DST-Accelerated Finite-Difference Solver for 2D and 3D Poisson Equations with Dirichlet Boundary Conditions

Jing Pei and Xiaozhong Tong ()
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Jing Pei: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Xiaozhong Tong: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China

Mathematics, 2025, vol. 13, issue 17, 1-17

Abstract: Finite-difference methods are widely used to solve partial differential equations in diverse practical applications. Despite their prevalence, the computational efficiency of these methods encounters limitations due to the need to solve linear equation systems through matrix inversion or iterative solver, which is particularly challenging in scenarios involving high dimensions. The demand for numerical methods with high accuracy and fast computational speed is steadily increasing. To address this challenge, we present an efficient and accurate algorithm for high-dimensional numerical modeling. This approach combines a central finite-difference method with the discrete Sine transform (DST) scheme to solve the Poisson equation under Dirichlet boundary conditions (DBCs). To balance numerical accuracy and computation, the DST scheme is applied along one direction in the 2D case and two directions in the 3D case. This strategy effectively reduces problem complexity while maintaining low computational cost. The hybrid DST-accelerated finite-difference approach substantially lowers the computational cost associated with solving the Poisson equation on large grids. Comprehensive numerical experiments for 2D and 3D Poisson equations with DBCs have been conducted. The obtained numerical results demonstrate that the proposed hybrid method not only significantly reduces the computational expenses, but also maintains the central finite-difference accuracy.

Keywords: Poisson equation; Dirichlet boundary conditions (DBCs); finite-difference method; discrete sine transform (DST) (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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