Wei Zhang , Dongdong Hu , Wenjun Cai , Yushun Wang
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Unconditional convergence of a linearly implicit energy-conserving scheme for the 2D NLSW equation
A novel linear modified energy-conserving scheme for the Two-Dimensional (2D) fractional Non Linear Schrödinger Wave (NLSW) equation, recently proposed by Hu et al. (2023), demonstrates high efficiency in long-time computations. However, the convergence analysis provided is conditional, as the time-step size depends on the dimension of the approximation space. This paper aims to establish a linearly implicit energy-conserving scheme with unconditional convergence that is as efficient as the aforementioned scheme for the 2D NLSW equation. Theoretically, discrete modified energy conservation and unique solvability are rigorously proved. Furthermore, an optimal discrete convergence analysis is presented without any restrictions on the time-step size, where the “lifting” technique is utilized to address the most significant difficulty, i.e., the discrete estimate of numerical solutions. On the numerical side, a fast implementation algorithm is briefly outlined, and several numerical experiments are conducted to validate the theoretical analysis and demonstrate the high efficiency of our scheme.
期刊介绍:
The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest.
The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.