论文标题
基于Faber多项式的明确指数时间集成器及其应用于地震波建模
An explicit exponential time integrator based on Faber polynomials and its application to seismic wave modelling
论文作者
论文摘要
指数时间积分器已成功应用于几个与物理相关的微分方程。但是,它们在具有吸收边界的双曲线系统中的应用,例如在地震成像中产生的界限,仍然缺乏理论和实验研究。本工作对使用Faber多项式进行了深入的指数整合研究,其中包括使用Chebyshev多项式的流行指数方法的概括。这允许解决从经典的地震波传播问题中出现的非对称算子,并吸收了边界。为Faber近似提供了理论和数值结果。理论上的贡献之一是针对正常矩阵指数的近似误差的尖锐结合的建议。我们还展示了确定涵盖离散操作员的最佳椭圆形的实际重要性,以确保和增强Faber指数系列的收敛性。此外,基于用广泛使用的吸收边界方法对波动方程离散操作员的频谱的估计,我们数值研究了Faber指数方案的稳定性,分散,收敛和计算效率。总体而言,我们得出的结论是,该方法适用于地震波问题,并且可以以较大的时间步长提供准确的结果,并且随着近似程度的增加,计算效率的提高。
Exponential time integrators have been applied successfully in several physics-related differential equations. However, their application in hyperbolic systems with absorbing boundaries, like the ones arising in seismic imaging, still lacks theoretical and experimental investigations. The present work conducts an in-depth study of exponential integration using Faber polynomials, consisting of a generalization of a popular exponential method that uses Chebyshev polynomials. This allows solving non-symmetric operators that emerge from classic seismic wave propagation problems with absorbing boundaries. Theoretical as well as numerical results are presented for Faber approximations. One of the theoretical contributions is the proposal of a sharp bound for the approximation error of the exponential of a normal matrix. We also show the practical importance of determining an optimal ellipse encompassing the full spectrum of the discrete operator, in order to ensure and enhance convergence of the Faber exponential series. Furthermore, based on estimates of the spectrum of the discrete operator of the wave equations with a widely used absorbing boundary method, we numerically investigate stability, dispersion, convergence and computational efficiency of the Faber exponential scheme. Overall, we conclude that the method is suitable for seismic wave problems and can provide accurate results with large time step sizes, with computational efficiency increasing with the increase of the approximation degree.