A Fast Method for Linear Waves Based on Geometrical Optics

We develop a fast method for solving the one-dimensional wave equation based on geometrical optics. From geometrical optics (e.g., Fourier integral operator theory or WKB approximation) it is known that high-frequency waves split into forward and backward propagating parts, each propagating with the wave speed, with amplitude that is slowly changing depending on the medium coefficients, under the assumption that the medium coefficients vary slowly compared to the wavelength. Based on this we construct a method of optimal, $O(N)$ complexity, with basically the following steps: 1. decouple the wavefield into an approximately forward and an approximately backward propagating part; 2. propagate each component explicitly along the characteristics over a time step that is small compared to the medium scale but can be large compared to the wavelength; 3. apply a correction to account for the errors in the explicit propagation; repeat steps 2 and 3 over the necessary amount of time steps; and 4. reconstruct the full field by adding forward and backward propagating components again. Due to step 3 the method accurately computes the full wavefield. A variant of the method was implemented and outperformed a standard order (4,4) finite difference method by a substantial factor. The general principle is applicable also in higher dimensions, but requires efficient implementations of Fourier integral operators which are still the subject of current research.

[1]  Laurent Demanet,et al.  Wave atoms and time upscaling of wave equations , 2009, Numerische Mathematik.

[2]  L. Hörmander,et al.  Fourier integral operators. II , 1972 .

[3]  Randolph E. Bank,et al.  An optimal order process for solving finite element equations , 1981 .

[4]  Hart F. Smith A Hardy space for Fourier integral operators , 1998 .

[5]  L. Hörmander Fourier integral operators. I , 1995 .

[6]  Christiaan C. Stolk,et al.  On the modeling and inversion of seismic data , 2000 .

[7]  L. Trefethen Spectral Methods in MATLAB , 2000 .

[8]  E. Candès,et al.  The curvelet representation of wave propagators is optimally sparse , 2004, math/0407210.

[9]  Randall J. LeVeque,et al.  Convergence of a large time step generalization of Godunov's method for conservation laws , 1984 .

[10]  Stanley Osher,et al.  Fast Wavelet Based Algorithms for Linear Evolution Equations , 1994, SIAM J. Sci. Comput..

[11]  Y. Egorov,et al.  Fourier Integral Operators , 1994 .

[12]  François Treves,et al.  Introduction to Pseudodifferential and Fourier Integral Operators , 1980 .

[13]  Laurent Demanet,et al.  Fast Computation of Fourier Integral Operators , 2006, SIAM J. Sci. Comput..

[14]  G. Strang On the Construction and Comparison of Difference Schemes , 1968 .

[15]  A. Cohen Numerical Analysis of Wavelet Methods , 2003 .

[16]  W. Dahmen Wavelet and multiscale methods for operator equations , 1997, Acta Numerica.

[17]  C. Micchelli,et al.  Using the refinement equation for evaluating integrals of wavelets , 1993 .

[18]  Michael Taylor,et al.  Reflection of singularities of solutions to systems of differential equations , 1975 .

[19]  M. Czubak,et al.  PSEUDODIFFERENTIAL OPERATORS , 2020, Introduction to Partial Differential Equations.

[20]  G. Beylkin,et al.  Wave propagation using bases for bandlimited functions , 2005 .

[21]  Gary Cohen Higher-Order Numerical Methods for Transient Wave Equations , 2001 .

[22]  J. Lions,et al.  Non-homogeneous boundary value problems and applications , 1972 .