Skip to main content
Log in

Recovering Exponential Accuracy in Fourier Spectral Methods Involving Piecewise Smooth Functions with Unbounded Derivative Singularities

  • Published:
Journal of Scientific Computing Aims and scope Submit manuscript

Abstract

Fourier spectral methods achieve exponential accuracy both on the approximation level and for solving partial differential equations, if the solution is analytic. If the solution is discontinuous but piecewise analytic up to the discontinuities, Fourier spectral methods produce poor pointwise accuracy, but still maintain exponential accuracy after post-processing (Gottlieb and Shu in SIAM Rev 30:644–668, 1997) . In Chen and Shu (J Comput Appl Math 265:83–95, 2014), an extended technique is provided to recover exponential accuracy for functions which have end-point singularities, from the knowledge of point values on standard collocation points. In this paper, we develop a technique to recover exponential accuracy from the first \(N\) Fourier coefficients of functions which are analytic in the open interval but have unbounded derivative singularities at end points. With this post-processing method, we are able to obtain exponential accuracy of spectral methods applied to linear transport equations involving such functions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Adcock, B., Richardson, M.: New exponential variable transform methods for functions with endpoint singularities. SIAM J. Numer. Anal. 52, 1887–1912 (2014)

    Article  MATH  MathSciNet  Google Scholar 

  2. Archibald, R., Chen, K., Gelb, A., Renaut, R.: Improving tissue segmentation of human brain MRI through preprocessing by the Gegenbauer reconstruction method. NeuroImage 20, 489–502 (2003)

    Article  Google Scholar 

  3. Archibald, R., Gelb, A.: A method to reduce the Gibbs ringing artifact in MRI scans while keeping tissue boundary integrity. IEEE Med. Imaging 21, 305–319 (2002)

    Article  Google Scholar 

  4. Archibald, R., Gelb, A.: Reducing the effects of noise in image reconstruction. J. Sci. Comput. 17, 167–180 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  5. Archibald, R., Hu, J., Gelb, A., Farin, G.: Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction. IEEE Trans. Med. Imaging 13, 459–466 (2004)

    Google Scholar 

  6. Bateman, H.: Higher Transcendental Functions, v2. McGraw-Hill, New York (1953)

    Google Scholar 

  7. Chen, Z., Shu, C.-W.: Recovering exponential accuracy from collocation point values of smooth functions with end-point singularities. J. Comput. Appl. Math. 265, 83–95 (2014)

    Article  MATH  MathSciNet  Google Scholar 

  8. Gottlieb, D., Gottlieb, S.: Spectral methods for compressible reactive flows. C. R. Mec. 333, 3–16 (2005)

    Article  MATH  Google Scholar 

  9. Gottlieb, D., Shu, C.-W.: Resolution properties of the Fourier method for discontinuous waves. Comput. Methods Appl. Mech. Eng. 116, 27–37 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  10. Gottlieb, D., Shu, C.-W.: On the Gibbs phenomenon IV: recovering exponential accuracy in a sub-interval from a Gegenbauer partial sum of a piecewise analytic function. Math. Comput. 64, 1081–1095 (1995)

    MATH  MathSciNet  Google Scholar 

  11. Gottlieb, D., Shu, C.-W.: On the Gibbs phenomenon V: recovering exponential accuracy from collocation point values of a piecewise analytic function. Numer. Math. 71, 511–526 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  12. Gottlieb, D., Shu, C.-W.: On the Gibbs phenomenon III: recovering exponential accuracy in a sub-interval from a spectral partial sum of a piecewise analytic function. SIAM J. Numer. Anal. 33, 280–290 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  13. Gottlieb, D., Shu, C.-W.: On the Gibbs phenomenon and its resolution. SIAM Rev. 30, 644–668 (1997)

    Article  MathSciNet  Google Scholar 

  14. Gottlieb, D., Shu, C.-W., Solomonoff, A., Vandeven, H.: On the Gibbs phenomenon I: recovering exponential accuracy from the Fourier partial sum of a non-periodic analytic function. J. Comput. Appl. Math. 43, 81–98 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  15. Gottlieb, S., Gottlieb, D., Shu, C.-W.: Recovering high order accuracy in WENO computations of steady state hyperbolic systems. J. Sci. Comput. 28, 307–318 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  16. Hesthaven, J.S., Gottlieb, S., Gottlieb, D.: Spectral Methods for Time-Dependent Problems. Cambridge Monographs on Applied and Computational Mathematics, Vol. 21. Cambridge University Press, Cambridge (2007)

    Book  MATH  Google Scholar 

  17. Jung, J.-H., Gottlieb, S., Kim, S.O., Bresten, C.L., Higgs, D.: Recovery of high order accuracy in radial basis function approximations of discontinuous problems. J. Sci. Comput. 45, 359–381 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  18. Shu, C.-W., Wong, P.S.: A note on the accuracy of spectral method applied to nonlinear conservation laws. J. Sci. Comput. 10, 357–369 (1995)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chi-Wang Shu.

Additional information

Research supported by NSF Grants DMS-1112700 and DMS-1418750, and AFOSR Grant F49550-12-1-0399.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Z., Shu, CW. Recovering Exponential Accuracy in Fourier Spectral Methods Involving Piecewise Smooth Functions with Unbounded Derivative Singularities. J Sci Comput 65, 1145–1165 (2015). https://doi.org/10.1007/s10915-015-0011-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10915-015-0011-x

Keywords

Navigation