The Numerical Inversion of the Laplace Transform in a Multi-Precision Environment
- 1 School of Physics Astronomy and Mathematics, University of Hertfordshire, Hertfordshire, UK
- 2 School of Physics Astronomy and Mathematics, University of Hertfordshire, Hertfordshire, UK
Abstract
This paper examines the performance of five algorithms for numerically inverting the Laplace transform, in standard, 16-digit and multi-precision environments. The algorithms are taken from three of the four main classes of numerical methods used to invert the Laplace transform. Because the numerical inversion of the Laplace transform is a perturbed problem, rounding errors which are generated in numerical approximations can adversely affect the accurate reconstruction of the inverse transform. This paper demonstrates that working in a multi-precision environment can substantially reduce these errors and the resulting perturbations exist in transforming the data from the s-space into the time domain and in so doing overcome the main drawback of numerically inverting the Laplace transform. Our main finding is that both the Talbot and the accelerated Gaver functionals perform considerably better in a multi-precision environment increasing the advantages of using Laplace transform methods over time-stepping procedures in solving diffusion and more generally parabolic partial differential equations.
- Abate, J. and Valkó, P.P. (2004) Multi-Precision Laplace Transform Inversion. International Journal for Numerical Methods in Engineering, 60, 979-993. https://doi.org/10.1002/nme.995
- Logan, J.D. (2013) Transport Modeling in Hydrogeochemical Systems, Volume 15. Springer Science & Business Media, Berlin.
- Spiegel, M.R. (1965) Schaum’s Outline of Theory and Problems of Laplace Transforms. McGraw-Hill, New York.
- Talbot, A. (1979) The Accurate Numerical Inversion of Laplace Transforms. IMA Journal of Applied Mathematics, 23, 97-120. https://doi.org/10.1093/imamat/23.1.97
- Stehfest, H. (1970) Algorithm 368: Numerical Inversion of Laplace Transforms [D5]. Communications of the ACM, 13, 47-49. https://doi.org/10.1145/361953.361969
- Gaver Jr., D.P. (1966) Observing Stochastic Processes, and Approximate Transform Inversion. Operations Research, 14, 444-459. https://doi.org/10.1287/opre.14.3.444
- Wimp, J. (1981) Sequence Transformations and Their Applications. Academic Press, Cambridge.
- Crump, K.S. (1976) Numerical Inversion of Laplace Transforms Using a Fourier Series Approximation. Journal of the ACM (JACM), 23, 89-96. https://doi.org/10.1145/321921.321931
- Davies, A. and Crann, D. (2004) A Handbook of Essential Mathematical Formulae. University of Hertfordshire Press, Hatfield.
- Cohen, A.M. (2007) Numerical Methods for Laplace Transform Inversion, Volume 5. Springer Science & Business Media, Berlin.
- Epstein, C.L. and Schotland, J. (2008) The Bad Truth about Laplace’s Transform. SIAM Review, 50, 504-520. https://doi.org/10.1137/060657273
- Kuhlman, K.L. (2012) Comparison of Inverse Laplace Transform Algorithms for Laplace-Space Numerical Approaches. Technical Report, Sandia National Laboratories, Albuquerque.
- Defreitas, C.L. and Kane, S.J. (2018) The Noise Handling Properties of the Talbot Algorithm for Numerically Inverting the Laplace Transform. Journal of Algorithms & Computational Technology, 13, 1-14. https://doi.org/10.1177/1748301818797069
- Duffy, D.G. (1993) On the Numerical Inversion of Laplace Transforms: Comparison of Three New Methods on Characteristic Problems from Applications. ACM Transactions on Mathematical Software (TOMS), 19, 333-359. https://doi.org/10.1145/155743.155788
- Narayanan, G.V. and Beskos, D.E. (1982) Numerical Operational Methods for Timedependent Linear Problems. International Journal for Numerical Methods in Engineering, 18, 1829-1854. https://doi.org/10.1002/nme.1620181207