Efficient scaling and squaring method for the matrix exponential
Authors/Creators
Description
This work presents a new algorithm to compute the matrix exponential within a given tolerance. Combined with the scaling and squaring procedure, the algorithm incorporates Taylor, partitioned and classical Padé methods shown to be superior in performance to the approximants used in state-of-the-art software. The algorithm computes matrix--matrix products and also matrix inverses, but it can be implemented to avoid the computation of inverses, making it convenient for some problems. If the matrix A belongs to a Lie algebra, then exp(A) belongs to its associated Lie group, being a property which is preserved by diagonal Padé approximants, and the algorithm has another option to use only these. Numerical experiments show the superior performance with respect to state-of-the-art implementations.
Files
readme.pdf
Additional details
Identifiers
Related works
- Is supplement to
- Software: https://github.com/nakopylov/AdaptiveExp/tree/0.1.0 (URL)
Dates
- Other
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2024-04
Software
- Programming language
- MATLAB
References
- Blanes, S., Kopylov, N., & Seydaoğlu, M. (2024). Efficient scaling and squaring method for the matrix exponential (0.1.0). Zenodo. https://doi.org/10.5281/zenodo.11071265