The Scaling and Squaring Method for the Matrix Exponential Revisited

Higham, Nicholas J. (2009) The Scaling and Squaring Method for the Matrix Exponential Revisited. SIAM Review, 51 (4). pp. 747-764. ISSN 0036-1445

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The scaling and squaring method is the most widely used method for computing the matrix exponential, not least because it is the method implemented in the MATLAB function expm. The method scales the matrix by a power of 2 to reduce the norm to order 1, computes a Pad´e approximant to the matrix exponential, and then repeatedly squares to undo the effect of the scaling. We give a new backward error analysis of the method (in exact arithmetic) that employs sharp bounds for the truncation errors and leads to an implementation of essentially optimal efficiency. We also give a new rounding error analysis that shows the computed Pad´e approximant of the scaled matrix to be highly accurate. For IEEE double precision arithmetic the best choice of degree of Pad´e approximant turns out to be 13, rather than the 6 or 8 used by previous authors. Our implementation of the scaling and squaring method always requires at least two fewer matrix multiplications than the expm function in MATLAB 7.0 when the matrix norm exceeds 1, which can amount to a 37% saving in the number of multiplications, and it is typically more accurate, owing to the fewer required squarings. We also investigate a different scaling and squaring algorithm proposed by Najfeld and Havel that employs a P ad´e approximation to the function x coth(x). This method is found

Item Type: Article
Additional Information: SIGEST article
Uncontrolled Keywords: matrix function, matrix exponential, Pad\'e approximation, matrix polynomial evaluation, scaling and squaring method, MATLAB\@, {\tt expm}, backward error analysis, performance profile
Subjects: MSC 2010, the AMS's Mathematics Subject Classification > 15 Linear and multilinear algebra; matrix theory
MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis
Depositing User: Nick Higham
Date Deposited: 04 Nov 2009
Last Modified: 20 Oct 2017 14:12

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