Algorithms for the Matrix Exponential

MATRIX_EXPONENTIAL is a Python library which exhibits and compares some algorithms for approximating the matrix exponential function.

Formally, for a square matrix A and scalar t, the matrix exponential exp(A*t) can be defined as the sum:

exp(A*t) = sum ( 0 <= i < oo ) A^i t^i / i!

The simplest form of the matrix exponential problem asks for the value when t = 1. Even for this simple case, and for a matrix of small order, it can be quite difficult to compute the matrix exponential accurately.


The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.


MATRIX_EXPONENTIAL is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

TEST_MAT, a Python library which defines test matrices.

TEST_MATRIX_EXPONENTIAL, a Python library which defines a set of test cases for computing the matrix exponential.


  1. Alan Laub,
    Review of "Linear System Theory" by Joao Hespanha,
    SIAM Review,
    Volume 52, Number 4, December 2010, page 779-781.
  2. Cleve Moler, Charles VanLoan,
    Nineteen Dubious Ways to Compute the Exponential of a Matrix, SIAM Review,
    Volume 20, Number 4, October 1978, pages 801-836.
  3. Cleve Moler, Charles VanLoan,
    Nineteen Dubious Ways to Compute the Exponential of a Matrix, Twenty-Five Years Later,
    SIAM Review,
    Volume 45, Number 1, March 2003, pages 3-49.
  4. Roger Sidje,
    EXPOKIT: Software Package for Computing Matrix Exponentials,
    ACM Transactions on Mathematical Software,
    Volume 24, Number 1, 1998, pages 130-156.
  5. Robert Ward,
    Numerical computation of the matrix exponential with accuracy estimate,
    SIAM Journal on Numerical Analysis,
    Volume 14, Number 4, September 1977, pages 600-610.

Source Code:

You can go up one level to the Python source codes.

Last modified on 06 February 2017.