jacobi_eigenvalue, a FORTRAN90 code which computes the eigenvalues and eigenvectors of a real symmetric matrix.

Given a real symmetric NxN matrix A, the code carries out an iterative procedure known as Jacobi's iteration, to determine a N-vector D of real, positive eigenvalues, and an NxN matrix V whose columns are the corresponding eigenvectors, so that, for each column J of the eigenmatrix:

        A * Vj = Dj * Vj


The computer code and data files made available on this web page are distributed under the MIT license


jacobi_eigenvalue 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:

ARPACK, a FORTRAN90 code which uses Arnoldi methods to compute some eigenvalues and eigenvectors of matrices, which may be very large.


LAPACK_EXAMPLES, a FORTRAN90 code which demonstrates the use of the LAPACK linear algebra library.

TEST_EIGEN, a FORTRAN90 code which implements test matrices for eigenvalue analysis.

TEST_MAT, a FORTRAN90 code which defines test matrices, some of which have known determinants, eigenvalues and eigenvectors, inverses and so on.


  1. Gene Golub, Charles VanLoan,
    Matrix Computations, Third Edition,
    Johns Hopkins, 1996,
    ISBN: 0-8018-4513-X,
    LC: QA188.G65.

Source Code:

Last revised on 20 July 2020.