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In linear algebra, the modal matrix is used in the diagonalization process involving eigenvalues and eigenvectors. Specifically the modal matrix for the matrix is the n × n matrix formed with the eigenvectors of as columns in . It is utilized in the similarity transformation where is an n × n diagonal matrix with the eigenvalues of on the main diagonal of and zeros elsewhere. The matrix is called the spectral matrix for . The eigenvalues must appear left to right, top to bottom in the same order as their corresponding eigenvectors are arranged left to right in . The matrix has eigenvalues and corresponding eigenvectors A diagonal matrix , similar to is One possible choice for an invertible matrix such that is Note that since eigenvectors themselves are not unique, and since the columns of both and may be interchanged, it follows that both and are not unique. Let be an n × n matrix. A generalized modal matrix for is an n × n matrix whose columns, considered as vectors, form a canonical basis for and appear in according to the following rules: All Jordan chains consisting of one vector (that is, one vector in length) appear in the first columns of . All vectors of one chain appear together in adjacent columns of . Each chain appears in in order of increasing rank (that is, the generalized eigenvector of rank 1 appears before the generalized eigenvector of rank 2 of the same chain, which appears before the generalized eigenvector of rank 3 of the same chain, etc.). One can show that where is a matrix in Jordan normal form. By premultiplying by , we obtain Note that when computing these matrices, equation () is the easiest of the two equations to verify, since it does not require inverting a matrix. This example illustrates a generalized modal matrix with four Jordan chains. Unfortunately, it is a little difficult to construct an interesting example of low order. The matrix has a single eigenvalue with algebraic multiplicity .

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Modal matrix

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