Eigenvalue problems are omnipresent in physics. Important examples are the time independent Schrödinger equation in a finite orthogonal basis or the harmonic motion of a molecule around its equilibrium structure. Most important are ordinary eigenvalue problems, which involve the solution of a homogeneous system of linear equations with a Hermitian (or symmetric, if real) matrix.
Matrices of small dimension can be diagonalized directly by determining the roots of the characteristic polynomial and solving a homogeneous system of linear equations. The Jacobi method uses successive rotations to diagonalize a matrix with a unitary transformation. A very popular method for not too large symmetric matrices reduces the matrix to tridiagonal form which can be diagonalized efficiently with the QL algorithm. Certain tridiagonal matrices can be diagonalized analytically. Special algorithms are available for matrices of very large dimension, for instance the famous Lanczos method.
KeywordsCharacteristic Polynomial Unitary Transformation Homogeneous System Eigenvalue Equation Orthogonal Transformation