Convergence analysis of an optimization algorithm for computing the largest eigenvalue of a symmetric matrix

A new optimization algorithm for computing the largest eigenvalue of a real symmetric matrix is considered. The algorithm is based on a sequence of plane rotations increasing the sum of the matrix entries. It is proved that the algorithm converges linearly and it is shown that it can be regarded as a relaxation method for the Rayleigh quotient.