The Eigenvalue Shift Technique and Its Eigenstructure Analysis of a Matrix
For researchers in matrix computations, this work addresses a known challenge of shifting multiple eigenvalues, but the contribution appears incremental.
The paper proposes a new method for shifting eigenvalues with multiple multiplicities in a matrix, extending Brauer's technique, and analyzes the resulting Jordan canonical form.
The eigenvalue shift technique is the most well-known and fundamental tool for matrix computations. Applications include the search of eigeninformation, the acceleration of numerical algorithms, the study of Google's PageRank. The shift strategy arises from the concept investigated by Brauer [1] for changing the value of an eigenvalue of a matrix to the desired one, while keeping the remaining eigenvalues and the original eigenvectors unchanged. The idea of shifting distinct eigenvalues can easily be generalized by Brauer's idea. However, shifting an eigenvalue with multiple multiplicities is a challenge issue and worthy of our investigation. In this work, we propose a new way for updating an eigenvalue with multiple multiplicities and thoroughly analyze its corresponding Jordan canonical form after the update procedure.