 Jacobi eigenvalue algorithm

The Jacobi eigenvalue algorithm is an iterative method used to find the eigenvalues and eigenvectors of a symmetric matrix. It is particularly useful for small to medium-sized matrices and is based on the idea of diagonalizing the matrix through a series of similarity transformations. ### Key Features of the Jacobi Eigenvalue Algorithm: 1. **Symmetric Matrices**: The algorithm is designed specifically for symmetric matrices, which have real eigenvalues and orthogonal eigenvectors.