It seems like such a special case of a sparse eigenvalue problem that a homemade C++ algorithm would be most efficient, but I'm not really sure. The tridiagonal matrix is square 100 x 100. It's symmetric and even better all the off-diagonal entries are equal.
Small example: [2, -1, 0, 0; -1, 7, -1, 0; 0, -1, 42, -1; 0, 0, -1, 3]
I want it to be efficient because this eigendecomp is part of a fitness calculation in a genetic algorithm.
Small example: [2, -1, 0, 0; -1, 7, -1, 0; 0, -1, 42, -1; 0, 0, -1, 3]
I want it to be efficient because this eigendecomp is part of a fitness calculation in a genetic algorithm.
