* Solves Ax = λx, where λ is the smallest nonzero eigenvalue of A, and x is the corresponding eigenvector. * * Input: , the complex positive definite sparse matrix whose eigendecomposition is being computed. * Returns: The smallest eigenvector of A. */
| 38 | * Returns: The smallest eigenvector of A. |
| 39 | */ |
| 40 | Vector<std::complex<double>> solveInversePowerMethod(const SparseMatrix<std::complex<double>>& A) { |
| 41 | |
| 42 | // TODO |
| 43 | return Vector<std::complex<double>>::Zero(1); |
| 44 | } |
nothing calls this directly
no outgoing calls
no test coverage detected