Tao and the other researchers discovered an easier method to calculate eigenvectors using eigenvalues. Finding eigenvalues was already possible because of the use of a matrix associated with ...

and for finding eigenvectors and eigenvalues of the combinatorial Laplacian. The algorithms provide an exponential speed-up over the best currently known classical algorithms for topological data ...

BR><BR>This problem in particular was difficult:<BR><BR>A matrix, A, has eigenvalues 1 and 2. The eigenvector corresponding ... who knows their shit could find the damn matrix for me so I can ...

Seems like GE on a 2x2 matrix should be pretty darn fast.... especially if you use scalar * vector type operations.

Positive eigenvalues are associated with clustering of interconnected ... even with more efficient methods for finding eigenvectors (e.g. the Lanczos Algorithm (Parlett, 1979)). The network is very ...

Quantum approaches to finding eigenvalues have previously ... processing unit (CPU), which variationally computes the eigenvalues and eigenvectors of . By using a variational algorithm, this ...