The divide-and-conquer eigenvalue algorithm is a numerical method used to compute the eigenvalues (and often the corresponding eigenvectors) of a symmetric (or Hermitian in the complex case) matrix. This algorithm is especially effective for large matrices, leveraging the structure of the problem to reduce computational complexity and improve efficiency.
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