The QR algorithm is a numerical method used to compute the eigenvalues and eigenvectors of a matrix by decomposing it into an orthogonal matrix Q and an upper triangular matrix R. This algorithm is significant because it allows for efficient and stable computations in linear algebra, connecting closely with concepts like Schur decomposition and numerical stability.
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