Efficiently find all eigenvalues of a real symmetric tridiagonal matrix with a proven, adaptive approach.
This work presents an accelerated Sturm bisection method that enhances the classic technique by using interpolation and adaptive updates to converge faster.
The description explains how to count eigenvalues with sign observations, avoid costly rescalings, and incorporate adaptive parameters to handle well-isolated and clustered eigenvalues. It also discusses practical implementation issues, including handling determinants, rescaling, and tabulating results for specific hardware."synopsis" may belong to another edition of this title.
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