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 Post subject: RMatrixEVD
PostPosted: Wed May 03, 2017 3:43 pm 
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Does this procedure work with a degenerate spectrum?


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 Post subject: Re: RMatrixEVD
PostPosted: Thu May 04, 2017 10:10 am 
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It may be problematic. Nonsymmetric EVD subroutines often have convergence problems on such matrices.

Do you have any specific matrix to try? Can you describe your task in more details?


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 Post subject: Re: RMatrixEVD
PostPosted: Thu May 04, 2017 10:58 am 
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While I use only a symmetric matrix. I use RMatrixEVD for the sake of versatility. RMatrixEVD works well with degenerate symmetric matrices. I want to get official confirmation.

My matrix is a real matrix of Hermitian operators.


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 Post subject: Re: RMatrixEVD
PostPosted: Thu May 04, 2017 11:59 am 
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> "degenerate symmetric matrices".

For the purposes of EVD, symmetric matrices are perfect. They have orthogonal eigenvectors, and it eliminates at least one possible failure point for nonsymmetric EVD - inverse iteration part which finds eigenvectors. So, RMatrixEVD performs very well on these matrices.

However, I recommend you to use specialized symmetric EVD functions because they perform much, much faster. And they are more precise at handling clustered eigenvalues (multiple eigenvectors having same eigenvalue).


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 Post subject: Re: RMatrixEVD
PostPosted: Thu May 04, 2017 12:09 pm 
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Good. Thank you.


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