Community
cancel
Showing results for 
Search instead for 
Did you mean: 
Felix_W_
Beginner
23 Views

Eigenvalue precision

Hello everyone,

I am working on a project where it is important to distinguish between 0 eigenvalues and non zero eigenvalues. Using the MKL routine LAPACKE_zheev returns me a list of eigenvalues which include some very close to zero. I was wondering what the precision on those is or rather whether they can be reliably distinguished from a zero eigenvalue by the algorithm.

The only thing I have found on this topic so far is an article in the LAPACK specifications on Error bounds:

http://www.netlib.org/lapack/lug/node89.html

Does this article apply to the MKL routines aswell? I.e. is an eigenvalue larger than EERRBD guaranteed to belong to a non zero true eigenvalue? Is there a MKL routine that can be called to get the errorbound?

If anyone has information on this thanks in advance.

0 Kudos
1 Reply
Zhang_Z_Intel
Employee
23 Views

The precision on the returned eigenvalues from LAPACKE_zheev is "double precision".

The error bounds of the results depend on both machine epsilon and the input matrix. There is a code sample right on the netlib page that you referenced showing exactly how to compute the error bounds.