Macports petsc7/29/2023 ![]() I think this might be related to the fact that B contains rows of zeros, although my understanding of linear algebra is somewhat basic. The main problem I have is the error: "zero pivot in LU factorisation!" when I use the default settings. However, if I substitute a smaller sized test version of my problem (6000圆000), I get a variety of errors depending on the command line arguments I supply. I got this to work fine using the matrices provided. Exercise 7 ( ) reads matricies A and B from a file and outputs the solutions. ![]() I have been trying out SLEPc using the examples provided as part of the tutorial. I want to move onto using PETSc with the SLEPc eigenvalue solvers. I have decided to see if I can achieve better performance through using the SLEPc library. As far as I know, these use LAPACK and ARPACK respectively to do the heavy lifting. However, I would be happy if I could get it to work for problems where all eigenvalues have real parts < 0 apart from the eigenvalue of interest.Īt the moment I have used the scipy linalg.eig and sparse.eigs functions. Ideally, I want to be able to find them even if they are internal (i.e when there are other eigenvalues with larger positive real part in the spectrum). The eigenvalues I am interested in are ones with the largest real part near 0 0i. The matrix will be at its largest about 48000 by 48000, and I want to find the eigenvalues. Thanks for the help! Details of the problem The rest of the below is details about the problem and things I have tried so far. ![]() My problem is essentially that when using the SLEPc generalised eigenvalue solver I get the error "zero pivot in LU factorisation". My matrix B is diagonal and positive semi-definite. I have a generalised matrix problem: $A x = \lambda B x$ from a spectral method on a linear stability analysis problem. ![]()
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