[petsc-users] eigenvalue problem involving inverse of a matrix
Pierre Jolivet
pierre.jolivet at lip6.fr
Mon Aug 14 03:45:27 CDT 2023
> On 14 Aug 2023, at 10:39 AM, maitri ksh <maitri.ksh at gmail.com> wrote:
>
>
> Hi,
> I need to solve an eigenvalue problem Ax=lmbda*x, where A=(B^-H)*Q*B^-1 is a hermitian matrix, 'B^-H' refers to the hermitian of the inverse of the matrix B. Theoretically it would take around 1.8TB to explicitly compute the matrix B^-1 . A feasible way to solve this eigenvalue problem would be to use the LU factors of the B matrix instead. So the problem looks something like this:
> (((LU)^-H)*Q*(LU)^-1)*x = lmbda*x
> For a guess value of the (normalised) eigen-vector 'x',
> 1) one would require to solve two linear equations to get 'Ax',
> (LU)*y=x, solve for 'y',
> ((LU)^H)*z=Q*y, solve for 'z'
> then one can follow the conventional power-iteration procedure
> 2) update eigenvector: x= z/||z||
> 3) get eigenvalue using the Rayleigh quotient
> 4) go to step-1 and loop through with a conditional break.
>
> Is there any example in petsc that does not require explicit declaration of the matrix 'A' (Ax=lmbda*x) and instead takes a vector 'Ax' as input for an iterative algorithm (like the one above). I looked into some of the examples of eigenvalue problems ( it's highly possible that I might have overlooked, I am new to petsc) but I couldn't find a way to circumvent the explicit declaration of matrix A.
You could use SLEPc with a MatShell, that’s the very purpose of this MatType.
Thanks,
Pierre
> Maitri
>
>
>
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