I have come across a curious issue when attempting to find the nullspace of a sparse structurally symmetric matrix A with PARDISO, i.e. solving the problem A x = b where b is the zero vector. When I set the RHS (the vector b) to be identically zero, I get only the trivial solution (x = the zero vector) with a residual of nan. However, when I make b arbitrarily small (e.g. all elements = 1e-16) I obtain a solution, but the residual is exceedingly high (on the order of 1, while the elements in the solution vector are on the order of 10^4).
Am I misusing PARDISO or are we intended to set b to some arbitrarily small value rather than zero when we wish to find the nullspace? Is there sample code that where the goal is to compute the nullspace specifically? I didn't encounter such problems when b was a vector of ones. If PARDISO cannot compute the nullspace, is there another MKL function which allows for computation of the nullspace of large, real-valued, indefinite, structurally symmetric sparse matrices?
Thank you.
