36 research outputs found
Fast non-Hermitian Toeplitz eigenvalue computations, joining matrix-less algorithms and FDE approximation matrices
The present work is devoted to the eigenvalue asymptotic expansion of the
Toeplitz matrix whose generating function is complex valued and
has a power singularity at one point. As a consequence, is
non-Hermitian and we know that the eigenvalue computation is a non-trivial task
in the non-Hermitian setting for large sizes. We follow the work of Bogoya,
B\"ottcher, Grudsky, and Maximenko and deduce a complete asymptotic expansion
for the eigenvalues. After that, we apply matrix-less algorithms, in the spirit
of the work by Ekstr\"om, Furci, Garoni, Serra-Capizzano et al, for computing
those eigenvalues. Since the inner and extreme eigenvalues have different
asymptotic behaviors, we worked on them independently, and combined the results
to produce a high precision global numerical and matrix-less algorithm.
The numerical results are very precise and the computational cost of the
proposed algorithms is independent of the size of the considered matrices for
each eigenvalue, which implies a linear cost when all the spectrum is computed.
From the viewpoint of real world applications, we emphasize that the matrix
class under consideration includes the matrices stemming from the numerical
approximation of fractional diffusion equations. In the final conclusion
section a concise discussion on the matter and few open problems are presented.Comment: 21 page
Numerical methods for large-scale Lyapunov equations with symmetric banded data
The numerical solution of large-scale Lyapunov matrix equations with
symmetric banded data has so far received little attention in the rich
literature on Lyapunov equations. We aim to contribute to this open problem by
introducing two efficient solution methods, which respectively address the
cases of well conditioned and ill conditioned coefficient matrices. The
proposed approaches conveniently exploit the possibly hidden structure of the
solution matrix so as to deliver memory and computation saving approximate
solutions. Numerical experiments are reported to illustrate the potential of
the described methods