3 papers
math.NA2024
A low-memory Lanczos method with rational Krylov compression for matrix functions
Angelo A. Casulli, Igor Simunec
In this work we introduce a memory-efficient method for computing the action of a Hermitian matrix function on a vector. Our method consists of a rational Lanczos algorithm combine…
math.NA2024
Computing Functions of Symmetric Hierarchically Semiseparable Matrices
Angelo A. Casulli, Daniel Kressner, Leonardo Robol
The aim of this work is to develop a fast algorithm for approximating the matrix function of a square matrix that is symmetric and has hierarchically semiseparable (HSS)…
math.NA2022
Low-rank tensor structure preservation in fractional operators by means of exponential sums
Angelo A. Casulli, Leonardo Robol
The use of fractional differential equations is a key tool in modeling non-local phenomena. Often, an efficient scheme for solving a linear system involving the discretization of a…