RT Journal Article
T1 Generalized convolution quadrature for non smooth sectorial problems
A1 Guo, J.
A1 López-Fernández, María
K1 Convoluciones (Matemáticas)
AB We consider the application of the generalized convolution quadrature (gCQ) to approximate the solution of an important class of sectorial problems. The gCQ is a generalization of Lubich’s convolution quadrature (CQ) that allows for variable steps. The available stability and convergence theory for the gCQ requires non realistic regularity assumptions on the data, which do not hold in many applications of interest, such as the approximation of subdiffusion equations. It is well known that for non smooth enough data the original CQ, with uniform steps, presents an order reduction close to the singularity. We generalize the analysis of the gCQ to data satisfying realistic regularity assumptions and provide sufficient conditions for stability and convergence on arbitrary sequences of time points. We consider the particular case of graded meshes and show how to choose them optimally, according to the behaviour of the data. An important advantage of the gCQ method is that it allows for a fast and memory reduced implementation. We describe how the fast and oblivious gCQ can be implemented and illustrate our theoretical results with several numerical experiments.
PB Springer
YR 2024
FD 2024
LK https://hdl.handle.net/10630/35617
UL https://hdl.handle.net/10630/35617
LA eng
NO Guo, J., Lopez-Fernandez, M. Generalized convolution quadrature for non smooth sectorial problems. Calcolo 62, 5 (2025). https://doi.org/10.1007/s10092-024-00629-6
NO Funding for open access publishing: Universidad Málaga/CBUA.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026