Parallel preconditioners for high order discretizations arising from full system modeling for brain microwave imaging

TL;DR

This paper presents a combined approach of high order finite element methods and parallel domain decomposition preconditioners to efficiently solve electromagnetic problems in brain microwave imaging, reducing computational costs for practical brain stroke diagnosis.

Contribution

It introduces a novel coupling of high order finite elements with parallel preconditioners specifically designed for brain microwave imaging applications.

Findings

Reduced computational time for electromagnetic simulations

Maintained high accuracy with high order finite element methods

Effective parallel preconditioning improves solver performance

Abstract

This paper combines the use of high order finite element methods with parallel preconditioners of domain decomposition type for solving electromagnetic problems arising from brain microwave imaging. The numerical algorithms involved in such complex imaging systems are computationally expensive since they require solving the direct problem of Maxwell's equations several times. Moreover, wave propagation problems in the high frequency regime are challenging because a sufficiently high number of unknowns is required to accurately represent the solution. In order to use these algorithms in practice for brain stroke diagnosis, running time should be reasonable. The method presented in this paper, coupling high order finite elements and parallel preconditioners, makes it possible to reduce the overall computational cost and simulation time while maintaining accuracy.