Structured Backward Error Analysis with Preserving Sparsity for Three-by-Three Block Saddle Point Problems

Backward error (BE) analysis emerges as a powerful tool for assessing the backward stability and strong backward stability of iterative algorithms. In this paper, we explore structured BEs for a class of three-by-three block saddle point problems (TBSPPs), aiming to assess the strong backward stability of iterative algorithms devised to find their solution. Our investigations preserve the inherent matrix structure and sparsity pattern in the corresponding perturbation matrices and derive explicit formulae for the structure BEs. Moreover, we provide formulae for the structure-preserving minimal perturbation matrices for which the structured BE is attained. Furthermore, using the obtained structured BEs, we propose three new termination criteria for the iterative algorithms to solve the TBSPP. Numerical experiments are performed to test the strong backward stability of various iterative algorithms, as well as the reliability and effectiveness of the proposed termination criteria.