Adaptive BDDC algorithms for the system arising from plane wave discretization of Helmholtz equations
This work provides a scalable preconditioning technique for high-frequency Helmholtz problems discretized by plane wave methods, addressing a known bottleneck in large-scale coarse problems.
The paper develops adaptive BDDC preconditioners for plane wave discretizations of Helmholtz equations, proving a condition number bound dependent on a user-defined tolerance and the maximum number of interfaces per subdomain. Numerical results confirm the efficiency of the algorithms.
Balancing domain decomposition by constraints (BDDC) algorithms with adaptive primal constraints are developed in a concise variational framework for the weighted plane wave least-squares (PWLS) discritization of Helmholtz equations with high and various wave numbers. The unknowns to be solved in this preconditioned system are defined on elements rather than vertices or edges, which are different from the well-known discritizations such as the classical finite element method. Through choosing suitable "interface" and appropriate primal constraints with complex coefficients and introducing some local techniques, we developed a two-level adaptive BDDC algorithm for the PWLS discretization, and the condition number of the preconditioned system is proved to be bounded above by a user-defined tolerance and a constant which is only dependent on the maximum number of interfaces per subdomain. A multilevel algorithm is also attempted to resolve the bottleneck in large scale coarse problem. Numerical results are carried out to confirm the theoretical results and illustrate the efficiency of the proposed algorithms.