A Symmetry-Based Decomposition Approach to Eigenvalue Problems

In this paper, we propose a decomposition approach to differential eigenvalue problems with Abelian or non-Abelian symmetries. In the approach, we divide the original differential problem into eigenvalue subproblems which require less eigenpairs and can be solved independently. Our approach can be seamlessly incorporated with grid-based discretizations such as finite difference, finite element, or finite volume methods. We place the approach into a two-level parallelization setting, which saves the CPU time remarkably. For illustration and application, we implement our approach with finite elements and carry out electronic structure calculations of some symmetric cluster systems, in which we solve thousands of eigenpairs with millions of degrees of freedom and demonstrate the effectiveness of the approach.