4 papers
A quasi-orthogonal method based on the inverse operator for Schr{ö}dinger eigenvalue problems
Shengyue Wang, Aihui Zhou
Computing many eigenpairs of the Schr{ö}dinger operator presents a computational bottleneck in large-scale quantum simulations due to the global communication overhead of explicit…
An Iterative Method with Asymptotic Orthogonality for Simultaneous Eigenpair Computation
Shengyue Wang, Aihui Zhou
The simultaneous computation of a cluster of eigenpairs with mutually orthogonal eigenvectors is a basic task in scientific computing. We develop a predictor--corrector discretizat…
An orthogonality-preserving approach for eigenvalue problems
Tianyang Chu, Xiaoying Dai, Shengyue Wang +1
Solving large-scale eigenvalue problems poses a significant challenge due to the computational complexity and limitations on the parallel scalability of the orthogonalization opera…
A quasi-Grassmannian gradient flow model for eigenvalue problems
Shengyue Wang, Aihui Zhou
We propose a quasi-Grassmannian gradient flow model for eigenvalue problems of linear operators, aiming to efficiently address many eigenpairs. Our model inherently ensures asympto…