Deflated and restarted symmetric Lanczos methods for eigenvalues and linear equations with multiple right-hand sides

Abstract

A deflated restarted Lanczos algorithm is given for both solving symmetric linear equations and computing eigenvalues and eigenvectors. The restarting limits the storage so that finding eigenvectors is practical. Meanwhile, the deflating from the presence of the eigenvectors allows the linear equations to generally have good convergence in spite of the restarting. Some reorthogonalization is necessary to control roundoff error, and several approaches are discussed. The eigenvectors generated while solving the linear equations can be used to help solve systems with multiple right-hand sides. Experiments are given with large matrices from quantum chromodynamics that have many right-hand sides.

20 pages, 13 figures

Cited by in corpus (7)

• Virtual crystal description of III-V semiconductor alloys in the tight binding approach
• Improved Seed Methods for Symmetric Positive Definite Linear Equations with Multiple Right-hand Sides
• Multigrid deflation for Lattice QCD
• Extending the eigCG algorithm to nonsymmetric Lanczos for linear systems with multiple right-hand sides
• Disconnected Loop Subtraction Methods in Lattice QCD
• Numerical experiments using deflation with the HISQ action
• Untangling the valley structure of states for intravalley exchange anisotropy in lead chalcogenides quantum dots