Nonlinear Jacobi-Davidson algorithm with deflation
Newton-based methods are well-established techniques for solving nonlinear eigenvalue problems. If a larger portion of the spectrum is sought, however, their tendency to reconverge to previously determined eigenpairs is a hindrance. To overcome this limitation, a deflation strategy for nonlinear eigenvalue problems, based on the concept of minimal invariant pairs, has been proposed and analyzed in .
The software at hand implements the nonlinear Jacobi-Davidson algorithm with deflation presented in . The software has been developed and tested under Matlab 7.13 (R2011b), 64-bit.
- C. Effenberger. Robust successive computation of eigenpairs for nonlinear eigenvalue problems. Technical report, July 2012.
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This software is research code and not intended for production use.