In this paper we use the conjugate gradient predictor corrector method (CGPCM) in the context of continuation methods. By exploiting symmetry in certain nonlinear eigenvalue problems, we can decompose the centered difference discretization matrices into small ones and reduce computational cost. We use the cyclic group of order two to divide the system into two smaller systems. We reduce the cost and the computational time by combining CGPCM with the idea of the exploiting symmetries. Theoretical and numerical results are presented. Conclusions are given.
|Number of pages||11|
|Journal||Chaos, Solitons and Fractals|
|Publication status||Published - Mar 2008|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Physics and Astronomy(all)
- Applied Mathematics