Abstract
We apply truncated RQ-iteration (TRQ) and the Jacobi-Davidson (JD) method to perform vibrational (eigenvalue) analysis for large-scale molecular systems. Both algorithms employ a preconditioned iterative solver to construct a low-dimensional subspace that contains desired vibrational modes. We discuss several strategies for speeding up the eigenvalue calculation. In particular, we illustrate how to construct effective preconditioners and analyze the quality of these preconditioners. We show that convergence can be improved by choosing appropriate shifts and deflating the translational and rotational modes. Numerical examples are provided to demonstrate the efficiency of our computation.
Original language | English |
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Pages (from-to) | 563-582 |
Number of pages | 20 |
Journal | SIAM Journal on Scientific Computing |
Volume | 23 |
Issue number | 2 |
DOIs | |
State | Published - 2002 |
Externally published | Yes |
Keywords
- Eigenvalue computation
- Normal coordinate analysis
- Preconditioner