Algorithms for sparse, symmetric, definite quadratic lambda-matrix eigenproblems
Conference
·
OSTI ID:6404126
Methods are presented for computing eigenpairs of the quadratic lambda-matrix, M lambda/sup 2/ + C lambda + K, where M, C, and K are large and sparse, and have special symmetry-type properties. These properties are sufficient to insure that all the eigenvalues are real and that theory analogous to the standard symmetric eigenproblem exists. The methods employ some standard techniques such as partial tri-diagonalization via the Lanczos Method and subsequent eigenpair calculation, shift-and- invert strategy and subspace iteration. The methods also employ some new techniques such as Rayleigh-Ritz quadratic roots and the inertia of symmetric, definite, quadratic lambda-matrices.
- Research Organization:
- Union Carbide Corp., Oak Ridge, TN (USA). Computer Sciences Div.
- DOE Contract Number:
- W-7405-ENG-26
- OSTI ID:
- 6404126
- Report Number(s):
- CONF-810251-1
- Country of Publication:
- United States
- Language:
- English
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