The parametrized $SR$ algorithm for Hamiltonian matrices
Electronic transactions on numerical analysis, Tome 26 (2007), pp. 121-145.

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Summary: The heart of the implicitly restarted symplectic Lanczos method for Hamiltonian matrices consists of the algorithm, a structure-preserving algorithm for computing the spectrum of Hamiltonian matrices. The $$###$$§$$###$$ symplectic Lanczos method projects the large, sparse Hamiltonian matrix onto a small, dense $\ddot \copyright \ddot \copyright \ddot $ Hamiltonian -Hessenberg matrix , . This Hamiltonian matrix is uniquely determined by $\ddot !\copyright \ddot "\ddot $ # parameters. Using these # parameters, one step of the algorithm can be carried out in %' %' ###(###$$ )10243 arithmetic operations (compared to arithmetic operations when working on the actual Hamiltonian matrix).$$
Classification : 65F15
Keywords: Hamiltonian matrix, eigenvalue problem, algorithm $$###(###$$
@article{ETNA_2007__26__a19,
     author = {Fa{\ss}bender, H.},
     title = {The parametrized $SR$ algorithm for {Hamiltonian} matrices},
     journal = {Electronic transactions on numerical analysis},
     pages = {121--145},
     publisher = {mathdoc},
     volume = {26},
     year = {2007},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ETNA_2007__26__a19/}
}
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Faßbender, H. The parametrized $SR$ algorithm for Hamiltonian matrices. Electronic transactions on numerical analysis, Tome 26 (2007), pp. 121-145. http://geodesic.mathdoc.fr/item/ETNA_2007__26__a19/