On Adaptive Choice of Shifts in Rational Krylov Subspace Reduction of Evolutionary Problems

We compute $u(t)=\exp(-tA)\varphi$ using rational Krylov subspace reduction for $0\leq t<\infty$, where $u(t),\varphi\in\mathbf{R}^N$ and $0<A=A^*\in\mathbf{R}^{N\times N}$. A priori optimization of the rational Krylov subspaces for this problem was considered in [V. Druskin, L. Knizhnerman, a...

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Bibliographic Details
Main Authors: Druskin, Vladimir (Author), Lieberman, Chad E. (Contributor), Zaslavsky, Mikhail (Author)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Society of Industrial and Applied Mathematics (SIAM), 2011-01-14T18:40:10Z.
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Online Access:Get fulltext
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100 1 0 |a Druskin, Vladimir  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics  |e contributor 
100 1 0 |a Lieberman, Chad E.  |e contributor 
100 1 0 |a Lieberman, Chad E.  |e contributor 
700 1 0 |a Lieberman, Chad E.  |e author 
700 1 0 |a Zaslavsky, Mikhail  |e author 
245 0 0 |a On Adaptive Choice of Shifts in Rational Krylov Subspace Reduction of Evolutionary Problems 
260 |b Society of Industrial and Applied Mathematics (SIAM),   |c 2011-01-14T18:40:10Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/60578 
520 |a We compute $u(t)=\exp(-tA)\varphi$ using rational Krylov subspace reduction for $0\leq t<\infty$, where $u(t),\varphi\in\mathbf{R}^N$ and $0<A=A^*\in\mathbf{R}^{N\times N}$. A priori optimization of the rational Krylov subspaces for this problem was considered in [V. Druskin, L. Knizhnerman, and M. Zaslavsky, SIAM J. Sci. Comput., 31 (2009), pp. 3760-3780]. There was suggested an algorithm generating sequences of equidistributed shifts, which are asymptotically optimal for the cases with uniform spectral distributions. Here we develop a recursive greedy algorithm for choice of shifts taking into account nonuniformity of the spectrum. The algorithm is based on an explicit formula for the residual in the frequency domain allowing adaptive shift optimization at negligible cost. The effectiveness of the developed approach is demonstrated in an example of the three-dimensional diffusion problem for Maxwell's equation arising in geophysical exploration. We compare our approach with the one using the above-mentioned equidistributed sequences of shifts. Numerical examples show that our algorithm is able to adapt to the spectral density of operator $A$. For examples with near-uniform spectral distributions, both algorithms show the same convergence rates, but the new algorithm produces superior convergence for cases with nonuniform spectra. 
546 |a en_US 
655 7 |a Article 
773 |t SIAM Journal on Scientific Computing