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A residual a posteriori error estimator for the eigenvalue problem for the Laplace-Beltrami operatorPester, Cornelia 06 September 2006 (has links)
The Laplace-Beltrami operator corresponds to the Laplace operator on curved surfaces. In this paper, we consider an eigenvalue problem for the Laplace-Beltrami operator on subdomains of the unit sphere in $\R^3$. We develop a residual a posteriori error estimator for the eigenpairs and derive a reliable estimate for the eigenvalues. A global parametrization of the spherical domains and a carefully chosen finite element discretization allows us to use an approach similar to the one for the two-dimensional case. In order to assure results in the quality of those for plane domains, weighted norms and an adapted Clément-type interpolation operator have to be introduced.
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Structured Krylov Subspace Methods for Eigenproblems with Spectral SymmetriesBenner, Peter 12 June 2010 (has links)
We consider large and sparse eigenproblems where the spectrum exhibits
special symmetries. Here we focus on Hamiltonian symmetry, that is,
the spectrum is symmetric with respect to the real and imaginary
axes. After briefly discussing quadratic eigenproblems with
Hamiltonian spectra we review structured Krylov subspace methods to
aprroximate parts of the spectrum of Hamiltonian operators. We will
discuss the optimization of the free parameters in the resulting
symplectic Lanczos process in order to minimize the conditioning of
the (non-orthonormal) Lanczos basis. The effects of our findings are
demonstrated for several numerical examples.
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Two-sided Eigenvalue Algorithms for Modal ApproximationKürschner, Patrick 22 July 2010 (has links)
Large scale linear time invariant (LTI) systems arise in many physical and technical fields. An approximation, e.g. with model order reduction techniques, of this large systems is crucial for a cost efficient simulation.
In this thesis we focus on a model order reduction method based on modal approximation, where the LTI system is projected onto the left and right eigenspaces corresponding to the dominant poles of the system. These dominant poles are related to the most dominant parts of the residue expansion of the transfer function and usually form a small subset of the eigenvalues of the system matrices. The computation of this dominant poles can be a formidable task, since they can lie anywhere inside the spectrum and the corresponding left eigenvectors have to be approximated as well.
We investigate the subspace accelerated dominant pole algorithm and the two-sided and alternating Jacobi-Davidson method for this modal truncation approach. These methods can be seen as subspace accelerated versions of certain Rayleigh quotient iterations. Several strategies that admit an efficient computation of several dominant poles of single-input single-output LTI systems are examined.
Since dominant poles can lie in the interior of the spectrum, we discuss also harmonic subspace extraction approaches which might improve the convergence of the methods.
Extentions of the modal approximation approach and the applied eigenvalue solvers to multi-input multi-output are also examined.
The discussed eigenvalue algorithms and the model order reduction approach will be tested for several practically relevant LTI systems.
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Canonical forms for Hamiltonian and symplectic matrices and pencilsMehrmann, Volker, Xu, Hongguo 09 September 2005 (has links) (PDF)
We study canonical forms for Hamiltonian and
symplectic matrices or pencils under equivalence
transformations which keep the class invariant.
In contrast to other canonical forms our forms
are as close as possible to a triangular structure
in the same class. We give necessary and
sufficient conditions for the existence of
Hamiltonian and symplectic triangular Jordan,
Kronecker and Schur forms. The presented results
generalize results of Lin and Ho [17] and simplify
the proofs presented there.
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A posteriori error estimation for non-linear eigenvalue problems for differential operators of second order with focus on 3D vertex singularitiesPester, Cornelia 07 May 2006 (has links) (PDF)
This thesis is concerned with the finite element
analysis and the a posteriori error estimation for
eigenvalue problems for general operator pencils on
two-dimensional manifolds.
A specific application of the presented theory is the
computation of corner singularities.
Engineers use the knowledge of the so-called singularity
exponents to predict the onset and the propagation of
cracks.
All results of this thesis are explained for two model
problems, the Laplace and the linear elasticity problem,
and verified by numerous numerical results.
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Implementierung eines Algorithmus zur Partitionierung von GraphenRiediger, Steffen 05 July 2007 (has links) (PDF)
Partitionierung von Graphen ist im Allgemeinen sehr schwierig. Es stehen
derzeit keine Algorithmen zur Verfügung, die ein allgemeines Partitionierungsproblem
effizient lösen. Aus diesem Grund werden heuristische
Ansätze verfolgt.
Zur Analyse dieser Heuristiken ist man derzeit gezwungen zufällige Graphen
zu Verwenden. Daten realer Graphen sind derzeit entweder nur
sehr schwer zu erheben (z.B. Internetgraph), oder aus rechtlichen bzw.
wirtschaftlichen Gründen nicht zugänglich (z.B. soziale Netzwerke). Die
untersuchten Heuristiken liefern teilweise nur unter bestimmten Voraussetzungen
Ergebnisse. Einige arbeiten lediglich auf einer eingeschränkten
Menge von Graphen, andere benötigen zum Erkennen einer Partition
einen mit der Knotenzahl steigenden Durchschnittsgrad der Knoten, z.B.
[DHM04].
Der im Zuge dieser Arbeit erstmals implementierte Algorithmus aus
[CGL07a] benötigt lediglich einen konstanten Durchschnittsgrad der
Knoten um eine Partition des Graphen, wenn diese existiert, zu erkennen.
Insbesondere muss dieser Durchschnittsgrad nicht mit der Knotenzahl
steigen.
Nach der Implementierung erfolgten Tests des Algorithmus an zufälligen
Graphen. Diese Graphen entsprachen dem Gnp-Modell mit eingepflanzter Partition. Die untersuchten Clusterprobleme waren dabei große
Schnitte, kleine Schnitte und unabhängige Mengen. Der von der Art des
Clusterproblems abhängige Durchschnittsgrad wurde während der Tests
bestimmt.
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Canonical forms for Hamiltonian and symplectic matrices and pencilsMehrmann, Volker, Xu, Hongguo 09 September 2005 (has links)
We study canonical forms for Hamiltonian and
symplectic matrices or pencils under equivalence
transformations which keep the class invariant.
In contrast to other canonical forms our forms
are as close as possible to a triangular structure
in the same class. We give necessary and
sufficient conditions for the existence of
Hamiltonian and symplectic triangular Jordan,
Kronecker and Schur forms. The presented results
generalize results of Lin and Ho [17] and simplify
the proofs presented there.
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New results on the degree of ill-posedness for integration operators with weightsHofmann, Bernd, von Wolfersdorf, Lothar 16 May 2008 (has links)
We extend our results on the degree of ill-posedness for linear integration opera-
tors A with weights mapping in the Hilbert space L^2(0,1), which were published in
the journal 'Inverse Problems' in 2005 ([5]). Now we can prove that the degree one
also holds for a family of exponential weight functions. In this context, we empha-
size that for integration operators with outer weights the use of the operator AA^*
is more appropriate for the analysis of eigenvalue problems and the corresponding
asymptotics of singular values than the former use of A^*A.
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A rational SHIRA method for the Hamiltonian eigenvalue problemBenner, Peter, Effenberger, Cedric 07 January 2009 (has links)
The SHIRA method of Mehrmann and Watkins belongs among the structure preserving Krylov subspace methods for solving skew-Hamiltonian eigenvalue problems. It can also be applied to Hamiltonian eigenproblems by considering a suitable transformation. Structure induced shift-and-invert techniques are employed to steer the algorithm towards the interesting region of the spectrum. However, the shift cannot be altered in the middle of the computation without discarding the information that has been accumulated so far. This paper shows how SHIRA can be combined with ideas from Ruhe's Rational Krylov algorithm to yield a method that permits an adjustment of shift after every step of the computation, adding greatly to the flexibility of the algorithm. We call this new method rational SHIRA. A numerical example is presented to demonstrate its efficiency.
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Adaptive finite element computation of eigenvaluesGallistl, Dietmar 17 July 2014 (has links)
Gegenstand dieser Arbeit ist die numerische Approximation von Eigenwerten elliptischer Differentialoperatoren vermittels der adaptiven finite-Elemente-Methode (AFEM). Durch lokale Netzverfeinerung können derartige Verfahren den Rechenaufwand im Vergleich zu uniformer Verfeinerung deutlich reduzieren und sind daher von großer praktischer Bedeutung. Diese Arbeit behandelt adaptive Algorithmen für Finite-Elemente-Methoden (FEMs) für drei selbstadjungierte Modellprobleme: den Laplaceoperator, das Stokes-System und den biharmonischen Operator. In praktischen Anwendungen führen Störungen der Koeffizienten oder der Geometrie auf Eigenwert-Haufen (Cluster). Dies macht simultanes Markieren im adaptiven Algorithmus notwendig. In dieser Arbeit werden optimale Konvergenzraten für einen praktischen adaptiven Algorithmus für Eigenwert-Cluster des Laplaceoperators (konforme und nichtkonforme P1-FEM), des Stokes-Systems (nichtkonforme P1-FEM) und des biharmonischen Operators (Morley-FEM) bewiesen. Fehlerabschätzungen in der L2-Norm und Bestapproximations-Resultate für diese Nichtstandard-Methoden erfordern neue Techniken, die in dieser Arbeit entwickelt werden. Dadurch wird der Beweis optimaler Konvergenzraten ermöglicht. Die Optimalität bezüglich einer nichtlinearen Approximationsklasse betrachtet die Approximation des invarianten Unterraums, der von den Eigenfunktionen im Cluster aufgespannt wird. Der Fehler der Eigenwerte kann dazu in Bezug gesetzt werden: Die hierfür notwendigen Eigenwert-Fehlerabschätzungen für nichtkonforme Finite-Elemente-Methoden werden in dieser Arbeit gezeigt. Die numerischen Tests für die betrachteten Modellprobleme legen nahe, dass der vorgeschlagene Algorithmus, der bezüglich aller Eigenfunktionen im Cluster markiert, einem Markieren, das auf den Vielfachheiten der Eigenwerte beruht, überlegen ist. So kann der neue Algorithmus selbst im Fall, dass alle Eigenwerte im Cluster einfach sind, den vorasymptotischen Bereich signifikant verringern. / The numerical approximation of the eigenvalues of elliptic differential operators with the adaptive finite element method (AFEM) is of high practical interest because the local mesh-refinement leads to reduced computational costs compared to uniform refinement. This thesis studies adaptive algorithms for finite element methods (FEMs) for three model problems, namely the eigenvalues of the Laplacian, the Stokes system and the biharmonic operator. In practice, little perturbations in coefficients or in the geometry immediately lead to eigenvalue clusters which requires the simultaneous marking in adaptive finite element methods. This thesis proves optimality of a practical adaptive algorithm for eigenvalue clusters for the conforming and nonconforming P1 FEM for the eigenvalues of the Laplacian, the nonconforming P1 FEM for the eigenvalues of the Stokes system and the Morley FEM for the eigenvalues of the biharmonic operator. New techniques from the medius analysis enable the proof of L2 error estimates and best-approximation properties for these nonstandard finite element methods and thereby lead to the proof of optimality. The optimality in terms of the concept of nonlinear approximation classes is concerned with the approximation of invariant subspaces spanned by eigenfunctions of an eigenvalue cluster. In order to obtain eigenvalue error estimates, this thesis presents new estimates for nonconforming finite elements which relate the error of the eigenvalue approximation to the error of the approximation of the invariant subspace. Numerical experiments for the aforementioned model problems suggest that the proposed practical algorithm that uses marking with respect to all eigenfunctions within the cluster is superior to marking that is based on the multiplicity of the eigenvalues: Even if all exact eigenvalues in the cluster are simple, the simultaneous approximation can reduce the pre-asymptotic range significantly.
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