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    <title>A priori convergence analysis for Krylov subspace eigensolvers</title>
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    <namePart>Bai, Zhaojun</namePart>
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  <abstract type="Summary">This thesis contributes to the convergence theory of Krylov subspace eigensolvers for discretized self-adjoint elliptic differential operators. A central topic refers to a priori convergence estimates with weak assumptions and concise bounds, which can reasonably predict the convergence rate, in particular for clustered eigenvalues. By avoiding the dependence on current approximate eigenvalues, such estimates significantly improve certain state-of-the-art estimates with regard to their sharpness and applicability.&lt;eng&gt;</abstract>
  <abstract type="Summary">Diese Arbeit widmet sich der Konvergenztheorie Krylovraum-basierter Lösungsverfahren für Eigenwertprobleme diskretisierter selbstadjungierter elliptischer Differentialoperatoren. Ein zentrales Thema bezieht sich auf A-priori-Konvergenzabschätzungen mit schwachen Voraussetzungen und prägnanten Schranken, welche die Konvergenzrate vernünftig vorhersagen können, insbesondere bei dicht aneinanderliegenden Eigenwerten. Durch Vermeidung der Abhängigkeit von aktuellen Näherungseigenwerten lassen sich einige State-of-the-art-Abschätzungen hinsichtlich Schärfe und Anwendbarkeit deutlich verbessern.&lt;ger&gt;</abstract>
  <note type="statement of responsibility">vorgelegt von Ming Zhou</note>
  <note>GutachterInnen: Klaus Neymeyr (Universität Rostock) ; Daniel Kressner (École polytechnique fédérale de Lausanne) ; Zhaojun Bai (University of California, Davis)</note>
  <note type="thesis">Habilitationsschrift Universität Rostock 2021</note>
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      <title>A priori convergence analysis for Krylov subspace eigensolvers</title>
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      <publisher>Rostock, 2020</publisher>
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      <form>4, 141 Seiten</form>
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    <identifier type="local">(DE-627)1767330685</identifier>
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      <namePart>Zhou, Ming, 1978 - </namePart>
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