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<p>This paper introduces a multi-parameter preconditioner for the double saddle point problem arising from liquid crystal directors modeling. We conduct a detailed analysis of the eigenvalue distribution and corresponding eigenvectors for the preconditioned matrix. As the performance of the multi-parameter preconditioner is highly dependent on parameter selection, we also derive nearly optimal values for these parameters. Numerical experiments demonstrate the superiority of the proposed preconditioner over several existing ones.</p>

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A multi-parameter preconditioner for double saddle point problem arising from liquid crystal directors modeling

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • Yu-Lan Liu,
  • Bo Wu

摘要

This paper introduces a multi-parameter preconditioner for the double saddle point problem arising from liquid crystal directors modeling. We conduct a detailed analysis of the eigenvalue distribution and corresponding eigenvectors for the preconditioned matrix. As the performance of the multi-parameter preconditioner is highly dependent on parameter selection, we also derive nearly optimal values for these parameters. Numerical experiments demonstrate the superiority of the proposed preconditioner over several existing ones.