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arXiv 1107.2172math.SPcs.NAmath.APmath.NA
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关于边界上Neumann特征函数的估计,以及用于计算它们的“特解法”

Estimates on Neumann eigenfunctions at the boundary, and the "Method of Particular Solutions" for computing them

Dartmouth College(达特茅斯学院);Australian National University(澳大利亚国立大学)

A. H. Barnett, Andrew Hassell

AI总结:

本文针对Laplacian算子的Dirichlet或Neumann边界条件特征值问题,利用“特解法”构造近似特征函数,并通过边界数据给出特征值误差的尖锐包含界,尤其对Neumann情形需要更复杂的技术。

摘要:

我们考虑用“特解法”数值计算光滑有界区域Ω⊂R^n上Laplacian算子Δ在Dirichlet或Neumann边界条件下的特征值和特征函数。该方法构造近似特征值E和近似特征函数u,使得在Ω内满足Δu=Eu,但不满足精确边界条件。包含界则是根据u的边界数据估计E与Laplacian实际谱的距离。我们证明了由真实特征函数的边界值构造的L^2(∂Ω)上某些算子的算子范数估计,并表明这些估计导致尖锐的包含界,即它们关于E的标度是最优的。这对于大特征值的精确计算是有利的。Dirichlet情形可以用初等论证处理,并已出现在SIAM J. Num. Anal. 49 (2011), 1046-1063中,而Neumann情形似乎需要更复杂的技术。我们包含Neumann情形的初步数值例子。

英文摘要:

We consider the "Method of particular solutions" for numerically computing eigenvalues and eigenfunctions of the Laplacian $Δ$ on a smooth, bounded domain Omega in RR^n with either Dirichlet or Neumann boundary conditions. This method constructs approximate eigenvalues E, and approximate eigenfunctions u that satisfy $Δu=Eu$ in Omega, but not the exact boundary condition. An inclusion bound is then an estimate on the distance of E from the actual spectrum of the Laplacian, in terms of (boundary data of) u. We prove operator norm estimates on certain operators on $L^2(\partial Ω)$ constructed from the boundary values of the true eigenfunctions, and show that these estimates lead to sharp inclusion bounds in the sense that their scaling with $E$ is optimal. This is advantageous for the accurate computation of large eigenvalues. The Dirichlet case can be treated using elementary arguments and has appeared in SIAM J. Num. Anal. 49 (2011), 1046-1063, while the Neumann case seems to require much more sophisticated technology. We include preliminary numerical examples for the Neumann case.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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