使高特征值最大化的量子树是不平衡的

Jonathan Rohleder
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引用次数: 1

摘要

研究了在给定平均边长的树类中,度量树图上拉普拉斯算子的所有特征值最大化的等周问题。结果证明,在重新缩放之前,k k个正特征值的唯一最大化器是具有3条边长度为2 k−1 2 k - 1 1 1和1 1的星图。这补充了先前已知的结果,即第一个非零特征值被所有等边星图最大化,并表明等边问题的高特征值优化器在其形状上可能不太平衡-这一观察从欧几里得域上拉普拉斯算子的高特征值优化的数值结果中已知。
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Quantum trees which maximize higher eigenvalues are unbalanced
The isoperimetric problem of maximizing all eigenvalues of the Laplacian on a metric tree graph within the class of trees of a given average edge length is studied. It turns out that, up to rescaling, the unique maximizer of the k k -th positive eigenvalue is the star graph with three edges of lengths 2 k − 1 2 k - 1 , 1 1 and 1 1 . This complements the previously known result that the first nonzero eigenvalue is maximized by all equilateral star graphs and indicates that optimizers of isoperimetric problems for higher eigenvalues may be less balanced in their shape—an observation which is known from numerical results on the optimization of higher eigenvalues of Laplacians on Euclidean domains.
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