对称张量
数学
张量(固有定义)
笛卡尔张量
Hilbert空间的张量积
张量收缩
特征向量
张量密度
对称矩阵
矩阵的特征分解
张量不变量
幂迭代
基质(化学分析)
等角多边形
数学分析
纯数学
张量场
张量积
几何学
广义相对论的精确解
算法
物理
迭代法
复合材料
量子力学
材料科学
单调多边形
作者
Tommi Muller,Elina Robeva,Konstantin Usevich
摘要
.The tensor power method generalizes the matrix power method to higher-order arrays, or tensors. Like in the matrix case, the fixed points of the tensor power method are the eigenvectors of the tensor. While every real symmetric matrix has an eigendecomposition, the vectors generating a symmetric decomposition of a real symmetric tensor are not always eigenvectors of the tensor. In this paper we show that whenever an eigenvector is a generator of the symmetric decomposition of a symmetric tensor, then (if the order of the tensor is sufficiently high) this eigenvector is robust, i.e., it is an attracting fixed point of the tensor power method. We exhibit new classes of symmetric tensors whose symmetric decomposition consists of eigenvectors. Generalizing orthogonally decomposable tensors, we consider equiangular tight frame decomposable and equiangular set decomposable tensors. Our main result implies that such tensors can be decomposed using the tensor power method.Keywordstensor power methodrobust eigenvectorsymmetric tensorequiangular tight frametensor decompositionMSC codes15A6915A1842C1565F15
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