On orthogonal tensors and best rank-one approximation ratio
Zhening Li, Yuji Nakatsukasa, Tasuku Soma, Andr\'e Uschmajew

TL;DR
This paper investigates the minimal spectral-to-Frobenius norm ratio for tensors, characterizes when orthogonal tensors attain this bound, and explores their existence related to classical algebraic problems, with implications for higher-order tensors.
Contribution
It establishes the conditions under which orthogonal and unitary tensors attain the minimal spectral-to-Frobenius ratio and links their existence to the Hurwitz problem, extending understanding of tensor approximation ratios.
Findings
Orthogonal tensors attain the minimal ratio iff they are orthogonal up to scaling.
Existence of real orthogonal tensors of size is limited to dimensions 1, 2, 4, 8.
Complex unitary tensors exist only when .
Abstract
As is well known, the smallest possible ratio between the spectral norm and the Frobenius norm of an matrix with is and is (up to scalar scaling) attained only by matrices having pairwise orthonormal rows. In the present paper, the smallest possible ratio between spectral and Frobenius norms of tensors of order , also called the best rank-one approximation ratio in the literature, is investigated. The exact value is not known for most configurations of . Using a natural definition of orthogonal tensors over the real field (resp., unitary tensors over the complex field), it is shown that the obvious lower bound is attained if and only if a tensor is orthogonal (resp., unitary) up to scaling. Whether or not orthogonal or unitary tensors exist depends on the dimensions…
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Taxonomy
TopicsTensor decomposition and applications · Matrix Theory and Algorithms · Advanced Optimization Algorithms Research
