Joint distributions of eigenvectors of symmetric random tensors

Abstract We compute the joint distributions of arbitrary numbers of eigenvectors of real and complex symmetric random tensors by the quantum field theoretical methods which were previously used to compute the mean distributions. We obtain the random matrix representations and the large-dimension asymptotics of the joint distributions. The latter can be expressed by a common function of tensor geometries, extending the universality found for the mean distributions to the joint distributions. Several crosschecks of our results are carried out by Monte Carlo computations.

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Publication Details

Journal
Progress of Theoretical and Experimental Physics
Published
2026-07-27
DOI
https://doi.org/10.1093/ptep/ptag143
Primary Topic
Tensor decomposition and applications
Type
article
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article

Joint distributions of eigenvectors of symmetric random tensors

Naoki Sasakura
Progress of Theoretical and Experimental Physics
Tensor decomposition and applications
article

Joint distributions of eigenvectors of symmetric random tensors

Naoki Sasakura
article en

Abstract

Abstract We compute the joint distributions of arbitrary numbers of eigenvectors of real and complex symmetric random tensors by the quantum field theoretical methods which were previously used to compute the mean distributions. We obtain the random matrix representations and the large-dimension asymptotics of the joint distributions. The latter can be expressed by a common function of tensor geometries, extending the universality found for the mean distributions to the joint distributions. Several crosschecks of our results are carried out by Monte Carlo computations.

Progress of Theoretical and Experimental Physics
Kyoto University (JP)
Openalex Percentile: Top 8%
Tensor decomposition and applications
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