English

Spectral aspects of random heavy-tailed tensors

Probability 2026-07-27 v1

Abstract

We investigate heavy-Wigner tensors: symmetric random tensors whose independent entries, up to the tensor symmetries, are centered and have moments of order N(p1)N^{-(p-1)}, where NN is the tensor dimension. This framework includes normalized adjacency tensors of sparse Erd\H{o}s-R\'enyi hypergraphs and truncated heavy-tailed tensor models. We study trace invariants, a complete family of polynomial invariants under permutations of the tensor indices. We prove that, after the natural normalization, the only non-vanishing asymptotic contributions are those associated with fat hypertrees, and we derive a central limit theorem for these injective trace invariants. As applications, we first analyze Erd\H{o}s-R\'enyi pp-uniform hypergraphs with edge probability αN=c/Np1\alpha_N=c/N^{p-1}. We prove local weak convergence to a uniform Galton-Watson hypertree with Poisson offspring distribution. We also prove convergence of the empirical spectral distribution of the matrix obtained by contracting the adjacency tensor; in the sparse regime the limiting law depends on the sparsity parameter cc and has unbounded support, while in the regime Np1αNN^{p-1}\alpha_N\to\infty with Np1(1αN)N^{p-1}(1-\alpha_N)\to\infty, the limiting spectral distribution is the semicircle law. This result generalizes for matrices obtained by contracting an arbitrary heavy-Wigner tensor and we derive an explicit formula for the moments of the limiting spectral measure.

Keywords

Cite

@article{arxiv.2607.24695,
  title  = {Spectral aspects of random heavy-tailed tensors},
  author = {Remi Bonnin and Alexis Imbert},
  journal= {arXiv preprint arXiv:2607.24695},
  year   = {2026}
}

Comments

31 pages