Multi-entropy in random tensor networks

Miao Hu; Simon Lin; Ion Nechita

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arXiv · 2606.04470

Multi-entropy in random tensor networks

Miao Hu·Simon Lin·Ion Nechita

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Abstract

We study the evaluation of R\'enyi multi-entropies $S^{(q)}_n$ in Random Tensor Network (RTN) states in the large bond-dimension limit. For the case of R\'enyi index $n=2$ and arbitrary number of parties $q$, we prove that that multi-entropies are determined by minimal multiway cuts through the network. When the minimal multiway cut is degenerate, we characterize the full minimizer set via compatible families of minimal cuts and give a criterion for all minimizers to come from ordinary cut partitions. For $n=2$, this gives a natural generalization of the minimal cut description of bipartite entanglement to multipartite systems with arbitrarily many parties. For the case of integer $n>2$, we show that the minimal multiway cut conjecture is in general \emph{not true} by providing explicit counter examples for both the single random tensor and for the network built from isometric tilings. We discuss the implication for our results on the multipartite entanglement structures in RTN and holography.

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Miao Hu, Simon Lin, Ion Nechita. 2026-06-03. Multi-entropy in random tensor networks. https://arxiv.org/abs/2606.04470

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