Adjacency spectral characterizations for the toughness of hypergraphs

Toughness measures how well a graph remains connected after vertex deletions. Fan et al. (2023) presented spectral conditions for a graph to be t -tough. Motivated by their work, this paper investigates the adjacency spectrum of hypergraphs and establishes spectral radius conditions for t -tough in hypergraphs. These results extend the corresponding theories in graphs and provide a complete characterization of the extremal hypergraphs.

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Publication Details

Journal
Discrete Applied Mathematics
Published
2026-10-03
DOI
https://doi.org/10.1016/j.dam.2026.09.040
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
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article

Adjacency spectral characterizations for the toughness of hypergraphs

Lei Zhang, Qiannan Niu, Haizhen Ren, Yanhong Zhang
Discrete Applied Mathematics
Tensor decomposition and applications
article

Adjacency spectral characterizations for the toughness of hypergraphs

Lei Zhang, Qiannan Niu, Haizhen Ren, Yanhong Zhang
article en

Abstract

Toughness measures how well a graph remains connected after vertex deletions. Fan et al. (2023) presented spectral conditions for a graph to be t -tough. Motivated by their work, this paper investigates the adjacency spectrum of hypergraphs and establishes spectral radius conditions for t -tough in hypergraphs. These results extend the corresponding theories in graphs and provide a complete characterization of the extremal hypergraphs.

Discrete Applied MathematicsVol. 397
Qinghai Normal University (CN)
Openalex Percentile: Top 12%
Tensor decomposition and applications
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