Bounds for the Energy of Hypergraphs

The concept of the energy of a graph has been widely explored in the field of mathematical chemistry and is defined as the sum of the absolute values of the eigenvalues of its adjacency matrix. The energy of a hypergraph is the trace norm of its connectivity matrices, which generalize the concept of graph energy. In this paper, we establish bounds for the adjacency energy of hypergraphs in terms of the number of vertices, maximum degree, eigenvalues, and the norm of the adjacency matrix. Additionally, we compute the sum of squares of adjacency eigenvalues of linear k-hypergraphs and derive its bounds for k-hypergraph in terms of number of vertices and uniformity of the k-hypergraph. Moreover, we determine the Nordhaus–Gaddum type bounds for the adjacency energy of k-hypergraphs.

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Journal
Axioms
Published
2024-11-19
DOI
https://doi.org/10.3390/axioms13110804
Primary Topic
Tensor decomposition and applications
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article
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article

Bounds for the Energy of Hypergraphs

Chithra A. Velu, Liya Jess Kurian
Axioms
Tensor decomposition and applications
article

Bounds for the Energy of Hypergraphs

Chithra A. Velu, Liya Jess Kurian
article en

Abstract

The concept of the energy of a graph has been widely explored in the field of mathematical chemistry and is defined as the sum of the absolute values of the eigenvalues of its adjacency matrix. The energy of a hypergraph is the trace norm of its connectivity matrices, which generalize the concept of graph energy. In this paper, we establish bounds for the adjacency energy of hypergraphs in terms of the number of vertices, maximum degree, eigenvalues, and the norm of the adjacency matrix. Additionally, we compute the sum of squares of adjacency eigenvalues of linear k-hypergraphs and derive its bounds for k-hypergraph in terms of number of vertices and uniformity of the k-hypergraph. Moreover, we determine the Nordhaus–Gaddum type bounds for the adjacency energy of k-hypergraphs.

AxiomsVol. 13(11)
National Institute of Technology Calicut (IN)
Affordable and clean energy
Openalex Percentile: Top 81%
Tensor decomposition and applications
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Bounds for the Energy of Hypergraphs — Chithra A. Velu, Liya Jess Kurian · Axioms (2024) | TGRS Research Map | TGRS