175
Views
1
CrossRef citations to date
0
Altmetric
Research Article

The high order spectrum of a graph and its applications in graph colouring and clique counting

, &
Pages 2354-2365 | Received 16 Oct 2021, Accepted 18 May 2022, Published online: 31 Jul 2022
 

Abstract

D. Cvetković, M. Doob and H. Sachs considered the high order eigenvalue problems of graphs. The high order eigenvalues of a graph G are solutions of the high degree homogeneous polynomial equations derived from G. We propose the adjacency tensor A(G) of a graph G and show that the high order eigenvalues of G can be regarded as eigenvalues of A(G). Some results of the spectrum of the adjacency matrix are extended to the spectrum of A(G) by using the spectral theory of nonnegative tensors. An upper bound of chromatic number is given via the spectral radius of A(G). Our upper bound is a generalization of Wilf's bound χ(G)ρ(G)+1 (where ρ(G) is the spectral radius of the adjacency matrix of a graph G) and sharper than the bound of Wilf in some classes of graphs. A formula of the number of cliques of fixed size which involve the spectrum of A(G) is obtained.

AMS Classifications:

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by the National Natural Science Foundation of China (No. 12071097 and No. 11801115), the Natural Science Foundation of the Heilongjiang Province (No. QC2018002) and the Fundamental Research Funds for the Central Universities.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 670.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.