On Adjacency Matrices and Descriptors of Signed Cycle Graphs

TL;DR

This paper explores the spectral properties of adjacency matrices of signed cycle graphs and evaluates their effectiveness in classification and chemical descriptor applications.

Contribution

It introduces methods for analyzing eigenvalues and eigenvectors of signed cycle graphs and assesses their utility in classification and chemical descriptor calculations.

Findings

Eigenvalues and eigenvectors are computed for signed cycle graphs.

Spectral methods show effectiveness in classifying signed cycles.

Numerical indices are evaluated for their efficacy in applications.

Abstract

This paper deals with adjacency matrices of signed cycle graphs and chemical descriptors based on them. The eigenvalues and eigenvectors of the matrices are calculated and their efficacy in classifying different signed cycles is determined. The efficacy of some numerical indices is also examined.