Relation between generalized distance spread and some topological indices

Let [Formula: see text] be a connected graph. The generalized distance matrix is defined as [Formula: see text], where [Formula: see text], [Formula: see text] is the distance matrix whose [Formula: see text]th entry is the distance between the [Formula: see text]th and [Formula: see text]th vertices in [Formula: see text] and [Formula: see text] is the diagonal matrix where each nonzero entry corresponds to the total distance to a vertex. The generalized distance spread, [Formula: see text] was defined as the difference between the largest eigenvalue and the smallest eigenvalue of [Formula: see text]. In this paper some lower bounds for [Formula: see text] in terms of [Formula: see text], the Wiener index and [Formula: see text] is presented and the equality cases are discussed. For a graph with prescribed diameter, a lower bound for [Formula: see text] as function of the vertex transmissions, distances between vertices, the diameter and [Formula: see text] is presented. A lower bound for this graph invariant in the class of trees is given. Additionally, lower bounds for [Formula: see text] as function of some known topological indices are presented. Some closed formulas for [Formula: see text] of known vertex-transitive graphs such as the polyhex nanotorus and hypercube are presented as applications of previous results. Moreover, some lower bounds (as function of [Formula: see text]) for some known molecular graphs are also presented.

Authors

Institutions

Publication Details

Journal
Discrete Mathematics Algorithms and Applications
Published
2025-02-13
DOI
https://doi.org/10.1142/s1793830925500363
Primary Topic
Topological and Geometric Data Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relation between generalized distance spread and some topological indices

Modjtaba Ghorbani, Enide Andrade, Maryam Baghipur, Hilal A. Ganie
Discrete Mathematics Algorithms and Applications
Topological and Geometric Data Analysis
article

Relation between generalized distance spread and some topological indices

Modjtaba Ghorbani, Enide Andrade, Maryam Baghipur, Hilal A. Ganie
article en

Abstract

Let [Formula: see text] be a connected graph. The generalized distance matrix is defined as [Formula: see text], where [Formula: see text], [Formula: see text] is the distance matrix whose [Formula: see text]th entry is the distance between the [Formula: see text]th and [Formula: see text]th vertices in [Formula: see text] and [Formula: see text] is the diagonal matrix where each nonzero entry corresponds to the total distance to a vertex. The generalized distance spread, [Formula: see text] was defined as the difference between the largest eigenvalue and the smallest eigenvalue of [Formula: see text]. In this paper some lower bounds for [Formula: see text] in terms of [Formula: see text], the Wiener index and [Formula: see text] is presented and the equality cases are discussed. For a graph with prescribed diameter, a lower bound for [Formula: see text] as function of the vertex transmissions, distances between vertices, the diameter and [Formula: see text] is presented. A lower bound for this graph invariant in the class of trees is given. Additionally, lower bounds for [Formula: see text] as function of some known topological indices are presented. Some closed formulas for [Formula: see text] of known vertex-transitive graphs such as the polyhex nanotorus and hypercube are presented as applications of previous results. Moreover, some lower bounds (as function of [Formula: see text]) for some known molecular graphs are also presented.

Discrete Mathematics Algorithms and ApplicationsVol. 18(02)
University of Aveiro (PT), Shahid Rajaee Teacher Training University (IR)
Reduced inequalities
Openalex Percentile: Top 97%
Topological and Geometric Data Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.