On the Connectivity of Quasi-random Graphs

Graph theory is widely used to study the structural properties of complex discrete systems. Thus, to assess the ability of a system to maintain certain structural properties when the con-nections between its elements are broken, it is important to study different types of graph con-nectivity. Quasi-random graphs are a model of complex discrete systems with random disrup-tions of connections between system elements. The problem of estimating the probability of connectivity in quasi-random graphs is considered. The concepts of multiframe and polynomi-al of a connected graph are introduced. A new estimator of connectivity for quasi-random graphs based on a 3-edge connected graphs is presented.

Authors

Publication Details

Journal
Èlektronnoe modelirovanie
Published
2024-12-11
DOI
https://doi.org/10.15407/emodel.46.06.003
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the Connectivity of Quasi-random Graphs

O.D. Glukhov
Èlektronnoe modelirovanie
Complex Network Analysis Techniques
article

On the Connectivity of Quasi-random Graphs

O.D. Glukhov
article en

Abstract

Graph theory is widely used to study the structural properties of complex discrete systems. Thus, to assess the ability of a system to maintain certain structural properties when the con-nections between its elements are broken, it is important to study different types of graph con-nectivity. Quasi-random graphs are a model of complex discrete systems with random disrup-tions of connections between system elements. The problem of estimating the probability of connectivity in quasi-random graphs is considered. The concepts of multiframe and polynomi-al of a connected graph are introduced. A new estimator of connectivity for quasi-random graphs based on a 3-edge connected graphs is presented.

Èlektronnoe modelirovanieVol. 46(6)
Openalex Percentile: Top 77%
Complex Network Analysis Techniques
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.

On the Connectivity of Quasi-random Graphs — O.D. Glukhov · Èlektronnoe modelirovanie (2024) | TGRS Research Map | TGRS