Irreversible k-Threshold Number Ck(G) and Saturation Probability P[G] for Corona Product and Double Corona Product Graphs

We discuss the Irreversible k-conversion process for graphs, where a vertex becomes saturated and remains saturated indefinitely if at least k of its neighbors are saturated. We investigate sets S0, which when initially saturated, lead to complete graph saturation. We are interested in the minimum |S0| = Ck(G), called the k-threshold number. We consider the construction of the Corona Product Graphs (of Cn and Kp). Additionally, we extend our analysis by defining and exploring Double Corona Product Graphs (of Cn and Kp). Then we incorporate probabilistic methods to assess how saturation is affected by randomly selecting S0, when |S0| = Ck(G). Our findings provide insights into the relationship between graph structure, probabilistic behavior, and saturation dynamics, with applications in epidemiology and social influence modeling.

Publication Details

Journal
FHSU Scholars Repository (Fort Hays State University)
Published
2025-04-01
Primary Topic
Complex Network Analysis Techniques
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article
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article

Irreversible k-Threshold Number Ck(G) and Saturation Probability P[G] for Corona Product and Double Corona Product Graphs

FHSU Scholars Repository (Fort Hays State University)
Complex Network Analysis Techniques
article

Irreversible k-Threshold Number Ck(G) and Saturation Probability P[G] for Corona Product and Double Corona Product Graphs

article en

Abstract

We discuss the Irreversible k-conversion process for graphs, where a vertex becomes saturated and remains saturated indefinitely if at least k of its neighbors are saturated. We investigate sets S0, which when initially saturated, lead to complete graph saturation. We are interested in the minimum |S0| = Ck(G), called the k-threshold number. We consider the construction of the Corona Product Graphs (of Cn and Kp). Additionally, we extend our analysis by defining and exploring Double Corona Product Graphs (of Cn and Kp). Then we incorporate probabilistic methods to assess how saturation is affected by randomly selecting S0, when |S0| = Ck(G). Our findings provide insights into the relationship between graph structure, probabilistic behavior, and saturation dynamics, with applications in epidemiology and social influence modeling.

FHSU Scholars Repository (Fort Hays State University)
Openalex Percentile: Top 50%
Complex Network Analysis Techniques
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