The evolution of network topology by selective removal

Area of Science:

• Network science
• Complex systems analysis
• Graph theory

Background:

• Large-scale networks (social, technical, biological) exhibit broad-tailed, scale-free properties.
• Power-law distributions characterize vertex connectivity in these networks.
• Preferential attachment is the dominant model for scale-free network growth.

Purpose of the Study:

• To propose a novel network model generating broad-tailed networks.
• To demonstrate scale-free properties in networks without continuous growth.
• To explore network topology formation mechanisms beyond preferential attachment.

Main Methods:

• Development of a new network model incorporating vertex addition and selective elimination.
• Vertex elimination probability inversely proportional to first- and second-order connectivity.
• Analysis of resulting network topology and connectivity distributions.

Main Results:

• The proposed model successfully generates broad-tailed networks.
• Scale-free-like connectivity patterns emerge without network growth.
• Selective vertex removal is a viable mechanism for creating scale-free networks.

Conclusions:

• Network topology can evolve towards scale-free characteristics without growth.
• Selective node removal offers an alternative mechanism for generating broad-tailed networks.
• This model provides new insights into the formation of complex network structures.