A network cell with molecular agents that divides from centrosome signals.

Area of Science:

• Computational chemistry
• Network science
• Artificial life

Background:

• Artificial chemistry models explore emergent behavior in chemical systems.
• Network topology significantly influences system dynamics and organization.
• Simulating molecular interactions is key to understanding self-organization.

Purpose of the Study:

• To introduce a novel network artificial chemistry (NAC) model.
• To investigate how molecular agents with programs can dynamically alter network topology.
• To demonstrate the emulation of biological-like organization within a network.

Main Methods:

• Developed a NAC model with mobile molecular agents executing assembler programs.
• Agents' node-rewiring behavior is determined by their hydrophilic or hydrophobic types.
• Conducted numerical experiments with centrosome, hydrogen, and van der Waals agent types.

Main Results:

• The NAC model successfully created pseudo-lattice structures between hydrophilic nodes.
• Demonstrated repulsion effects between hydrophilic and hydrophobic nodes.
• Emulated the division of a network cell, visualized as a hydrophilic cluster.

Conclusions:

• The revised NAC model effectively simulates emergent network organization based on molecular interactions.
• Agent-based network rewiring can lead to complex, large-scale topological structures.
• This model provides a framework for studying self-organization in artificial systems.