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Related Experiment Video

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

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Mutation at Expanding Front of Self-Replicating Colloidal Clusters.

Hidenori Tanaka^1,2, Zorana Zeravcic^1,3, Michael P Brenner^1,2

¹Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA.

Physical Review Letters

|December 17, 2016

Summary

This study introduces a model for self-replicating particle clusters, demonstrating their spread via Fisher waves. Introducing mutations allows these artificial systems to evolve and adapt, paving the way for artificial evolution studies.

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Area of Science:

Artificial life
Complex systems
Statistical physics

Background:

Self-replication is a fundamental characteristic of life.
Understanding the emergence of complex behaviors from simple rules is a key scientific challenge.
Artificial systems offer a controlled environment to study evolutionary dynamics.

Purpose of the Study:

To construct and validate a computational model for self-replicating particle clusters in two dimensions.
To investigate the dynamics of self-replication, including propagation patterns and the effects of mutations.
To explore the potential for studying evolutionary dynamics in an artificial system.

Main Methods:

Development of a simulation scheme for self-replicating square particle clusters.
Validation using computer simulations in a finite-temperature heat bath.
Introduction of spatially localized mutations in replication rules.

Main Results:

Self-replication reactions were observed to propagate as Fisher waves through the simulated environment.
The model, inspired by colloidal systems, allowed for multi-generational simulations.
Mutated cluster populations demonstrated survival and spread within the expanding front.

Conclusions:

The developed model provides a platform for studying artificial evolution.
Fisher waves are a relevant mechanism for the propagation of self-replication.
Spatially localized mutations can lead to adaptive evolution in artificial systems.