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Entropy and the arrow of time in population dynamics
Diogo Costa-Cabanas1, Fabio A C C Chalub2, Max O Souza3
1Departamento de Matemática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Quinta da Torre, 2829-516, Caparica, Portugal.
Bio Systems
|November 27, 2022
Summary
This study explores a new entropy formula for stochastic processes, linking statistical physics and population genetics. It examines the Moran process and related models, connecting non-extensive entropies to epistasis and genetic symmetries.
Area of Science:
- Statistical physics
- Population genetics
- Stochastic processes
Background:
- Entropy in statistical physics is linked to irreversible macroscopic processes.
- Stochastic processes with multiple absorbing states are crucial in population genetics.
- The Moran process is a key model in population genetics.
Purpose of the Study:
- To explore a novel entropy formula for stochastic processes with multiple absorbing states.
- To investigate the applicability of this formula to the Moran process and other models.
- To analyze the relationship between non-extensive entropies, epistasis, and symmetries in population genetics.
Main Methods:
- Application of a recently introduced entropy formula.
- Analysis of the Moran process as a representative model.
- Extension of the analysis to other relevant population genetics models.
- Investigation of connections between non-extensive entropies and epistasis.
- Examination of the role of symmetries in population genetic models.
Main Results:
- The study demonstrates the utility of the new entropy formula for analyzing complex population genetics models.
- Connections are established between statistical physics concepts of entropy and biological concepts like epistasis.
- The role of symmetries in shaping population genetic dynamics is highlighted.
Conclusions:
- The explored entropy formula provides a valuable tool for understanding irreversible processes in population genetics.
- This work bridges theoretical physics and evolutionary biology by linking entropy, epistasis, and genetic symmetries.
- Further research into these connections can deepen our understanding of evolutionary dynamics.
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