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Cellular automata analysis of life as a complex physical system

Tropp, Simon LU (2020) FYSK02 20201
Mathematical Physics
Department of Physics
Abstract
This thesis regards the study of cellular automata, with an outlook on biological systems. Cellular automata are non-linear discrete mathematical models that are based on simple rules defining the evolution of a cell, depending on its neighborhood. Cellular automata show surprisingly complex behavior, hence these models are used to simulate complex systems where spacial extension and non-linear relations are important, such as in a system of living organisms. In this thesis, the scale invariance of cellular automata is studied in relation to the physical concept of self-organized criticality. The obtained power laws are then used to calculate the entropy of such systems and thereby demonstrate their tendency to increase the entropy, with... (More)
This thesis regards the study of cellular automata, with an outlook on biological systems. Cellular automata are non-linear discrete mathematical models that are based on simple rules defining the evolution of a cell, depending on its neighborhood. Cellular automata show surprisingly complex behavior, hence these models are used to simulate complex systems where spacial extension and non-linear relations are important, such as in a system of living organisms. In this thesis, the scale invariance of cellular automata is studied in relation to the physical concept of self-organized criticality. The obtained power laws are then used to calculate the entropy of such systems and thereby demonstrate their tendency to increase the entropy, with the intention to increase the number of possible future available states. This finding is in agreement with a new definition of entropic relations called causal entropy. (Less)
Popular Abstract
The mystery of life may sound complex, but what if the complexity could be concretized by something as simple as a pile of sand?
Please use this url to cite or link to this publication:
author
Tropp, Simon LU
supervisor
organization
alternative title
Cellulär automata analys av liv som ett komplext fysikaliskt system
course
FYSK02 20201
year
type
M2 - Bachelor Degree
subject
keywords
Cellular Automata, Self-organized Criticality, Casual Entropy, Entropy Maximization, Causal Entropic Forces, Biological Systems, Life, Game of Life, Statistical Physics, Non-linear Models
language
English
id
9008778
date added to LUP
2020-06-11 16:02:28
date last changed
2020-06-11 16:02:28
@misc{9008778,
  abstract     = {{This thesis regards the study of cellular automata, with an outlook on biological systems. Cellular automata are non-linear discrete mathematical models that are based on simple rules defining the evolution of a cell, depending on its neighborhood. Cellular automata show surprisingly complex behavior, hence these models are used to simulate complex systems where spacial extension and non-linear relations are important, such as in a system of living organisms. In this thesis, the scale invariance of cellular automata is studied in relation to the physical concept of self-organized criticality. The obtained power laws are then used to calculate the entropy of such systems and thereby demonstrate their tendency to increase the entropy, with the intention to increase the number of possible future available states. This finding is in agreement with a new definition of entropic relations called causal entropy.}},
  author       = {{Tropp, Simon}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Cellular automata analysis of life as a complex physical system}},
  year         = {{2020}},
}