Algorithmic Information Theory for Physicists and Natural Scientists
Sean D Devine
Algorithmic information theory (AIT), or Kolmogorov complexity as it is known to mathematicians, can provide a useful tool for scientists to look at natural systems, however, some critical conceptual issues need to be understood and the advances already made collated and put in a form accessible to scientists. This book has been written in the hope that readers will be able to absorb the key ideas behind AIT so that they are in a better position to access the mathematical developments and to apply the ideas to their own areas of interest. The theoretical underpinning of AIT is outlined in the earlier chapters, while later chapters focus on the applications, drawing attention to the thermodynamic commonality between ordered physical systems such as the alignment of magnetic spins, the maintenance of a laser distant from equilibrium, and ordered living systems such as bacterial systems, an ecology, and an economy.
- Presents a mathematically complex subject in language accessible to scientists
- Provides rich insights into modelling far-from-equilibrium systems
- Emphasises applications across range of fields, including physics, biology and econophysics
- Empowers scientists to apply these mathematical tools to their own research