Analysis of non-thermodynamic properties of networked dynamical systems using stochastic thermodynamics using Markov Chains
Social networks of political voters, gene regulatory networks, recurrent neural networks or groups of flocking birds, all are examples of out-of-equilibrium systems of interdependent and co-evolving units. Even though there is no thermodynamic interpretation, it is still useful to quantify the irreversibility of these systems in terms of stochastic thermodynamics, namely by calculating the entropy production of the whole system as well as for each subsystem and relate it with the topological properties (such as Speed Limit Theorem) of the underlying network.
The two notebooks presents Speed Limit Theorem results on two types of chains - discrete and continuous first order markov chains. The proofs are visualized graphically for various network types and sizes.