New Special Issue "Dynamics and Information Theory in Phase Space"

Dear Colleagues,

In this age of big data, a quantitative compact summary of the essential features of the system and how to extract them is needed throughout the sciences. This is especially the case when the system is evolving in time and one seeks to also describe its history. In the more quantitative sciences, the time course requires two ingredients: the law of change and the initial state of the system. The Laplace demon was an early practitioner. The demon had a very definite initial state. Beginning with Boltzmann and Gibbs, phase space is where the incomplete specification of the initial conditions lives and where it is convenient to describe how the system evolves. We need to know how to infer the initial state and how to propagate it in time. As the equation of motion, Boltzmann used a kinetic scheme while Gibbs used classical mechanics. The exponential growth of activities in quantum technologies provides us with novel tools for exploring the sampling of the phase space of complex systems. So, two key aspects of our subject are what methodology generates the time translation and are there ways of learning it. Next, we need to deal with reduction of the size of the problem. Lastly, we have custom-made approaches that have been tailored to the class of systems of interest (e.g., protein folding; what is the reaction coordinate; information transduction in a network). As the number of degrees of freedom grows, computational aspects become of increasing importance. What is the holy grail? Most likely, it is to converge on the function (operator) that generates the time displacement on a reduced level of description. Thermodynamics tell us that under well-defined conditions this is the free energy. How do we generalize it?

Prof. Dr. Raphael Levine

Prof. Dr. Fran?oise Remacle

Dr. Ksenia Komarova

Guest Editors

https://www.mdpi.com/journal/entropy/special_issues/phase_space