III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

D. Non-Equilibrium Thermodynamics of Living Systems

Zenil, Hector, et al. The Thermodynamics of Network Coding, and an Algorithmic Refinement of the Principle of Maximum Entropy. Entropy. 21/6, 2019. This paper by the Karolinska Institute, Stockholm computational theorists HZ, Narsis Kiani and Jesper Tegner is noted by the voluminous online journal site as among its most popular, because readers (like me) sense the authors are indeed closing on brilliant insights, however couched in technicalities, as the Abstract conveys. Something is really going on by itself as we ever try to get a good read and bead upon it, which may well be our cosmic purpose.

The principle of maximum entropy (Maxent) is often used to obtain prior probability distributions as a method to obtain a Gibbs measure under some restriction giving the probability that a system will be in a certain state compared to the rest of the elements. Here we take advantage of a causal algorithmic calculus to derive a thermodynamic-like result based on how difficult it is to reprogram a computer code. Using the distinction between computable and algorithmic randomness, we quantify the cost in information loss associated with reprogramming. To illustrate this, we apply the algorithmic refinement to Maxent on graphs and introduce a generalized Maximal Algorithmic Randomness Preferential Attachment (MARPA) Algorithm. Our study motivates further analysis of the origin and consequences of the aforementioned asymmetries, reprogrammability, and computation. (Abstract excerpt)

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