The Entropy of a Markov Chain
This article explores the intersection of thermodynamics and information theory by applying the concept of entropy to Markov chains. It seeks to bridge the gap between physical definitions of entropy and abstract mathematical models of life and equilibrium.
10 2 Share Clausius (1865)¹ defines a quantity called entropy. By decomposing physical processes as a chain of engines, he shows that entropy always increases for irreversible processes. For reversible processes like Carnot's ideal engine, the change in entropy is zero. But when an irreversible process occurs, entropy can never decrease unless energy is applied to a system. This is what is known as the second law of thermodynamics.
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