The Principle of Minimum Justified Correlation
Why nature favors the simplest explanations when information is limited
Three different ways of measuring disorder—Shannon entropy, Fisher information, and quantum kinetic energy—turn out to be the same thing: measures of correlation between variables. When you destroy correlations by treating variables as independent, all three measures decrease in predictable ways. This suggests a fundamental principle: given what we know about a physical system, the most justified description is the one with the least correlation among its parts.
This work bridges information theory, statistics, and quantum mechanics under a single principle, potentially explaining why simple, uncorrelated models often work so well in physics and why quantum systems behave the way they do. If the principle holds up across different domains, it could provide a new foundation for choosing which mathematical descriptions best match physical reality—moving beyond intuition to a concrete rule for what makes an explanation 'good enough.'