Universal Law of Descent (LUDC): A Physical Bound on Combinatorial Entropy Reduction — Extending the Universal Stability Law

The Universal Law of Descent (LUDC) establishes a physical bound on the rate of entropy reduction in computational and self-organizing systems:

**Equation:** −dS/dt ≤ κ · C(t) · P(t)

where C(t) represents structural conductance and P(t) operational power.
Extending the Universal Stability Law (USL), the LUDC unifies informational geometry, stochastic thermodynamics, and computational complexity, providing a measurable physical constraint on the ordering rate of systems — from combinatorial algorithms (SAT, TSP) to dynamical models (machine learning, sandpile automata).

Simulations across domains show less than 5% deviation from the theoretical bound, suggesting that entropy reduction — and thus computational efficiency — is limited by universal energetic constraints.

This work bridges the physics of information and the foundations of complexity theory, offering an experimentally testable perspective on the P vs NP problem.