
Every state change has a minimum thermodynamic price — and now we can audit whether someone actually paid it. This paper establishes the information-theoretic foundation of Zero Leap Theory by proving Paper 50's Conjecture 14.3: the minimum entropy production for any state transition s₀ → s₁ satisfies ΔS_min ≥ k_B · D_KL(p_s₁ ‖ p_s₀), under explicit admissibility and stochastic regularity conditions (SR1–SR5). The bound is tight: quasi-static paths saturate it. We strengthen the result to a full Jarzynski equality and Crooks fluctuation theorem under microscopic reversibility, unifying ZLT with non-equilibrium statistical mechanics. We resolve two computational problems from Paper 50: gate estimation is #P-hard in general but admits an FPRAS under product structure (Problem 14.4), and optimal path computation is NP-hard but admits an FPTAS for fixed gate dimension (Problem 14.5). The operational payoff: the ZLT Audit Index η_ZLT := k_B · D_KL / Σ_measured flags any claim where η_ZLT > 1 as physically impossible — either the measurement is wrong or the intervention didn't happen. We extend this to a real-time Predictive Collapse Auditor that detects imminent lock-in before irreversibility sets in. A worked Markov chain example demonstrates bound saturation and Jarzynski verification within statistical error. All claims are conditional on stated assumptions and falsifiable by stated conditions.
Zero Leap Theory, KL divergence bound, entropy production, Jarzynski equality, Crooks fluctuation theorem, stochastic thermodynamics, audit index, gate estimation complexity, FPRAS, FPTAS, predictive collapse, information-theoretic bound, dissipation decomposition, systems with memory
Zero Leap Theory, KL divergence bound, entropy production, Jarzynski equality, Crooks fluctuation theorem, stochastic thermodynamics, audit index, gate estimation complexity, FPRAS, FPTAS, predictive collapse, information-theoretic bound, dissipation decomposition, systems with memory
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