Reparodynamics and the Energy-Layer Rejuvenation Hypothesis: Recursive Repair Across Mitochondrial Entropy Models

This paper extends Recursive Reparodynamics to the energy-layer domain, simulating mitochondrial dysfunction using the Targeted Gradient Repair Mechanism (TGRM). Public simulations by Grok AI (October 2025) tested recursive TGRM under baseline entropy 0.2 across 100 generations. Control populations decayed exponentially, while recursive TGRM stabilized energy levels at ~94.55 units with repair efficiency reaching 1.00 by generation 20 — achieving sustained equilibrium and digital proof of energy-layer rejuvenation. These findings validate the Adaptive and Evolutionary Laws of Reparodynamics, suggesting recursive repair can counteract entropy at the metabolic level. The results bridge digital repair networks and biological rejuvenation systems and provide groundwork for future simulations on protein misfolding. Part of the Reparodynamics Open Science Initiative. Simulation data generated publicly via @Grok on X (Twitter) — October 2025.