
The PTPC–Energy Feedback Controller (PEFC) is a physics-based adaptive control algorithm derived from the Parry Tensional Phase Collapse (PTPC) cosmological framework.It applies a real-time entropy-reset principle to manage energy dissipation in AI hardware and data-center systems.By continuously monitoring an effective tension field Teff(t)constructed from power, rate-of-change, and thermal load, the controller triggers a controlled entropy reset when Teff>Tcrit.This mechanism stabilizes computation while reducing redundant dissipation. Simulations demonstrate 10 – 18 % power reduction under light load and up to 35 % during dynamic stress tests, with full stability recovery.The same thermodynamic principle that governs cosmic rebirth here governs sustainable computation. This white paper formalizes the theoretical foundation, algorithmic implementation, and energy-efficiency outcomes of the PEFC model, extending PTPC cosmology into practical computation and sustainable AI engineering.This document is released as a scientific white paper and technical note outlining the PTPC–Energy Feedback Controller framework.This work is released under the Parry Open Research License (PORL-1.0).Non-exclusive, royalty-free for research and educational use. Commercial or derivative use requires written permission from the author.
GPU clusters, tension field, Universal Heartbeat Theory, PTPC, entropy reset, sustainable computing, physics-based algorithms, adaptive control, AI energy optimization, thermodynamic feedback
GPU clusters, tension field, Universal Heartbeat Theory, PTPC, entropy reset, sustainable computing, physics-based algorithms, adaptive control, AI energy optimization, thermodynamic feedback
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