Abstract Distributed computational systems operating under nonequilibrium conditions frequently experience synchronization turbulence, collision cascades, and entropy amplification during recovery and coordination phases. In this work, we propose the existence of a critical informational damping regime characterized by a dimensionless parameter κP ≈ 2.3097, which we denote the Panzano Attractor. The attractor emerges from the minimization of an effective entropy production functional describing the competition between synchronization collisions, damping dissipation, and overdamped latency accumulation. We derive the stationary condition associated with this minimum and demonstrate that the resulting regime behaves as a stable nonequilibrium fixed point under Lyapunov analysis. Key Practical Implications Thermodynamic Efficiency & Data Centers: Minimizes computational friction and retry storms, directly curtailing physical heat generation and lowering cooling costs in large-scale infrastructures. Hardware Demarginalization: Optimizes geometric coordination instead of raw power, allowing legacy infrastructure and older machinery to achieve a radical leap in velocity. Quantum Operating Systems: Provides a stable fixed point for classical control layers, acting as an active thermodynamic shield to mitigate decoherence and preserve qubit state longevity. Sovereign Universal Grid: Eliminates cloud centralization by utilizing irrational phase spacing (φ) to coordinate high-density networks across heterogeneous edge devices. Licensing Notice This project operates under a Dual-Licensing Framework (Open-Core / BSL 1.1): Community & Research License: Free and unrestricted access for academic research, non-commercial experimentation, and deployments under the threshold of 1,000 concurrent nodes (N ≤ 10³). Commercial Production License: Required for enterprise, production, or profit-generating cloud infrastructures exceeding the node threshold. Pricing is indexed against audited reductions in thermal and informational entropy. Formulation developed within the OASIS Framework ecosystem. Genesis and Submission Date: May 18, 2026.
Mariano Panzano Caballé (Mon,) studied this question.