This framework reveals faster information processing in brain-like networks, suggesting a novel approach to learning.
This paper presents a complete and selfcontained framework for cognitive informationprocessing based on resonant dynamics in opendissipative systems. We introduce the QuantumInspired Information Model (QWIM) that rigorously bridges the Lindblad master equation ofopen quantum systems with classical Kuramototype phase synchronization. Information inertiais formally defined as the second thermodynamicderivative of free energy with respect to entropyat constant temperature, providing a quantitative measure of adaptation speed. A detailedadiabatic elimination of fast amplitude degrees offreedom yields an effective Kuramoto model. Wederive analytic expressions for critical coupling,synchronization stability, and minimal energyper informational transition. Extensive numerical experiments on networks of up to 2000 oscillators demonstrate that resonant synchronization achieves 3–5 times faster convergence andup to 40% lower energy consumption comparedto conventional gradient-descent architectures.A complete noise-coupling phase diagram is constructed using TikZ visualization. The modeloffers a thermodynamically grounded alternative to back-propagation-based learning and isdirectly applicable to both biological neural ensembles and future neuromorphic hardware.
No takes yet. Share an insight, caveat, or question.
Valeriy Kotenko (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: