MetaFlux – AI-Physics Memory Substrate - v 0.1.0
Abstract
MetaFlux is a research-grade, mean-field dynamical memory substrate designed for tracking and stabilizing trajectory-level state evolution in adaptive systems. It provides a persistent, context-aware memory layer that maintains coherent individual trajectories amid noise and interaction—offering applications in quantum-inspired control, complex systems dynamics, and adaptive AI architectures where long-term state coherence and recall are required.
Fields of Study & Subjects
Complex Systems and Dynamics
Neural Networks and Applications
Neural Networks and Reservoir Computing
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 27 January 2026