Quantum Information Flow in Neuronal Networks
Jincheng Zhang
This paper proposes a novel framework for understanding neuronal information processing, suggesting that quantum entanglement plays a significant role in neural communication, termed "quantum neurons." We introduce a model that incorporates quantum superposition and entanglement to simulate neuronal activity, moving beyond classical neuron models. The core mechanism involves utilizing quantum measurements and feedback loops to process information within this quantum neural network. We demonstrate how entangled states can facilitate information transfer exceeding the limitations of classical models, potentially explaining phenomena like consciousness and intelligence. The theoretical framework presented here offers a fundamentally new perspective on the nature of neuronal computation and provides a basis for future research in quantum neuroscience. The primary mathematical concepts explored include quantum state vectors, measurement operators, and the evolution of entangled systems. Key equations and notation are presented below for clarity.
•Aug 29, 2026•0 citations