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基于多体量子场论的意识模拟

Jincheng Zhang

Zenodo (CERN European Organization for Nuclear Research) September 3, 2026 DOI: 10.5281/zenodo.22264844 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Key points Proposes that multi-particle quantum field theory, using quantum entanglement as a mechanism, could simulate neural correlates of consciousness and potentially reveal novel insights beyond traditional neural network models.

Abstract

This paper explores the potential of utilizing the framework of multi-particle quantum field theory (MQFT) to simulate the neural correlates of consciousness. The core claim is to develop a system capable of mimicking brain activity and information flow, leveraging quantum entanglement as a fundamental mechanism. We propose a model centered around simulating neural networks through quantum entanglement, analyzing the impact of quantum phenomena on consciousness, and ultimately seeking to understand the underlying principles of this complex phenomenon. The research aims to move beyond traditional neural network models by incorporating a quantum perspective, potentially unlocking novel insights into the nature of consciousness.