Researchers release v2 of paper testing the entangled neuron hypothesis using Chinese intraday stock market data
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Haochen Li, Xinshuai Guo, Jingdong Ouyang, Wei Zhang, and Leilei Shi published paper v2 in arXiv q-fin on October 22, 2026, modeling the collective behavior of adaptive interactive agents based on a generalized probability wave framework, and testing the Liu-Chen-Ao (LCA) entangled neurofiber hypothesis using Chinese intraday stock market data. The paper states that analysis shows adaptive entangled game patterns can explain 82%–94% of decision patterns, 2%–12% of behavior adjusts with news, events, and environment, and fully independent behavior accounts for less than 5%; this result contrasts with predictions of independent rational agents under neoclassical finance assumptions. The authors state that this research provides new ideas for building more efficient and robust artificial general intelligence.
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- arXiv q-finAdaptive Entanglement Neurons in the Brain and Natural Intelligence Simulation for Artificial General Intelligence
The study models the collective behavior of adaptive interactive agents based on a generalized probability wave framework, and verifies the Liu-Chen-Ao (LCA) entangled neural fiber hypothesis by analyzing Chinese intraday stock market data. The results show that adaptive entanglement game patterns can explain 82%-94% of decision-making patterns, with less than 5% of behaviors being completely independent. This research provides new ideas for building more efficient and robust artificial general intelligence.
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