量子逻辑自动机产生类 IV 模式和 1/f 噪声

IF 2 4区 生物学 Q2 BIOLOGY
Yuki Tokuyama , Yoshihiko Ohzawa , Yukio-Pegio Gunji
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引用次数: 0

摘要

由于近年来脑科学和人工智能的进步,研究人员倾向于关注自组织临界性或混沌边缘的概念。另一方面,源于量子力学的量子认知有望解决各种认知错觉。然而,直到最近,人们才提出临界性与量子力学之间的联系。Gunji 等人(2024 年)最近提出了一种称为量子逻辑自动机的联系,它不仅包括量子逻辑,还包括以幂律分布为特征的临界性。虽然量子逻辑自动机可以从各种结构中衍生出来,但目前只提出并讨论了其中一种。在此,我们定义了另一种涉及量子逻辑的量子逻辑自动机,并证明对称量子逻辑自动机会导致复杂的类 IV 模式和幂律分布。我们的研究结果支持临界性与量子理论之间的关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum logic automata generate class IV-like patterns and 1/f noise

Owing to recent advancements in brain science and AI, researchers tend to focus on the concept of self-organized criticality or the edge of chaos. On the other hand, quantum cognition, which is rooted in quantum mechanics, is promising for resolving various cognitive illusions. However, until recently, no connection between criticality and quantum mechanics was proposed. Gunji et al. (2024) recently introduced a linkage termed quantum logic automata, which encompasses not only quantum logic but also criticality characterized by power-law distributions. While quantum logic automata can be derived from various structures, only one of them has been proposed and discussed. Here, we define another type of quantum logic automata involving quantum logic and demonstrate that symmetric quantum logic automata lead to complex Class IV-like patterns and power-law distributions. Our findings support the association between criticality and quantum theory.

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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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