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arXiv 2109.04237quant-ph
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通过多智能体动力学量子博弈开展的纠缠研究

Study of entanglement via a multi-agent dynamical quantum game

Bar Ilan University(巴伊兰大学);Ben-Gurion University of the Negev(内盖夫本-古里安大学)

Bar Y. Peled, Amit Te'eni, Eliahu Cohen, Avishy Carmi

AI总结:

本研究拓展量子博弈理论,以多捕食者单猎物的生态模型为对象,发现量子纠缠强度显著影响系统渐近行为,还提出量子关联网络建模方法以借用经典网络理论工具,为量子博弈及相关应用提供新视角。

摘要:

在概念与应用层面,量子物理学既带来了新机遇,也存在根本性限制。我们提出假设性问题:受种群动力学启发的量子博弈能否从量子力学的纠缠、非定域性等独特特性中获益?为此我们拓展了量子博弈理论,并证明在模拟生态系统的特定模型(即多种捕食者捕食同一猎物的场景)中,不同物种间的量子纠缠强度对系统的渐近行为有显著影响。例如,若存在足够多的捕食者物种,且所有捕食者都与猎物具有同等程度的关联,则所有捕食者都会走向灭绝。我们通过两种方式推导得出结果:一是分析系统的渐近动力学,二是将系统建模为量子关联网络。后一种方法使我们能够将经典网络理论的多种工具应用于上述量子场景。文中还讨论了若干推广方向与应用场景。

英文摘要:

At both conceptual and applied levels, quantum physics provides new opportunities as well as fundamental limitations. We hypothetically ask whether quantum games inspired by population dynamics can benefit from unique features of quantum mechanics such as entanglement and nonlocality. For doing so we extend quantum game theory and demonstrate that in certain models mimicking ecological systems where several predators feed on the same prey, the strength of quantum entanglement between the various species has a profound effect on the asymptotic behavior of the system. For example, if there are sufficiently many predator species who are all equally correlated with their prey, they are all driven to extinction. Our results are derived in two ways: by analyzing the asymptotic dynamics of the system, and also by modeling the system as a quantum correlation network. The latter approach enables us to apply various tools from classical network theory in the above quantum scenarios. Several generalizations and applications are discussed.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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