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arXiv:2508.14456 · Physical Review A

Multiplayer conflict avoidance through entangled quantum walks

Honoka Shiratori, Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana, André Röhm, Ryoichi Horisaki

Published Nov 13, 2025• 1 citation
arXivHTMLPDF

Abstract

Quantum computing has the potential to solve complex problems faster and more efficiently than classical computing. It can achieve speedups by leveraging quantum phenomena like superposition, entanglement, and tunneling. Quantum walks (QWs) form the foundation for many quantum algorithms. Unlike classical random walks, QWs exhibit quantum interference, leading to unique behaviors such as linear spreading and localization. These properties make QWs valuable for various applications, including universal computation, time series prediction, encryption, and quantum hash functions. One emerging application of QWs is decision-making. Previous research has used QWs to model human decision processes and solve multiarmed bandit problems. This paper extends QWs to collective decision-making, focusing on minimizing decision conflicts, cases where multiple agents choose the same option, leading to inefficiencies like traffic congestion or overloaded servers. Prior research using quantum interference has addressed two-player conflict avoidance but struggled with three-player scenarios. This paper proposes a method using QWs to entirely eliminate decision conflicts in three-player cases, demonstrating its effectiveness in collective decision-making.

DOI
10.1103/zxx8-j2d4

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Quantum walks (QWs) have a property that classical random walks (RWs) do not possess-the coexistence of linear spreading and localization-and this property is utilized to implement various kinds of applications. This paper proposes RW- and QW-based algorithms for multi-armed-bandit (MAB) problems. We show that, under some settings, the QW-based model realizes higher performance than the corresponding RW-based one by associating the two operations that make MAB problems difficult-exploration and exploitation-with these two behaviors of QWs.
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Collective decision-making plays a crucial role in information and communication systems. However, decision conflicts among agents often impede the maximization of potential utilities within the system. Quantum processes have shown promise in achieving conflict-free joint decisions between two agents through the entanglement of photons or the quantum interference of orbital angular momentum (OAM). Nonetheless, previous studies have shown symmetric resultant joint decisions, which, while preserving equality, fail to address disparities. In light of global challenges such as ethics and equity, it is imperative for decision-making systems to not only maintain existing equality but also address and resolve disparities. In this study, we investigate asymmetric collective decision-making theoretically and numerically using quantum interference of photons carrying OAM or entangled photons. We successfully demonstrate the realization of asymmetry; however, it should be noted that a certain degree of photon loss is inevitable in the proposed models. We also provide an analytical formulation for determining the available range of asymmetry and describe a method for obtaining the desired degree of asymmetry.
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This paper explores the application of quantum walks as a novel approach to optimization within the realm of combinatorial problems. The core argument posits that quantum walks, leveraging the principles of quantum mechanics like superposition and interference, can potentially outperform classical walk-based optimization methods, particularly when dealing with complex problem landscapes. We propose a framework where combinatorial problems are represented as graphs and navigated via quantum walks. The implementation utilizes the inherent probabilistic nature of quantum walks to explore the solution space more efficiently through constructive interference, while suppressing destructive interference that would lead to unproductive exploration. We detail the theoretical underpinnings, focusing on the mathematical formulation of the quantum walk and its interaction with the problem graph. The key objective is to demonstrate a potential speedup in convergence compared to traditional optimization techniques. This work provides a foundational exploration, aiming to lay the groundwork for future research and development in this emerging field.
The competitive multi-armed bandit (CMAB) problem is related to social issues such as maximizing total social benefits while preserving equality among individuals by overcoming conflicts between individual decisions, which could seriously decrease social benefits. The study described herein provides experimental evidence that entangled photons physically resolve the CMAB in the 2-arms 2-players case, maximizing the social rewards while ensuring equality. Moreover, we demonstrated that deception, or outperforming the other player by receiving a greater reward, cannot be accomplished in a polarization-entangled-photon-based system, while deception is achievable in systems based on classical polarization-correlated photons with fixed polarizations. Besides, random polarization-correlated photons have been studied numerically and shown to ensure equality between players and deception prevention as well, although the CMAB maximum performance is reduced as compared with entangled photon experiments. Autonomous alignment schemes for polarization bases were also experimentally demonstrated based only on decision conflict information observed by an individual without communications between players. This study paves a way for collective decision making in uncertain dynamically changing environments based on entangled quantum states, a crucial step toward utilizing quantum systems for intelligent functionalities.