量子游戏玩家可以没有不和谐的优势
Quantum game players can have advantage without discord
摘要：
量子信息处理是近二十年来迅速发展起来的一种研究“量子优势“在各种信息处理任务中的能力和极限的新范式。诸如量子优势何时存在，如果存在，它可能有多大等问题，处于这些研究的中心位置。在一个广泛的场景中，至少有两个参与方（隐式或显式）共享一个状态，并且这种共享状态的相关性是所关注的效率的关键因素。在这些场景中，共享的\emph{entanglement}或\emph{discord}通常是量子优势的原因。在本文中，我们从博弈论的角度来研究这种性质的一个基本问题，博弈论是研究两个或多个玩家自私行为的应用数学分支。我们展示了一个自然的零和游戏，其中任何玩家赢得游戏的机会只取决于最终的相关性。我们表明，在某种经典均衡中，没有参与者可以通过任何局部经典操作进一步增加她的收益的情况下，无论谁首先使用量子计算机，都比它的经典对手有很大的优势。这种均衡对双方都是公平的，而且作为一种共有的相关性，它不包含任何不和谐，但量子优势仍然存在。这表明，至少在博弈论中，当有两个具有不同目标的参与者时，需要重新审视先前作为非经典相关性度量的不和谐概念。
英文摘要：
The last two decades have witnessed a rapid development of quantum information processing, a new paradigm which studies the power and limit of "quantum advantages" in various information processing tasks. Problems such as when quantum advantage exists, and if existing, how much it could be, are at a central position of these studies. In a broad class of scenarios, there are, implicitly or explicitly, at least two parties involved, who share a state, and the correlation in this shared state is the key factor to the efficiency under concern. In these scenarios, the shared \emph{entanglement} or \emph{discord} is usually what accounts for quantum advantage. In this paper, we examine a fundamental problem of this nature from the perspective of game theory, a branch of applied mathematics studying selfish behaviors of two or more players. We exhibit a natural zero-sum game, in which the chance for any player to win the game depends only on the ending correlation. We show that in a certain classical equilibrium, a situation in which no player can further increase her payoff by any local classical operation, whoever first uses a quantum computer has a big advantage over its classical opponent. The equilibrium is fair to both players and, as a shared correlation, it does not contain any discord, yet a quantum advantage still exists. This indicates that at least in game theory, the previous notion of discord as a measure of non-classical correlation needs to be reexamined, when there are two players with different objectives.
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。
