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首页> 外文期刊>Physical Review, A >Stochastic gradient ascent outperforms gamers in the Quantum Moves game
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Stochastic gradient ascent outperforms gamers in the Quantum Moves game

机译:随机梯度上升Quantum Moves游戏中的游戏玩家

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摘要

In a recent work on quantum state preparation, S?rensen and co-workers [Nature (London) 532, 210 (2016)] explore the possibility of using video games to help design quantum control protocols. The authors present a game called "Quantum Moves" (https://www.scienceathome.org/games/quantum-moves/) in which gamers have to move an atom from A to B by means of optical tweezers. They report that, "players succeed where purely numerical optimization fails." Moreover, by harnessing the player strategies, they can "outperform the most prominent established numerical methods." The aim of this Rapid Communication is to analyze the problem in detail and show that those claims are untenable. In fact, without any prior knowledge and starting from a random initial seed, a simple stochastic local optimization method finds near-optimal solutions which outperform all players. Counterdiabatic driving can even be used to generate protocolswithout resorting to numeric optimization. The analysis results in an accurate analytic estimate of the quantum speed limit which, apart from zero-point motion, is shown to be entirely classical in nature. The latter might explain why gamers are reasonably good at the game. A simple modification of the BringHomeWater challenge is proposed to test this hypothesis.
机译:在最近的量子州准备工作中,S?rensen和同事[性质(伦敦)532,210(2016)]探索使用视频游戏来帮助设计量子控制协议的可能性。作者呈现一个名为“Quantum Moves”的游戏(https://www.scienceare.org/games/quantum-moves/),其中游戏玩家必须通过光学镊子将原子从A移动到B.他们报告说,“玩家成功,在纯粹数值优化失败的地方。”此外,通过利用玩家策略,他们可以“胜过最突出的既定的数值方法”。这种快速沟通的目的是详细分析问题,并表明这些声明是站不住脚的。事实上,没有任何先前的知识和从随机初始种子开始,简单的随机局部优化方法发现了近乎最佳的解决方案,优先突出所有玩家。甚至可以使用抵抗驾驶来生成协议,诉诸数字优化。分析导致对零点运动之外的量子速度限制的准确分析估计,其在自然界中完全古典。后者可能会解释为什么游戏玩家在游戏中合理良好。提出了一种简单的改变盗窃的挑战,以测试这一假设。

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