Retracted: Exploring the quantum speed limit with computer games (Publication with Expression of Concern. See vol. 581, 2020) (Publication with Expression of Concern. See vol. 581, 2020) (Retracted Article)
Retracted: Exploring the quantum speed limit with computer games (Publication with Expression of Concern. See vol. 581, 2020) (Publication with Expression of Concern. See vol. 581, 2020) (Retracted Article)
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DOI：
10.1038/nature17620
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发表时间：
2016-04-14
期刊：
影响因子：
64.8
通讯作者：
Sherson, Jacob F.
中科院分区：
文献类型：
--
作者：
Sorensen, Jens Jakob W. H.;Pedersen, Mads Kock;Sherson, Jacob F.
人类通常通过直观地形成简单的，低维的启发式策略来解决巨大的计算复杂性问题（1，2）。公民科学（或众包）是一种通过向非专家提出科学研究问题来利用这种能力的方式。“游戏化”--游戏元素在非游戏环境中的应用--是一种有效的工具，可以让公民科学家为研究问题提供解决方案。市民科学游戏Foldit（3）、EteRNA（4）和EyeWire（5）已经成功地用于研究蛋白质和RNA折叠以及神经元映射，但到目前为止，游戏化还没有应用于量子物理问题。在这里，我们报告量子移动，一个在线平台游戏化量子物理学中的优化问题。我们表明，人类玩家能够找到与量子计算任务相关的困难问题的解决方案。玩家在纯数值优化失败的地方取得了成功，对他们的解决方案的分析提供了对更深刻和一般性质的优化问题的见解。使用球员策略，我们因此开发了一个少参数启发式优化方法，有效地优于最突出的建立数值方法。与时间最优解相关的数值复杂性随着处理持续时间的缩短而增加。为了更好地理解这一点，我们制作了优化景观的低维渲染。这个渲染揭示了为什么传统的优化方法在接近量子速度限制（即具有完美保真度的最短过程持续时间）时失败（7-9）。优化景观和启发式解决方案策略的组合分析可能会使量子物理及其他领域的更广泛的优化问题受益。
Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies(1,2). Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. 'Gamification'-the application of game elements in a non-game context-is an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit(3), EteRNA(4) and EyeWire(5) have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing(6). Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity)(7-9). Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.