如何来呈现复杂系统的演化？

 

感知的持续时间是什么？

 

如何通过电脑游戏探索量子速度极限？

 

进化中的复杂系统的时间尺度探测 

（Detection of timescales in evolving complex systems）

 

April 14, 7:43 PM

 

BY Richard K. Darst, Clara Granell, Alex Arenas, Sergio Gómez, Jari Saramäki, Santo Fortunato

 

(Translated by -张皓)

 

世界上大多数的复杂系统本质上都是动态的。我们通常是通过一系列的快照来呈现复杂系统的演化，每一个快照都描述了系统在一个特定时间点的状态信息。如此，我们便可以直接跟踪这些快照是如何随时间而演化的，或者通过将一段时间间隔内的快照聚集在一起来形成具有代表性的系统状态演化的“切片”。我们通常采用恒定的间隔来实现上述操作，而间隔的长短取决于我们对系统及其动力学本质的判断。根据系统的活动快慢来确定时间尺度的划分也许是个更好的方案。而更好的替代方案是定义一个能够匹配系统状态演化的动态间隔。为此，我们提出了一种探测复杂系统状态变化的方法，并由此生成时间间隔。 我们展示了，可以根据数据中连续时间发生的事件所产生的峰值相似性来确定演化的时间尺度。在一个简单的玩具模型中，我们进行了测试，揭示出这项技术能够发现时变数据的演化化时间尺度，无论演化是平滑的还是急剧的。进一步，通过分析不同的真实数据集，我们进一步证实了这个观点。我们的方法能扩展到极大的数据集，并且计算效率很高。这使得我们可以对复杂系统的演化化进行快速的无参数的多尺度探测。

 

 

Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. Then, one may directly follow how the snapshots evolve in time, or aggregate the snapshots within some time intervals to form representative "slices" of the evolution of the system configuration. This is often done with constant intervals, whose duration is based on arguments on the nature of the system and of its dynamics. A more refined approach would be to consider the rate of activity in the system to perform a separation of timescales. However, an even better alternative would be to define dynamic intervals that match the evolution of the system's configuration. To this end, we propose a method that aims at detecting evolutionary changes in the configuration of a complex system, and generates intervals accordingly. We show that evolutionary timescales can be identified by looking for peaks in the similarity between the sets of events on consecutive time intervals of data. Tests on simple toy models reveal that the technique is able to detect evolutionary timescales of time-varying data both when the evolution is smooth as well as when it changes sharply. This is further corroborated by analyses of several real datasets. Our method is scalable to extremely large datasets and is computationally efficient. This allows a quick, parameter-free detection of multiple timescales in the evolution of a complex system.

 

原文链接：http://arxiv.org/abs/1604.00758

 

 

时间片：感知的持续时间是什么？

 (Time Slices: What Is the Duration of a Percept?)

 

PLOS April 14, 11:49 PM

 

BY Michael H. Herzog, Thomas Kammer,  Frank Scharnowski

 

(Translated by -dan)

 

我们感知的世界是无缝的知觉流。然而，有趣的幻觉和近期的一些实验都暗示这个世界是非连续被意识感知的。反而，感知更像是离散的，就像电影看起来是连续的，但实际上是离散画面组成的一样。为了解释相比于缓慢的意识感知来说，人类视觉处理的时间分辨率有多快，我们提出了一个新的概念框架，其中物体的特征，比如颜色，是由潜意识用高时间分辨率分析的，是准连续的。时间特征，比如持续时间，也如同其他特征一样被编码为量化的标签。当潜意识处理完成以后，所有的特征才同步地被意识以离散的方式感知，有时甚至发生在刺激之后的几百个毫秒。

 

我们感知的世界是无缝的知觉流。然而，迷人的错觉和最近的实验都暗示这个世界是非连续转化为意识感知的。反而，感知更像是离散的，就像电影看起来是连续的，但实际上电影是离散画面组成的。为了解释人类视觉处理的时间分辨率相比缓慢的意识感知有多快，我们提出了一个新的概念框架，其中物体的特性，比如颜色，是由潜意识用高时间分辨率分析的，是准连续的。如同其他特性一样，时间特性，比如持续时间，也编码为数字标签。当潜意识处理完成以后，所有的特性才同步地被意识感知，并且在时间上是离散的，有时滞后刺激源的出现达几百个毫秒。

 

 

We experience the world as a seamless stream of percepts. However, intriguing illusions and recent experiments suggest that the world is not continuously translated into conscious perception. Instead, perception seems to operate in a discrete manner, just like movies appear continuous although they consist of discrete images. To explain how the temporal resolution of human vision can be fast compared to sluggish conscious perception, we propose a novel conceptual framework in which features of objects, such as their color, are quasi-continuously and unconsciously analyzed with high temporal resolution. Like other features, temporal features, such as duration, are coded as quantitative labels. When unconscious processing is “completed,” all features are simultaneously rendered conscious at discrete moments in time, sometimes even hundreds of milliseconds after stimuli were presented.

 

原文链接： http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002433

 

 

通过电脑游戏探索量子速度极限 

Exploring the quantum speed limit with computer games

 

Nature 532, 210–213 (14 April 2016) April 15, 6:57 PM

 

BY Jens Jakob W. H. Sørensen, Mads Kock Pedersen, Michael Munch, Pinja Haikka, Jesper Halkjær Jensen, Tilo Planke, Morten Ginnerup Andreasen, Miroslav Gajdacz, Klaus Mølmer, Andreas Lieberoth & Jacob F. Sherson

 

(Translated by -秦德盛)

 

人们往往通过直观的方式形成低维度的简单启发式策略，从而解决具有巨大计算复杂性的问题。公民科学（citizen science，直译为公民科学，也作公众科学、群智科学，或称众包）是一种通过向非专业人群提出科学研究问题来开发该能力的途径。“游戏化”——在非游戏背景下运用游戏元素——是一种非常有效的工具，它可以向公民科学家提供研究问题的解决方案。公民科学游戏人们往往通过直观的方式形成低维度的简单启发式策略，从而解决具有巨大计算复杂性的问题。公民科学（或称众包）是一种通过向非专业人群提出科学研究问题来开发该能力的途径。“游戏化”——在非游戏背景下运用游戏元素——是一种非常有效的工具，它可以向公民科学家提供研究问题的解决方案。公民科学游戏Foldit、EteRNA和EyeWire已经成功地将这种方法应用于蛋白质和RNA的折叠以及神经元映射的研究当中。但是到目前为止，游戏化尚未应用于量子物理的问题研究中。在这里，我们提出了一个量子移动游戏（Quantum Moves），它是一个可以将量子物理领域中的优化问题进行游戏化的在线平台。我们发现，人类玩家可以解决量子计算领域中具有挑战意义的难题。玩家可以在纯数值优化方法失败之处取得成功，并且他们的策略可以为研究人员在优化问题上提供一种更深刻而普适的视角。凭借玩家的策略，我们已经开发出一种多参数的启发式优化方法，它明显优于现有的最优秀的数值算法。对于较短的过程来说，它的数值复杂性（与时间最优解相关）会不断增加。为了更好地理解这一点，我们生成了一个最优景观的低维渲染图，以揭示为什么传统优化方法在接近量子速度极限（即完美保真度的最短持续时间）的时候会失败。将景观优化和启发式求解策略相结合可能有利于量子物理乃至更多领域中广泛存在的优化问题的求解。

 

 

Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies. 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, EteRNA and EyeWire 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. 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, 8, 9. Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.

 

原文链接：http://www.pnas.org/content/113/15/3932.abstract

 

特别鸣谢：

 

感谢集智创始人张江老师和傅渥成大神对译文进行的细心审校。