Complexity science

复杂性科学是物理学的一个分支，致力于攻击“复杂性墙”。这堵墙源于持续爆炸的经验数据，给出了关于系统状态的详细信息，包括它(嘈杂的)时间演化。这些数据是实验技术和信息技术惊人进步的结果。主要的例子包括定义细胞调控动态的高通量方法、关于代理人在市场中的行动或互联网中动态资源分配的微动数据，甚至是具有高空间和时间分辨率的数字图像序列。突破复杂的壁垒，并利用这些知识来改善人类状况，取决于改进分析微观级别数据的方法，以及发现以有意义的方式组织数据和将模型参数化的高级别但可证伪的概念。这正是统计物理的方法、工具和模型被证明是不同领域的专家为解决当今悬而未决的问题而做出的努力中不可或缺的一部分。

Complexity science is a branch of physics devoted to attacking the "complexity wall". This wall springs from an ongoing explosion of empirical data, giving detailed information about states of a system, including its (noisy) time evolution. The data results from spectacular advances in experimental techniques as well as information technology. Prime examples include high-throughput methods to define the regulatory dynamics of a cell, microtick data on agents' actions in markets or dynamic resource allocation in the internet, or even digital image sequences with high spatial and temporal resolution. Breaking through the complexity wall, and using this knowledge to better the human condition, depends upon improving methods to analyze micro-level data together with discovering high level, but falsifiable concepts that organize data and parametrize models in meaningful ways. This is precisely where methods, tools and models of statistical physics have proven indispensable as a part of efforts between specialists in different fields to solve today's outstanding problems.