复杂系统结构及动力学现象的统计物理研究

近年来生物学、信息学和社会科学海量数据的积累，推动了各类定量分析手段的发展.统计力学作为联系多体系统微观与宏观描述的数学理论，在复杂性科学的发展历程中正发挥着作用.本文结合复杂网络和非平衡态系统的若干研究成果，对统计物理方法在复杂现象的描述、主要变量及其相互依赖关系的确定、模型的提出与分析、及普适性规律的发现等方面的进展作一简单介绍，并探讨统计物理学与相应学科深层次交叉所面临的机遇和挑战.

The rapid accumulation of massive amounts of data in biology information technology and various branches of social science in recent years has prompted the development of novel quantitative methods. Statistical mechanics, as a mathematical theory that connects microscopic and macroscopic descriptions of systems with many degrees of freedom, can play an important role in this process. A short review of recent progress in the application of statistical physics methods to a broad range of complex phenomena is presented here. From the examples discussed one may obtain a glimpse of the power of the statistical mechanical approach in capturing the system dynamics at different levels of representation and on many different time scales. With the help of simplified models and approximate treatments, the key variables and their interdependencies can be elucidated. Further theoretical considerations and comparative studies may lead to the discovery of unifying principles. The opportunities and challenges in a closer integration of statistical physics and complex systems science are briefly discussed.