摘要
远离平衡态的开放复杂系统遍及自然、社会和技术领域,是复杂性科学的主要研究对象.通过与外界的能量和物质交换,复杂系统通过自组织形成了多种多样的内在结构、秩序和规律,对认识和预测复杂系统提出了艰巨的挑战.随着实验技术的提高和科技的进步,反映和体现各种复杂系统机理的数据呈指数增长,为研究复杂系统提供了新的机遇.通过系统行为表象数据,揭示复杂系统结构和动力学属于物理领域的反问题,是认识复杂系统的基础,是预测系统状态演化的前提,对于实现系统状态的调控必不可少.然而,复杂系统的多样性和复杂性给解决这一反问题造成了极大的困难.因此,需要开阔思路,借助多学科的交叉与融合,充分挖掘数据中隐藏的知识和深层次机理.本文综述了近年来复杂系统,特别是复杂结构重构和推断方面的研究成果,希望能够启发复杂系统反问题方面的创新.同时,也希望呼吁各领域学者都能关注复杂系统反问题,推动自然、社会、经济、生物、科技领域的交叉与融合,解决大家共同面对的科学问题.
Open complex systems far from equilibrium widely exist in the nature and the fields of society and technology, which are the main research objects of complexity science. Through the exchange of energy and material with the outside world, complex systems can form a variety of internal structures, orders and laws by self-organization behaviors, which poses an arduous challenge to the understanding and predicting complex systems. With the improvement of experimental technology and the progress of science and technology, the data reflecting the mechanism of various complex systems are increasing exponentially, thereby providing new opportunities for studying complex systems. Revealing the structures and dynamics of complex systems from the measured data is an inverse problem in the field of physics, which is the premise of understanding complex systems, predicting the evolution of system state, and regulating system state. However, it is very difficult to solve this inverse problem due to the diversity and complexity of complex system. Therefore, we need to fully mine the hidden knowledge and deep mechanism in the data with the help of interdisciplinary integration. In this paper we briefly review the research results of complex system in recent years, especially the reconstruction of complex network structures, hoping to inspire the innovation to the inverse problem of complex systems.Meanwhile, we hope that researchers in different fields can pay much attention to the inverse problems of complex systems, promote the cross and integration of nature, society, economy, biology and technology, and solve the scientific problems that we are facing.
作者
张海峰
王文旭
Zhang Hai-Feng;Wang Wen-Xu(School of Mathematical Science,Anhui University,Hefei 230601,China;State Key Laboratory of Cognitive Neuroscience and Learning IDG/McGovern Institute for Brain&Research,School of Systems Science,Beijing Normal University,Beijing 100875,China)
出处
《物理学报》
SCIE
EI
CAS
CSCD
北大核心
2020年第8期281-291,共11页
Acta Physica Sinica
基金
国家自然科学基金(批准号:61973001,11975049,71631002)资助的课题.
关键词
统计物理
复杂系统
反问题
网络重构
statistical physics
complex systems
inverse problem
network reconstruction
作者简介
通信作者:王文旭,E-mail:wenxuwang@bnu.edu.cn。
