经济金融中的自组织临界性

 复杂性科学在最近二三十年取得了突破性进展, 目前从这个学科中发展起来的许多范式和方法都已经渗透到多门传统学科并与其不断融合促成了各种门类的交叉学科和方向。其中自组织临界性就是复杂性科学领域发展出来的一种独特方法, 也是理论物理学家对理解复杂系统的一般规律的一个最重要的贡献。在理解和解释由大量个体通过相互作用所导致的复杂系统时空长程相关特性问题上, 自组织临界性理论提供了一种非常新颖和通用的机制方法, 其应用领域涵盖了物理学、地学、生物学、经济学等多门学科以及它们的交叉方向。本文重点介绍自组织临界模型在经济金融系统中的可能应用及其发展前景。     

物理学研究的新领域——探索复杂性

文章介绍了近代科学思想和方法论中的两个基本模式,即还原论和系统论,指出在物理学及其交叉学科中探索复杂系统将是未来科学发展的一个重要领域,它们共同构成复杂性科学.文章说明了复杂网络的一些特殊性质,它们可以用来描述一些复杂系统的结构和功能.作为一个导引,文章还介绍了国内外研究复杂系统的主要学术流派,并重申复杂性研究以及交叉学科对中国中长期科学发展的重要意义.     

动态复杂网络中节点影响力的研究进展

节点影响力的识别和预测具有重要的理论意义和应用价值,是复杂网络的热点研究领域.目前大多数研究方法都是针对静态网络或动态网络某一时刻的快照进行的,然而在实际应用场景中,社会、生物、信息、技术等复杂网络都是动态演化的.因此在动态复杂网络中评估节点影响力以及预测节点未来影响力,特别是在网络结构变化之前的预测更具意义.本文系统地总结了动态复杂网络中节点影响力算法面临的三类挑战,即在增长网络中,节点影响力算法的计算复杂性和时间偏见;网络实时动态演化时,节点影响力算法的适应性;网络结构微扰或突变时,节点影响力算法的鲁棒性,以及利用网络结构演变阐释经济复杂性涌现的问题.最后总结了这一研究方向几个待解决的问题并指出未来可能的发展方向.     

复杂网络可控性研究现状综述

控制复杂系统是人们对复杂系统模型结构及相关动力学进行研究的最终目标, 反映人们对复杂系统的认识能力. 近年来, 通过控制理论和复杂性科学相结合,复杂网络可控性的研究引起了人们的广泛关注. 在过去的几年内, 来自国内外不同领域的研究人员从不同的角度对复杂网络可控性进行了深入的分析研究, 取得了丰硕的成果. 本文重点讨论了复杂网络的结构可控性研究进展, 详细介绍了基于最大匹配方法的复杂网络结构可控性分析框架, 综述了自2011年以来复杂网络可控性的相关研究成果, 具体论述了不同类型的可控性、可控性与网络拓扑结构统计特征的关联、基于可控性的网络及节点度量、控制的鲁棒性和可控性的相关优化方法. 最后, 对网络可控性未来的研究动态进行了展望, 有助于国内同行开展网络可控性的相关研究.     

用于混沌时间序列预测的多簇回响状态网络

研究了混沌时间序列预测问题.提出了一种由五元生长因子组调控的类皮层神经网络模型,即多簇回响状态网络模型（MCESN）.研究表明该生长因子组能够有效决定模型的拓扑性质;同时具备小世界和无标度等复杂网络特征的MCESN能够获得较优的预测结果.通过Monte Carlo仿真实验表明,该模型不仅训练算法简单,而且与常规回响状态网络比较,预测结果的精度更高、标准差更小. 关键词： 混沌时间序列预测 回响状态网络 复杂网络 Ω复杂性')" href="#">Ω复杂性     

统计物理和复杂系统专题编者按

从20世纪中叶至今,复杂系统研究迅速发展,成为了引人注目并具有广泛应用的新领域.复杂系统要么具有结构的复杂性,要么具有演化的复杂性,在多数情况下二者兼具.不同于传统物理学通常处理的规则介质,许多复杂系统具有复杂结构,近年来受到极大关注的复杂网络结构就是其中最典型的代表.同时复杂系统也可表现为演化行为的多样性和复杂性.即便系统结构并不复杂,系统中的非线性相互作用可能产生复杂的演化行为,包括:形形色色的不稳定性;丰富的斑图动力学;各种各样的自组织、涌现及进化行为等等.物理学从一开始就深深进入了复杂系统研究领域,其中统计物理无疑是研究和理解复杂系统最主要的工具.     

激波与复杂流动专题序言

激波是指传播速度大于声速的扰动波波面前后流场速度、温度、压力等物理量呈现强间断.激波及其诱导的复杂流动广泛存在于核聚变能源、航空发动机、国防尖端武器等重大工程应用中已成为高速流动领域的重要前沿研究方向在高速空气动力学、涡动力学、流动稳定性、湍流生成演化机理等方面有着重大的科学意义.目前我国学科前沿研究和国家空天科技领域的重大需求带给激波和激波管领域的科技工作者一个新的机遇.然而由于在实际工程中存在极端环境条件已有实验数据非常有限缺乏深刻的物理机理认识深入开展与之相关的基础科学问题研究至关重要.     

大数据分析技术在装备监测系统中应用研究

针对装备状态监测系统中长期积累的大量数据缺乏有效分析手段、利用率低等问题,对装备监测系统中存储的在线监测数据和积累的历史数据,建立可分析挖掘的大数据集;运用数据分析和机理分析的方法建立比较模型,采用异步信息融合的算法对数据进行处理,利用大数据的多尺度特性研究装备生命周期的分析预测、优化运行、预知维修等目标,提高了装备运用知识的获取速度,有利于构建完整的装备生命周期预测诊断体系。     

低信噪比条件下多节点声呐目标跟踪算法*

低信噪比条件下,单个主动或单个被动声呐节点难以实现目标跟踪。多节点声呐系统希望通过增加探测节点提高系统探测能力,但其性能提高与否取决于选择合适的数据融合算法。本文利用双节点声呐试验数据研究低信噪比条件下的目标跟踪方法,采用“结合置信度水平的表决融合”算法对多个探测节点得到的数据进行融合,既考虑了目标回波信号的信噪比特性,又考虑了目标运动的连续性特征,还考虑了各节点探测结果的决策优化,最终实现较高精度的目标跟踪。算法实现了数据级、特征级和决策级的统一、融合,通过对判决依据进行量化、分层,简化判决的复杂性。试验数据处理结果表明,该方法能较好地解决低信噪比条件下多节点声呐目标跟踪问题,目标跟踪精度较高。     

散斑及压缩计算成像研究进展

计算成像是集光学、计算科学、信息科学于一体的新兴交叉领域技术。该技术基于多维光场调控与解调的信息传输原理,利用前端光电成像系统与后端数据处理的“一体化设计”,解决光场信息维度与探测维度不匹配的问题,从而有效提升感知能力和探测性能,目前已成为光电成像领域的前沿方向。其中,散斑成像能够通过调控散斑场来实现强散射光成像,打破了光散射妨碍成像的传统观点;空域和时域压缩计算成像通过对光场信号的编码,能够突破半导体工艺、大量数据传递与处理对高分辨率、高速探测器的限制;压缩计算光谱成像结合光学调制、复用探测与计算重构,解决了传统光谱成像中系统复杂、数据采集效率低和分辨率受限的问题。详细介绍这3类计算成像模式的原理方法和最新研究进展,分析当前尚存的问题,并对这类技术的未来发展方向进行了展望。     

Dissipative Structures,Organisms and Evolution

Self-organization in nonequilibrium systems has been known for over 50 years. Under nonequilibrium conditions, the state of a system can become unstable and a transition to an organized structure can occur. Such structures include oscillating chemical reactions and spatiotemporal patterns in chemical and other systems. Because entropy and free-energy dissipating irreversible processes generate and maintain these structures, these have been called dissipative structures. Our recent research revealed that some of these structures exhibit organism-like behavior, reinforcing the earlier expectation that the study of dissipative structures will provide insights into the nature of organisms and their origin. In this article, we summarize our study of organism-like behavior in electrically and chemically driven systems. The highly complex behavior of these systems shows the time evolution to states of higher entropy production. Using these systems as an example, we present some concepts that give us an understanding of biological organisms and their evolution.     

Investigating the topology of interacting networks

Network theory provides various tools for investigating the structural or functional topology of many complex systems found in nature, technology and society. Nevertheless, it has recently been realised that a considerable number of systems of interest should be treated, more appropriately, as interacting networks or networks of networks. Here we introduce a novel graph-theoretical framework for studying the interaction structure between subnetworks embedded within a complex network of networks. This framework allows us to quantify the structural role of single vertices or whole subnetworks with respect to the interaction of a pair of subnetworks on local, mesoscopic and global topological scales. Climate networks have recently been shown to be a powerful tool for the analysis of climatological data. Applying the general framework for studying interacting networks, we introduce coupled climate subnetworks to represent and investigate the topology of statistical relationships between the fields of distinct climatological variables. Using coupled climate subnetworks to investigate the terrestrial atmosphere’s three-dimensional geopotential height field uncovers known as well as interesting novel features of the atmosphere’s vertical stratification and general circulation. Specifically, the new measure “cross-betweenness” identifies regions which are particularly important for mediating vertical wind field interactions. The promising results obtained by following the coupled climate subnetwork approach present a first step towards an improved understanding of the Earth system and its complex interacting components from a network perspective.     

Observation of an anomalous discontinuous liquid-structure change with temperature

The nature of liquid structures with their changing behaviors remains an unsolved fundamental problem in many fields of science and technology. It has been widely accepted that liquid structures change gradually with temperature and/or pressure. With x-ray diffraction in the melt In-Sn80, however, we have confirmed that a temperature-dependent discontinuous structural change could occur in some binary liquids, which does not fall into any other up-to-date recognized liquid-liquid changes. This finding, together with the recently recognized pressure-induced liquid change, suggests that the conventional view on liquids should be revised.     

基于超表面的多光谱成像系统设计

超表面是一种人工制造的亚波长结构阵列平面,重量轻,易集成,可实现多种功能,被广泛应用于诸多领域。传统光谱成像系统依赖于色散元件及光程累积相位差实现不同波长的色散与聚焦,无法满足系统集成化需求。不同于传统光学元件依赖电磁波在介质中传播累积相位差,超表面依靠界面相位变化来进行相位调控,可实现十分轻薄的光学系统。研究传输相位型超表面,使用时域有限差分算法(FDTD算法)优化单元结构。将超表面引入光谱成像系统中,通过优化亚波长结构尺寸,进行结构排布,开展超表面光谱成像系统研究,实现多波长色散与聚焦独立调控。利用该方法,扫描不同单元结构参数对相位的影响,依照聚焦的相位分布针对不同波长设计对应的位相分布,仿真实现了一个波段范围为510～720 nm,焦距为2 mm,谱段数为八个的超表面多光谱成像系统。通过电磁仿真软件FDTD solutions和数据处理软件计算全模结构电场的远场分布,并分析了系统的成像性能。相比于传统光栅或棱镜分光结构,超表面光谱成像系统可有效减小系统体积,其超轻、超薄、便携特点解决了现有光谱成像系统的应用局限性,为小型化、轻量化光谱成像系统的研制提供了一种新的解决方案。     

Smart structures—The relevance of fiber optics

The concept of the smart structure integrates structural engineering, sensing, control systems, and actuation to provide a mechanical assembly that is capable of responding to its environment and/or loading conditions. The realization of the smart structure requires integration of skills in a variety of scientific and engineering disciplines ranging from mechanical engineering through materials science into signal processing, data analysis, sensing, and actuation. The sensing technology must have a number of key features of which the ability to take distributed measurements of various parameters throughout the structure is paramount. Therefore, fiber optics technology promises to have a significant role to play in the evolution of the smart structures concept. This article analyzes this role in detail, presents an assessment of the current state of the art in fiber optic technology related to smart structures, and presents a scenario for future developments.     

Solitary wave solutions of nonlinear financial markets :data-modeling-concept-practicing

This paper seeks to solve the difficult nonlinear problem in financial markets on the complex system theory and the nonlinear dynamics principle, with the data-model-concept-practice issue-oriented reconstruction of the phase space by the high frequency trade data. In theory, we have achieved the differentiable manifold geometry configuration, discovered the Yang-Mills functional in financial markets, obtained a meaningful conserved quantity through corresponding space-time non-Abel localization gauge symmetry transformation, and derived the financial solitons, which shows that there is a strict symmetry between manifold fiber bundle and guage field in financial markets. In practical applications of financial markets, we have repeatedly carried out experimental tests in a fluctuant evolvement, directly simulating and validating the existence of solitons by researching the price fluctuations (society phenomena) using the same methods and criterion as in natural science and in actual trade to test the stock Guangzhou Proprietary and the futures Fuel Oil in China. The results demonstrate that the financial solitons discovered indicates that there is a kind of new substance and form of energy existing in financial trade markets, which likely indicates a new science paradigm in the economy and society domains beyond physics.      

智能材料——材料科学发展新趋势

材料的智能化代表了材料科学发展的最新方向，智能材料的研究主要是依照仿生学方法，采用各种先进复合技术，实现复杂材料体系的多功能复合，并最终实现材料智能能化和器件集成化，文章在简要介绍有关材料概念的基础上，总结了智能材料的设计思想，路线及合成技术途径，综述了最近国内外有关智能材料的发展动向及研究进展，指出了一些应用背景及现在面临的问题。     

Solitary wave solutions of nonlinear financial markets: data-modeling-concept-practicing

This paper seeks to solve the difficult nonlinear problem in financial markets on the complex system theory and the nonlinear dynamics principle, with the data-model-concept-practice issue-oriented reconstruction of the phase space by the high frequency trade data. In theory, we have achieved the differentiable manifold geometry configuration, discovered the Yang-Mills functional in financial markets, obtained a meaningful conserved quantity through corresponding space-time non-Abel localization gauge symmetry transformation, and derived the financial solitons, which shows that there is a strict symmetry between manifold fiber bundle and guage field in financial markets. In practical applications of financial markets, we have repeatedly carried out experimental tests in a fluctuant evolvement, directly simulating and validating the existence of solitons by researching the price fluctuations (society phenomena) using the same methods and criterion as in natural science and in actual trade to test the stock Guangzhou Proprietary and the futures Fuel Oil in China. The results demonstrate that the financial solitons discovered indicates that there is a kind of new substance and form of energy existing in financial trade markets, which likely indicates a new science paradigm in the economy and society domains beyond physics.     

逆合成孔径成像激光雷达实包络成像算法

逆合成孔径激光成像雷达受激光调制技术以及回波相位信息易受大气湍流破坏的限制,采用常规的相位相干积累类方法得到目标二维高分辨图像很困难.针对这一情况,提出了一种基于逆Radon变换的实包络成像算法.利用回波距离脉冲压缩后的实包络信息,实现方位向的非相干积累,最终得到二维高分辨图像.通过该算法,成像系统可以使用非相干激光信号,在脉冲重复频率较低且存在大气湍流的情况下,也可以获得高质量的成像结果.仿真实验验证了此算法的有效性和优越性.