"大学物理"网络答疑

计算机及网络技术的发展，为网络教学提供了可能．本文从大学物理课外答疑的实际需要出发，结合大学物理课程特点，设计出大学物理课程“网络答疑”的实施方案并对实施情况进行介绍和分析。     

复杂网络研究概述

近年来，真实网络中小世界效应和无标度特性的发现激起了物理学界对复杂网路的研究热潮．复杂网络区别于以前广泛研究的规则网络和随机网络最重要的统计特征是什么?物理学家研究复杂网络的终极问题是什么?物理过程以及相关的物理现象对拓扑结构是否敏感?物理学家进入这一研究领域的原因和意义何在?复杂网络研究领域将来可能会向着什么方向发展?文章围绕上述问题，从整体上概述了复杂网络的研究进展．     

大学物理运用网络教学的有益尝试

大学物理课程运用网络教学非常必要，探讨如何制作网络课件、课堂教学的组织与实施，以及如何使大学物理的网络教学得以拓展，及其他探索与体会．     

计算机通信网络的防雷技术

鉴于近年来计算机通信网络遭受雷击损坏的情况日益严重，因此如何对计算机通信网络实施切实有效的防雷保护，保证系统安全可靠的运行，成为当前一项紧迫的重要课题．本文首先通过对计算机通信网络系统遭受雷击损坏的情况进行统计调查和现场勘测，以及对其相应电路模型的理论分析和模拟试验论证，较详细地分析了计算机通信网络系统遭受雷击损害的主要原因以及可能的侵入途径．在此基础上，介绍了如何通过模拟雷电冲击试验对计算机通信网络接口的雷电冲击伏－安特性进行测试研究，为制定计算机通信系统保护方案提供数据依据．最后，文章重点阐述了计算机通信网络系统的防雷保护方案，其中主要介绍了计算机通信网络接口或通信设备的防雷装置及其安装要求以及通信网络线路和地线回路的布放方式、相应的屏蔽措施等方面的问题．     

小世界网络的临界阈值

“小世界”网络可以为真实世界提供大量的信息和各种状态的模拟，例如真实世界中的互联网到供电的电力网，从生活中常发生的流行病传播到大选时的民意测验等都是一种小世界网络．一个“小世界”网络一般包含一定数量的网点，称为网络中心．它们具有非常广泛的联系，通常可以从一个网络中心经过简单的几步就能进行到其它网点．     

关于探究式教学中"分析与论证"要素的若干解读

探究式教学中的“分析与论证”是指学习者在探究过程中，在获得实证的基础上，将探究结果与自己原有的知识联系起来，运用分析、综合、归纳、演绎等科学研究方法，找到事件的因果关系或其他解释，形成超越学生原有知识和当前观察结果的新的理解．“分析与论证”是构成探究式学习过程中的诸多要素之一．那么，分析论证在科学探究中有什么意义？高中物理新课标对“分析论证”要素提出了什么要求？分析论证要素与探究要素之间的关系如何？教学中如何引导学生进行分析论证？本文试围绕这些问题，谈谈对分析论证要素的若干认识．     

信息技术与物理实验整合的理论和实践

如今已进入信息时代，无处不在的信息技术，无时无刻不在改变我们的工作、学习和生活．在教学中，信息技术也开始挑战传统教学手段，网络和多媒体技术使师生的眼前一亮，原来世上还有这样的技术能这样地使我们事半功倍，能这样地扩大我们的视野!信息技术的发展带动了教育技术的改革创新，使枯燥的教学变成了生动的游戏．如何实现以“教师为主导、以学生为主体”?如何培养学生的创新意识和动手能力?     

"量身定做"单光子波包:在量子网络中控制光子/自旋量子界面

文章简要地介绍了如何在量子网络中控制量子界面动力学以实现静态量子比特和动态量子比特的相互转换．具体言之，该界面由半导体量子点、固体光学微腔以及光学波导管构成，静态及动态比特分别为量子点中的电子自旋和波导管中的单光子波包所携带．界面动力学的控制则是基于对量子点、微腔和波导管耦合系统的量子电动力学的严格求解．据此可实现网络中两个远距离节点间的量子态传输、交换以及确定性的建立量子纠缠等量子操作．上述量子界面亦可用于任意指定波形的单光子源或者单光子探测装置。     

例析两种"水位落差"

高三物理复习阶段的综合练习中，经常会遇到水电站和潮汐电站这类题目．学生在分析这类题目时，“落差”就往往成为解决这类题目的瓶颈，也是决定这类问题能不能正确解答的关键所在．如何解决?只有找到这二类“落差”的本质．下面就这二类问题的落差作一比较．     

教科书的内容应当重视科学发生的过程--漫谈课程标准《高中物理必修1》的编写思想

在《普通高中物理课程标准(实验)》(以下简称《课标》)中，关于教科书的编写建议部分，在内容选择上提出了6条意见，其中有一条是“教科书的内容应当重视科学发生的过程”．如何来理解这条意见?在教科书的编写中又如何实现?下面谈一谈我们的认识与做法．     

Stresses in isostatic granular systems and emergence of force chains

Progress is reported on several questions that bedevil understanding of granular systems: (i) Are the stress equations elliptic, parabolic, or hyperbolic? (ii) How can the often-observed force chains be predicted from a first-principles continuous theory? (iii) How do we relate insight from isostatic systems to general packings? Explicit equations are derived for the stress components in two dimensions including the dependence on the local structure. The equations are shown to be hyperbolic and their general solutions, as well as the Green function, are found. It is shown that the solutions give rise to force chains, and the explicit dependence of the force chains trajectories and magnitudes on the local geometry is predicted. Direct experimental tests of the predictions are proposed. Finally, a framework is proposed to relate the analysis to nonisostatic and more realistic granular assemblies.     

Demystifying the Light Source Experience

How does a synchrotron work? What is an X-ray laser? How can light sources help solve research problems? How do X-rays interact with matter? What is X-ray Absorption Spectroscopy (XAS)? Transmission X-ray Microscopy (TXM)? Small Angle X-ray Scattering (SAXS)?

These may seem like odd questions for scientists who are already familiar with and rely on access to light source techniques and instrumentation as an essential part of their research. However, if you put yourself in the shoes of a new researcher, you would likely ask these same questions and find the whole topic rather mysterious. Recognizing these difficulties, a workshop was developed to lower the activation barrier for researchers wanting to incorporate light source science into their research. The talks were video recorded and are available online as a resource to the community (https://itunes.apple.com/itunes-u/slac-conferences/id511971711).     

Hierarchical organization unveiled by functional connectivity in complex brain networks

How do diverse dynamical patterns arise from the topology of complex networks? We study synchronization dynamics in the cortical brain network of the cat, which displays a hierarchically clustered organization, by modeling each node (cortical area) with a subnetwork of interacting excitable neurons. We find that in the biologically plausible regime the dynamics exhibits a hierarchical modular organization, in particular, revealing functional clusters coinciding with the anatomical communities at different scales. Our results provide insights into the relationship between network topology and functional organization of complex brain networks.     

Some minimal notes on notation and minima: A comment on “How particular is the physics of the free energy principle?” by Aguilera,Millidge, Tschantz,and Buckley

We comment on a technical critique of the free energy principle in linear systems by Aguilera, Millidge, Tschantz, and Buckley, entitled “How Particular is the Physics of the Free Energy Principle?” Aguilera and colleagues identify an ambiguity in the flow of the mode of a system, and we discuss the context for this ambiguity in earlier papers, and their proposal of a more adequate interpretation of these equations. Following that, we discuss a misinterpretation in their treatment of surprisal and variational free energy, especially with respect to their gradients and their minima. In sum, we argue that the results in the target paper are accurate and stand up to rigorous scrutiny; we also highlight that they, nonetheless, do not undermine the FEP.     

Road traffic: A case study of flow and path-dependency in weighted directed networks

How much can we tell about flows through networks just from their topological properties? Whereas flow distributions of river basins, trees or cardiovascular systems come naturally to mind, more complex topologies are not so immediate, especially if the network is large and heterogeneously directed. Our study is motivated by the question of how the distribution of path-dependent trails in directed networks is correlated to the distribution of network flows. As an example we have studied the path-dependencies in closed trails in four metropolitan areas in England and the USA and computed their global and spatial correlations with measured traffic flows. We have found that the heterogeneous distribution of traffic intensity is mirrored by the distribution of agglomerate path-dependency and that high traffic roads are packed along corridors at short-to-medium trail lengths from the ensemble of nodes.     

Graph dynamical networks for forecasting collective behavior of active matter

After decades of theoretical studies, the rich phase states of active matter and cluster kinetic processes are still of research interest. How to efficiently calculate the dynamical processes under their complex conditions becomes an open problem. Recently, machine learning methods have been proposed to predict the degree of coherence of active matter systems. In this way, the phase transition process of the system is quantified and studied. In this paper, we use graph network as a powerful model to determine the evolution of active matter with variable individual velocities solely based on the initial position and state of the particles. The graph network accurately predicts the order parameters of the system in different scale models with different individual velocities, noise and density to effectively evaluate the effect of diverse condition. Compared with the classical physical deduction method, we demonstrate that graph network prediction is excellent, which could save significantly computing resources and time. In addition to active matter, our method can be applied widely to other large-scale physical systems.     

Energetics: An emerging frontier in cellular mechanosensing: Reply to comments on “Cellular mechanosensing of the biophysical microenvironment: A review of mathematical models of biophysical regulation of cell responses”

How do cells can sense the substrate stiffness? Our recent review highlighted a range of theoretical models and simulations that have been proposed to answer this important question. In response to this review, three leading groups in the field noted some important omissions not only from our review itself but also from the field. These groups noted, correctly, that much of our understanding of cellular mechanosensing arises from models that take advantage of equilibrium thermodynamics, and that this is inappropriate because living cells are never in thermodynamic equilibrium. In this response, we highlight some promising research aimed at resolving this conundrum.     

Density functional theory simulations of water–metal interfaces: waltzing waters, a novel 2D ice phase, and more

There are few molecules, if any, more important than water. Yet remarkably little is known about how it interacts with solid surfaces, particularly at the all important atomic level. This is true despite widespread general interest and compelling environmental and economic incentives. Here, I will discuss detailed density-functional theory studies aimed at putting our understanding of water–solid interfaces, specifically water–metal interfaces, on a much firmer footing. In this paper, I will attempt to answer some key questions: Where do isolated water monomers adsorb on flat metal surfaces? How do water monomers diffuse across metal surfaces? How do water dimers adsorb and diffuse across metal surfaces? What factors control the structure and stability of water bilayers on metal surfaces?     

Kinetics and dynamics of muon localisation and trapping

The physics of muons in solids involved three basic questions: Where do muons go? Through which states do they pass during their lifetime? How can we establish mechanisms for these solid state processes? This paper discusses the underlying factors of quantum diffusion, the dynamics of trapping, and the importance of metastable states. A further central factor is the random strain present in even the best crystals, and its character and influence are outlined. I shall summarise the growing evidence for the importance of transient states in semiconductors, metal hydrides and in metals like Al and Cu, and indicate some of the consequences of the non-equilibrium behaviour.