一维冲击波和爆轰波计算程序SSS

本文叙述一维程序SSS的理论和结构。介质采用流体弹塑性模型。爆轰反应有四种可选方式:Arrhenius律、C-J比容法、方波法和Forest Fire方程。爆轰产物可选用HOM或JWL状态方程。SSS程序的特殊功能有,激光效应、爆轰增长、强爆炸波、散心爆轰和瞬时爆轰等,初始起爆或能量释放位置可任意设定。本程序部分参考了美国洛斯阿拉莫斯实验室的一维程序SIN。本文列举的算例把这两个程序作了比较。     

The Antiferromagnetic Correlations in the Half—Filled Double—Exchange Model at Finite Temperature

We extend a previous result of ours [G.S.Tian,Phys.Rev.B63 (2001) 224413] on the antiferromagnetic spin correlations in the half-filled Hubbard model at finite temperature to the double-exchange model.To overcome the mathematical difficulty cused by the S=3/2 localized spin freedom in this model,we apply both Zener‘s argument and the finite-temperature spin-reflection-positivity method to show rigorously that,at any temperature T,the spin correlations in the half-filled double-exchange model are predominantly antiferromagnetic.This conclusion is completely consistent with the experimental observations and the previous theoretical results by approximate methods.     

Heisenberg-Integrable Spin Systems

We investigate certain classes of integrable classical or quantum spin systems. The first class is characterized by the recursively defined property P saying that the spin system consists of a single spin or can be decomposed into two uniformly coupled or disjoint subsystems with property P. For these systems the time evolution can be explicitly calculated. The second class consists of spin systems where all non-zero coupling constants have the same strength (spin graphs) possessing N − 1 independent, commuting constants of motion of Heisenberg type. These systems are shown to have the above property P and can be characterized as spin graphs not containing chains of length four as vertex-induced sub-graphs. We completely enumerate and characterize all spin graphs up to N = 5 spins. Applications to the construction of symplectic numerical integrators for non-integrable spin systems are briefly discussed.      

Order preservation in a generalized version of Krause’s opinion dynamics model

Krause’s model of opinion dynamics has recently been the subject of several studies, partly because it is one of the simplest multi-agent systems involving position-dependent changing topologies. In this model, agents have an opinion represented by a real number and they update it by averaging those agent opinions distant from their opinion by less than a certain interaction radius. Some results obtained on this model rely on the fact that the opinion orders remain unchanged under iteration, a property that is consistent with the intuition in models with simultaneous updating on a fully connected communication topology.Several variations of this model have been proposed. We show that some natural variations are not order preserving and therefore cause potential problems with the theoretical analysis and the consistence with the intuition. We consider a generic version of Krause’s model parameterized by an “influence function” that encapsulates most of the variations proposed in the literature. We then derive a necessary and sufficient condition on this function for the opinion order to be preserved.     

Community structure of complex software systems: Analysis and applications

Due to notable discoveries in the fast evolving field of complex networks, recent research in software engineering has also focused on representing software systems with networks. Previous work has observed that these networks follow scale-free degree distributions and reveal small-world phenomena, while we here explore another property commonly found in different complex networks, i.e. community structure. We adopt class dependency networks, where nodes represent software classes and edges represent dependencies among them, and show that these networks reveal a significant community structure, characterized by similar properties as observed in other complex networks. However, although intuitive and anticipated by different phenomena, identified communities do not exactly correspond to software packages. We empirically confirm our observations on several networks constructed from Java and various third party libraries, and propose different applications of community detection to software engineering.     

基于多源卫星多光谱遥感数据的过火面积估算研究

露天生物质燃烧是重要的大气污染物排放源,导致空气质量恶化并引起气候变化。卫星遥感数据能够提供大尺度、多时相的监测信息,然而燃烧火点监测和火烧迹地监测两种方式都存在着局限性。以美国东南部地区为研究区域,通过结合卫星遥感获取的高分辨率燃烧面积数据及多时相的燃烧火点数据,建立时空匹配模型估算露天生物质燃烧过火面积。通过分析植被燃烧前后的光谱变化特征,基于高分辨率的Landsat-5 TM4波段(0.84 μm)与7波段(2.22 μm)数据, 利用差分归一化燃烧比(dNBR: the differential normalized burn ratio)提取燃烧面积数据;而燃烧火点数据则通过分析燃烧植被的热红外光谱特征利用MODIS 4与11 μm波段数据提取。结果显示,该地区燃烧面积与燃烧火点数量之间相关系数达0.63,并且二者之间的比例关系随植被类型而发生变化,林地、草地、灌木、耕地和沼泽五种植被类型对应的像元燃烧面积分别为0.69,1.27,0.86,0.72和0.94 km2。通过与美国火灾中心(national interagency fire center, NIFC)地面调查数据比对,模型估算的美国东南部过火面积数据较为精确,而同期的MODIS燃烧面积产品(MCD45)及燃烧源清单产品(global fire emissions database, GFED)遗漏了该区域大量的小面积燃烧事件。因此,本研究建立的过火面积估算模型能够提供更为精确的排放源参数信息,有利于区域空气质量模式准确地模拟露天生物质燃烧排放状况。     

The distribution of landed property

The distribution of property is established through various mechanisms. In this paper we study the acreage distribution of land plots owned by natural persons in the Zlín Region of the Czech Republic. We show that the data are explained in terms of a simple model in which the inheritance and market behavior are combined.     

Integrated BVRIJHK photometry of galactic globular clusters

Summary We present preliminary BVRI photometric data of 22 galactic globular clusters of the Southern hemisphere. The observations were carried out at the ESO Observatory, during two observing runs in August 1988 (VRI) and March 1989 (BVRI). In both periods half of the total number of nights was used to perform near-infrared (JHK) photometry of the same clusters: the goal of this quasi-contemporary photometry was to obtain a homogeneus sample of galactic clusters photometric observations, on a wavelength range as wide as possible. Paper presented at the V Cosmic Physics National Conference, S. Miniato, November 27–30, 1990.     

On the nature of striped phases: striped phases as a stage of “melting” of 2D crystals

We discuss striped phases as a state of matter intermediate between two extreme states: a crystalline state and a segregated state. We argue that this state is very sensitive to weak interactions, compared to those stabilizing a crystalline state, and to anisotropies. Moreover, under suitable conditions a 2D system in a striped phase decouples into (quasi) 1D chains. These observations are based on results of our studies of an extension of a microscopic quantum model of crystallization, proposed originally by Kennedy and Lieb.     

Integrable Noncommutative Equations on Quad-graphs. The Consistency Approach

We extend integrable systems on quad-graphs, such as the Hirota equation and the cross-ratio equation, to the noncommutative context, when the fields take values in an arbitrary associative algebra. We demonstrate that the three-dimensional consistency property remains valid in this case. We derive the noncommutative zero curvature representations for these systems, based on the latter property. Quantum systems with their quantum zero curvature representations are particular cases of the general noncommutative ones.     

Agreement dynamics of finite-memory language games on networks

We propose a Finite-Memory Naming Game (FMNG) model with respect to the bounded rationality of agents or finite resources for information storage in communication systems. We study its dynamics on several kinds of complex networks, including random networks, small-world networks and scale-free networks. We focus on the dynamics of the FMNG affected by the memory restriction as well as the topological properties of the networks. Interestingly, we found that the most important quantity, the convergence time of reaching the consensus, shows some non-monotonic behaviors by varying the average degrees of the networks with the existence of the fastest convergence at some specific average degrees. We also investigate other main quantities, such as the success rate in negotiation, the total number of words in the system and the correlations between agents of full memory and the total number of words, which clearly explain the nontrivial behaviors of the convergence. We provide some analytical results which help better understand the dynamics of the FMNG. We finally report a robust scaling property of the convergence time, which is regardless of the network structure and the memory restriction.     

A preliminary investigation on the topology of Chinese and climate networks

Complex networks have been studied across many fields of science in recent years. In this paper, we give a brief introduction of networks, then follow the original works by Tsonis et al (2004, 2006) starting with data of the surface temperature from 160 Chinese weather observations to investigate the topology of Chinese climate networks. Results show that the Chinese climate network exhibits a characteristic of regular, almost fully connected networks, which means that most nodes in this case have the same number of links, and so-called super nodes with a very large number of links do not exist there. In other words, though former results show that nodes in the extratropical region provide a property of scale-free networks, they still have other different local fine structures inside. We also detect the community of the Chinese climate network by using a Bayesian technique; the effective number of communities of the Chinese climate network is about four in this network. More importantly, this technique approaches results in divisions which have connections with physics and dynamics; the division into communities may highlight the aspects of the dynamics of climate variability.     

Fast-ionic-conductor behavior of driven lattice-gas models

We discuss driven diffusive lattice-gas systems as a model for fast ionic conductors, derive associated hydrodynamic equations and expressions for transport coefficients, and compare mean-field theory, Monte Carlo results and experimental observations. The comparison between model and real behaviours helps to understand some properties of those materials which seem to be characterized by the occurrence of nonequilibrium steady states and phase transitions. In particular, our study suggests the existence in Nature of a novel (nonequilibrium) universality class.     

Trajectory divergence for coupled relaxation oscillators: Measurements and models

The exponential divergence of nearby phase space trajectories is a hallmark of nonperiodic (chaotic) behavior in dynamical systems. We present the first laboratory of measurements of divergence rates (or characteristic exponents), using a system of coupled tunnel diode relaxation oscillators. This property of sensitive dependence on initial conditions is reliably associated with broadband spectra, and both methods are used to characterize the motion as a function of the coupling strength and natural frequency ratio of the two oscillators. A simple piecewise linear model correctly predicts the major periodic and non-periodic regions of the parameter space, thus confirming that the chaotic behavior involves only a few degrees of freedom.Work supported by the National Science Foundation and the Research Corporation.     

The elastic theory of a single DNA molecule

We study the elastic responses of double-(ds) and single-stranded (ss) DNA at external force fields. A double-strand-polymer elastic model is constructed and solved by path integral methods and Monte Carlo simulations to understand the entropic elasticity, cooperative extensibility, and supercoiling property of dsDNA. The good agreement with experiments indicates that short-ranged base-pair stacking interaction is crucial for the stability and the high deformability of dsDNA. Hairpin-coil transition in ssDNA is studied with generating function method. A threshold force is needed to pull the ssDNA hairpin patterns, stabilized by base pairing and base-pair stacking, into random coils. This phase transition is predicted to be of first order for stacking potential higher than some critical level, in accordance with experimental observations.     

Review of the Forest fire model for high explosives

Forest fire is a burn model for reactive hydro simulations that is widely used to describe both initiation and propagation of detonation waves in solid high explosives. Here we thoroughly review the assumptions of the model. In analogy with Whitham–Chisnell shock dynamics, we derive the Forest fire rate based on a characteristic analysis of a shock-to-detonation transition. Code issues with implementing the Forest fire model are also discussed. The analysis leading to the Forest fire rate is more general than the simplifying assumptions used by the model. The Forest fire analysis provides important constraints needed for any burn model to fit shock initiation data. This data is fundamental to ignition sensitivity of high explosives.     

Hopping Wave Function in Quantum Kicked Systems

A model of a kicked particle in an infinite potential well is studied. We presented the wave functions of the system applying a direct perturbation method. Theoretical analyses and numerical calculations show that the wave function is discontinuous across each kicking instant. As an extension of this result, we find that the wave function of any periodically kicked system usually has this property. Therefore, at each kicking instant, the wave function chooses randomly between the limits on either side and may be hopping.     

Dissipative or conservative cosmology with dark energy?

All evolutional paths for all admissible initial conditions of FRW cosmological models with dissipative dust fluid (described by dark matter, baryonic matter and dark energy) are analyzed using dynamical system approach. With that approach, one is able to see how generic the class of solutions leading to the desired property—acceleration—is. The theory of dynamical systems also offers a possibility of investigating all possible solutions and their stability with tools of Newtonian mechanics of a particle moving in a one-dimensional potential which is parameterized by the cosmological scale factor. We demonstrate that flat cosmology with bulk viscosity can be treated as a conservative system with a potential function of the Chaplygin gas type. We characterize the class of dark energy models that admit late time de Sitter attractor solution in terms of the potential function of corresponding conservative system. We argue that inclusion of dissipation effects makes the model more realistic because of its structural stability. We also confront viscous models with SNIa observations. The best fitted models are obtained by minimizing the χ² function which is illustrated by residuals and χ² levels in the space of model independent parameters. The general conclusion is that SNIa data supports the viscous model without the cosmological constant. The obtained values of χ² statistic are comparable for both the viscous model and ΛCDM model. The Bayesian information criteria are used to compare the models with different power-law parameterization of viscous effects. Our result of this analysis shows that SNIa data supports viscous cosmology more than the ΛCDM model if the coefficient in viscosity parameterization is fixed. The Bayes factor is also used to obtain the posterior probability of the model.     

Message Passing-Based Inference for Time-Varying Autoregressive Models

Time-varying autoregressive (TVAR) models are widely used for modeling of non-stationary signals. Unfortunately, online joint adaptation of both states and parameters in these models remains a challenge. In this paper, we represent the TVAR model by a factor graph and solve the inference problem by automated message passing-based inference for states and parameters. We derive structured variational update rules for a composite “AR node” with probabilistic observations that can be used as a plug-in module in hierarchical models, for example, to model the time-varying behavior of the hyper-parameters of a time-varying AR model. Our method includes tracking of variational free energy (FE) as a Bayesian measure of TVAR model performance. The proposed methods are verified on a synthetic data set and validated on real-world data from temperature modeling and speech enhancement tasks.     

Discrete chaotic cryptography

In the paper we propose a new method of constructing cryptosystems utilising a nonpredictability property of discrete chaotic systems. We formulate the requirements for such systems to assure their safety. We also give examples of practical realisation of chaotic cryptosystems, using a generalisation of the method presented in [7]. The proposed algorithm of encryption and decryption is based on multiple iteration of a certain dynamical chaotic system. We assume that some part of the initial condition is a plain message. As the secret key we assume the system parameter(s) and additionally another part of the initial condition.