A finite volume method for approximating 3D diffusion operators on general meshes

A finite volume method is presented for discretizing 3D diffusion operators with variable full tensor coefficients. This method handles anisotropic, non-symmetric or discontinuous variable tensor coefficients while distorted, non-matching or non-convex n-faced polyhedron meshes can be used. For meshes of polyhedra whose faces have not more than four edges, the associated matrix is positive definite (and symmetric if the diffusion tensor is symmetric). A second-order (resp. first-order) accuracy is numerically observed for the solution (resp. gradient of the solution).     

太赫兹通信中的一种高速并行均衡算法及其FPGA实现

基于驰豫超前变换中的超前展开、求和近似和延时近似技术,提出了流水线并行自适应CMA盲均衡算法。利用基于迭代短卷积的并行FIR滤波算法分析了提出的并行自适应盲均衡算法的滤波部分的高效实现结构;再利用基于组合短卷积的并行自适应系数更新算法分析了提出的并行均衡算法的系数更新部分的高效实现结构,从而得到了基于短卷积的流水线并行自适应盲均衡的完整实现框图,并分析了各模块的流水线延时需满足的关系。最后对该并行自适应盲均衡算法进行了FPGA量化实现,并通过MATLAB仿真及实际FPGA实现结果的对比,验证了本并行均衡算法的正确性和有效性。     

太赫兹通信中的一种高速并行均衡算法及其FPGA实现

基于驰豫超前变换中的超前展开、求和近似和延时近似技术,提出了流水线并行自适应CMA盲均衡算法。利用基于迭代短卷积的并行FIR滤波算法分析了提出的并行自适应盲均衡算法的滤波部分的高效实现结构;再利用基于组合短卷积的并行自适应系数更新算法分析了提出的并行均衡算法的系数更新部分的高效实现结构,从而得到了基于短卷积的流水线并行自适应盲均衡的完整实现框图,并分析了各模块的流水线延时需满足的关系。最后对该并行自适应盲均衡算法进行了FPGA量化实现,并通过MATLAB仿真及实际FPGA实现结果的对比,验证了本并行均衡算法的正确性和有效性。     

一种改良的啁啾变换算法及其应用

快速啁啾算法引入两次快速傅里叶变换（FFT）及一个解析高斯核,计算复杂度低于卷积算法.通过对啁啾算法实现过程进行的改进,避免了该算法在实现过程中存在的一些问题,比如输出窗口小、信号丢失、计算复杂度稍大等缺点. 把算法用于简单的可求得解析解的系统并与之做比较. 对高斯函数,最大误差通常在10^-15数量级,而对矩形函数,由于受FFT算法计算精度的影响,误差在10^-3数量级,但这并不影响算法的性能. 最后把算法用于一种典型的标量衍射系统及分数傅里叶变换的计算,获得了很好的结果. 关键词： 快速啁啾算法 啁啾Z变换 菲涅耳变换 分数傅里叶变换     

The G-Scheme: A framework for multi-scale adaptive model reduction

The numerical solution of mathematical models for reaction systems in general, and reacting flows in particular, is a challenging task because of the simultaneous contribution of a wide range of time scales to the system dynamics. However, the dynamics can develop very-slow and very-fast time scales separated by a range of active time scales. An opportunity to reduce the complexity of the problem arises when the fast/active and slow/active time scales gaps becomes large. We propose a numerical technique consisting of an algorithmic framework, named the G-Scheme, to achieve multi-scale adaptive model reduction along-with the integration of the differential equations (DEs). The method is directly applicable to initial-value ODEs and (by using the method of lines) PDEs. We assume that the dynamics is decomposed into active, slow, fast, and when applicable, invariant subspaces. The G-Scheme introduces locally a curvilinear frame of reference, defined by a set of orthonormal basis vectors with corresponding coordinates, attached to this decomposition. The evolution of the curvilinear coordinates associated with the active subspace is described by non-stiff DEs, whereas that associated with the slow and fast subspaces is accounted for by applying algebraic corrections derived from asymptotics of the original problem. Adjusting the active DEs dynamically during the time integration is the most significant feature of the G-Scheme, since the numerical integration is accomplished by solving a number of DEs typically much smaller than the dimension of the original problem, with corresponding saving in computational work. To demonstrate the effectiveness of the G-Scheme, we present results from illustrative as well as from relevant problems.     

A roe-average algorithm for a granular-gas model with non-conservative terms

A Roe-average algorithm has been derived for a granular-gas model, proposed by Goldshtein and Shapiro [Goldshtein, Shapiro, Mechanics of collisional motion of granular materials: Part 1. General hydrodynamic equations, J. Fluid Mech. 282 (1995) 75–114], which contains non-conservative terms in the Euler-like hyperbolic governing equations apart from sink terms, which arise from inelastic collision of granules and are present only in the energy equation. The non-conservative terms introduce non-isentropic effects in acoustic-wave propagation within granular media and they also contribute to the Rankine–Hugoniot relations across a discontinuity. A Roe-average algorithm, based on the same granular-gas model, was derived in the literature [V. Kamenetsky, A. Goldshtein, M. Shapiro, D. Degani, Evolution of a shock wave in a granular gas, Phys. Fluids, 12 (2000) 3036–3049] which then required the implementation of a shock-fitting technique at a discontinuity. In the present work, Roe-averaged variables have been obtained from the Rankine–Hugoniot jump relations and the non-conservative terms have been incorporated in the numerical flux formula consistent with upwind principles associated with the granular speed of sound. Results for unsteady one-dimensional granular flows, colliding with a wall, demonstrate the capability of the proposed algorithm to capture strong shocks in addition to flow features not found in molecular gases, such as a fluidized region downstream of the shock and a compacted solid-block region adjacent to the wall.     

An improved shooting algorithm and its application to high-power fiber lasers

An improved shooting algorithm for high-power fiber laser is proposed based on the relation of the two-end boundary laser powers. By the improved shooting algorithm, the evolutions of the pump and laser powers along the fiber position for Yb-doped and Tm-doped high-power double-clad fiber lasers with the laser scattering loss are analyzed. The results prove that the improved shooting algorithm can be efficient even if the pump power is up to kilowatt level, and the initial value can all be fast convergent as long as the initial guessed laser power is smaller than the truth value. So, this improved shooting algorithm can be used in high-power double-clad fiber lasers efficiently.     

总变差约束的数据分离最小图像重建模型及其Chambolle-Pock求解算法

基于优化的迭代法,可以结合压缩感知和低秩矩阵等稀疏优化技术高精度地重建图像.其中,总变差最小（total variation minimization,TV）模型是一种简单有效的优化模型.传统的约束TV模型,使用数据保真项为约束项,TV正则项为目标函数.本文研究TV约束的、数据分离最小（TV constrained,data divergence minimization,TVcDM）新型TV模型及其求解算法.详细推导了TVcDM模型的Chambolle-Pock（CP）算法,验证了模型及算法的正确性;分析了算法的收敛行为;评估了模型的稀疏重建能力;分析了模型参数的选择对重建的影响及算法参数对收敛速率的影响.研究表明,TVcDM模型有高精度稀疏重建能力;TVcDM-CP算法确保收敛,但迭代过程中有振荡现象;TV限对重建有重要影响,参数值过大会引入噪声而过小会模糊图像细节;算法参数的不同选取会导致不同的收敛速率.     

Scheme for purifying a general mixed entangled state and its linear optical implementation

We propose a scheme for purification of a general mixed entangled state. In this scheme, we start from a large number of general mixed entangled states and end up, after local operation and classical communication, with a smaller number of Bell diagonal states with higher entanglement. In particular, the scheme can purify one maximally entangled state from two entangled pairs prepared in a class of mixed entangled state. Furthermore we propose a linear optical implementation of the present scheme with polarization beam splitters and photon detectors.     

An improved TOA estimation algorithm based on denoised MVDR for B5G positioning

This paper proposes an improved minimum variance distortionless response (MVDR) based TOA estimation algorithm for 5G NR signals under multipath environments. The proposed algorithm achieves high resolution by exploiting a large number of subcarriers of 5G signals and reduces the dimension of the covariance matrix involved in MVDR substantially by utilizing a novel smoothing scheme. Since MVDR requires a relatively high signal-to-noise ratio (SNR), a denoising method is used to improve the TOA estimation performance. Simulation results show that the proposed algorithm achieves much higher resolution than the Bartlett beamformer (BF) and the TOA estimation accuracy remains high over a wide range of SNRs.     

An improved EEHEMT model for kink effect on AIGaN/GaN HEMT

In this paper, a new current expression based on both the direct currect （DC） characteristics of the A1GaN/GaN high election mobility transistor （HEMT） and the hyperbolic tangent function tanh is proposed, by which we can describe the kink effect of the A1GaN/GaN HEMT well. Then, an improved EEHEMT model including the proposed current expression is presented. The simulated and measured results of Ⅰ-Ⅴ, S-parameter, and radio frequency （RF） large-signal characteristics are compared for a self-developed on-wafer A1GaN/GaN HEMT with ten gate fingers each being 0.4-μm long and 125-p-m wide （Such an A1GaN/GaN HEMT is denoted as A1GaN/GaN HEMT （10 × 125 μm））. The improved large signal model simulates the Ⅰ-Ⅴ characteristic much more accurately than the original one, and its transconductance and RF characteristics are also in excellent agreement with the measured data.     

Particle filtering with path sampling and an application to a bimodal ocean current model

This paper introduces a recursive particle filtering algorithm designed to filter high dimensional systems with complicated non-linear and non-Gaussian effects. The method incorporates a parallel marginalization (PMMC) step in conjunction with the hybrid Monte Carlo (HMC) scheme to improve samples generated by standard particle filters. Parallel marginalization is an efficient Markov chain Monte Carlo (MCMC) strategy that uses lower dimensional approximate marginal distributions of the target distribution to accelerate equilibration. As a validation the algorithm is tested on a 2516 dimensional, bimodal, stochastic model motivated by the Kuroshio current that runs along the Japanese coast. The results of this test indicate that the method is an attractive alternative for problems that require the generality of a particle filter but have been inaccessible due to the limitations of standard particle filtering strategies.     

Curvatures,volumes and norms of derivatives for curves in Riemannian manifolds

The well-known formulas express the curvature and the torsion of a curve in R³${\mathbb{R}}^3$ in terms of euclidean invariants of its derivatives. We obtain expressions of this kind for all curvatures of curves in arbitrary Riemannian manifolds. Our motivation comes from physics. It follows that regular curves in Rⁿ${\mathbb{R}}^n$ are determined up to isometry by the norms of their n$n$ consecutive derivatives. We extend this fact to two-point homogeneous spaces.     

一种超混沌图像加密算法的安全性分析及其改进

根据Kerckhoff准则, 从选择明文攻击和选择密文攻击出发, 对一种超混沌图像加密算法进行分析,结果表明该算法密钥流与明文无关,并且一个明文字节只能影响一个密文字节,导致利用选择明文攻击和选择密文攻击能够以很小的计算代价破译密文.基于此,本文提出一种改进的超混沌图像加密算法,并进行了统计分析、差分分析、相关性分析及密钥敏感性测试.理论分析及仿真结果表明,改进算法不仅可以抵御选择明文攻击和选择密文攻击,而且具有较好的统计特性及差分特性等密码学特性. 关键词： 超混沌 选择明文攻击 选择密文攻击 Matlab分析     

An improved model for soil ionization around grounding system and its application to stratified soil

An improved model for taking into account the effect of the soil ionization around grounding system under lightning strike is proposed in this paper. In this model, the soil ionization region is assumed to retain 7% of its pre-ionization resistivity, which is consistent with the experimental results on soil ionization found in literature (Trans. SA Inst. Electr. Eng. (1988) 63; AIEE Trans. 61 (1942) 349; Proc. IEE 121(2) (1974) 123) and our own laboratory experiments (Time domain modelling of the response of grounding systems subjected to lightning currents, Licenciate Thesis, Uppsala University, 2003). Compared with modelling the soil ionization as an increase in the size of the ground conductor, the model presented here will not overestimate the beneficial influence of the soil ionization in reducing the ground potential rise, especially in high resistivity soil. The model is also applied to study the transient behaviour of grounding conductors in stratified soil under lightning strike including soil ionization. It shows that making the grounding conductor to penetrate the lower resistivity soil layer could help to decrease the ground potential rise at the injection point several times.     

Numerical study of a stochastic particle algorithm solving a multidimensional population balance model for high shear granulation

This paper is concerned with computational aspects of a multidimensional population balance model of a wet granulation process. Wet granulation is a manufacturing method to form composite particles, granules, from small particles and binders. A detailed numerical study of a stochastic particle algorithm for the solution of a five-dimensional population balance model for wet granulation is presented. Each particle consists of two types of solids (containing pores) and of external and internal liquid (located in the pores). Several transformations of particles are considered, including coalescence, compaction and breakage. A convergence study is performed with respect to the parameter that determines the number of numerical particles. Averaged properties of the system are computed. In addition, the ensemble is subdivided into practically relevant size classes and analysed with respect to the amount of mass and the particle porosity in each class. These results illustrate the importance of the multidimensional approach. Finally, the kinetic equation corresponding to the stochastic model is discussed.     

An embedding for general relativity and its implications for new physics

We show that any solution of the 4D Einstein equations of general relativity in vacuum with a cosmological constant may be embedded in a solution of the 5D Ricci-flat equations with an effective 4D cosmological “constant” Λ that is a specific function of the extra coordinate. For unified theories of the forces in higher dimensions, this has major physical implications. Authors Bahram Mashhoon and Paul Wesson belong to The S.T.M. Consortium, http://astro.uwaterloo.ca/~wesson.     

Exponential sine chaotification model for enhancing chaos and its hardware implementation

Chaotic systems have been intensively studied for their roles in many applications, such as cryptography, secure communications, nonlinear controls, etc. However, the limited complexity of existing chaotic systems weakens chaos-based practical applications. Designing chaotic maps with high complexity is attractive. This paper proposes the exponential sine chaotification model (ESCM), a method of using the exponential sine function as a nonlinear transform model, to enhance the complexity of chaotic maps. To verify the performance of the ESCM, we firstly demonstrated it through theoretical analysis. Then, to exhibit the high efficiency and usability of ESCM, we applied ESCM to one-dimensional (1D) and multi-dimensional (MD) chaotic systems. The effects were examined by the Lyapunov exponent and it was found that enhanced chaotic maps have much more complicated dynamic behaviors compared to their originals. To validate the simplicity of ESCM in hardware implementation, we simulated three enhanced chaotic maps using a digital signal processor (DSP). To explore the ESCM in practical application, we applied ESCM to image encryption. The results verified that the ESCM can make previous chaos maps competitive for usage in image encryption.     

一种适于光学实现的非线性神经网络模型及其蒙特卡洛学习算法

本文用计算机仿真研究了一种适于光学实现的非线性神经网络模型的存储客量α_c和寻址能力,提出了一个改进其触突互联矩阵的蒙特卡洛学习算法.数值研究表明,经过学习修正后的神经网络模型的寻址能力及存储容量都有较大的改进.     

Fast quantum search algorithm for databases of arbitrary size and its implementation in a cavity QED system

We propose a method for implementing the Grover search algorithm directly in a database containing any number of items based on multi-level systems. Compared with the searching procedure in the database with qubits encoding, our modified algorithm needs fewer iteration steps to find the marked item and uses the carriers of the information more economically. Furthermore, we illustrate how to realize our idea in cavity QED using Zeeman?s level structure of atoms. And the numerical simulation under the influence of the cavity and atom decays shows that the scheme could be achieved efficiently within current state-of-the-art technology.