量子卷积码的编译码方法

对于量子卷积码理论的研究旨在保护长距离通信中的量子信息序列. 定义了量子态的多项式表示形式，根据Calderbank-Shor-Steane(CSS)型量子码的构造方法，给出了CSS型量子卷积码的一种新的编译码方法，描述了编译码网络. 该方法将码字基态变换为信息多项式与生成多项式的乘积，然后用量子态上的多项式乘法操作实现编译码网络. 最后借鉴经典卷积码的译码思想，给出了具有线性复杂度的量子Viterbi算法. 关键词： 量子信息 量子卷积码 编译码 纠错算法     

基于算符正规乘积的若干厄米多项式关系式证明

主要利用量子力学的方法证明了厄米多项式的递推关系.另外,根据厄米多项式的表达式,得出了两个与厄米多项式有关的积分公式.     

厄米本征值问题的探究

给出了用探索性方法进行数学物理方法教学的一个案例.从厄米本征值问题出发,经过合情推理,归纳出厄米多项式的递推公式,并猜想出通项公式.该方法可以在传授知识的同时,培养学生的探索意识与创新能力.     

激光并行加工DM码实验研究

DM（data matrix）码信息存储容量大、编码范围广、可靠性高，是信息交流的重要载体。为了实现DM码并行加工方法，分析了DM码间距值与灰度值对识别时间的影响规律，并对不同情况下的DM码进行多次扫描，记录识读时间，确定了DM码识读成功的临界圆点直径为11像素，临界灰度值为220。在此基础上，设计了一种基于空间光调制器的DM码并行加工方法，并在石英玻璃内部进行了激光并行加工DM码实验验证，与传统的单光束激光标刻二维码的方式相比，加工效率得到了提高。     

类氧离子能级的递推公式

推广ＨＦ方程的微扰展开式，导出类氧离了的４５个组态能级的递推公式，该公式适用于２７≤Ｚ≤９２的类氧离子。     

谐振子薛定谔方程的超对称解法

通过构造哈密顿量与谐振子系统哈密顿量对易的超对称系统,量子谐振子的性质就可以通过对超对称系统的研究来得到.利用超对称系统的性质,在没有用到厄米多项式的情况下,给出了谐振子本征函数中展开系数间的递推关系,由递推关系可以直接得到本征函数.此方法下得到的归一化本征函数与用厄米多项式表达的本征函数完全相同,并且本征函数的宇称可以明显的显示出来.     

并行重叠/变形混合网格生成技术及其应用

为了适用于柔性变形、相对运动等复杂动边界问题，建立了并行环境下重叠和变形相结合的动态混合网格生成技术.通过计算区域分解以及分布式并行实现了重叠和变形技术的结合，其中重叠网格采用了并行化的隐式装配方法，并发展了两种并行化查询策略.变形网格则采用了并行化的径向基函数（RBF）插值方法.并行化动态网格生成方法大幅提高了动态网格生成效率，有利于处理大规模的动边界问题.在此基础上，发展了基于变形/重叠动态混合网格的流动/运动/控制一体化数值模拟方法，进一步改进了耦合模拟软件平台——HyperFLOW.典型应用算例证明了该动态混合网格技术及一体化算法的实用性.      

一种成像测量图像径向几何畸变的校正方法

通过对具有径向畸变的摄像机模型的分析,设计了一套求解图像径向几何畸变中心和畸变多项式系数的方案。首先,依据校正样板曲线的弯曲程度应用一元线性回归法和逐次逼近法求取光学图像的几何畸变中心,然后应用递推最小二乘法求解径向几何畸变的多项式系数,最后根据所得到的畸变中心和畸变多项式系数对图像进行校正得到满足要求的图像。仿真试验证明:该方法可以通过一次采集单幅图像对成像系统进行高精度标定,能够对成像测量系统的径向几何畸变进行一定精度的校正。实践证明:该方法通过图像处理的方法提高成像测量系统的精度,降低了系统的设计成本,可以作为成像测量系统中单独标定摄像机畸变参数的一种简单有效的方法。     

双变量厄米多项式递推关系与积分公式的简捷推导

基于正规乘积和反正规乘积性质与双变量厄米多项式的母函数形式,利用相干态表象完备性的高斯积分形式,系统而全面的导出双变量厄米多项式的算符恒等式、递推关系与积分公式,此推导方法简捷明了.     

无简并微扰公式的递推形式在Lipkin模型中的应用

本文给出了量子体系无筒并态微扰公式的递推形式．在微扰计算收敛的情况下，利用它可以方便地计算任意级的微扰近似．列出了在Ｌｉｐｋｉｎ可解模型下的理论计算结果．     

基于表面阻抗边界条件的等离子体薄涂层电磁散射的时域有限差分分析

基于表面阻抗边界条件时域有限差分(FDTD)方法研究了一维斜入射情况下非磁化等离子体薄涂层涂敷金属材料的电磁散射特性, 该方法忽略对薄层背景材料进行网格剖分, 大大减少了计算量. 首先推导了理想导体涂敷等离子体薄涂层的表面阻抗频域表达式, 然后代入边界条件并变换到时域, 再用分段线性递推卷积方法将时域表达式离散得到FDTD迭代式. 编程计算了垂直及斜入射情形下的平行极化和垂直极化反射系数, 通过验证算例与解析解对比, 结果表明该方法的准确性和有效性. 最后利用该方法分析了不同入射角对反射系数的影响.     

Nonlinear identification of NMR spin systems by adaptive filtering

In this paper, we present two new methods for identifying NMR spin systems. These methods are based on nonlinear adaptive filtering. The spin system is assumed to be time-invariant with memory. The first method uses a truncated discrete Volterra series to describe the nonlinear relationship between excitation (input) and system response (output). First-, second-, and third-order kernels of this series are estimated employing the least mean square (LMS) algorithm. Three parallel filters can then model the NMR spin system so that its output is no more than simple sum of three convolution products between combinations of the input signal and filters coefficients. It is also shown that the contribution of the Volterra second-order term to the total system response is neglected compared with the contributions of the first- and the third-order terms. In the second identification method, the output signal is related to the input signal through a recursive nonlinear difference equation with constant coefficients. The LMS algorithm is used again to estimate the equation coefficients. The two methods are validated with a simulated NMR system model based on Bloch equations. The results and the performances of these methods are analyzed and compared. It is shown that our methods permit a simple identification of NMR spin systems. The field of applications of this study is promising in the optimization of NMR signal detection, especially in the cases of low signal-to-noise ratios where optimum signal filtering and analysis must be performed.     

Efficient and flexible memory architecture to alleviate data and context bandwidth bottlenecks of coarse-grained reconfigurable arrays

The computational capability of a coarse-grained reconfigurable array(CGRA)can be significantly restrained due to data and context memory bandwidth bottlenecks.Traditionally,two methods have been used to resolve this problem.One method loads the context into the CGRA at run time.This method occupies very small on-chip memory but induces very large latency,which leads to low computational efficiency.The other method adopts a multi-context structure.This method loads the context into the on-chip context memory at the boot phase.Broadcasting the pointer of a set of contexts changes the hardware configuration on a cycle-by-cycle basis.The size of the context memory induces a large area overhead in multi-context structures,which results in major restrictions on application complexity.This paper proposes a Predictable Context Cache(PCC)architecture to address the above context issues by buffering the context inside a CGRA.In this architecture,context is dynamically transferred into the CGRA.Utilizing a PCC significantly reduces the on-chip context memory and the complexity of the applications running on the CGRA is no longer restricted by the size of the on-chip context memory.Data preloading is the most frequently used approach to hide input data latency and speed up the data transmission process for the data bandwidth issue.Rather than fundamentally reducing the amount of input data,the transferred data and computations are processed in parallel.However,the data preloading method cannot work efficiently because data transmission becomes the critical path as the reconfigurable array scale increases.This paper also presents a Hierarchical Data Memory(HDM)architecture as a solution to the efficiency problem.In this architecture,high internal bandwidth is provided to buffer both reused input data and intermediate data.The HDM architecture relieves the external memory from the data transfer burden so that the performance is significantly improved.As a result of using PCC and HDM,experiments running mainstream video decoding programs achieved performance improvements of 13.57%–19.48%when there was a reasonable memory size.Therefore,1080p@35.7fps for H.264high profile video decoding can be achieved on PCC and HDM architecture when utilizing a 200 MHz working frequency.Further,the size of the on-chip context memory no longer restricted complex applications,which were efficiently executed on the PCC and HDM architecture.     

基于GPU的液晶大气湍流模拟器波面生成的并行实现

为了使液晶大气湍流模拟器具有实时大气模拟能力,在GPU通用计算架构下提出了基于GPU的液晶大气湍流模拟器实时波面生成计算方法。针对液晶湍流模拟器高分辨率、高精度的特点介绍了湍流波面生成计算方法,论述了CUDA通用计算架构。建立基于GPU的波面生成模型,并对该模型进行了并行化优化和共享存储器优化。给出了采用CPU与GPU进行波面生成的实验对比结果。结果表明:采用GPU生成分辨率为256×256,192项Zernike多项式进行波面生成的平均时间为2.5ms,生成速度比CPU少两个量级,满足实时波面生成的要求。     

Stabilization of interferometric response using a polarization scrambler

This paper shows, theoretically and experimentally, how a polarization scrambler increases the response stability of a fiber Mach–Zehnder interferometer. We have studied the situation when the scrambler is placed in one of the interferometer branches and also when it is placed at the interferometer input. The measurements carried out using a scrambler based on the Faraday effect, agree with the simulation results.     

A software channel compression technique for faster reconstruction with many channels

In magnetic resonance imaging, highly parallel imaging using coil arrays with a large number of elements is an area of growing interest. With increasing channel numbers for parallel acquisition, the increased reconstruction time and extensive computer memory requirements have become significant concerns. In this work, principal component analysis (PCA) is used to develop a channel compression technique. This technique efficiently reduces the size of parallel imaging data acquired from a multichannel coil array, thereby significantly reducing the reconstruction time and computer memory requirement without undermining the benefits of multichannel coil arrays. Clinical data collected with a 32-channel cardiac coil are used in all of the experiments. The performance of the proposed method on parallel, partially acquired data, as well as fully acquired data, was evaluated. Experimental results show that the proposed method dramatically reduces the processing time without considerable degradation in the quality of reconstructed images. It is also demonstrated that this PCA technique can be used to perform intensity correction in parallel imaging applications.     

等概率符号化样本熵应用于脑电分析

样本熵(或近似熵)以信息增长率刻画时间序列的复杂性,能应用于短时序列,因而在生理信号分析中被广泛采用.然而,一方面由于传统样本熵采用与标准差线性相关的容限,使得熵值易受非平稳突变干扰的影响,另一方面传统样本熵还受序列概率分布的影响,从而导致其并非单纯反映序列的信息增长率.针对上述两个问题,将符号动力学与样本熵结合,提出等概率符号化样本熵方法,并对其物理意义、数学推导及参数选取都做了详细阐述.通过对噪声数据的仿真计算,验证了该方法的正确性及其区分不同强度时间相关的有效性.此方法应用于脑电信号分析的结果表明,在不对信号做人工伪迹去除的前提下,只需要1.25 s的脑电信号即可有效地区分出注意力集中和注意力发散两种状态.这进一步证明了该方法可很好地抵御非平稳突变干扰,能快速获得短时序列的潜在动力学特性,对脑电生物反馈技术具有很大的应用价值.     

有耗介质层上多导体传输线的电磁耦合时域分析方法

目前,针对空间电磁场作用有耗介质层上传输线的电磁耦合,仍缺乏有效的数值分析方法.因此,本文提出一种高效的时域混合算法,很好地解决了有耗介质层上传输线电磁耦合建模难的问题.首先,对经典传输线方程进行改进,推导了适用于有耗介质层上多导体传输线电磁耦合分析的修正传输线方程.然后,结合时域有限差分方法和相应插值技术,求解修正传输线方程,获得多导线及其端接负载上的电压和电流响应,并实现空间电磁场辐射与多导线瞬态响应的同步计算.最后,通过相应计算实例的数值模拟,与CST软件的仿真结果进行对比,验证了时域混合算法的正确性和高效性.     

一种混沌伪随机序列复杂度分析法

分析了已有的序列线性复杂度分析方法，提出了用近似熵算法计算混沌运动的测度熵，作为衡量混沌伪随机序列复杂度的标准.理论研究表明，利用较短的观察序列，该方法能够准确地反映混沌系统和混沌伪随机序列复杂度的大小，可以作为判断利用混沌系统产生的伪随机序列的复杂度准则.实验结果表明该方法的有效性和理论结果的正确性. 关键词： 混沌 伪随机序列 熵     

分布式发电系统感性负载的远程混沌同步

对含有大规模感性负载分布式发电系统（DG）的远程同步进行研究.以风力发电机作为DG发电节点，以永磁同步电机作为实际感性负载，建立一个具有网络耦合作用的DG数学模型，分析不同拓扑网络结构（包括星型、多层网络结构型、随机网络结构型、实际电网IEEE39系统）DG系统感性负载的远程同步特性，进行数值仿真.研究表明：感性负载通过发电机组的中继作用可实现远程混沌同步.研究结果对保证分布式发电系统的同步稳定运行具有意义.