"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。     

图形处理器并行计算用于离子发动机粒子模拟

 为了研究离子发动机羽流对航天器的影响,采用质点网格-蒙特卡罗碰撞方法对离子发动机羽流中的交换电荷离子进行了模拟。利用计算设备统一架构技术,开发出一套基于图形处理器的并行粒子模拟程序。随机数生成采用并行MT19937伪随机数生成器算法,电场方程使用完全近似存储格式的代数多重网格法求解。r-z轴对称坐标系中,在z=0 m处获得的电流密度均值为4.5×10^-5 A/m²,图形处理器所得结果与中央处理器模拟结果吻合。在16核心的NVIDIA GeForce 9400 GT图形显示卡上,取得相对于Intel Core 2 E6300中央处理器4.5~10.0倍的加速比。     

基于LabWindows/CVI的导弹舵机测控系统设计

舵机是导弹控制系统的重要执行机构,为实现对电动及气动多种型号导弹舵机性能的测试,设计开发了一种基于LabWindows/CVI虚拟仪器的测控系统。介绍了该测控系统硬件组成和软件结构流程,软件设计过程中充分利用多线程、数据库等技术,准确快速完成舵机自动化性能测试。应用结果表明:该舵机测控系统工作稳定,测试精度和自动化程度高,满足舵机试验测试精度和技术指标要求,为舵机的性能研究和维修维护提供了良好的测试环境。     

Derivative temporal clustering analysis: detecting prolonged neuronal activity

Temporal clustering analysis (TCA) and independent component analysis (ICA) are promising data-driven techniques in functional magnetic resonance imaging (fMRI) experiments to obtain brain activation maps in conditions with unknown temporal information regarding the neuronal activity. Although comparable to ICA in detecting transient neuronal activities, TCA fails to detect prolonged plateau brain activations. To eliminate this pitfall, a novel derivative TCA (DTCA) method was introduced and its algorithms with different subtraction intervals were tested on simulated data with a pattern of prolonged plateau brain activation. It was found that the best performance of DTCA method in generating functional maps could be obtained if the subtraction interval is equal to or larger than the length of the rising time of the fMRI response. The DTCA method and its theoretical predication were further investigated and validated using in vivo fMRI data sets. By removing the limitations in the previous TCA, DTCA has shown its powerful capability in detecting prolonged plateau neuronal activities.     

混沌系统中可预报性的研究

针对简化的气候模式、Rossler吸引子和超混沌系统,进一步阐明了不确定原理,在数值求解时由于计算机固有精度而引起的舍入误差,造成对解的不确定性,存在最优步长和最大有效计算时间.运用自忆性原理,导出了各混沌系统的自忆性方程,取最优步长时,其预报性能有明显的改善 关键词： 自忆性 不确定原理 最优步长     

等高线图分析技术在GC／FTIR联用数据处理中的应用

在三种高聚物的裂解大口径毛细管气相色谱－傅里叶变换红外光谱联用分析（ＰｙＷＢＣＧＣ／ＦＴＩＲ）数据获得的基础上，介绍应用等高线图（ＣＴＤ）分析技术处理色谱重叠峰，并在该分析提供的信息指导下进行红外光谱累加及差减技术，获得了重叠峰中各纯物质较好信噪比的气相红外谱图并予以定性，显著了等高线图分析技术在联用数据中的优点，充分发挥了ＧＣ／ＦＴＩＲ联用特有的光谱分离离度优势。     

Numerical algorithms for uniform Airy-type asymptotic expansions

Airy-type asymptotic representations of a class of special functions are considered from a numerical point of view. It is well known that the evaluation of the coefficients of the asymptotic series near the transition point is a difficult problem. We discuss two methods for computing the asymptotic series. One method is based on expanding the coefficients of the asymptotic series in Maclaurin series. In the second method we consider auxiliary functions that can be computed more efficiently than the coefficients in the first method, and we do not need the tabulation of many coefficients. The methods are quite general, but the paper concentrates on Bessel functions, in particular on the differential equation of the Bessel functions, which has a turning point character when order and argument of the Bessel functions are equal.     

改进的2PPJ格式

提出了解线性代数方程组的一种方法,称为改进的2PPJ(Modified two parameters parallel Jacobi-type)格式,简记为M2PPJ.讨论了它的收敛性和最优参数的选取.收敛速度比2PPJ格式快一倍以上.给出的数值结果说明本方法的优越性.     

Data Envelopment Analysis of multiple response experiments

Taguchi method is the usual strategy in robust design and involves conducting experiments using orthogonal arrays and estimating the combination of factor levels that optimizes a given performance measure, typically a signal-to-noise ratio. The problem is more complex in the case of multiple responses since the combinations of factor levels that optimize the different responses usually differ. In this paper, an Artificial Neural Network, trained with the experiments results, is used to estimate the responses for all factor level combinations. After that, Data Envelopment Analysis (DEA) is used first to select the efficient (i.e. non-dominated) factor level combinations and then for choosing among them the one which leads to a most robust quality loss penalization. Mean Square Deviations of the quality characteristics are used as DEA inputs. Among the advantages of the proposed approach over traditional Taguchi method are the non-parametric, non-linear way of estimating quality loss measures for unobserved factor combinations and the non-parametric character of the performance evaluation of all the factor combinations. The proposed approach is applied to a number of case studies from the literature and compared with existing approaches.     

Finding weak defining hyperplanes of PPS of the BCC model

Production possibility set (PPS) is intersection of the several halfspaces. Every halfspace corresponds with one strong or weak defining hyperplane (facet). This research proposes a method to find weak defining hyperplanes of PPS of BCC model. We state and prove some properties relative to our method. Numerical examples are provided for illustration.