Simple Algorithm for Partial Quantum Search

Quite often in database search, we only need to extract portion of the information about the satisfying item. We consider this problem in the following form: the database of N items is separated into K blocks of size b = N / K elements each and an algorithm has just to find the block containing the item of interest. The queries are exactly the same as in the standard database search problem. We present a quantum algorithm for this problem of partial search that takes about 0.34 fewer iterations than the quantum search algorithm.     

Simulation of the interaction of methane,carbon dioxide and coal

Gas adsorption has an important influence on gas flow in a coal body. Research on the characteristics of coal and gas adsorption is the theoretical basis for studying gas flow in coal. In this paper, the interaction between methane, carbon dioxide and surface molecules of anthracite was simulated using the quantum chemistry method. Adsorption energy and adsorption configurations of different quantities of gas molecules absorbed on the coal surface were calculated. The results show that adsorption between coal and the two kinds of gas molecules is a physical adsorption process and there is an optimal configuration. Gas molecules are more easily adsorbed in the hydroxyl-containing side chain, while it is difficult for them to be adsorbed at the position of the benzene ring. Besides, carbon dioxide molecules are more readily adsorbed on the coal surface than methane molecules. The findings have an important significance in revealing the nature of gas adsorption in coal.     

Classical and superposed learning for quantum weightless neural networks

A supervised learning algorithm for quantum neural networks (QNN) based on a novel quantum neuron node implemented as a very simple quantum circuit is proposed and investigated. In contrast to the QNN published in the literature, the proposed model can perform both quantum learning and simulate the classical models. This is partly due to the neural model used elsewhere which has weights and non-linear activations functions. Here a quantum weightless neural network model is proposed as a quantisation of the classical weightless neural networks (WNN). The theoretical and practical results on WNN can be inherited by these quantum weightless neural networks (qWNN). In the quantum learning algorithm proposed here patterns of the training set are presented concurrently in superposition. This superposition-based learning algorithm (SLA) has computational cost polynomial on the number of patterns in the training set.     

基于MapReduce模型的并行量子进化算法

利用MapReduce模型可自动编写串行程序及编程接口简单的优点,实现量子进化算法在MapReduce模型下的并行化,提出基于MapReduce模型的并行量子进化算法MRQEA,并将其部署到Hadoop云计算平台上运行。对0-1背包问题的测试结果证明,MRQEA算法在处理大型数据集时具有良好的加速比和并行效率。     

基于QPSO-LSSVM的数据库相似重复记录检测算法

针对大规模数据库的相似重复记录的检测问题,提出了一种量子群优化算法(QPSO)与最小二乘支持向量 机(LSSVM)相结合的相似重复记录检测方法(QPSC}LSSVM)。首先计算记录字段的相似度值;然后利用QPSO对 LSSVM参数进行优化,构建相似重复记录检测模型;最后通过具体数据集进行仿真测试实验。仿真结果表明,QPSCL LSSVM不仅提高了重复记录检测准确率,而且提高了检测效率,是一种有效的相似重复记录检测算法。     

量子演化算法的改进研究

从两个方面对量子演化算法进行改进：（1）因量子染色体的量子位处于叠加态和纠缠态,无法使用传统的交叉方式对量子位进行操作,设计了针对测量后的经典染色体进行全干扰交叉,这样既不会破坏量子染色体的固有的并行性,又可以增加测量后染色体的多样性,继而影响量子染色体进化方向,加快算法的收敛速度,有效地防止＂早熟＂;（2）设计了概率触发器启动量子非门进行量子变异。实验表明,改进的量子演化算法比起先前的算法具有更好的寻优能力,更稳定的收敛度。     

Integrated plasma-aided nanofabrication facility: Operation, parameters, and assembly of quantum structures and functional nanomaterials

The development, operation, and applications of two configurations of an integrated plasma-aided nanofabrication facility (IPANF) comprising low-frequency inductively coupled plasma-assisted, low-pressure, multiple-target RF magnetron sputtering plasma source, are reported. The two configurations of the plasma source have different arrangements of the RF inductive coil: a conventional external flat spiral “pancake” coil and an in-house developed internal antenna comprising two orthogonal RF current sheets. The internal antenna configuration generates a “unidirectional” RF current that deeply penetrates into the plasma bulk and results in an excellent uniformity of the plasma over large areas and volumes. The IPANF has been employed for various applications, including low-temperature plasma-enhanced chemical vapor deposition of vertically aligned single-crystalline carbon nanotips, growth of ultra-high aspect ratio semiconductor nanowires, assembly of optoelectronically important Si, SiC, and Al_1-xIn_xN quantum dots, and plasma-based synthesis of bioactive hydroxyapatite for orthopedic implants.     

旋转机械故障诊断的量子神经网络算法

针对故障模式之间存在交叉数据的诊断不确定问题，将多层激励函数的量子神经网络引入多传感器信息融合之中，提出一种基于量子神经网络的多传感器信息融合故障诊断算法。并将其应用到旋转机械故障诊断中，通过测试被诊断设备的振动速度和加速度信号，求出两传感器对各故障模式的故障隶属度，利用多层激励函数的量子神经网络进行信息融合，得到融合的各故障模式隶属度值，确定真正的故障模式，提高了故障诊断的准确率。     

Quantum PLC在水电厂现地控制单元改造中的应用

本文主要介绍水电厂现地控制单元的改造方案，详细介绍了Quantum系列PLC在功能实现和程序的编制上的应用技巧，现场实践证明该方案设计合理、运行稳定。     

Scattering and space-charge effects in Wigner Monte Carlo simulations of single and double barrier devices

Transport in single and double barrier devices is studied using a Monte Carlo solver for the Wigner transport equation. This approach allows the effects of tunneling and scattering to be included. Several numerical methods have been improved to render the Wigner Monte Carlo technique more robust, including a newly developed particle annihilation algorithm. A self-consistent iteration scheme with the Poisson equation was introduced. The role of scattering and space charge effects on the electrical characteristics of n-i-n nanostructures, ultra-scaled double gate MOSFETs, and GaAs resonant tunneling diodes is demonstrated. An erratum to this article can be found at