Two-qubit and three-qubit controlled gates with cross-Kerr nonlinearity

Schemes for two-qubit and three-qubit controlled gates based on cross-Kerr nonlinearity are proposed in this paper.The probability of the success of these gates can be increased by quantum nondemolition detectors,which are used to judge which paths the signal photons pass through.These schemes are almost deterministic and require no ancilla photon.The advantages of these gates over the existing ones include less resource consumption and a higher probability of success,which make our schemes more feasible with current technology.

Nonlocal multi-target controlled controlled gate using Greenberger–Horne–Zeilinger channel and qutrit catalysis

We present a scheme for implementing locally a nonlocal N-target controlled–controlled gate with unit probability of success by harnessing two（N＋1）-qubit Greenberger–Horne–Zeilinger（GHZ） states as quantum channel and N qutrits as catalyser. The quantum network that implements this nonlocal（N＋2）-body gate is built entirely of local single-body and two-body gates, and has only（3N＋2） two-body gates. This result suggests that both the computational depth of quantum network and the quantum resources required to perform this nonlocal gate might be significantly reduced. This scheme can be generalized straightforwardly to implement a nonlocal N-target and M-control qubits gate.

One step to generate quantum controlled phase-shift gate using a trapped ion

This paper presents a very simple scheme for generating quantum controlled phase-shift gate with only one step by using the two vibrational modes of a trapped ion as the two qubits. The scheme couples two vibration degrees of freedom coupled with a suitable chosen laser excitation via the ionic states.

Direct implementation of a scalable non-local multi-qubit controlled phase gate via optical fibres and adiabatic passage

This paper presents a direct implementation scheme of the non-local multi-qubit controlled phase gate by using optical fibres and adiabatic passage. The smaller operation number for implementing the multi-qubit controlled phase gate and needlessness for addressing individually save physical resource and lower the difficulties of experiment. Mean- while, the scheme is immune from some decoherence effects such as the atomic spontaneous emission and fibre loss. In principle, it is scalable.

Research on reform schemes of control methods of inlet gate in Jiaxin Hydropower Station

The simple gate control system which is made of traditional manual or proximity switch cannot meet the requirements of connecting with the computer monitoring system of hydropower station, it must be reformed. On the basis of the integrated analysis for small hydropower station, the paper discussed the singlechip as the core to realize the methods of gate automatic control system in small hydropower station. The designs for hardware and software of gate control system were introduced. And the control system was reformed from customary manual control to computer automatic control. The simulation experiment shows that this scheme is feasible.

Implementing remote controlled-NOT gates and entanglement swapping via geometric phase gates in ion-trap systems

We propose a scheme for the implementation of remote controlled-NOT gates and entanglement swapping via geometric phase gates in ion-trap systems. The proposed scheme uses the two ground states of the A-type ions as memory instead of the vibrational mode. And the system is robust against the spontaneous radiation and the dephasing.

Synthesis of Nonlinear Control of Switching Topologies of Buck-Boost Converter Using Fuzzy Logic on Field Programmable Gate Array (FPGA)

An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the converter was mapped into a look-up table that was synthesized into a set of Boolean equations. A VLSI chip–a field programmable gate array (FPGA) was used to implement the Boolean equations. Features include the size of RAM chip independent of number of rules in the knowledge base, on-chip fuzzification and defuzzification, faster response with speeds over giga fuzzy logic inferences per sec (FLIPS), and an inexpensive VLSI chip. The key application areas are: 1) on-chip integrated controllers;and 2) on-chip co-integration for entire system of sensors, circuits, controllers, and detectors for building complete instrument systems.

基于注意力机制和特征融合的股票预测方法

基于人工智能在金融数据中的应用,提出了一种新的股票预测方法,称为AFG。AFG使用位置编码和时间编码获取股票数据的位置信息和时间信息,然后通过门控循环单元和多头自注意力机制对股票数据分别进行特征提取。在将两类股票特征融合之后,由全连接层导出最终的股票预测曲线。

Preparation of Hadamard Gate for Open Quantum Systems by the Lyapunov Control Method

In this paper, the control laws based on the Lyapunov stability theorem are designed for a two-level open quantum system to prepare the Hadamard gate, which is an important basic gate for the quantum computers. First, the density matrix interested in quantum system is transferred to vector formation.Then, in order to obtain a controller with higher accuracy and faster convergence rate, a Lyapunov function based on the matrix logarithm function is designed. After that, a procedure for the controller design is derived based on the Lyapunov stability theorem. Finally, the numerical simulation experiments for an amplitude damping Markovian open quantum system are performed to prepare the desired quantum gate. The simulation results show that the preparation of Hadamard gate based on the proposed control laws can achieve the fidelity up to 0.9985 for the different coupling strengths.

基于模态分解及GRU-XGBoost短期电力负荷预测

精确的短期电力负荷预测能有效提高电力系统运营水平。针对电力负荷数据受多种因素影响,波动性和随机性强等问题,提出了一种基于模态分解及混合模型的负荷预测方法。首先,采用主成分分析法(principal component analysis,PCA)对负荷特征向量进行处理,去掉冗余信息,再用完全自适应噪声集合经验模态分解(complete ensemble empirical mode decomposition with adaptive noise,CEEMDAN)将历史负荷分解为简化的几个子序列;其次,选择引入样本熵(sample entropy,SE)来计算子序列熵值,将相近的子序列重构得到随机、细节、低频和趋势分量后选用不同结构门控循环单元(gate recurrent unit,GRU)对不同分量类型进行预测,再使用极致梯度提升模型(extreme gradient boosting,XGBoost)对各分量残差进行拟合,各重组序列的预测值为GRU预测值与XBGoost拟合值之和,重组各序列得到最终预测值。选取3年时电力负荷数据进行实验,结果表明,所提模型的均方根误差(root mean square error,RMSE)、平均绝对百分比误差(mean absolutepercentage error,MAPE)和平均绝对误差(mean absolute error,MAE)分别为370.676 MW、99.07%和246.89 MW,与单一模型和混合模型相比,实现了评价指标的明显减少。

考虑泄洪设施闸门控制的水库防洪调度

【目的】水库防洪调度在防汛工作中具有举足轻重的地位,而如何控制泄洪设施闸门是水库防洪调度方案实施的关键。为此,【方法】建立了考虑泄洪闸门调度的水库防洪优化调度模型以实现精细化调度,并提出一种两层嵌套算法对模型进行求解。在内层建立了包括所有泄洪闸门可行组合的泄洪闸门组合表,外层采用POA算法对水库坝前水位和总泄水量进行优化,并通过查询闸门组合表确定各泄洪闸门的运行状态。【结果】澜沧江漫湾水库防洪优化调度的实例分析结果表明:所提出的两层嵌套方法计算效率较高,对于100年一遇和10年一遇的洪水事件,洪峰分别从12010 m^(3)/s减少到10611 m^(3)/s和从5003 m^(3)/s减少到3351 m^(3)/s,分别减少了11.6%和33.0%,洪水波动幅度分别降低了94.5%和8.8%,极大地缓解了下游防洪压力。此外,与不考虑泄洪闸门调度的传统防洪调度模型相比,所提出的模型能生成更加符合实际、更易于执行的防洪调度方案。【结论】该方法能够实现水库防洪优化调度向泄洪设施运行控制的精细化转变,对于增强防洪优化调度成果的可操作性、提升水库防洪调度管理水平具有一定意义。

纳米材料中的界面现象

在课程教学中融入科学前沿实例不仅可以阐明所学基本原理的实际意义,还可以为基本原理的灵活应用提供范例,启发学生独立思考能力。界面化学是物理化学课程中的重要学习内容,但由于在常规尺度的多相体系中界面现象并不显著,学生对该部分知识常有忽视。近年来纳米材料已成为国内外研究的热点。纳米材料由于其高界面分子比例而表现出更为显著的界面现象。将界面化学的基本原理应用于纳米材料的研究中,已取得了一系列令人瞩目的成果。本文首先对附加压力、接触角等相关界面现象的基本原理进行梳理,然后分别介绍根据这些基本原理所发展出的分子马达、光控微流控器件、液体门控技术以及超疏水表面四项科技突破。

船舶拥堵水域通行能力预测技术

针对船舶交通流量大、水域繁忙情况下,通行能力预测难度过高的问题,提出船舶拥堵水域通行能力预测技术。利用船舶坐标位置以及航行速度,确定船舶状态,建立船舶航行队列模型。依据船舶领域模型确定船舶航行对应的椭圆形区域,作为船舶拥堵水域的领域。确定船舶领域内,影响航道容量的相关因素。设置船舶密度、船舶航行速度等水域通行能力影响指标,作为长短时记忆网络的输入。长短时记忆网络通过遗忘门、输入门以及输出门3个门控单元,选择保留或遗忘输入的数据,输出船舶拥堵水域通行能力预测结果。实验结果表明,该技术能够有效预测船舶拥堵水域通行能力,提高航道利用率,保障水域交通安全性。

改进Transformer在产油量预测中的应用研究

产油量预测有利于制定合理的采油策略。本文提出一种包含卷积神经网络、门控循环单元和Transformer的组合模型CNN-GRU-Transformer,可用于产油量预测。该模型应用CNN提取部分深层空间特征,GRU提取产油量数据的时序特征,并根据油井数据的特点,改进了Transformer原有结构。通过改进的Transformer,将提取到的特征与预测相结合。实验的结果表明,CNN-GRU-Transformer模型在预测产油量各项指标中均为最优值,在适应产油量基本趋势方面表现最佳。

基于模内组装的环式挂链多功能注射模具设计

结合某新款窗帘环式挂链6种组合状态塑件的注射成型要求,基于模内组装设计方法,设计了一副多功能三板注射模具,用作该环式挂链6种组装态产品的注射成型。模具中,模腔由6个独立的单环模腔构成,并且,两环之间的空腔形成90°垂直交叉型环套环状态,有利于通过对各独立模腔浇口的开闭控制,满足6种组装状态组装环挂链的生产要求。为实现对6个模腔浇口的独立开闭控制,设计了一种插板式浇口开闭控制机构,机构由6根插板、1个插座及1个压块组成,用6个螺丝对插板的停留位置进行锁紧。模具能满足单环、2环、3环、4环、5环、6环,共6种组装态的模内直接组装生产要求,具有较好的设计参考价值。

智能感潮系统在江都东闸的应用

通过智能感潮系统判断潮位涨落趋势、及时预报引潮开关闸时间,按时自动开关闸引潮,大大减轻了运行值班人员的劳动强度,提高了工作效率,同时避免因人为因素导致引潮不及时,确保最大限度地引水,提升水闸精准调度水平,确保工程安全应用和效益的充分发挥。

基于GRU-BP算法的高精度动态物流称重系统

针对动态物流秤测量精度对载重、采样频率、带速较为敏感的问题,提出了一种高精度动态物流称重系统。首先,采用三因素五水平正交试验法,结合皮尔逊相关性检验原则,使用低通巴特沃斯与卡尔曼滤波器对传感器压力信号进行了滤波降噪处理,并将加速度信号作为模型输入信号,进行了特征补偿;然后,基于深度学习算法,提出了一种改进的门控循环单元模型,在该模型采样区间内将压力与振动改写为时序化信号,并将其共同输入门控循环单元(GRU)模型;最后,对GRU模型进行了改进,对其结构输出了层堆叠误差反向传播神经网络(BP),有效加强了模型的非线性映射能力。研究结果表明:在各类传动速度及测试货物下,该模型的最大测量误差相对于同类型深度学习模型长短期记忆(LSTM)神经网络、循环神经网络(RNN)时序模型及传统数值平均模型的误差,依次降低了16.14%、27.14%、76%,可用于各类称重系统。

宁夏引黄灌区农业灌溉测控闸门应用现状调查与评估

测控设施作为灌区用水管理的重要工具、数字化灌区建设的基础硬件支撑,可有效帮助管理者准确掌握水源来水及用户实时用水量情况,也可为灌区水费收取、用水总量控制与定额管理提供有力保障。以宁夏引黄灌区测控闸门为例,系统分析其应用现状,重点从提高灌区管理水平、夯实用水权确权成果、提高水费计收透明度等方面总结凝练了取得的主要成效,从设备硬件水平、规划设计、运行维护等方面提出了应用中存在的关键问题,并对今后测控设施选型设计提出了相关意见和建议。

明渠模型预测控制快速优化计算方法

针对基于圣维南方程使用启发式算法进行渠道预测控制时,现有优化计算方法生成调控方案时间过长、无法满足实时控制需求的问题,提出了一种基于多目标优化算法的快速优化方法.以一处试验渠道的数值模型作为控制对象,应用此方法构建了预测控制模型以生成调控方案,并构建了一维水动力模型对调控方案进行验证.研究发现在闸门控制系统中,超出水位控制范围的最大值最小、超出水位控制范围的平均值最小、闸门动作次数最少、闸门开度总变化量最小4个目标间能够相互诱导,加速优化计算过程4倍以上.在该试验渠道的流量计划调整工况中,验证了此种方法的有效性,将单次计算时间缩短至1 s内.验证效果表明,该方法在提高了水位控制效果的同时,能够减少由单独设置超出水位控制范围的最大值最小目标导致的非必要闸门调控,总计减少69%的闸门调控次数.

多波束测深声呐自主数据质量监测及门限控制

为满足水面无人艇等海洋无人平台的需求,确保多波束测深声呐系统在无人监控和参数调节下具备可靠自主工作能力,本文提出一种数据质量在线监测及门限参数控制方法。通过建立基于质量和异常因子的监测模型,结合粒子滤波技术,提高海底地形跟踪门限控制抗差性。仿真和湖上试验显示该方法能判定数据有效性、适应地形变化,并提供合理深度门限,适用于多波束测深声呐系统的在线数据质量监测和无人自主控制。