Ascertaining the influences of auxiliary qubits on the Einstein–Podolsky–Rosen steering and its directions

Einstein–Podolsky–Rosen(EPR) steering is an example of nontrivial quantum nonlocality and characteristic in the non-classical world.The directivity(or asymmetry) is a fascinating trait of EPR steering,and it is different from other quantum nonlocalities.Here,we consider the strategy in which two atoms compose a two-qubit X state,and the two atoms are owned by Alice and Bob,respectively.The atom of Alice suffers from a reservoir,and the atom of Bob couples with a bit flip channel.The influences of auxiliary qubits on EPR steering and its directions are revealed by means of the entropy uncertainty relation.The results indicate that EPR steering declines with growing time t when adding fewer auxiliary qubits.The EPR steering behaves as damped oscillation when introducing more auxiliary qubits in the strong coupling regime.In the weak coupling regime,the EPR steering monotonously decreases as t increases when coupling auxiliary qubits.The increases in auxiliary qubits are responsible for the fact that the steerability from Alice to Bob(or from Bob to Alice) can be more effectively revealed.Notably,the introductions of more auxiliary qubits can change the situation that steerability from Alice to Bob is certain to a situation in which steerability from Bob to Alice is certain.

A new adaptive co-site broadband interference cancellation method with auxiliary channel

With the boom of the communication systems on some independent platforms(such as satellites,space stations,airplanes,and vessels),co-site interference is becoming prominent.The adaptive interference cancellation method has been adopted to solve the co-site interference problem.But the broadband interference cancellation performance of traditional Adaptive Co-site Interference Cancellation System(ACICS)with large delay mismatching and antenna sway is relatively poor.This study put forward an Adaptive Co-site Broadband Interference Cancellation System With Two Auxiliary Channels(ACBICS-2A).The system model was established,and the steady state weights and Interference Cancellation Ratio(ICR)were deduced by solving a time-varying differential equation.The relationship of ICR,system gain,modulation factor,interference signal bandwidth and delay mismatching degree was acquired through an in-depth analysis.Compared with traditional adaptive interference cancellation system,the proposed ACBICS-2A can improve broadband interference cancellation ability remarkably with large delay mismatching and antenna sway for the effect of auxiliary channel.The maximum improved ICR is more than 25 dB.Finally,the theoretical and simulation results were verified by experiments.

A GENERALIZED SCALAR AUXILIARY VARIABLE METHOD FOR THE TIME-DEPENDENT GINZBURG-LANDAU EQUATIONS

This paper develops a generalized scalar auxiliary variable(SAV)method for the time-dependent Ginzburg-Landau equations.The backward Euler method is used for discretizing the temporal derivative of the time-dependent Ginzburg-Landau equations.In this method,the system is decoupled and linearized to avoid solving the non-linear equation at each step.The theoretical analysis proves that the generalized SAV method can preserve the maximum bound principle and energy stability,and this is confirmed by the numerical result,and also shows that the numerical algorithm is stable.

Research on uninterruptable power supply technology for auxiliary winding of electric locomotive while passing the neutral section

Purpose–Auxiliary power system is an indispensable part of the train;the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways,which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters.Powered by DC-link voltage of traction converters,the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking.Meanwhile,powered by traction transformers,the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.Design/methodology/approach–Uninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied.Failure reasons why previous solutions cannot be realized are analyzed.An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper.The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive.This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.Findings–This scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid.Control objectives of uninterrupted power supply technology are proposed,which are no overvoltage,no overcurrent and uninterrupted power supply.Originality/value–The control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section.Furthermore,this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

2024 National Practical Technical Training on Textile Printing and Dyeing Auxiliary Preparation Succeeds

From July 16th to 19th,2024,2024 National Practical Technical Training on Textile Printing and Dyeing Auxiliary Preparation,organized by China Research Institute of Daily Chemical and National Engineering Research Center for Surfactants,and co-organized by the Dyeing and Finishing Technology Research Institute of Zhejiang Fashion Institute of Technology and the High Fastness Plant-based Dye Research Base of China Textile Engineering Society,was held successfully in Shangyu,Zhejiang Province,with 92 representatives from 64 work units from all over China.

Auxiliary Software for Defining the Parameters of the Structural Organization of a Complex System

The developed auxiliary software serves to simplify, standardize and facilitate the software loading of the structural organization of a complex technological system, as well as its further manipulation within the process of solving the considered technological system. Its help can be especially useful in the case of a complex structural organization of a technological system with a large number of different functional elements grouped into several technological subsystems. This paper presents the results of its application for a special complex technological system related to the reference steam block for the combined production of heat and electricity.

Evolutionary Multitasking With Global and Local Auxiliary Tasks for Constrained Multi-Objective Optimization

Constrained multi-objective optimization problems(CMOPs) include the optimization of objective functions and the satisfaction of constraint conditions, which challenge the solvers.To solve CMOPs, constrained multi-objective evolutionary algorithms(CMOEAs) have been developed. However, most of them tend to converge into local areas due to the loss of diversity. Evolutionary multitasking(EMT) is new model of solving complex optimization problems, through the knowledge transfer between the source task and other related tasks. Inspired by EMT, this paper develops a new EMT-based CMOEA to solve CMOPs, in which the main task, a global auxiliary task, and a local auxiliary task are created and optimized by one specific population respectively. The main task focuses on finding the feasible Pareto front(PF), and global and local auxiliary tasks are used to respectively enhance global and local diversity. Moreover, the global auxiliary task is used to implement the global search by ignoring constraints, so as to help the population of the main task pass through infeasible obstacles. The local auxiliary task is used to provide local diversity around the population of the main task, so as to exploit promising regions. Through the knowledge transfer among the three tasks, the search ability of the population of the main task will be significantly improved. Compared with other state-of-the-art CMOEAs, the experimental results on three benchmark test suites demonstrate the superior or competitive performance of the proposed CMOEA.

Auxiliary guidance manufacture and revealing potential mechanism of perovskite solar cell using machine learning

To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

Auxiliary Classifier of Generative Adversarial Network for Lung Cancer Diagnosis

The classification of lung nodules is a challenging problem as the visual analysis of the nodules and non-nodules revealed homogenous textural patterns.In this work,an Auxiliary Classifier(AC)-Generative Adversarial Network(GAN)based Lung Cancer Classification(LCC)system is developed.The pro-posed AC-GAN-LCC system consists of three modules;preprocessing,Lungs Region Detection(LRD),and AC-GAN classification.A Wienerfilter is employed in the preprocessing module to remove the Gaussian noise.In the LRD module,only the lung regions(left and right lungs)are detected using itera-tive thresholding and morphological operations.In order to extract the lung region only,floodfilling and background subtraction.The detected lung regions are fed to the AC-GAN classifier to detect the nodules.It classifies the nodules into one of the two classes,i.e.,binary classification(such as nodules or non-nodules).The AC-GAN is the extended version of the conditional GAN that predicts the label of a given image.Three different optimization techniques,adaptive gradient optimi-zation,root mean square propagation optimization,and Adam optimization are employed for optimizing the AC-GAN architecture.The proposed AC-GAN-LCC system is evaluated on the Lung Image Database Consortium(LIDC)data-base Computed Tomography(CT)scan images.The proposed AC-GAN-LCC system classifies∼15000 CT slices(7310 non-nodules and 7685 nodules).It pro-vides an overall accuracy of 98.8%on the LIDC database using Adam optimiza-tion by a 10-fold cross-validation approach.

Multi-Objective Optimization Analysis of Auxiliary Flux Modulator Magnetic Gear with Unequal Magnetic Poles

To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an asymmetric sector and a trapezoidal combined N-S pole structure,featuring Halbach arrays for the arrangement of permanent magnets(PMs).The outer rotor PMs adopt a Spoke-type configuration.To optimize the CMG for high output torque and low torque ripple,a sensitivity analysis is conducted to identify key size parameters that significantly influence the optimization objectives.Based on the sensitivity hierarchy of these parameters,a multi-objective optimization analysis is performed using a genetic algorithm(GA)to determine the optimal structural parameter values of the CMG.In addition,a coaxial magnetic gear(CMG)topology with 4 inner and 17 outer pole pairs is adopted,and the parametric model is established.Finally,the electromagnetic properties of the CMG are evaluated using the finite element method.The results indicate a remarkable reduction in torque ripple,specifically by 46.15%.

国医大师熊继柏治疗失眠的方药规律分析

目的对国医大师熊继柏教授治疗失眠的病案进行数据挖掘,分析熊继柏教授诊治失眠的用方、用药经验。方法基于中医传承辅助平台软件(V3.5),归纳和分析熊继柏教授在湖南中医药大学第一附属医院治疗失眠患者的门诊病历数据,利用该平台软件的关联规则、复杂系统熵聚类等统计方法进行数据挖掘和分析,总结药物的性味、归经、应用频次、药对组合及合方,对“证-症-方”“证-症-药”“证-方-药”进行关联,结合熊继柏教授对失眠病因病机、治则治法的认识,明确核心用药,探索其对失眠的诊治规律及遣方用药心得。结果通过总结分析,共纳入病历276份,处方中用药频次较多的有酸枣仁、龙齿、茯神、甘草,重在补虚安神;黄连、陈皮、竹茹、半夏、珍珠母、远志,重在清热化痰安神。用药性味偏甘、苦、辛,归经多为心、脾经。并归纳出虚证治疗常用合方为酸枣仁汤、枕中丹和甘麦大枣汤;因痰所致失眠治疗的主方为温胆汤及温胆汤类方(枣仁温胆汤、黄连温胆汤及十味温胆汤)。结论国医大师熊继柏治疗失眠以“补脾化痰清热,养血补肝宁心”为治疗原则,以温胆汤为基础进行加减化裁。

滤波辨识(10):多变量Box-Jenkins系统的滤波辅助模型递阶广义增广参数辨识

针对多变量Box-Jenkins模型,即多变量输出误差自回归滑动平均(M-OEARMA)系统,利用滤波辨识理念和辅助模型辨识思想,研究和提出了滤波辅助模型递阶广义增广随机梯度辨识方法、滤波辅助模型递阶多新息广义增广随机梯度辨识方法、滤波辅助模型递阶广义增广递推梯度辨识方法、滤波辅助模型递阶多新息广义增广递推梯度辨识方法、滤波辅助模型递阶广义增广最小二乘辨识方法、滤波辅助模型递阶多新息广义增广最小二乘辨识方法。这些滤波辅助模型递阶广义增广辨识方法可以推广到其他有色噪声干扰下的线性和非线性多变量随机系统中。

三电平辅助变流器寿命优化控制

辅助变流系统是动车组车辆上关键的电气组成部分,主要为空调机组、风机、照明等交流负载提供稳定的三相电源。结温是影响动车组三电平辅助变流器IGBT(Insulated-gate Bipolar Transistor)模块寿命的主要因素。为了提高动车组三电平中点钳位(Neutral-Point Clamped,NPC)型辅助变流器寿命,提出一种降低结温的模型预测电流控制(Model Predictive Current Control,MPCC)策略。首先,考虑传统MPCC在每个采样周期需要代入27个电压矢量循环计算,计算量较大,因此将三电平基本电压矢量划分在间隔60°的6个扇区中,通过计算电压矢量在两相静止坐标下的相角,进而判断参考电压矢量所处扇区,将备选矢量数目从27缩减至10,减少了计算量;其次,传统MPCC直接应用于动车组辅助变流器会使IGBT模块的结温较高,老化速度加快,对变流器安全稳定运行产生不可预测的损害,本文对IGBT模块的开关损耗和导通损耗进行近似等效,得到了和集射极电压、集电极电流相关的功率损耗因子。通过预测每相电流的方向,进而预测IGBT模块的开关和导通情况,动态加入功率损耗因子,并在代价函数中约束每相IGBT及其续流二极管(Free Wheeling Diode,FWD)的功率损耗,使得最优电压矢量在降低功率损耗的同时保证一定的控制性能。通过仿真与实验验证,本文所提方法相比传统MPCC策略降低了功率器件的结温,提高了变流器寿命。

面向人脸属性编辑的三阶段对抗扰动生成主动防御算法

针对恶意人脸属性编辑行为,基于取证的被动防御技术只能对篡改行为进行取证并不能防止其产生,从而难以消除恶意篡改行为已经造成的损失.因此,主动防御技术应运而生,其可以破坏属性编辑的输出从而避免人脸被篡改使用.然而,现有两阶段训练人脸篡改主动防御框架存在迁移性和扰动鲁棒性不足的问题,为此本文通过优化两阶段训练架构及损失函数和引入一个辅助分类器,提出一种三阶段对抗扰动主动防御框架.本文首先修改两阶段训练架构中的代理目标模型并基于此设计了训练扰动生成器的属性编辑损失,以提升代理模型的重建性能和属性约束能力,从而减少对代理模型的过拟合;其次,在训练阶段引入辅助分类器对代理模型提取的编码后特征进行源属性分类并基于此设计训练扰动生成器的辅助分类器损失,从而将原本的两阶段交替训练改为代理目标模型、辅助分类器和扰动生成器的三阶段交替训练,期望通过对抗攻击辅助分类器以促进对篡改模型的主动防御;最后,在扰动生成器的训练中,引入攻击层以促进对抗扰动对滤波和JPEG压缩的鲁棒性.实验结果验证,本文提出的框架能够比现有框架更好地将主动防御从白盒的代理目标模型迁移到黑盒的属性编辑模型,黑盒性能提升16.17%,且生成的对抗扰动较基线算法具有更强的鲁棒性,针对JPEG压缩的性能(PSNR)提升13.91%,针对高斯滤波提升17.76%.

MATLAB在“张量分析”课程教学中的应用

张量分析是一种重要的数学工具,它在相对论、电磁场论和连续介质力学等诸多学科都有着广泛的应用。掌握这种数学工具,已成为从事相关科学研究的必备基础。然而,张量分析中非欧几里得空间局部切标架的存在,增加了张量计算和分析的复杂性。学生在学习“张量分析”课程时面临着抽象概念和复杂公式的理解上的困难。本文提出利用MATLAB工具在绘图、脚本编程和符号推导等方面的强大功能,从旋度分析、坐标变换和定理辅助证明这三个方面,并结合MATLAB脚本代码,展示MATLAB工具辅助于该课程教学的重要作用。教师借助该工具开展课程教学,将帮助学生有效提高对张量分析知识的理解。学生掌握了该课程的基础知识后,便能进一步使用MATLAB的张量工具箱或Pytorch深度学习库进行张量运算操作。

基于数值模拟和变形监测的副井稳定性评价

急倾斜矿体开采时一般将副井布置在矿体下盘不远处,以致副井附近矿体开采可能诱发副井井壁应力集中或损坏。为此,以湖北三鑫为例,利用FLAC3D仿真软件,探究沿走向或垂直走向布置采场引起的副井围岩应力、位移变化,并采用应变计、位移计监测井壁应力与位移变化,评价副井稳定性。结果表明:沿矿体走向布置采场对采场围岩、悬空底柱及开采段副井井壁的稳定都极为不利,沿走向或大宽度垂直走向布置采场都不会引起地表及开采标高段附近的副井发生明显位移,但都会引起井口以下约250 m内的井壁因变形而发生应力集中;必须垂直走向布置采场并缩小采场宽度;采取4 m×4 m进路上向胶结充填二步骤采矿后,除岩土分界面附近井壁偶尔因开快车而造成连续2次垂直位移、应力差分别超1.2 mm、1.4 MPa外,其他监测值变化基本可忽略;地表基岩沉降观测表明各点沉降值变化一般不超过3 mm。

滤波辨识(13):类多变量方程误差ARMA系统的滤波递阶广义增广迭代参数辨识

针对类多变量方程误差自回归滑动平均(M-EEARMA-like)系统,利用滤波辨识理念和递阶辨识原理,研究和提出了滤波递阶广义增广梯度迭代辨识方法、滤波递阶多新息广义增广迭代梯度辨识方法、滤波递阶广义增广最小二乘迭代辨识方法、滤波递阶多新息广义增广最小二乘迭代辨识方法。这些滤波递阶广义增广迭代参数辨识方法可以推广到其他有色噪声干扰下的线性和非线性多变量方程误差随机系统中。

气吸式杂交稻单粒排种器研制

针对气力式水稻精量排种器充种不稳定、单粒播种精度不高和播种量大的问题,该研究设计了一种具有矩形吸种孔和辅助充种装置的气吸式杂交稻单粒排种器。根据“吉田优”型杂交稻的长短轴重力分布情况,确定排种盘吸种孔形状;基于CFD-DEM(Computational fluid dynamics,Discrete element method)流固耦合理论,以吸附力为指标,进行5类具有相同面积的吸种孔单因素仿真试验,确定吸附力最大的吸种孔规格为0.8 mm×2.25 mm;以该型吸种孔为基础,选取辅助充种角、工作转速和工作负压为试验因素,以单粒率S、多粒率M和漏播率L为试验指标,开展Box-Bhnken台架试验,对试验结果进行响应曲面分析和多目标优化,得到排种盘辅助充种角为80.90°、工作转速为42.65 r/min、工作负压为621 Pa时,排种器的单粒率为86.91%,漏播率为3.63%。验证试验结果的排种器单粒率为86.36%、漏播率为3.41%,与优化结果吻合。研究结果可为后续气吸式杂交稻单粒排种器的优化设计和直播机整机作业精度的提高提供指导。

砻谷机转子系统结构参数辅助计算系统的设计与实现

[目的]提高胶辊砻谷机转子系统机械工作效率。[方法]基于VB与Matlab平台开发可在Windows系统下独立安装运行的胶辊砻谷机转子系统结构参数辅助计算系统(RRHRSPD)。根据等效设计方法和传统机械设计方法建立了砻谷机的工艺参数、动力参数、结构参数间的耦联关系,探明了转子系统结构参数的设计计算原理;采用VB开发系统操作界面并实时调用Matlab动态链接库,形成系统的核心运算机制,并对系统进行封装发布。[结果]开发了一套胶辊砻谷机转子系统结构参数辅助计算系统。[结论]该系统的计算结果准确、可靠,不仅可用于砻谷机转子系统机械结构的设计计算,也可用于砻谷机性能分析的虚拟试验平台。