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 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.

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.

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%.

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.

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。

薄壁结构件的正向吸附辅助支撑钻削工艺研究

航空航天领域中薄壁结构件的连接装配要求加工高精度的连接孔,但此类结构件钻削加工时变形大、易振动,严重影响制孔精度和表面质量,传统装夹方法存在装夹跨距大、难以充分有效支撑等问题。本文提出通过正向吸附辅助支撑,提高薄壁结构件加工时的局部刚度,进而提高薄壁结构件的加工质量,并通过仿真和试验相结合的方式研究了正向吸附辅助支撑对薄壁结构件钻削加工的影响。结果表明,在本文仿真和试验条件下,正向吸附辅助支撑可使钻削位置刚度提升40倍以上,孔壁粗糙度值降低67%以上,圆度公差降低60%以上,孔径偏差降低50%以上,同一孔的靠近出口、入口位置的孔径偏差降低90%以上。可见,正向吸附辅助支撑可显著提高薄壁结构件的制孔精度和质量。

基于布鲁姆教育理论的船舶辅机混合式实验教学

为了满足工程教育专业认证对航海类专业人才培养的新要求,优化虚实结合的实验教学模式,以“液压起货机的操作与管理”实践环节为例,提出基于布鲁姆教育理论的船舶辅机混合式实验教学。在构建知识和能力目标的基础上,进一步增设价值目标,引导学生培养安全责任意识,树立正确的工程价值观念。根据虚拟系统和实物设备的教学优势开展教学活动,结合传统的实验考核方法与动态变化的实操题目实施教学评价,显著提高了学生的专业实践技能,对工程教育专业认证背景下轮机专业实践类课程的改革起到了推动作用。

基于Qt框架的课堂实训任务智能辅助评分系统研究

智能辅助评分系统从教师和学生对实训教学评价实时反馈的需求出发,以Linux操作系统基础课程为实践案例,确定系统的结构组成,完成用户端界面的设计,并实现任务获取与判定、任务成绩数据显示、学生行为监控和数据库四大系统模块功能。教师在系统中进行实训任务的分发和收集、实时查看每个学生每个实训任务的成绩汇总数据。学生则在每次实训的时候获得即时评分反馈,持续优化实训任务的完成情况,以此提高实训教学的教学效率和教学效果。

围压条件下粒子冲击破岩裂隙扩展机理研究

为揭示粒子冲击下围压对岩石裂隙形成及扩展机制的影响,开展了粒子冲击破岩试验和微纳米工业CT(compnted tomography)扫描试验,明确了围压对粒子冲击作用下岩石裂隙扩展特征的影响;并对不同围压条件下的粒子冲击进行数值模拟,分析了岩石的应力场和裂隙场演化过程,揭示了围压影响裂隙扩展的内在机制。结果表明,粒子冲击岩石后,在岩石内部形成破碎区和晶间主裂隙扩展区。压应力导致形成的剪切应力和拉应力是破碎区形成的主要原因,而晶间主裂隙扩展区形成的主要原因是切向衍生拉应力。围压使岩石颗粒间产生预应力,导致切向衍生拉应力需克服颗粒之间的初始压应力才能形成张拉裂隙;围压的增大导致岩石颗粒间剪切裂隙比例和摩擦效应提升,产生相同裂隙数目消耗能量增大,抑制了晶间主裂隙扩展区和破碎区的形成,破碎效果降低。

直接前方入路联合髋关节正前方辅助小切口可吸收螺钉固定治疗PipkinⅠ、Ⅱ型股骨头骨折疗效分析

目的探讨直接前方入路(direct anterior approach,DAA)联合髋关节正前方辅助小切口可吸收螺钉固定治疗PipkinⅠ、Ⅱ型股骨头骨折的临床疗效。方法回顾性分析我院骨科2017年2月至2022年7月收治的13例PipkinⅠ、Ⅱ型股骨头骨折病人的临床资料,男7例,女6例,平均年龄41.6岁(28~57岁);PipkinⅠ型8例,PipkinⅡ型5例。病人经DAA入路联合髋关节正前方辅助小切口可吸收螺钉固定手术治疗。收集病人手术时间、术中出血量、并发症发生情况;通过术后X线片、CT随访了解骨折愈合时间;末次随访时采用疼痛视觉模拟量表(visual analogue scale,VAS)评分、Harris评分、Thompson⁃Epstein评分进行髋关节功能评价。结果13例病人平均手术时间103.7 min(86~116 min),平均术中出血量96.3 mL(70~100 mL),平均随访时间14.6个月(12~18个月)。未发生股神经、股外侧皮神经、股血管损伤等并发症,无切口感染。末次随访时病人VAS评分、Harris评分为(0.15±0.38)分、(95.00±7.15)分,均较术前[(5.38±1.19)分、(17.00±4.78)分]明显改善,差异有统计学意义(P<0.001)。所有病人骨折均愈合,平均愈合时间3.6个月(3~8个月)。末次随访时无股骨头坏死、异位骨化发生,1例病人发生髋关节创伤性关节炎。末次随访Thompson⁃Epstein评价结果,优11例、良2例。结论DAA入路联合髋关节正前方辅助小切口可吸收螺钉固定治疗PipkinⅠ、Ⅱ型股骨头骨折,软组织损伤小,骨折部位显露清楚,可吸收螺钉固定效果确切,并发症发生率低,可作为PipkinⅠ、Ⅱ型股骨头骨折的手术治疗方案。

主动磁悬浮轴承系统保护轴承热特性研究及减摩设计

针对主动磁悬浮轴承系统(AMBs)转子跌落过程中转子与保护轴承碰摩产生巨大冲击、振动和大量摩擦热,易使保护轴承失效的问题,对立式转子跌落到保护轴承过程中的热特性进行了研究,分析了转子跌落对保护轴承造成破坏的主要影响因素,进而提出了一种采用磁控溅射技术在保护轴承关键表面沉积固体润滑薄膜(类石墨碳基薄膜,GLC)的减摩方法,并对镀膜、未镀膜的保护轴承进行了转子跌落试验。研究结果表明:跌落转速为20000 r/min时,保护轴承的最高温度为210.60℃,出现在转子与轴承内圈端面高速碰摩阶段,该温度超过了轴承钢160℃的回火温度,导致轴承烧伤而失效。在跌落试验中,镀有GLC薄膜的自润滑保护轴承试验后的沟道和端面外观明显优于未镀膜保护轴承,由碰摩发热导致的内圈端面硬度下降也较轻,质心轨迹和轴向位移更加平稳,温升更低,GLC薄膜起到了关键的自润滑和减摩功能,提高了保护轴承的使用寿命和服役可靠性,为解决主动磁悬浮轴承系统中保护轴承易失效而发生重大事故的问题提供了一种思路和方法。

印染助剂生产与应用过程中的生态风险防范与应对策略

印染助剂在印染过程中扮演着至关重要的角色。然而,其生产与应用过程也对环境造成了负面影响。梳理印染助剂生产和应用过程的生态风险,提出选用环境友好型印染助剂、教育和培训等防范与应对生态风险的策略。

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%.

基于改进连续时间动态系统的模拟SAT求解器

针对布尔可满足性问题的高效求解进行了研究。首先,通过对k-SAT问题和基于耦合常微分方程形式的确定性连续时间动态系统的分析,提出了一种基于时延信息形式的改进连续时间动态系统方程,以保持集中搜索特性;然后,提出了实现该系统方程的三个主要组件即信号动态电路、辅助变量电路和数字验证电路的模拟设计。在信号动态电路的设计中,设计了一种获得更高性能、更小面积和更低功耗的模拟硬件形式;在提出的辅助变量电路和数字验证电路的模拟硬件设计中,实现了避免梯度下降搜索陷入无解和确定给定问题的解是否已经找到的目标;同时提出了降低面积和功耗的可替代辅助变量电路的两种设计方案。仿真实验结果表明,提出的新的模拟SAT求解器不仅是有效的,而且相比于单一软件算法实现的SAT求解器和其他硬件类SAT求解器具有更高的加速性能和更低的功耗。