快速响应的NV色心微波传感器实现及测量

高精度微波快速测量技术是电磁频谱分析监测的核心,微波测量技术为微波传感器的高精度测量提供了可能。通过建立NV色心空间磁场能级响应频率精密调谐模型,结合NV色心光学宽场成像技术,实现了高精度、响应快可调的微波测量。首先,通过连续光探测磁共振(ODMR)技术,结合宽场成像技术,通过像素级磁场强度-微波频率转化关系,实现宽场成像的微波测量;进而将连续扫频技术转变为施加定频进行检测,通过同步监测频点不同的响应特性,验证了测试结果的有效性。以上结果为高精度固态量子频谱分析仪、高瞬时带宽频谱微波传感器提供了重要技术基础。

近红外光调制下金刚石NV色心自旋动力学与电荷态转化研究

对金刚石氮-空位(nitrogen-vacancy,NV)色心电子自旋态进行光学操控的过程中,近红外光是一种重要手段,对色心自旋态和电荷态布居能产生显著影响,定量研究近红外光对NV色心自旋动力学的作用具有重要意义。文章用实验测量室温下532 nm激光连续激发单个NV色心产生的荧光时间曲线,并建立七能级模型进行数值模拟,得到各自旋能级间跃迁速率;在此基础上用1040 nm激光对色心荧光时间曲线进行调制,实验数据与数值模拟结果相吻合。研究结果表明,近红外光对金刚石NV色心自旋态的影响主要体现在对电荷态转化速率的提高上,使用功率为40 mW的1040 nm激光和532 nm激光一起照射,可以将电离速率和复合速率分别提升约15倍和30倍。

采用磁屏蔽环结构的金刚石NV色心全光直流互感器系统

针对目前电力系统对电流互感器的精度与灵敏度提出的更高要求,提出了一种基于金刚石氮-空位(NV)色心的全光直流互感器的系统方案,系统包括光源模块、激光反馈模块、激光分束模块、一次传感探头模块、激光分频模块、光电转换模块以及信号采集和数据处理模块。对系统中的磁屏蔽环进行了结构的设计与仿真,并对仿真结果进行了实验验证。最后搭建了单通道实验验证系统,系统实测结果表明,设计的全光直流互感器在5 000 A大电流下无磁屏蔽时可以达到0.35%的测量精度,加入磁屏蔽环后测量精度提升到了0.06%,从而为基于金刚石NV色心的全光直流互感器的研制提供了参考。

Preparing highly entangled states of nanodiamond rotation and NV center spin

A nanodiamond with an embedded nitrogen-vacancy(NV)center is one of the experimental systems that can be coherently manipulated within current technologies.Entanglement between NV center electron spin and mechanical rotation of the nanodiamond plays a fundamental role in building a quantum network connecting these microscopic and mesoscopic degrees of motions.Here we present a protocol to asymptotically prepare a highly entangled state of the total quantum angular momentum and electron spin by adiabatically boosting the external magnetic field.

Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

Effects of virtual agents on interaction efficiency and environmental immersion in MR environments

Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.

Design and simulation of an accelerometer based on NV center spin–strain coupling

The nitrogen-vacancy (NV) center quantum systems have emerged as versatile tools in the field of precision measurement because of their high sensitivity in spin state detection and miniaturization potential as solid-state platforms.In this paper,an acceleration sensing scheme based on NV spin–strain coupling is proposed,which can effectively eliminate the influence of the stray noise field introduced by traditional mechanical schemes.Through the finite element simulation,it is found that the measurement bandwidth of this ensemble NV spin system ranges from 3 kHz to hundreds of kHz with structure√optimization.The required power is at the sub-μW level,corresponding to a noise-limited sensitivity of 6.7×10^(-5) /√Hz.Compared with other types of accelerometers,this micro-sized diamond sensor proposed here has low power consumption,exquisite sensitivity,and integration potential.This research opens a fresh perspective to realize an accelerometer with appealing comprehensive performance applied in biomechanics and inertial measurement fields.

Effects and Causes of VR-Supported Interpreting Learning Environment on the Interpretation Classroom Anxiety of Student Interpreter

Interpreting activity is considered a high-anxiety activity due to its immediacy, multitasking, complexity of cognitive processing, and uncertainty of cognitive processing. Research has shown that interpreting anxiety, as the biggest emotional obstacle in the interpreting process, is the main emotional factor that leads to individual differences in interpreting. Students often claim to have fear or anxiety behaviors in interpreting exams, interpreting competitions, and interpreting classes. However, the research on interpreting teaching attaches importance to the cultivation of language knowledge, cultural knowledge, and interpreting skills, and does not pay enough attention to emotional factors such as motivation and anxiety in interpreting learning, which makes it difficult for the cultivated interpreters to meet the requirements of professional practice. In recent years, virtual reality technology (VR) has been gradually applied in the field of foreign language and interpreting teaching for creating a real, interactive and experiential language learning environment. Situated Learning Theory stresses that the fundamental mechanism for learning to take place is for individuals to participate in the real context in which knowledge is generated, and to realize the construction of knowledge through the interaction with the community of practice and the environment. Virtual reality technology can satisfy the needs of language learners for real contexts by providing learners with immersive, imaginative and interactive scenario simulations, and has a certain positive effect on alleviating learning anxiety. Therefore, relying on the virtual simulation course “United Nations Kubuqi International Desert Ecological Science and Technology Innovation International Volunteer Language Service Practical Training System”, this paper adopts a combination of quantitative and qualitative analyses to investigate the interpretation anxiety level of the interpreter trainees and the factors affecting them in the VR situation to help them discover effective responses to interpreter anxiety.

Autonomous VR Exposure Therapy for Anxiety Disorders Using Conversational AI—Ethical and Technical Implications and Preliminary Results

The need for psychotherapy is very high and the lack of care causes a lot of suffering and high costs. This paper presents an interdisciplinary approach to creating an AI-guided exposure therapy for fear of heights in virtual reality (VR). First, ethical principles for the use of conversational AI in psychotherapy were translated into technical requirements and made measurable. Based on this, an autonomous virtual reality exposure therapy was iteratively developed with a therapist. The feasibility and implementation of the ethical principles were tested with a patient. The patient was very satisfied with the VR setup. The AI therapist was also rated positively, although there is still room for improvement regarding conversational skills. Overall, the paper shows how AI can contribute responsibly to improving the psycho-therapeutic supply. It also provides guidelines that make ethical principles tangible and measurable for developers.

Hybrid Prairie Dog and Beluga Whale Optimization Algorithm for Multi-Objective Load Balanced-Task Scheduling in Cloud Computing Environments

The cloud computing technology is utilized for achieving resource utilization of remotebased virtual computer to facilitate the consumers with rapid and accurate massive data services.It utilizes on-demand resource provisioning,but the necessitated constraints of rapid turnaround time,minimal execution cost,high rate of resource utilization and limited makespan transforms the Load Balancing(LB)process-based Task Scheduling(TS)problem into an NP-hard optimization issue.In this paper,Hybrid Prairie Dog and Beluga Whale Optimization Algorithm(HPDBWOA)is propounded for precise mapping of tasks to virtual machines with the due objective of addressing the dynamic nature of cloud environment.This capability of HPDBWOA helps in decreasing the SLA violations and Makespan with optimal resource management.It is modelled as a scheduling strategy which utilizes the merits of PDOA and BWOA for attaining reactive decisions making with respect to the process of assigning the tasks to virtual resources by considering their priorities into account.It addresses the problem of pre-convergence with wellbalanced exploration and exploitation to attain necessitated Quality of Service(QoS)for minimizing the waiting time incurred during TS process.It further balanced exploration and exploitation rates for reducing the makespan during the task allocation with complete awareness of VM state.The results of the proposed HPDBWOA confirmed minimized energy utilization of 32.18% and reduced cost of 28.94% better than approaches used for investigation.The statistical investigation of the proposed HPDBWOA conducted using ANOVA confirmed its efficacy over the benchmarked systems in terms of throughput,system,and response time.

An Adaptive Control Strategy for Energy Storage Interface Converter Based on Analogous Virtual Synchronous Generator

In the DC microgrid,the lack of inertia and damping in power electronic converters results in poor stability of DC bus voltage and low inertia of the DC microgrid during fluctuations in load and photovoltaic power.To address this issue,the application of a virtual synchronous generator(VSG)in grid-connected inverters control is referenced and proposes a control strategy called the analogous virtual synchronous generator(AVSG)control strategy for the interface DC/DC converter of the battery in the microgrid.Besides,a flexible parameter adaptive control method is introduced to further enhance the inertial behavior of the AVSG control.Firstly,a theoretical analysis is conducted on the various components of the DC microgrid,the structure of analogous virtual synchronous generator,and the control structure’s main parameters related to the DC microgrid’s inertial behavior.Secondly,the voltage change rate tracking coefficient is introduced to adjust the change of the virtual capacitance and damping coefficient flexibility,which further strengthens the inertia trend of the DC microgrid.Additionally,a small-signal modeling approach is used to analyze the approximate range of the AVSG’s main parameters ensuring system stability.Finally,conduct a simulation analysis by building the model of the DC microgrid system with photovoltaic(PV)and battery energy storage(BES)in MATLAB/Simulink.Simulation results from different scenarios have verified that the AVSG control introduces fixed inertia and damping into the droop control of the battery,resulting in a certain level of inertia enhancement.Furthermore,the additional adaptive control strategy built upon the AVSG control provides better and flexible inertial support for the DC microgrid,further enhances the stability of the DC bus voltage,and has a more positive impact on the battery performance.

Research on the Application of Virtual Simulation Experimental Teaching in the Securities Investment Course

With the rapid development of information technology and the increasing complexity of the financial market,the teaching methods and means of the Securities Investment course in universities are facing new challenges and opportunities.The purpose of this paper is to discuss the application and construction path of virtual simulation experimental teaching in the Securities Investment course.Firstly,it analyses the problems existing in the teaching of traditional securities investment courses,such as the disconnection between theory and practice and the single teaching mode.In order to solve these problems,this paper puts forward the necessity of introducing virtual simulation experimental teaching and details the specific application path of virtual simulation experimental teaching in the Securities Investment course.

基于无微波金刚石NV色心测磁技术的电流测量应用

为了在特高压(UHV)环境下使用氮-空位(NV)色心量子测量技术,研究了金刚石主轴与磁场夹角对相应曲线及电流测量精度的影响。构建金刚石氮-空位七能级超精细结构模型,根据仿真结果得到不同磁场方向下最高灵敏度范围和最佳测量范围,从而确定探头的最佳放置角度。基于无微波金刚石氮-空位技术搭建了直流大电流测量实验平台,测试了100~5000A范围内荧光电压对电流的响应曲线。实验结果表明,该平台对5000A直流电流测量误差在0.25%以内。作为无源器件,无微波金刚石氮-空位色心测磁传感器全光纤信号传输具备良好耐压性能,同时可在室温下工作,并具有结构紧凑、灵敏度高、抗电磁干扰能力强等优势,适用于特高压环境下的直流电流测量,为传统电力行业检测提供了新的检测方法。

基于虚拟仿真技术的汽车NVH实验教学研究

随着汽车工业的快速发展,人们对汽车产品驾乘体验要求的不断提高,汽车噪声、振动和声振舒适性(NVH)日益受到关注。汽车NVH实验教学已成为汽车工程领域教育的重要内容,传统的汽车NVH实验教学模式存在成本高昂、时间长、受环境影响大、安全风险高等问题,往往难以满足教学需求。虚拟仿真技术为汽车NVH实验教学提供了新的思路,虚拟仿真技术在汽车NVH工程领域应用广泛,将其引入汽车NVH实验教学,不仅能够提供更加灵活和安全的实验环境,而且能够提供更加直观和深入的学习体验,有助于学生更好地掌握NVH理论与实践知识。

基于局域表面等离激元Ag/金刚石纳米结构增强NV色心的荧光

在纳米光子学中,提高量子点的荧光强度是一个需要迫切解决的难题,现如今金属纳米材料是一种很有前途的荧光增强材料。通过Ag纳米结构的局域表面等离激元效应提高金刚石氮空位(NV)色心的荧光强度,制备了不同的Ag纳米结构(Ag纳米柱阵列和Ag纳米层),探究其对NV色心的荧光增强效果。结果表明,Ag纳米柱阵列结构的加入可将金刚石NV色心的荧光强度增强2.30倍,Ag纳米层结构的加入可将其增强1.54倍。并且,采用时域有限差分(FDTD)法分析激发和发射两个过程发现,金刚石NV色心的荧光强度随着Ag纳米结构的加入显著提高,由此验证了实验中Ag纳米结构对金刚石NV色心荧光增强的效果。此研究结果为后续进行量子点光致发光器件的设计提供了一定的参考。

Security Challenges of Virtualization Hypervisors in Virtualized Hardware Environment

The concept of virtualization machines is not new, but it is increasing vastly and gaining popularity in the IT world. Hypervisors are also popular for security as a means of isolation. The virtualization of information technology infrastructure creates the enablement of IT resources to be shared and used on several other devices and applications;this increases the growth of business needs. The environment created by virtualization is not restricted to any configuration physically or execution. The resources of a computer are shared logically. Hypervisors help in virtualization of hardware that is a software interact with the physical system, enabling or providing virtualized hardware environment to support multiple running operating system simultaneously utilizing one physical server. This paper explores the benefits, types and security issues of Virtualization Hypervisor in virtualized hardware environment.

金刚石NV色心在钢丝绳缺陷检测中的应用

氮-空位(NV)色心是金刚石中的一种晶格缺陷,由于其具有优异的自旋性质和光学性质,在量子精密测量领域受到广泛关注。利用金刚石的高灵敏度和高分辨率磁测量特性,实现灵敏且准确的钢丝绳缺陷检测。在磁场测量方面,该技术使用光学探测磁共振法测出NV色心的共振频率,从而计算出外界的磁场强度。在钢丝绳检测方面,以浓度为1.8×10^(17)~3.6×10^(17)的NV色心磁传感器为核心组成探头模块,三块高度集成的现场可编程门阵列(FPGA)板卡组成控制模块,搭建量子精密测量平台,检测钢丝绳断丝缺陷和微弱磨损缺陷。实验结果表明,该系统的磁场测量灵敏度可达6 nT/Hz,空间分辨率为200μm,可以对钢丝绳缺陷进行准确检测,为工业安全提供了新的检测方式。

基于磁集聚器的金刚石NV色心磁力计灵敏度的增强

对于金刚石氮空位(NV)色心磁力计,探索新的方法提高其灵敏度具有重要的意义。详细介绍了一种基于闭环反馈的频率调制技术结合磁集聚器的高灵敏度和高分辨率磁测量方法。设计了具有12倍磁放大倍数的T型磁集聚器。通过频率调制技术,磁力计灵敏度由1.5 nT/Hz^(1/2)提升到0.13 nT/Hz^(1/2)。同时,通过闭环锁定技术,磁力计最小可检测磁感应强度由10 nT增强到1 nT。该方法在理论和实验上均得到了验证,能够实现磁力计灵敏度和分辨率的提高,为高灵敏度和高分辨率磁力计的设计提供了参考,同时对自旋电子磁共振的基础研究也有着重要的意义。

基于金刚石NV色心的微角度测量方法

微角度检测在超高精密测量技术中有着重要的作用。研发了一种基于金刚石氮空位(NV)色心的微角度测量方法,其中NV色心作为微角度检测敏感单元,共轴磁铁作为传感单元,由于共轴磁铁和金刚石NV轴之间不同夹角下的磁场强度变化引起金刚石NV色心自旋能级波动,从而使得光学探测磁共振(ODMR)信号漂移,通过闭环频率锁定技术的实时追踪实现微角度的检测。并对微角度测量进行了理论分析和实验测试,理论和实验结果基本一致。同时,通过该方法获得了微角度传感检测的灵敏度为200 mV/deg,分辨率为10 mdeg,系统的等效角度均方根噪声为0.69 mdeg/Hz^(1/2)。该方法为高灵敏度、高分辨率的微角度检测提供了新的手段,同时实时追踪金刚石多个NV轴,可实现姿态矢量微角度检测。

集群金刚石NV色心量子自旋定向激发磁传感增强方法

为满足工业磁传感器高灵敏度、高信噪比(SNR)测量需求,基于自制的共聚焦磁检测系统,提出一种基于脉冲幅度调制技术的集群金刚石氮空位(NV)色心量子自旋定向激发(QSDE)方法。利用任意波形发生器构建sin型QSDE脉冲光探测磁共振序列,抑制传感体系中对微波敏感的Ns杂质与NV色心产生耦合效应带来的线宽展宽与噪声,提升谱线对比度的同时降低了线宽与噪声,突破微波强度对灵敏度和SNR的限制。经实验验证,相较连续波光探测磁共振(CW-ODMR)方法,该方法可将磁传感灵敏度和信噪比分别大约提升5倍和20 dB,为量子精密测量领域开辟了全新的技术路径和研究思路。