New trend for optical signal-to-noise ratio of disturbed Raman fiber amplifier

In a distributed Raman fiber amplifier (DRFA), Raman amplification allows a lower signal launch powers to transverse the span above the noise floor while still increasing the optical signal-to-noise ratio (OSNR). It improves the noise figure and reduces the nonlinear penalty of fiber systems. In this paper, we demonstrate a new trend of OSNR at different pump configurations: forward, backward and bidirectional pumping for DRFAs as a function of fiber length. We also present the variation of OSNR with both input pump power and input signal power. It is found that forward pumping provides the highest OSNR, reaching its maximum value of 37 dB. However, backward pumping provides the smallest OSNR that has its maximum of 22 dB and the bidirectional pumping provides the moderate OSNR between the others having its peak of 26 dB.     

Analytical investigation of response of birefringent fiber Bragg grating sensors in distributed monitoring system based on optical frequency domain reflectometry

When Fiber Bragg gratings (FBGs) are used as strain sensors, both longitudinal and lateral strain can be applied uniformly or non-uniformly over the length of the FBGs. In order for the demodulation of such FBG signal, this paper investigates the response of birefringent FBGs which are monitored by distributed measurement system based on optical frequency domain reflectometry. A numerical model of the distributed measurement system is built based on piece-wise uniform approach, which considers polarization states of propagating lights. The numerical model simulates analytical response of birefringent FBGs especially when birefringence induces power fluctuations in the distributed spectra, which can be noise or new opportunity for sensitive monitoring of birefringence. Simulation results show the relationships between the power fluctuations and the polarization states of the propagating lights. Consequently, appropriate methods of polarization control for sensitive distributed birefringent FBG monitoring are discussed.     

全三维电离粒子有源像素探测器优化仿真

提出了一种双外延高能离子注入的单片集成有源像素探测器的传感器结构,以提升传感器对电荷的收集性能和辐射加固,并进行了三维工艺模拟和物理级器件仿真计算.研究结果表明,所提出的传感器结构改善了内部电场和电势的分布,且目标电极的电荷收集效率提高70%,电荷收集时间减少64%.此外,当等效中子辐射流通量在1012—1015cm-2范围内时,所提出的传感器结构比标准传感器结构有更高的电荷收集能力.     

集体噪声信道上带身份认证的无信息泄露的量子对话协议

在集体噪声条件下提出三个带身份认证的量子对话协议,两个量子对话协议分别用于抵抗集体消相干噪声和集体旋转噪声,另一个用于同时抵抗这两种集体噪声.通信双方通过广义幺正变换将自己的秘密信息编码到量子态中;并根据自己的秘密信息和携带秘密信息的粒子的初末两量子态,便可推知对方的秘密信息实现量子对话.协议的效率、安全性和无信息泄露等性能分析表明了协议的有效性.     

线形离子阱囚禁199Hg＋实验的光学系统设计

利用Zemax软件为线形离子阱囚禁199 Hg＋实验设计了一套光学系统,该系统包括两部分,即光学激发系统和荧光收集系统。光学激发系统由202 H g无极谱灯和激发透镜组组成。激发透镜组将202 Hg无极谱灯的直径为15 mm的圆形面光源整形成23 mm ×4 mm的矩形光去激发199 H g＋能级跃迁,从而使其辐射出荧光,再利用荧光收集系统去收集该荧光。荧光收集系统由收集透镜组、滤波片和光电倍增管组成。设计结果表明：该收集透镜组可以很好地将荧光发光面成像在直径为23 m m的光电倍增管上,具有较高的荧光收集效率,约3％。经物理系统实验,结果表明,该光学系统满足实验要求且具有较高的信噪比,其值约为20。这为高性能线形199 H g＋微波频标的工程应用提供了基础。     

1.66 μm和 1.55 μm光源对长距离光纤拉曼温度传感器测量时间影响的理论对比

通过理论分析,在综合考虑长距离光纤拉曼温度传感器中各光学器件波长相关特性的基础上,比较了1.66 μm和1.55 μm光源对传感器测量时间的影响.计算结果表明,由于各光学器件在1.5 μm波段的高性能和最大允许入纤脉冲峰值功率的增加,采用1.66 μm光源的光纤拉曼温度传感器,最高可获得约1.94倍的背向反斯托克斯信号.在相同空间分辨率和温度分辨率的情况下,测量时间可以降低约3/4.     

光纤移频分布式布里渊光纤传感技术

提出了一种利用布里渊光纤环形腔移频技术实现分布式光纤布里渊传感的方法.该方法基于布里渊光时域分析法原理,将一束单纵模运转激光器输出的激光分为两束|一束光入射布里渊光纤环形腔中产生窄线宽的受激布里渊散射光作为斯托克斯光,另一束光经过低频相位调制后作为泵浦光|斯托克斯光和泵浦光分别相向入射进入传感光纤,通过测量布里渊谱得到光纤温度或应变.利用该方法可将十几GHz的微波频率转化为兆赫信号频率进行探测处理,仅需一台激光器,因此系统结构简单、成本低,还可减小激光器频率波动对测量准确度的影响.实验验证了该方法的可行性.     

A greedy-model-based reinforcement learning algorithm for Beyond-5G cooperative data collection

Data collection is an essential part of Beyond-5G and Internet of Things applications. In urban area, heterogeneous access points such as Wi-Fi routers and base stations can meet the required communication coverage and bandwidth in data collection processes. However, in remote area, without communication infrastructures, it is hard to guarantee the communication quality of a large-scale data aggregation network. An existing approach is to use an unmanned aerial vehicle (UAV) to act as a mobile sink to perform data collection and increase the coverage of intelligent wireless sensing and communications. The efficiency and the reliability of such a UAV-assisted data collection system can be significantly enhanced with an intelligent cooperative strategy for the sensors deployed in the field to communicate with the UAV. Furthermore, an energy-efficient trajectory planning algorithm is crucial to address the physical limitations of the UAV in this application. In this paper, a data collection process is modeled as a Markov decision process (MDP). The paper begins with proposing two heuristic greedy algorithms, namely distance-greedy (DG) algorithm and rate-greedy (RG) algorithm, which are designed based on prior knowledge of the system and can guarantee the completion of the data collection process in a remote area without the help of fixed communication infrastructures. Based on the outcomes, a multi-agent greedy-model-based reinforcement learning (MG-RL) algorithm is proposed, which specifically designs the environmental state and the reward scheme, and introduces multiple UAVs with different parameters to explore environments in parallel to accelerate the training. In conclusion, the two proposed greedy algorithms have lower complexity of implementation while the proposed MG-RL algorithm yields practical UAVs’ flight trajectories and shortens the time for completing a data collection task.     

Optimal control of time delay parabolic systems

Various optimal control problems for linear parabolic systems with multiple constant time delays are considered. Necessary and sufficient conditions of optimality are derived for the Neumann problem. The optimal control is obtained in the feedback formMaking use of the results of Schwartz's, the representation of the optimal feedback control is given. A simple example of application is also provided     

On optimal management of resources in distributed networks

In a network of processors, a distributed operating system must handle the management of shared resources. In this paper, it is shown how to solve this problem in using the model previously introduced in [1]. This model (interconnection of N Markov chains each representing locally a distributed process) allows us to prove the good functioning properties for some distributed problems such as the mutual exclusion problem and the deadlock problem, We also prove that fairness is a basic notion for setting the model’s parameters and obtain an optimal working of the network.