Material growth and device fabrication of terahertz quantum-cascade laser based on bound-to-continuum structure

The terahertz quantum-cascade laser （THz QCL） based on bound-to-continuum structure is demonstrated. The X-ray diffraction measurement of the material shows a high crystalline quality of the active region. A THz QCL device was fabricated with semi-insulating surface-plasmon waveguide. The test device is lasing at about 3 THz and operating up to 60 K. It shows a single frequency property under different drive currents and temperatures. At 9 K, the maximum output power is greater than 2 mW with a threshold current density of 159 A/cm2.     

太赫兹波在雾中的多重散射特性

太赫兹(THz)波作为微波和毫米波的延伸,它所提供的通信带宽和容量远大于毫米波。在随机介质中传播时,不但会发生时域和空域的形变,介质中的粒子还会对入射波发生散射,这些都会使得脉冲信号发生衰减。根据Mie理论与随机离散分布粒子的波传播与散射理论,计算了THz波信号入射下雾滴粒子的消光系数。结合雾滴粒子谱分布,得到了雾媒质的平均体系散射特性,采用蒙特卡罗法得到了平流雾对THz信号的多重散射特性,计算了THz波段信号对平流雾的透过率与反射率,分析了THz波段信号的前向、后向散射特性随散射角的分布。结果表明,低能见度大气环境中,雾对THz波产生的吸收和衰减不容忽视。相关研究结果对THz在大气传输、通信等方面的应用具有重要意义。     

紫外成像器件光电阴极封接焊料熔层缺陷对气密性的影响

为解决紫外成像器件光电阴极与管体封接漏气问题,对管体InSn合金熔化过程中出现的质量问题进行了深入分析,找出焊料熔层缺陷主要来源于对焊料除气不彻底和基底表面氧化及设备油污染。通过优化工艺参数,改进工艺质量和把化铟设备管体搁置焊料熔化改为浇铸熔化,使管体焊料熔化合格率达到了100%,光电阴极与管体封接气密性成品率达到98%。     

Relative density-based classification noise detection

Classification noise is a common byproduct of traditional data mining approaches, and no specialized approach for detecting classification noise is currently available. Methods for outlier detection are well-developed, but outliers and classification noise have characteristics different enough to make outlier detection algorithms unsuitable for classification noise detection. In this paper, a new, specialized approach to detect classification noise is proposed, named relative density based classification noise detection (RDBCND). Computational experiments in artificial data sets described herein show that RDBCND has time complexity of O(n log n), indicating greater efficiency than traditional approaches, which exhibit time complexity of at least O(n²). The use of classification noise detection to improve the generalization ability of common classifier algorithms is also described. In particular, a new unified approach based on RDBCND is compared to a cross validation approach applied to a BP neural network. Trials in both artificial and real-life datasets show that the RDBCND-based approach can greatly accelerate the process of identifying the best decision function. The novel method can also eliminate underfitting, as the algorithm simply searches for the highest training accuracy. The experiments also show that the RDBCND-based method has greater accuracy and lower cpu time in reaching global solutions than the cross-validation method. Since the relative density is a local concept, our new approach can be directly used in nonlinear datasets without data transformation. It is a great advantage compared to some linear classifier algorithms. As in current linear classifiers, the kernel functions or other transformations need to be used to make them suitable for non-linear datasets, and that will increase their complexity.     

A study on small-world brain functional networks altered by postherpetic neuralgia

Understanding the effect of postherpetic neuralgia (PHN) pain on brain activity is important for clinical strategies. This is the first study, to our knowledge, to relate PHN pain to small-world properties of brain functional networks. Functional magnetic resonance imaging (fMRI) was used to construct functional brain networks of the subjects during the resting state. Sixteen patients with PHN pain and 16 (8 males, 8 females for both groups) age-matched controls were studied. The PHN patients exhibited decreased local efficiency along with non-significant changes of global efficiency in comparison with the healthy controls. Moreover, regional nodal efficiency was found to be significantly affected by PHN pain in the areas related to sense (postcentral gyrus, inferior parietal gyrus and thalamus), memory/affective processes (parahippocampal gyrus) and emotional activities (putamen). Significant correlation (p < 0.05) was also found between the nodal efficiency of putamen and pain intensity in PHN patients. Our results suggest that PHN modulates the local efficiency, and the small-world properties of brain networks may have potentials to objectively evaluate pain information in clinic.     

红外双波段双层谐衍射光学系统设计

将谐衍射透镜应用在传统红外单波段佩茨瓦尔(Petzval)物镜上,设计得到工作波段处于3.4~4.2μm和8~11μm的红外双波段单层谐衍射光学系统。但单层谐衍射元件的衍射效率只在设计波长处衍射效率最高,随着波长相对设计中心波长向两侧偏离,主衍射级次的衍射效率逐渐下降。为提高含单层谐衍射元件光学系统的衍射效率,基于双层衍射元件衍射效率表达式研究了双层谐衍射元件的结构优化,给出了优化方法。设计出佩茨瓦尔型红外双波段双层谐衍射光学系统,其在3.4~4.2μm和8~11μm两个工作波段的衍射效率均达到90%以上,相比含有单层谐衍射面的光学系统衍射效率有了很大提升,提高了像面衬比度,完善了系统成像质量。     

1 053-nm all-fiber pulse multi-pass stretcher using a linear chirped fiber Bragg grating

An all-fiber optical laser pulse multi-pass stretcher using a chirped fiber Bragg grating (CFBG) is demonstrated. Pulses from a 1 053-nm mode-locked fiber seed oscillator are stretched by multiple passing through a chirped fiber grating set in a fiber regenerative amplifier structure. We stretch the pulse from 16 ps to 1.855 ns after it transmits seven loops in the stretcher. The main factors that affect the stretching results are discussed.     

超高精细度微光学腔共振频率及有效腔长的精密测量

超高精细度微共振器是实现原子或者其他偶极子与腔强耦合作用的基本部分, 在腔量子电动力学(QED)、弱光非线性效应及微光学器件研究中扮演着重要的角色. 微腔基本参数的精密测量最终可以确定腔与原子的耦合系数、腔场衰减率, 对决定系统的动力学特性具有重要的意义. 但是由于超高精细度光学微腔本身的构造和多层镀膜的特点, 高精度地确定其共振频率及有效腔长存在一定困难. 本文结合修正的多层介质膜模型, 实验上完成了膜层为37层的超高精细度光学微腔在不同共振频率下有效腔长的精密测量, 获得了超高精细度光学微腔的共振频率及波长; 理论计算分析与实验测量结果相符, 对纵模间隔的测量精度误差低于0.004 nm, 较为修正前提高了约两个量级. 同时给出了对应不同模式数下, 光波渗入到介质中的深度. 该方法可望应用到其他微共振器的精密测量中. 关键词： 光学微腔 高精细度 共振频率