Differential rotation of giant stars

From a set of high-resolution spectral observations of late type giant stars we used Doppler imaging to derive time-series temperature maps of the stellar surfaces. Using these temperature maps, it is possible to track the temporal changes of the spot features and derive estimates of the strength and sign of the differential surface rotation of these stars. Looking into the latitudinal changes of the surface maps, it is also possible to derive meridional flows on these stars. But due to the lower accuracy of the latitudes of the reconstructed spot features, the data requirements are higher than for the detection of differential rotation. Nevertheless, a correlation between the differential rotation and meridional flow estimates is suggested. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

一种低噪声硅微条探测器读出电子学系统的设计

硅微条探测器空间分辨率高、工作性能稳定, 广泛地应用于空间高能粒子探测领域. 如费米gamma射线空间望远镜(Fermi Gamma-ray Space Telescope, FGST)以及阿尔法磁谱仪(Alpha Magnetic Spectrometer 2, AMS-02)的径迹探测器中都采用了高位置分辨率的硅微条探测器. 基于硅微条探测器在空间观测领域的应用前景, 针对硅微条探测器单元设计了一套低噪声的电子学读出系统. 整个电子学系统分为前端电子学、数据获取电路和上位机软件. 前端电子学为提高集成度, 采用了一款电荷读出芯片VATAGP8, 实现了多通道、低噪声的电荷信号测量; 数据获取电路使用现场可编程门阵列(Field Programmable Gate Array, FPGA)实现了对前端电子学的时序控制以及对测量信号的采集控制; 上位机用来接收、处理数据获取电路采集的信号数据. 在对电子学通道的线性、基线、噪声等性能进行测试之后, 得到系统在0--200fC电荷输入范围内的线性增益约为13.41bin/fC, 积分非线性小于1%, 噪声小于0.093fC. 为了验证电子学读出系统对硅微条探测器单元的读出能力, 将两者集成在一起并测试了宇宙线缪子的能量沉积, 得到读出电子学系统的信噪比大于32, 缪子的电离损失能谱与Landau-Gaussian分布符合较好, 能够满足硅微条探测器单元读出电子学的设计要求.     

Standard techniques for presentation and analysis of crater size-frequency data

In September 1977, a crater studies workshop was held for the purpose of developing standardized data analysis and presentation techniques. This report contains the unanimous recommendations of the participants. This first meeting considered primarily crater size-frequency data. Future meetings will treat other aspects of crater studies such as morphologies.     

基于光变曲线的空间碎片基本形状分类

将未编目的空间碎片正确分类是空间态势感知的重要组成部分. 基于光变曲线, 通过仿真和实测实验, 探讨了空间碎片基本类型的机器学习分类方法. 在数据集中的仿真光变来自形状或材料不同的4类碎片, 实测光变从Mini-Mega TORTORA (MMT)数据库中提取, 实验以深度神经网络作为分类模型, 并和其他机器学习方法进行了比较. 结果显示深度卷积网络优于其他算法, 在仿真实验中对不同材料的圆柱体都能准确识别, 对其余两类卫星的识别率在90%左右; 实测实验中对火箭体和失效卫星的2分类准确率超过99%, 然而在进一步的型号/平台分类中, 准确率有所降低.     

应用地震连续形变观测技术有效监测地震前兆

依据地震观测技术的基本原理和大量观测事实,给出统一的地震连续形变观测技术仪器的特性曲线,分析和解释其对“前兆”信息响应差异的根本原因。地震连续形变前兆仪器对地震及其前兆响应的差异是因为仪器的传递函数不同和特性所致;其前兆观测中的分钟值采样数据中发现的震颤异常波,只是真实信号的一种“混叠”或映射,难以反映真实的地面运动。强震前的震颤异常波是否与地震有关？是否是震兆？尚需做更深入细致的分析和研究。     

Study of Radio Frequency Interference Mitigation Method Based on Wavelet Transform

In radio astronomy observations, radio frequency interference (RFI) is mixed into the telescope receiving system in various forms. The existence of RFI brings misjudgment to the observation or reduces the observational signal-to-noise ratio. In recent years, the domestic and overseas radio astronomy has developed rapidly. Large-scale radio telescopes and telescope arrays at home and abroad have been constructed successively. Observation sensitivity is greatly improved, and the influence of RFI is particularly prominent. With the development of science and technology and the intensification of human activities, the RFI has become increasingly serious and irreversible. We propose to use the two-dimensional discrete wavelet transform method to analyze the data of radio astronomy observations, and to perform wavelet transform on the time-frequency sequence output by the telescope system. According to the wavelet coefficients, the every component in the original signal is separated, and the corresponding threshold value is obtained by the statistics on each component. Each component is compared with the threshold to identify the interference component, and to mark it for removal. This method is used to process the actual observation data. The results show that this method can well mark and eliminate the interference signal, and improve the observational signal-to-noise ratio.