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.     

甚大面积伽马射线空间望远镜计划

高能伽马射线探测是研究极端天体物理的主要途径之一.空间高能伽马射线探测具有覆盖波段宽、时间连续性好、能量分辨率高等突出优势.在成功研发并运行我国首颗天文卫星—“悟空”号(DArk Matter Particle Explorer, DAMPE)的基础上,紫金山天文台联合国内的多家单位提议研制甚大面积伽马射线空间望远镜(Very Large Area gamma-ray Space Telescope, VLAST),该望远镜在GeV–TeV能段接受度高达10 m2·sr,并具有强的MeV–GeV波段探测能力,其综合性能预期比费米卫星的大面积伽马望远镜(Fermi-LAT (Large Area Telescope))提升10倍之上.重点介绍了VLAST的主要科学目标,探测器的初步配置及预期性能指标.     

暗物质空间探测器BGO量能器的读出设计

暗物质空间探测器是中国科学院紫金山天文台暗物质空间天文实验室提出的,其目的是为了探测暗物质粒子湮灭可能产生的高能电子和伽玛粒子.整个探测器主要由BGO(Bismuth germanate,锗酸铋)高能图像量能器和闪烁体径迹探测器构成.探测器的能量探测范围将覆盖10 GeV到10 TeV的高能电子和伽玛粒子,其中高能粒子的能量主要沉积在BGO量能器中.为了验证探测器方案,紫金山天文台暗物质空间天文实验室设计了暗物质空间探测器BGO量能器的读出系统原型,并对其进行了初步的测试.     

空间乳胶室探测器的研制

"实践八号"乳胶室探测器是我国首次用于空间观测高能电子及伽玛射线的乳胶 室探测器.介绍"实践八号"乳胶室探测器的设计原理、数据分析方法、设计过程和初步 观测结果等."实践八号"乳胶室探测器空间观测时间为15天,可探测的粒子能量范围为 100GeV～5TeV.     

暗物质粒子探测卫星有效载荷综合测试系统的设计与实现

暗物质粒子探测卫星(Dark Matter Particle Explorer,DAMPE)是一个空间高能宇宙射线探测器.DAMPE的有效载荷包括塑闪阵列探测器、硅阵列探测器、BGO(Bismuth germanate)量能器、中子探测器(Neutron Detector,NUD)以及载荷数管5个分系统,这5个分系统协同完成宇宙线事例信息的采集.卫星发射之前需要对有效载荷的功能进行系统性验证,因此基于Lab Windows/CVI(C programming language Virtual Instrument)开发平台建设了一套用于暗物质粒子探测卫星有效载荷系统测试的地面综合测试系统.该系统实现了有效载荷系统测试的集成化、自动化,提高了测试的安全性、可靠性和测试效率,为暗物质粒子探测卫星有效载荷的顺利交付提供了保障.     

BGO量能器大动态范围读出的线性标定系统的设计和实现

暗物质空间探测器是中国科学院紫金山天文台空间实验室提出的,其目的是为了探测暗物质粒子湮灭可能产生的高能电子和伽玛粒子.BGO量能器是暗物质粒子探测卫星主要载荷之一,高能粒子的能量主要沉积在BGO量能器中.为了使探测器覆盖5 GeV~10T'eV的探测范围,要求每个BGO探测单元具有约1.5×10~5的动态范围.为了对这一大动态范围的探测单元进行测试,提出一种比较简易的线性测试方法,并在实验室构建一个相应的测试系统,对BGO量能器探测单元读出系统的线性进行测试.测试结果表明BGO量能器探测单元读出的非线性度好于2.7%.     

基于暗物质粒子探测卫星的宇宙线直接探测研究

高能宇宙线的起源、加速和传播是重大的前沿科学问题,回答该问题需要对宇宙线的能谱、各向异性以及各类高能天体电磁辐射进行精确观测.通过空间粒子探测器对宇宙线各成分能谱的直接测量是研究宇宙线物理问题的重要手段.中国于2015年底发射并持续运行至今的暗物质粒子探测卫星以其大接受度、高能量分辨率等特点,在宇宙线直接探测方面取得了系列重要成果,揭示出质子、氦核、硼碳和硼氧比例等宇宙线能谱的新结构,为理解宇宙线起源等科学问题提供了新的依据.介绍了暗物质粒子探测卫星的仪器设置、运行状况、科学成果及其物理意义.     

举世瞩目的土星探险

土星是太阳系仅次于木星的第二大行星。人们在天文望远镜中所看到的行星中,土星是最美丽的,因为它腰部带有非常显著、宽阔和明亮的光环。从1979年"先驱者"11号开始,先后共有3个空间探测器飞越土星,但它们的探测只是浮光掠影,限于条件未做详细考察。1997年10月15日升空的"卡西尼"号探测器,将于2004年7月飞抵土星轨道。半年多后,"卡西尼"号将向土卫六大气层投放"惠更斯"号子探测器。人们正期盼着"卡西尼"号及其子探测器"惠更斯"号能早日传来土星探测新信息。     

基于FPGA的空间太阳磁像仪自校正稳像系统研制

太阳磁像仪是开展太阳磁场观测研究的核心仪器,其中的稳像系统是空间太阳磁像仪的关键技术之一,针对深空探测卫星系统对载荷重量、尺寸限制严苛的要求,设计了基于图像自校正方法的稳像观测系统.介绍了一套基于现场可编程门阵列(Field-Programmable Gate Array, FPGA)和数字信号处理器(Digital Signal Processor, DSP),通过基于自相关算法的高精度稳像方法设计,并结合精确偏振调制、准确交替采样控制等系统软硬件设计,克服由于卫星平台抖动、指向误差等因素造成的图像模糊,实现实时相关、校正、深积分的稳像观测系统.针对像素尺寸为1 K×1 K、帧频为20 fps的CMOS (Complementary Metal Oxide Semiconductor)探测器,实现了1像元以内的实时稳像观测精度.在完成实验室测试后, 2021年6月18日在国家天文台怀柔太阳观测基地35 cm太阳磁场望远镜上开展了实测验证,结果表明该系统能够有效地完成太阳磁像仪自校正稳像观测,获得了更高分辨率的太阳磁场数据.稳像系统的成功研制不仅可以为深空太阳磁像仪的研制提供轻量化、高...     

临界曲线附近的微引力透镜效应模拟

在光滑物质分布模型下,临界曲线是强引力透镜系统中像平面上一条放大率为无穷的线,而考虑少量离散质量的微透镜效应后,源平面上的放大率分布会出现复杂的结构,为暗物质成分的探测提供了一种有效途径.模拟临界曲线附近微透镜效应存在临界曲线上放大率无穷大和计算量巨大的困难.要达到所需的模拟精度,直接使用传统的光线追踪算法需要巨大的计算资源.为此发展了一个能实现海量计算的Graphics Processing Unit (GPU)并行方法来模拟临界曲线附近的微引力透镜效应.在型号为NVIDIA Tesla V100S PCIe 32 GB的GPU上,对于需要处理13000多个微透镜天体、发射1013量级光线的模拟,耗时在7000 s左右.在GPU并行的基础上,与直接的光线追踪算法相比,插值近似的引入使计算速度提升约两个数量级.利用该方法生成80个放大率分布图,并从中抽取800条光变曲线,进行了微焦散线数密度和峰值放大率的统计.     

High time-resolution spectroscopic imaging using intensified CCD detectors

The micro‐channel plate intensified CCD photon counting detector developed at University College London has been upgraded to allow time-resolved spectroscopic optical data to be acquired on periodical sources such as pulsars. First observing trials have been carried out, acquiring spectroscopic data on the Crab pulsar. The detector was phase locked to the pulsar period and a temporal resolution of 41.4 μs employed. The phase locking allowed the coaddition of time slices over a large number of pulsar periods to build up quantifiable spectroscopic data when observing in a flux-limited regime.     

A data analysis approach for detecting gravitational waves from PSR 0437–4715

A search for gravitational waves from the millisecond pulsar PSR 0437-4715 has been initiated using the bar detector NIOBE which is located at the University of Western Australia. We present a detailed report on the data analysis algorithm, called phase plane rotation , which will be used in this search. A discussion of the actual implementation of the algorithm is presented. The data analysis algorithm mentioned above has the advantage that it requires minimal changes to the already-existing data acquisition facility of NIOBE but, at the same time, it is as efficient as optimal filtering in detecting a signal. This search involves a very long coherent integration of the bar output which may stretch over a few years. With some planned improvements in the detector, a three-year integration should be able to put an upper limit of h  ∼ 10⁻²⁶ on the signal amplitude.     

基于单站短弧段光学观测的低轨卫星轨道预报算法

基于单站短弧段的目标跟踪预报技术是保证高精度光电经纬仪在非常规环境下正常跟踪捕获目标的重要途径.构建了基于非线性滤波器的跟踪预报算法,能够在正常情况下为闭环跟踪提供引导数据,同时构建了基于非线性变换的目标预报算法,可以在无有效观测数据情况下为经纬仪提供轨迹引导,保证目标不丢失.证明了非线性滤波在单站短弧段跟踪预报算法中比常规扩展卡尔曼滤波(Extended Kalman Filter,EKF)更有效.计算表明,本文设计的非线性滤波器可以作为光学跟踪设备的引导算法,引导精度同经纬仪的随机测量精度等量级,在设备系统误差达到50"时,预报60 s的精度可达到20",仍然满足跟踪设备的视场要求.     

An Orbital Prediction Algorithm for LEO Satellites Based on Optical Observations of Short Arcs at Single Station

The forecasting technique of the target tracking based on the short arcs at single station is an important way to guarantee that high-precision photoelectric theodolites can normally track and capture the targets in unconventional environments. We construct the tracking prediction algorithm based on nonlinear filter, which can provide the guiding data for the closed loop tracking under normal circumstances. At the same time we also construct the target prediction algorithm based on the nonlinear transformation, without valid observational data, which can provide a track guidance for the theodolite and ensure that the targets will not be lost. It is demonstrated that the nonlinear filtering is more effective than the EKF (extended Kalman filter) in the tracking prediction algorithm of the short arcs at single station. The results indicate that the nonlinear filter designed in this paper can be used as the guiding algorithm for the optical tracking equipments. And its guiding accuracy is in the same order of magnitude of the theodolite's random measurement accuracy. When the systematic error of the equipments reaches 50″, the accuracy can achieve 20″ for predictions in 60 s. This still satisfies the requirement of the field of view of the tracking equipments.     

Fast parameter estimation from the cosmic microwave background power spectrum

The statistical properties of a map of the primary fluctuations in the cosmic microwave background (CMB) may be specified to high accuracy by a few thousand power spectra measurements, provided the fluctuations are Gaussian, yet the number of parameters relevant for the CMB is probably no more than ∼10–20. Consequently, there is a large degree of redundancy in the power spectrum data. In this paper, we show that the moped data compression technique can reduce the CMB power spectrum measurements to ∼10–20 numbers (one for each parameter), from which the cosmological parameters can be estimated virtually as accurately as from the complete power spectrum. Combined with recent advances in the speed of generation of theoretical power spectra, this offers opportunities for very fast parameter estimation from real and simulated CMB skies. The evaluation of the likelihood itself, at Planck resolution, is speeded up by factors up to ∼10⁸, ensuring that this step will not be the dominant part of the data analysis pipeline.     

A fast Bayesian approach to discrete object detection in astronomical data sets – PowellSnakes I

A new fast Bayesian approach is introduced for the detection of discrete objects immersed in a diffuse background. This new method, called PowellSnakes, speeds up traditional Bayesian techniques by (i) replacing the standard form of the likelihood for the parameters characterizing the discrete objects by an alternative exact form that is much quicker to evaluate; (ii) using a simultaneous multiple minimization code based on Powell's direction set algorithm to locate rapidly the local maxima in the posterior and (iii) deciding whether each located posterior peak corresponds to a real object by performing a Bayesian model selection using an approximate evidence value based on a local Gaussian approximation to the peak. The construction of this Gaussian approximation also provides the covariance matrix of the uncertainties in the derived parameter values for the object in question. This new approach provides a speed up in performance by a factor of '100' as compared to existing Bayesian source extraction methods that use Monte Carlo Markov chain to explore the parameter space, such as that presented by Hobson & McLachlan. The method can be implemented in either real or Fourier space. In the case of objects embedded in a homogeneous random field, working in Fourier space provides a further speed up that takes advantage of the fact that the correlation matrix of the background is circulant. We illustrate the capabilities of the method by applying to some simplified toy models. Furthermore, PowellSnakes has the advantage of consistently defining the threshold for acceptance/rejection based on priors which cannot be said of the frequentist methods. We present here the first implementation of this technique (version I). Further improvements to this implementation are currently under investigation and will be published shortly. The application of the method to realistic simulated Planck observations will be presented in a forthcoming publication.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.     

Multidimensional indexing tools for the virtual observatory

The last decade has seen a dramatic change in the way astronomy is carried out. The dawn of the the new microelectronic devices, like CCDs has dramatically extended the amount of observed data. Large, in some cases all sky surveys emerged in almost all the wavelength ranges of the observable spectrum of electromagnetic waves. This large amount of data has to be organized, published electronically and a new style of data retrieval is essential to exploit all the hidden information in the multiwavelength data. Many statistical algorithms required for these tasks run reasonably fast when using small sets of in‐memory data, but take noticeable performance hits when operating on large databases that do not fit into memory. We utilize new software technologies to develop and evaluate fast multidimensional indexing schemes that inherently follow the underlying, highly non‐uniform distribution of the data: they are layered uniform indices, hierarchical binary space partitioning, and sampled flat Voronoi tessellation of the data. These techniques can dramatically speed up operations such as finding similar objects by example, classifying objects or comparing extensive simulation sets with observations. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

All-sky search algorithms for monochromatic signals in resonant bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman–Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.