VLBI软件相关处理机脉冲星信号脉冲轮廓搜索算法

VLBI观测比单天线观测拥有更高的角分辨率,在脉冲星观测,尤其是成图和定位研究中有着重要的作用。相关处理机在进行脉冲星信号处理时,首先必须知道脉冲信号到达时刻、脉冲星相位及脉冲宽度等脉冲轮廓信息。研究了利用脉冲信号自功率谱来绘制脉冲星轮廓图的算法,此算法只需对单站信号进行频谱分析就可确定脉冲位置和宽度,然后在VLBI软件相关处理机中完成脉冲信号的相关计算。实际的VLBI数据相关处理结果表明,用上述方法可准确获得脉冲星的轮廓。     

地球自转极移近120天准周期变化的小波分析及其大气激发机制

本文利用小波变换这一新的频谱分析方法研究了地球自转极移近１２０天准周期变化的时频特征，证实了在极移序列中存在显著的近１２０天准周期振荡，得到了极移准周期变化的周期与振幅随时间变化的规律．以地球自转动力学为基础，在时域内分析了大气变化对自转极移季节内变化的激发．表明大气激发在本文所研究的频段内是极移短周期变化的主要激发源。并发现在极移近１２０天准周期振荡平静时期，发生ＥＬＮｉｎｏ事件，同时日长变化近１２０天准周期变化增强．     

VLBI谱线测量中的钟校准

本文给出在VLBI谱线测量中钟校准的方法。利用美国三台站VLBI谱线观测资料,计算NRAO和HRAS氢脉泽钟相对于VLA的钟差和钟速差。经钟校准,钟差对羟基分子脉泽子源条纹率图相对位置精度的影响约为0″.002,从而大大提高了条纹率成图质量。     

CygX-1 X辐射的功率谱

运用自回归功率谱研究CygX－1X辐射的频谱特征,结果显示CygX－1转换态和高／软态时变频谱的连续成分,可以统一由有截断的幂律加噪声成分描述,转换态存在小于3Hz的宽峰结构及准周期振荡（QPO）成分（4－12Hz）,而高／软态完全可由截断幂律谱描述,不存在显著的QPO．截断频率在各态都相当稳定,在不同态的演化与平流为主的吸积流模型（ADAF）预期的情形一致．本文结果表明,自回归功率港分析是研究X射线双星光变特征的一个有效的方法．     

自由地核章动的时变特性

对VLBI观测确定的IAU1980章动模型的天极偏移序列进行分析,结果显示自由地核章动在1990年以前的幅值比其后为强,其时变强度比周年受迫章动的为大．另外,小波变换的时频谱分析结果显示在天极偏移序列中存在一幅值约0．1毫角秒的准两年周期信号．仅从目前的数据分析结果尚不足以确定此信号与顺向自由地核章动之间的关系,进一步的观测检,验和深入的内核动力学研究是非常必要的．     

谱分析的CLEAN方法及其在激变变星TT Ari短周期振荡分析中的应用

对适用于非等间隔时间序列的一维ＣＬＥＡＮ谱分析方法进行了研究。用模拟信号进行了检验,证实了它也适用于有噪声的序列,但谱质量和噪声强度密切相关,把这种方法应用到激变变变星ＴＴ Ａｒｉ的测光资料分析中,检测到近２０ｍｉｎ周期的准周期振荡。     

AO 0235＋164的喷流在旋转吗？

本文给出BLLac天体AO0235＋164在SGDz的多历元VLBI观测所得到的图象．在一定的假设条件下，根据VLBI观测结果可推算出该源的子源以税超光速速率向外扩展，最大的扩展速率为（27±6）C．从AO0235＋164喷流位置角的变化，我们推测该源的喷流可能在旋转和中央“引擎”有过动的可能性．进一步的多历元VLBI观测将被用来证实这种推断．为了得到更精细的射电结构，我们准备对AO0235＋164做空间VLBI观测．我们已做了相应的模拟试验．     

吸积盘随机振荡光度功率谱密度中低频准周期振荡现象的研究

采用含有频率涨落噪声和指数形式关联随机力作用的广义朗之万(Langevin)方程模型描述黑洞吸积盘的垂向振荡,推导出吸积盘随机振荡光度功率谱密度的解析表达式,并讨论了系统参数对功率谱密度中低频准周期振荡(Low Frequency Quasi-Periodic Oscillations,LFQPOs)现象的影响。研究结果发现选取合适的系统参数时,功率谱密度曲线上出现了一个基频和一个二次谐频的共振双峰低频准周期振荡,基频峰对应的中心频率为吸积盘振荡的特征频率;随机力关联时间决定了基频峰的高度和宽度,频率噪声强度和粘滞阻尼只对二次谐频峰产生影响。结果说明吸积盘的随机振荡模型可以作为低频准周期振荡起源的一种解释。     

太阳耀斑硬X射线爆分钟级准周期结构的统计特性及解释

本文提出和分析了一类新的具有分钟级准周期性结构特点的太阳硬X射线耀斑,这类耀斑主要由多个持续时间在40-150秒之间的爆发峰连按组成。对其中八个典型事件的分析表明,它们大部分对应于爆发面积较小的SB,1B级H_x耀斑,非热电子产生的硬x辐射高能端(ε>54Kev)的时间轮廓呈现分立的加速特性。此外,同一个事件的大部分分钟级峰在上升相特征时间,峰值时刻的谱指数等方面具有一定的相近性。在分析多种准周期性模型基础上,我们认为,不同时间尺度的准周期性可能来源于不同的爆发机制,而对于分钟级准周期结构,解释为同一磁环或磁环系统的多次连续爆发,则是较合适的模型。     

DDS输出频谱特点及改善方法

利用非均匀采样模型得到了存在相位截断时直接数字频率合成（ＤＤＳ）的输出频谱,通过分析频谱特点,讨论了改善频谱分布的方法     

宽带频谱序列干扰信号识别与统计方法

随着科学技术的不断进步,射电天文台站趋于自动化,各类电子设备的广泛使用使得射电天文台站的电磁环境变得尤为复杂,如何有效识别和统计复杂频谱中的干扰信号是当前射电天文台站亟需解决的问题,故提出一种宽带频谱序列干扰信号识别与统计方法.首先,对每组宽带频谱进行信噪分离、识别频谱中的干扰信号;然后,对第1组宽带频谱信号识别结果及信号特征建立模板库,后续每组频谱的信号识别结果与模板库中对应频率的信号进行相似性分析,根据相似性分析结果,统计信号次数,更新模板库;实现宽带频谱序列干扰信号的识别与统计.针对QTT (QiTai Radio Telescope)台站实测频谱,运用该方法进行干扰信号识别与统计,能够有效识别并标记频谱中的干扰信号,并统计干扰信号随时间、方向的变化趋势.     

CoRoT data reduction by example

Data reduction techniques published so far for the CoRoT N2 data product were targeted primarily on the detection of extrasolar planets. Since the whole dataset has been released, specific algorithms are required to process the lightcurves from CoRoT correctly. Though only unflagged datapoints must be chosen for scientific processing, some flags might be reconsidered. The reduction of data along with improving the signal‐to‐noise ratio can be achieved by applying a one dimensional drizzle algorithm. Gaps can be filled by linear interpolated data without harming the frequency spectrum. Magnitudes derived from the CoRoT color channels might be used to derive additional information about the targets. Depending on the needs, various filters in the frequency domain remove either the red noise background or high frequency noise. The autocorrelation function or the least squares periodogram are appropriate methods to identify periodic signals. The methods described here are not strictly limited to CoRoT data but may also be applied on Kepler data or the upcoming PLATO mission. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

面向单脉冲信号分类的集成特征选择与评价

受大量射频干扰信号影响, 快速从海量观测数据中准确识别出单脉冲信号已成为天文数据处理的一项重要任务, 而设计和提取有效数据特征, 是利用机器学习进行单脉冲信号高效识别的决定因素. 针对如何选择最优特征, 进而提升单脉冲信号的分类精度这一关键问题, 设计了面向单脉冲信号分类的集成特征选择方法. 方法首先混合单脉冲信号的参数特征、统计特征和抽象特征, 然后分别利用5种单一特征选择方法选出各自的最优特征集, 最后利用贪心策略对5种单一方法获取的最优特征集进行集成筛选, 获取最优集成特征集. 实验表明, 最优特征集合既包含统计特征也包含抽象特征. 在相同特征数量下, 利用集成特征选择比单一特征选择能获得更高的模型精度, 可使F1值最高提升1.8%. 在海量数据背景下, 集成特征选择对减少特征数量、提升分类性能和加快数据处理速度具有重要作用.     

Separation of instrumental and astrophysical foregrounds for mapping cosmic microwave background anisotropies

For the most sensitive present and future experiments dedicated to cosmic microwave background (CMB) anisotropy observations, the identification and separation of signals coming from different sources is an important step in the data analysis. This problem of the restitution of signals from the observation of their mixture is classically called 'component separation' in CMB mapping. In this paper, we address the general problem of separating, for millimetre-wave sky-mapping applications, components which include not only astrophysical emissions in two-dimensional maps, but also one-dimensional instrumental effects in the data streams. We show that component separation methods can be adapted to separate simultaneously both astrophysical emissions and components coming from time-dependent foreground signals which originate from the instrument itself. Such general methods can be used for the optimal processing of low-redundancy observations where multi-channel observations are a precious tool to remove systematic effects, as may be the case for the Planck mission.     

Autoregressive Spectral Estimation for Quasi-Periodic Oscillations

Modern methods of spectral estimation based on parametric time-series models are useful tools in power spectral analysis. We apply the autoregressive (AR) model to study quasi-periodic oscillations (QPOs). An empirical formula to estimate the expectation and standard deviation of the noise AR power densities is derived, which can be used to estimate the statistical significance of an apparent QPO peak in an AR spectrum. An iterative adding-noise algorithm in AR spectral analysis is proposed and applied to studying QPOs in the X-ray binary Cir X-1.     

The deduction of energy spectra of non-thermal electrons in flares from the observed dynamic spectra of hard X-ray bursts

The derivation of dynamic spectra of high energy electrons in flares from high resolution hard X-ray observations is considered. It is shown that the Bethe-Heitler formula for the electronproton bremsstrahlung cross-section over the 20–100 keV range of energies admits of a general analytic solution for the electron spectrum in terms of the X-ray spectrum, in a form convenient for computation. The bearing of this analysis on different models of flare conditions is considered. In examining the hypothesis that the X-rays are produced in regions of high ambient density, the duration of the burst being governed by modulation of the electron source rather than by the decay of trapped electrons injected impulsively, it is emphasised that the energy spectrum of the electrons at their source is different from their effective spectrum in the X-ray emitting region. This spectrum, at the source, is found to be much steeper than that in the X-ray region which means that the entire energy of the flare could reside in the injected electrons.     

Quasi-periodic climate teleconnections between northern and southern Europe during the 17th–20th centuries

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric variability in the North Atlantic region, influencing storm tracks and creating a dipole pattern of precipitation from north to south across Western Europe. This distinct spatial distribution of precipitation provides a framework that can be potentially used to identify and reconstruct patterns of past NAO-forced climate variability. In this study we use tree-ring width series from Western Europe, in conjunction with principal components analysis and advanced spectral methods, to prospect for quasi-periodic climate signals that are forced by the NAO. We identify a robust 25-yr anti-phased synchronization in climate variability between Scandinavia and the Mediterranean during the 17th–20th centuries. The amplitude of the 25-yr beat displays a long-term modulation in northern and southern Europe, with minimum amplitude during the late Maunder Minimum. This amplitude minimum coincides with a maximum in Δ¹⁴C, suggesting a potential solar or oceanic influence on the intensity of the 25-yr band of quasi-periodic variability.     

Recovering galaxy star formation and metallicity histories from spectra using VESPA

We introduce versatile spectral analysis (VESPA): a new method which aims to recover robust star formation and metallicity histories from galactic spectra. VESPA uses the full spectral range to construct a galaxy history from synthetic models. We investigate the use of an adaptative parametrization grid to recover reliable star formation histories on a galaxy-by-galaxy basis. Our goal is robustness as opposed to high-resolution histories, and the method is designed to return high time resolution only where the data demand it. In this paper we detail the method and we present our findings when we apply VESPA to synthetic and real Sloan Digital Sky Survey (SDSS) spectroscopic data. We show that the number of parameters that can be recovered from a spectrum depends strongly on the signal-to-noise ratio, wavelength coverage and presence or absence of a young population. For a typical SDSS sample of galaxies, we can normally recover between two and five stellar populations. We find very good agreement between VESPA and our previous analysis of the SDSS sample with MOPED.     

Solar radio filtering algorithm based on improved long short-term memory

The effective observation of burst events in solar radio research has been impeded by various interference signals,especially interference signals with a wide frequency range and high intensity,as they can partially or completely obscure the observation of burst events.Image processing methods that directly remove the interference signal channels and subtract the average of the interference signal channel are not suitable for processing all types of interference signals.This paper proposes the use of a specific kind of recurrent neural networks,called long short-term memory networks,to predict the value of the radio frequency interference signals with high intensity of the burst event in the solar radio spectrum.The predicted interference can then be removed in accordance with the principle that signals can be linearly added.Therefore,predicted value is subtracted from the data containing the burst event signals and the RFI signals(The radio frequency interference signals to be processed in this article refer to the signal of the broadcast signal that can be received in the frequency range,the signal transmitted by the mobile phone,and the signal transmitted by the sea vessel,and the like) to remove the interference.Then,in order to reduce the error caused by the stepwise prediction in the network and further improve the prediction accuracy,this paper analyzes the characteristics of the value of the radio interference and applies the digital mapping method to convert the prediction problem into the classification problem in the time series.The experimental results show that the proposed method can effectively remove the radio interference in the solar spectrum and clearly show the burst events.     

A New Solution Assessment Approach and Its Application to Space Geodesy Data Analysis

The statistics of the residuals are used in this paper to perform a quality assessment of the solutions from space geodesy data analysis. With the stochastic estimation and the relatively arbitrary empirical parameters being employed to absorb unmodelled errors, it has long been noticed that different estimate combinations or analysis strategies may achieve the same level of fitting yet result in significantly different solutions. Based on the postulate that no conceivable signals should remain in the residuals, solutions of the same level of root mean square error (RMS) and variance–covariance may be differentiated in the sense that for reasonable solutions, the residuals are virtually identical with noise. While it is possible to develop complex noise models, the Gaussian white noise model simplifies the solution interpretation and implies the unmodelled errors have been smoothed out. Statistical moments of the residuals as well as the Pearson chi-square are computed in this paper to measure the discrepancies between the residuals and Gaussian white noise. Applying to both satellite laser ranging (SLR) and global positioning system (GPS) data analysis, we evaluate different parameter estimate combinations and/or different strategies that would be hardly discriminated by the level of fitting. Unlike most solution assessment methods broadly termed as external comparison, no information independent of the data analyzed is required. This makes the immediate solution assessment possible and easy to carry out. While the external comparison is the best and most convincing quality assessment of the solution, the statistics of the residuals provide important information on the solutions and, in some cases as discussed in this paper, can be supported with external comparison.