依巴谷天文卫星及其输入星表数据库

本文简要介绍了欧洲空间局通过阿利亚那火箭发射的依巴谷天文卫星,也概述了为依巴谷卫星探测计划服务,并积累和编辑其观测资料的输入星表数据库。     

CCD漂移扫描观测星表ACR和CMC13的系统误差研究

对2000年前后发表的两部用CCD漂移扫描观测的天体测量星表——ACR(As- trometric calibration regions along the celestial equator)和CMC13(Carlsberg Merid- ian Catalog 13)进行误差分析.通过与UCAC2(The second U.S.Naval Observatory CCD Astrograph Catalog)星表比较,采用数值法,分析了误差的形式和量级大小.并从星表观测方式和数据归算的角度,分析了误差的主要可能来源.发现ACR和CMC13在赤纬方向存在明显的星等差,位置差值随赤经存在与CCD视场大小相近的周期性变化,位置差值随赤纬存在与归算带尺寸大小相近的系统性变化.     

中国开展的星表和天文常数研究活动(1990.7～1993.1)

叙述了1990年7月至1993年1月期间中国的星表和天文常数工作。它包括仪器的改进与研制,星表的观测和编算,天文常效、天球参考系的研究,以及其相应的方法与技术.     

测定天文大气折射和建立电磁波折射延迟实测模型(Ⅱ)-采用依巴谷星表作为工作星表

叙述了测定大气折射对工作星表的要求和星表系统误差的影响,并通过FK5星表相对于依巴谷星表的系统误差,来说明以往的各种基本星表都不适用的原因;文章说明了依巴谷星表所列星位置不含随天区而异的系统误差的特性,分析了该星表问世时的精度和十多年后的今天仍能达到的精度,说明它可以作为这种测定的工作星表,从而为直接测定天文大气折射值和折射率差提供了一个重要的条件;文章还介绍了依巴谷星表的星等分布,认为只需选用亮于6mag的依巴谷星,这一星等范围,为制定专用测量仪器终端的设计方案提供了依据。     

基于文件的大规模星表高效索引与融合

大规模星表的快速检索是交叉证认、多波段数据融合、暂现源搜寻等任务实现的基础,尤其是大视场暂现源搜寻需要在一个曝光周期内完成观测结果与大规模星表的检索与交叉证认,以发现正在变化的天体。现有的大规模星表通常包含数十亿天体,为了在有限内存的情况下对其进行快速检索,提出了一套解决方案。通过使用基于HEALPix的多分辨率动态划分算法,能够将星表按照不同天区天体密度切分成大小合适且均匀的星表文件;进而在开源序列化组件Protocol Buffers基础上设计出一套针对星表的序列化方案,作为星表切分和检索时的中间存储介质,以尽可能提高检索时的速度。还尝试应用Peano-Hilbert编号代替HEALPix原有Z型编号顺序遍历星表,提高了缓存命中率,实现了对大规模星表的高效融合,方便对数据的后续利用与研究。     

海量多波段星表数据的交叉证认的实现

许多天文学家需要星表来选源、证认和研究。目前国外有一些大的数据中心提供了星表查询、多源查询(即小样本交叉证认)、可视化等功能。但是随着大数据量及全波段天文时代的到来,这些服务已经越来越不能满足天文学家的需求。在详细分析了国外数据中心的服务后,提出了新的问题,并给出一套解决方案。着重讨论了任意两个星表的交叉证认和大数据量星表的交叉证认的实现,以及交叉证认结果的分类和参数的自由选择等方面的课题。     

天文时纬观测和地球动力学数据库的初步设想与实践

以PDP－11计算机为基础的“天时纬观测和地球动力学数据库”已初步形成。本概述了这一工作的设想与实践。     

射电天文文献数据库的建立与查询

本叙述在B6935计算机的TEXT－TRIEVE软件包支持下建立“射电天献数据库”的过程。通过对数据库查询的几个例子，说明其合作效果。经过实践提出了TEXT－TRIEVE软件对献检索的不足之处。     

江苏科技信息网之天文数据库

中国科学院紫金山天文台受江苏省科工委、江苏省科技信息中心委托研制的天文数据库,是省科技信息网的重要组成部分。该信息网包括工业、农业、土壤、地理等较为全面的科技信息,将于年底全面开通。天文数据库已于十月中旬上网。它包括了阴阳历对照、行星特殊天象、太阳、恒星、人造地球卫星等方面的内容。用ＦｏｘＰｒｏ５ ．０ 建立的天文数据库管理系统,包括了成百个数据库表,数据量５ 兆左右,记录约为５ 万余条。天体力学部和天体物理部等有关部门,在提供数据方面,给予了大力支持,在此一并表示感谢。     

A Comparison of BBN,ADTree and MLP in separating Quasars from Large Survey Catalogues

We compare the performance of Bayesian Belief Networks (BBN), Multilayer Perception (MLP) networks and Alternating Decision Trees (ADtree) on separating quasars from stars with the database from the 2MASS and FIRST survey catalogs. Having a train- ing sample of sources of known object types, the classifiers are trained to separate quasars from stars. By the statistical properties of the sample, the features important for classifica- tion are selected. We compare the classification results with and without feature selection. Experiments show that the results with feature selection are better than those without feature selection. From the high accuracy found, it is concluded that these automated methods are robust and effective for classifying point sources. They may all be applied to large survey projects (e.g. selecting input catalogs) and for other astronomical issues, such as the parame- ter measurement of stars and the redshift estimation of galaxies and quasars.     

中国地区天文夜晴空概率分布

利用１９９５～１９９７年静止气象卫星（ＧＭＳ）红外通道的数据,采用综合了时间判断法、空间判断法和红外阈值法等特征的一种综合判断有云无云的方法,统计分析了中国地区较高空间分辨率（优于２０ｋｍ）和时间分辨率（优于１ｈ）的晴空概率和天文夜晴空概率的分布．分析结果表明,全年天文夜晴空概率的极值出现在我国的西部和北部．冬半年的最大天文夜晴空概率值大于夏半年．其中西藏地区１２月的天文夜晴空概率可达到９５％．     

Construction of the Database for Pulsating Variable Stars

A database for pulsating variable stars is constructed to favor the study of variable stars in China. The database includes about 230,000 variable stars in the Galactic bulge, LMC and SMC observed in an about 10 yr period by the MACHO(MAssive Compact Halo Objects) and OGLE(Optical Gravitational Lensing Experiment) projects. The software used for the construction is LAMP, i.e., Linux+Apache+MySQL+PHP. A web page is provided for searching the photometric data and light curves in the database through the right ascension and declination of an object. Because of the flexibility of this database, more up-to-date data of variable stars can be incorporated into the database conveniently.     

Automated probabilistic classification of transients and variables

There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic) follow‐up facilities with varied capabilities in terms of instruments, depth, cadence, wavelengths, etc., most of which are geared toward some specific astrophysical phenomenon. As the number of detected transient events grows, an automated, probabilistic classification of the detected variables and transients becomes increasingly important, so that an optimal use can be made of follow‐up facilities, without unnecessary duplication of effort. We describe a methodology now under development for a prototype event classification system; it involves Bayesian and Machine Learning classifiers, automated incorporation of feedback from follow‐up observations, and discriminated or directed follow‐up requests. This type of methodology may be essential for the massive synoptic sky surveys in the future. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

EURONEAR: Data mining of asteroids and Near Earth Asteroids

Besides new observations, mining old photographic plates and CCD image archives represents an opportunity to recover and secure newly discovered asteroids, also to improve the orbits of Near Earth Asteroids (NEAs), Potentially Hazardous Asteroids (PHAs) and Virtual Impactors (VIs). These are the main research aims of the EURONEAR network. As stated by the IAU, the vast collection of image archives stored worldwide is still insufficiently explored, and could be mined for known NEAs and other asteroids appearing occasionally in their fields. This data mining could be eased using a server to search and classify findings based on the asteroid class and the discovery date as “precoveries” or “recoveries”. We built PRECOVERY, a public facility which uses the Virtual Observatory SkyBoT webservice of IMCCE to search for all known Solar System objects in a given observation. To datamine an entire archive, PRECOVERY requires the observing log in a standard format and outputs a database listing the sorted encounters of NEAs, PHAs, numbered and un‐numbered asteroids classified as precoveries or recoveries based on the daily updated IAU MPC database. As a first application, we considered an archive including about 13 000 photographic plates exposed between 1930 and 2005 at the Astronomical Observatory in Bucharest, Romania. Firstly, we updated the database, homogenizing dates and pointings to a common format using the JD dating system and J2000 epoch. All the asteroids observed in planned mode were recovered, proving the accuracy of PRECOVERY. Despite the large field of the plates imaging mostly 2.27° × 2.27° fields, no NEA or PHA could be encountered occasionally in the archive due to the small aperture of the 0.38m refractor insufficiently to detect objects fainter than V ∼ 15. PRECOVERY can be applied to other archives, being intended as a public facility offered to the community by the EURONEAR project. This is the first of a series of papers aimed to improve orbits of PHAs and NEAs using precovered data derived from archives of images to be data mined in collaboration with students and amateurs. In the next paper we will search the CFHT Legacy Survey, while data mining of other archives is planned for the near future (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Finding outlier light curves in catalogues of periodic variable stars

We present a methodology to discover outliers in catalogues of periodic light curves. We use a cross-correlation as the measure of 'similarity' between two individual light curves, and then classify light curves with lowest average 'similarity' as outliers. We performed the analysis on catalogues of periodic variable stars of known type from the MACHO and OGLE projects. This analysis was carried out in Fourier space and we established that our method correctly identifies light curves that do not belong to those catalogues as outliers. We show how an approximation to this method, carried out in real space, can scale to large data sets that will be available in the near future such as those anticipated from the Panoramic Survey Telescope & Rapid Response System (Pan-STARRS) and Large Synoptic Survey Telescope (LSST).