The advantages of being able to accurately measure redshift with photometric data are of great importance
for studying cosmology, large scale structure of the Universe, determination of fundamental astrophysical quantities
and so on, because photometric redshifts may provide approximate distances to the enormous set of
objects. At present various algorithms for photometric redshifts have been investigated. This is induced us
to develop a software platform that integrates different algorithms of estimating photometric redshifts, such
as color-magnitude-redshift (CMR), Support Vector Machines (SVMs), HyperZ and Artificial Neural Networks
(ANNs). The requirements of the software platform, architectural issues are addressed and its framework design
implemented are discussed. It provides a user-friendly interface, by which users can choose the method they
like, upload their own data, and then get their needed result by clicking a mouse. This framework is flexible and
extensible enough to measure photometric redshifts.
A new application framework for virtual observatory (VO) is designed for discovering unknown knowledge from thousands of astronomical catalogs which have already released and are accessible through VO services. The framework consist of two new technologies to seamlessly associate data queried from SkyNode supported databases with data mining (DM) algorithms, which either come from third-party software or are developed directly above the framework. The first one is a high level programming language, called Job Description Language (JDL), for describing jobs for data accessing and numerical computation based on web services. The second technology is a computation component standard with both local and web service invocation interface, which is named as CompuCell. It is a universal solution for integrating arbitrary third-party DM software into the framework so as to invoke them directly in JDL program. We implement a prototype with a JDL supported portal and achieve clustering algorithm in CompuCell components. We combine a series of data mining procedures with a data access procedure by programming in JDL on the portal. A scientific research, which recognizes OB associations from 2MASS catalog, is treated as a demonstration for the prototype. It confirms the feasibility of the application framework.
Virtual Observatory (VO) is a collection of interoperating data archives and software tools. Taking advantages of the latest information technologies, it aims to provide a data-intensively online research environment for astronomers all around the world.
A large number of high-qualified astronomical software packages and libraries are powerful and easy of use, and have been widely used by astronomers for many years. Integrating those toolkits into the VO system is a necessary and important task for the VO developers.
VO architecture greatly depends on Grid and Web services, consequently the general VO integration route is "Java Ready – Grid Ready – VO Ready". In the paper, we discuss the importance of VO integration for existing toolkits and discuss the possible solutions. We introduce two efforts in the field from China-VO project, "gImageMagick" and "Galactic abundance gradients statistical research under grid environment". We also discuss what additional work should be done to convert Grid service to VO service.
The International Virtual Observatory Alliance (IVOA: http://www.ivoa.net) represents 14 international projects working in coordination to realize the essential technologies and interoperability standards necessary to create a new research infrastructure for 21st century astronomy. This international Virtual Observatory will allow astronomers to interrogate multiple data centres in a seamless and transparent way, will provide new powerful analysis and visualisation tools within that system, and will give data centres a standard framework for publishing and delivering services using their data. The first step for the IVOA projects is to develop the standardised framework that will allow such creative diversity. Since its inception in June 2002, the IVOA has already fostered the creation of a new international and widely accepted, astronomical data format (VOTable) and has set up technical working groups devoted to defining essential standards for service registries, content description, data access, data models and query languages following developments in the grid community. These new standards and technologies are being used to build science prototypes, demonstrations, and applications, many of which have been shown in international meetings in the past two years. This paper reviews the current status of IVOA projects, the priority areas for technical development, the science prototypes and planned developments.
In order to explore the spectral energy distribution of various objects in a multidimensional parameter space, the multiwavelenghth data of quasars, BL Lacs, active galaxies, stars and normal galaxies are obtained by positional cross-identification, which are from optical(USNO A-2), X-ray(ROSAT), infrared(2MASS) bands. Different classes of X-ray emitters populate distinct regions of a multidimensional parameter space. In this paper, an automatic classification technique called Support Vector Machines(SVMs) is put forward to classify them using 7 parameters and 10 parameters. Finally the results show SVMs is an effective method to separate AGNs from stars and normal galaxies with data from optical, X-ray bands and with data from optical, X-ray, infrared bands. Furthermore, we conclude that to classify objects is influenced not only by the method, but also by the chosen wavelengths. Moreover it is evident that the more wavelengths we choose, the higher the accuracy is.