The Cross-match And Aggregation Of Large-scale Astronomical Catalogs Data

As an ancient discipline, astronomy has always played a very important role in human history. Cross-matching is significant in astronomical research as key technologies and methods for multi-band astronomical data fusion. By cross-match for multi-band of celestial body, we can get its information of different band, and then, we can reveal the information of its physical nature.The ability of data collection greatly enhanced with the substantial increase of the observing instruments and observation techniques. October2012, GuoShoujing Telescope (Large Sky Area-Multi-Object Fiber spectrum telescope, hereinafter referred to as LAMOST) began formal Sky Survey, this process will produce mass spectral data. At the same time, some newly released the catalog data also recently released. Large viewing angle Near Infrared Survey WISE (Wide-field Infrared Survey Explorer) catalog data is released in2012, the catalog contains563.921,584targets; FIRST (Faint Images of the Radio Sky at Twenty-Centimeters) catalog data in20122January16released a new version contains946,464records; SDSS DR9catalog data was released in July2012, contains1,231,051,050records. In addition, there are some other catalog data like2MASS catalog contains472,640,569targets, GALEX catalog contains225,565,338records. For such a massive catalog data, cross and integration of multi-band astronomical catalog data is extremely important.However, different catalog data has different optical band, resolution, and position accuracy (error radius). This makes the cross-identification of catalog data more difficult.The work consists of two parts:(1) By researching the two different pseudo2D spherical indexing methods of HTM and HEALPix, we develop a new algorithm to solve the lack of block-edge problem, increasing the accuracy of cross-match, decreasing the occurrence of block-edge problem. (2) We make some tests to verily the validity of this algorithm, also for the systematic error between two catalogs. Applying ThreadPool technology to accelerate cross-match process, reducing the time spent. We also analysis the "one-for-many’ and "many-for one" situation, and develop a method to solve the problem of spectra catalog.