Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Chinese Virtual Observatory Searching for Tidal Streams in SDSS 刘超 中国科学院国家天文台 Why search for Tidal Stream • Galactic Structure – Shape, Kinematics, chemical properties, etc. • Galactic Halo Origin – Two models debate • Cold Dark Matter Model – More dwarf galaxies disrupted China-VO 2006, Guilin 11/29-12/03 2 Currently Known Tidal Stream • Sgr dSph Tidal Streams(Majewski03;Belokurov06b) • Virgo Stream(Juric05) • Monoceros Ring(Newberg02) • Orphan Stream(GD06b) • GD-1(GD06b) • NGC5466 Tidal Tail(Belokurov06a) • Pal 5 Tidal Stream(GD06a) • NGC5053(Lauchner06) • NGC4147?? China-VO 2006, Guilin 11/29-12/03 3 UMa I CVn I Boo Will 1 Com UMa II CVn II Segue 1 References: Willman05a Her Willman05b Zucker06 Zucker06 Leo IV Belokurov 06c China-VO 2006, Guilin Belokurov06d 11/29-12/03 4 Why Use SDSS • Study methods – – – – Star count analysis Kinematics Chemical composition Comparison with other galaxies • Star count analysis is a prompt way • Large sky area survey – DSS – 2MASS – SDSS • SDSS – Deep space and mass dataset – Precise photometry – Cover Galactic North Pole China-VO 2006, Guilin 11/29-12/03 5 Our Approach • Binning a wide area sky – RA=120~270deg, DEC=25~70deg – i=19~22mag, g-i=0~1mag – Step=0.05deg • Pick out all over-densities – 2sigma higher above background • Color-Magnitude feature analysis – Isochrone line matching China-VO 2006, Guilin 11/29-12/03 6 Results China-VO 2006, Guilin 11/29-12/03 7 China-VO 2006, Guilin 11/29-12/03 8 GD-1 Our Result GNP NGC5466 Orphan Monoceros China-VO 2006, Guilin 11/29-12/03 9 Conclusion • Ten over-densities are most likely dwarf spheroidal galaxies or star clumps on tidal streams • Nine over-densities and Four known satellites compose a remarkable arc – Possibly a tidal stream • Distances are likely related to metalicity for the over-densities and known dSphs China-VO 2006, Guilin 11/29-12/03 10 Chinese Virtual Observatory China-VO Data Access Service (DAS) 刘超 中国科学院国家天文台 China-VO 2006, Guilin 11/29-12/03 11 Goals • Access mass data – – – – Query data from all over the world You need a BIG hard disk when study SDSS data database knowledge is necessary Furthermore, a lot of time are spent on data r/w: download data, save temp data, format transformation – Manage your data by yourself • DAS goals are simply do all above for you – – – – Let you focus on science and algorithms Save your query time and disk space Simplify data transferring and format transformation Manage your data on line China-VO 2006, Guilin 11/29-12/03 12 Functions • Multiple ways to access data – By a client application – By a web page – By web service interface • Image, Spectroscopy data as well as Catalog data • Data query result transfer – FTP, GridFTP, etc. • Data query result format transformation – ASCII, VOTable, FITS, etc. • Cross match among distributed catalogs • Function scalability – Add new databases – Add data mining tools – As a atomic service in a workflow China-VO 2006, Guilin 11/29-12/03 13 China-VO DAS Architecture DAS WSRF Service Interface Task Queue ADQL Parser Execution Plan DataResource WorkThread Metadata • DAS Server – A grid service provider complies with WSRF DAS Log DataResource Map Sessions Registry Proxy OGSA-DAI Client Authorization • Data Node MySpace Client Invoke/Return Data Transfer – A stand alone java application – A series of web page – A program coded by users MySpace Service Register Registry Upload/Download • Client Query – An OGSA-DAI server provides multiple data resources to community Upload/Download GT4 Java WS Core Data Node OGSA-DAI Service Activities Data Transform XMatch Image Query Spectrum Query Catalog Query Data Delivery MySpace Client CompuCell* Data Resources China-VO 2006, Guilin Authorization Metadata 11/29-12/03 GT4 Java WS Core 14 Features • ADQL for all – Catalogs, Images and Spectroscopies • Asynchronous query for mass data • Not a system but a community – Anybody can publish their database as a Data Node and share them to all users • Users can combine data query into their programs by Grid Service Interface so that data need not to be downloaded to local disk and data format will not be a problem • An unified entrance for all kinds of astronomical data • Basis of data mining tools – Send computation to data server in future China-VO 2006, Guilin 11/29-12/03 15 More details • DAS server: Tian Haijun • Cross match & ADQL execute planning: Gao Dan • Discover Data Node & Multi-type data support: Lu Yong • Client & Data Node: Yang Yang China-VO 2006, Guilin 11/29-12/03 16 Actions • Submit a query • Asynchronous execution • Data federation in distributed environment • Data format transformation • Data transportation • Job tracking China-VO 2006, Guilin 11/29-12/03 17 Status & Future work • Status – – – – DAS server can run a simple job without Data Node A java application Client is in developing A Data Node test server is established Data Node Discovery is in developing – – – – – – – The system query data in next spring Multiple data format support Distributed cross match Connect with MySpace? Data mining tools integration (e.g. JDL) Visualization Integration LAMOST data server? • Future work China-VO 2006, Guilin 11/29-12/03 18 Thanks!