Searching for Tidal Streams in SDSS

Chinese Virtual Observatory

刘 超

中国科学院国家天文台

11/29-12/03China-VO 2006, Guilin 2

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

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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??

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UMa I

CVn I Boo

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CVn II

Segue 1

Her

Leo IV

UMa II

Will 1

References:Willman05aWillman05bZucker06Zucker06Belokurov 06cBelokurov06d

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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

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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

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Results

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GNP

Our Result GD-1

Orphan

Monoceros

NGC5466

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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

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China-VO Data Access Service (DAS)

刘 超

中国科学院国家天文台

Chinese Virtual Observatory

11/29-12/03China-VO 2006, Guilin 12

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

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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

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Data Node

Authorization

GT4 Java WS Core

Metadata

OGSA-DAI Service

Data Resources

Activities

Data Transform

Data Delivery

Image Query

Catalog Query

Spectrum Query

XMatch

CompuCell*

China-VO DAS

GT4 Java WS Core

DAS WSRF Service Interface

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Registry Proxy

ADQL Parser

MySpace ClientAuthorization

OGSA-DAI Client

Registry MySpace Service

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DataResource Map

DataResource

Metadata

MySpace Client

Task Queue

SessionsExecution Plan

WorkThread

Architecture

• DAS Server– A grid service provider

complies with WSRF• Data Node

– An OGSA-DAI server provides multiple data resources to community

• Client– A stand alone java

application– A series of web page– A program coded by

users

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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

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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

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Actions

• Submit a query• Asynchronous execution• Data federation in distributed

environment• Data format transformation• Data transportation• Job tracking

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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

• Future work– 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?

Thanks!