1 / 26

“The VO in Australia” Melbourne Nov. 28/29 2002

“The VO in Australia” Melbourne Nov. 28/29 2002. What is the AVO? How did it develop - Grid computing – particle physics Current status of International VO projects (http://www.ivoa.net) Role for Australian Astronomy? Opportunities & challenges. What is the Virtual Observatory?.

mya
Download Presentation

“The VO in Australia” Melbourne Nov. 28/29 2002

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. “The VO in Australia” Melbourne Nov. 28/29 2002 • What is the AVO? • How did it develop - Grid computing – particle physics • Current status of International VO projects (http://www.ivoa.net) • Role for Australian Astronomy? • Opportunities & challenges Virtual Molonglo Observatory

  2. What is the Virtual Observatory? • NOT one project or the Web • Distributed CPU – AVO, NVO, ASTROGRID • Distributed data – images, catalogues, spectra, simulations & models • Distributed software – assorted acronyms • Resource broker, road map, nodes Virtual Molonglo Observatory

  3. What’s it all about? Grid computing deals with coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organisations. The resources are compute power, software, data and collaboration tools. Virtual Molonglo Observatory

  4. Some statistics on doubling times • Computing power (Moore’s law): 18 mths • Bandwidth (Nielsen’s law): 20 mths • Data archive size: 12 mths • Number of websites: 9 mths Virtual Molonglo Observatory

  5. Challenges & responses • Slow CPU growth distributed computing • Limited BW information hierarchies • Limited storage distributed data • Data diversity interoperability • SOLUTION: GRID COMPUTING Virtual Molonglo Observatory

  6. Technical Update • Big commitment in Europe & USA • Wide applications – business & science • VO-compliance & VO-table • Issues of access, security, universal querator, resource broker Virtual Molonglo Observatory

  7. Role of Australian Astronomy • Workshop focus on data and tools • Examples of current possibilities • Challenges and opportunities Virtual Molonglo Observatory

  8. Functional Requirements: A First Draft • Immediate processing of data from sensors (all s) • Formats for raw data in sensor databases • Transparent access to all databases • Correlation of data sets across databases • Facilitation and acceleration of the scientific • method using all databases AVO Project Management Gavin Thoms 27 November 2002 Virtual Molonglo Observatory

  9. 1. AAO & the IVOA - Strategy • Build/continue alliances with key groups • Assist in development of VO standards • Build VO-compliance into data & products • Facilitate development of analysis tools Virtual Molonglo Observatory

  10. Virtual Molonglo Observatory

  11. The Way forward: ARC grant for 2003 (1.5FTE@AAO) • Incorporate 2dF survey into VO-table (milestone: demo at IAU GA) • Integrate 2dF spectra & catalogue server (milestone: end 2003) • VO-compliance for 6dF from start (milestone: April 2003) • Route map for AAO VO-compliance (milestone: end 2003) Virtual Molonglo Observatory

  12. 2. Contribution from the Molonglo Observatory • Image availability - data calibration & quality • Source catalogues – integrity and interpretation • What is raw data? Case study at 408 MHz Virtual Molonglo Observatory

  13. Response Classification with a Decision Tree Blue ellipses - Sources Red ellipses - Artefacts Virtual Molonglo Observatory

  14. Current data pipeline • Automated observations • Manual transport of data (CDs) to Sydney • Customised analysis software programs • Image archive & source catalogue • Processed data back to Molonglo & Web • Resource intensive Virtual Molonglo Observatory

  15. 3. Machine Learning techniques • Goal – multiwavelength correlations • Problem – database mismatches • Traditional methods – closest position & other information Virtual Molonglo Observatory

  16. (B) (A) Y X RADIO: HIPASS 21cm surveyOPTICAL: SuperCOSMOS 10 arc min error diameter The correlation problem: which is the radio source? Virtual Molonglo Observatory

  17. Use Machine Learning • Data vectors from catalogues • Radio: RA, Dec, velocity, velocity width, flux • Optical: (RA, Dec, B,R,I mags, shape)N • Training sets • Optical counterparts with measured velocities • Machine learning • Support Vector Machine • Use all parameters for the classification: new physics? • Quadratic programming problem, so unique solutions Virtual Molonglo Observatory

  18. 4. Future: direct image analysis • Handwritten postcode recognition • US Postal Service database: each digit 16×16 pixels • 7,300 training patterns, 2,000 test patterns • Classifier % Error • Decision tree 16.2 • 5-layer neural net 5.1 • Support vector machine 4.1 • Human 2.5 • Direct analysis of optical pixel data? • Established for morphological galaxy classification • Too many pixels for radio identification problems? Virtual Molonglo Observatory

  19. 5. Example element of e-Astronomy Australia Build a pipeline processor (running aips++) to process radio synthesis data from ATCA archive on the fly • User can choose parameters of image • Field centre • Field size • Optimise algorithm for science question being asked • Can use latest version of calibration algorithm • Expert users can tweak parameters Virtual Molonglo Observatory

  20. Goals of e-Astronomy Australia • Survey and archive data from Australian telescopes available to all IVO users • Prospects to put full ATCA archive online • Set up datagrid and compute grid to give Australian astronomers access to IVO resources • Help develop techniques, protocols, etc for the IVO Virtual Molonglo Observatory

  21. 6. Tools – new and used • FITS – successful data format – keep? • Astronomy co-ordinate systems – several in use – IAU working group • VOtable – flexibility, greater complexity, incorporate current protocols Virtual Molonglo Observatory

  22. 7. New multicolour Survey • Imaging survey with Great Melbourne Telescope • A TRAGEDY! Virtual Molonglo Observatory

  23. Discussion: paradigm for a small country • Identify strengths or special roles in the international context • Identify any major international partners gains from the involvement • Identify gains for the small country from involvement in the project • Identify a realistic niche for a significant contribution • If any of 1- 4 are missing, withdraw! Virtual Molonglo Observatory

  24. Challenges & Opportunities • Continue training of future astronomers • Need resources to maintain and upgrade databases & fund future instruments • Cross-discipline collaborations • Maintain role in observational science • FIND A NICHE! Virtual Molonglo Observatory

  25. Where to now? • LIEF grant for 1 year – new grants? • Raise visibility in Europe, USA programs • Cross discipline links – herbarium, medical centre, particle physics • Identify areas of contribution to international VO – spectroscopy? • http://www.aus-vo.org (David Barnes) Virtual Molonglo Observatory

  26. Conclusions GOAL: To develop tools, data and organisational structures to facilitate international collaborations and individual research on multidimensional archives operating as a VO. Virtual Molonglo Observatory

More Related