eStar – Combining Telescopes and Databases

1. eStar – Combining Telescopes and Databases Tim Naylor - University of Exeter Iain Steele – Liverpool John Moores University Dave Carter - Liverpool John Moores University Chris Motram – Liverpool John Moores University Jason Etherton - Liverpool John Moores University Alasdair Allan - University of Exeter

2. In a galaxy a long time away astronomers had built a virtual observatory

3. In a galaxy a long time away astronomers had built a virtual observatory But a small, determined rebel group continued to make new observations!

4. In a galaxy a long time away astronomers had built a virtual observatory But a small, determined rebel group Continued to observe the real universe "What has the mighty federation of databases ever done for us?" they cried.

5. Imagine a system which… • Has unified access to observational data, • and to telescopes, • and to the scientific literature. • And has intelligent software to interpret the results (IAs).

6. Scenario 1 – The space density of dwarf novae. • Interacting binary stars – important for evolution. • Every CCD field taken in the world is compared with SuperCosmos. • Objects which brighten above fixed magnitude (say 16th  MV) compared with SIMBAD. • Known dwarf novae noted; other variables rejected. • Historical data searched for new objects, used to identify lightcurve type.

7. Space density of dwarf novae. • If cannot be classified, further observations requested. • As lightcurve builds up, future observations placed optimally. • Object type finally determined. • HST parallax requested to confirm distance. • Astronomer comes back from long lunch break and writes paper.

8. Scenario 2 – What was that? • 02:11:03UT: shutter closes on a WASP image of Centaurus. • 02:12:30UT: the data have been processed and a list of positions and magnitudes is available. • 02:12:45UT: An astronomer’s intelligent agent discovers a new, bright object is in the data. • 02:13:00UT: In response to the IA’s request for confirmation a small telescope slews to acquire another image.

9. Whilst waiting the IA queries SIMBAD and discovers there is no known variable at this point. • 02:15:06UT: The new image confirms the object, so the IA requests a spectrum from the Liverpool Telescope. • Whilst waiting, the IA pulls all the other available data and papers. • 02:22:34UT: The spectrum is odd, there hasn’t been -ray burst but VISTA shows a very faint red object, mentioned in a paper last year… • 02:22:50UT: An astronomer is woken up.

10. How close are we to this? • eScience Telescopes for Astronomical Research. • Funded as an e-Science demonstrator project by UK DTI. • Uses Meade LX200 & ETX telescopes + SBIG or Apogee cameras. • Functions across network, with telescopes sending data “we made earlier”. • Test on sky later this year.

11. Design Issues. • No overall supervisor (scalability). • Many telescopes each with own scheduler, which talk to • intelligent agents, written mainly in Perl, • via RTML and Globus. • Intelligent agents also talk to SIMBAD/ADS/USNO A-2/DSS web services. • Many intelligent agents and discovery nodes. • An IA is intended to do one science job, and probably resides on the astronomer’s computer.

12. Typical Sequence • IA opens up with a Globus resource discovery (LDAP), finding each telescope. • Asks which nodes can carry out a particular observation (scoring). • Requests an observation, which telescope places in queue (scheduling). • Data (raw and reduced) made available to IA.

14. What sort of variable? • Mines SIMBAD to find variable stars at this location.

15. How much is known? • Mines Astrophysical Data system for papers, and for other data.

16. What Next? • See the demo and http://www.estar.org.uk/ • Scheduling system needs refining. • More intelligent IAs. • Looking for industrial partners for transfer in both directions (DTI funded). • Looking for astronomy partners; telescopes willing to become part of a network. • But none of this will work well if VOs and ROs talk different languages.