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VOEventNet

VOEventNet. By Matthew J. Graham (Caltech). What is VOEventNet?. Real-time astronomy with a rapid-response telescope grid A peer-to-peer cyberinfrastructure to enable rapid and federated observations of the dynamic night sky

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VOEventNet

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  1. VOEventNet By Matthew J. Graham (Caltech)

  2. What is VOEventNet? • Real-time astronomy with a rapid-response telescope grid • A peer-to-peer cyberinfrastructure to enable rapid and federated observations of the dynamic night sky • A network of telescopes and computers working synergistically, under the watchful eye of humans, to find and study interesting astronomical events • A transportation of events to interested subscribers, automatically in seconds or minutes after discovery

  3. What is VOEventNet? really ^ • $600k 3 year NSF-funded project under the DDDAS (Dynamic Data-Driven Applications Systems) initiative involving Caltech, UC Berkeley and LANL • Personnel: Matthew Graham Ashish Mahabal Andrew Drake Derek Fox Przemek Wozniak Roy Williams (PI) Joshua Bloom George Djorgovski Shri Kulkarni Thomas Vestrand

  4. VOEvent database eStar GRB satellites Architecture Palomar-Quest PQ next-daypipelines baselinesky Raptor catalog Palomar 60” PQ Event Factory Event Synthesis Engine VOEventNet Pairitel SDSS 2MASS known variables known asteroids remote archives

  5. Palomar-Quest Survey • Synoptic sky survey using the 48” Palomar Samuel Oschin Schmidt telescope and the 112-CCD, 161-Megapixel Quest II camera • Collaboration between Caltech, Yale/Indiana U., NCSA, and JPL; et al. • VO compliance/standards built in from the start • Two modes: drift scan with UBRI/rizz or multiple repeated snapshots in one filter  ~70GB of data/night • 15000 deg2 observed a minimum of 8 times with baselines minutes to years

  6. Real PQ data: The Big Picture • A 152 ft  20 ft mural produced for Griffith Observatory from PQ survey BRI images • A swath of 15.2 2.0 swath through the center of the Virgo cluster, sampled at 0.4 arcsec/pixel, giving a 136,800 18,000 pixel image • Computed at CACR using HyperAtlas and a custom data cleaning pipeline • Reproduced on 114 steel-backed porcellain plates, expected to last many decades • Will be seen by millions of visitors • Associated website will include NVO outreach

  7. The Big Picture: detail The Big Picture: detail

  8. The Big Picture: more detail The Big Picture: Tile C12 (M87) Zoom-in

  9. Transients in the Big Picture 740 Cantabia Tile b07

  10. VOEvent database eStar GRB satellites Architecture Palomar-Quest PQ next-daypipelines baselinesky Raptor catalog Palomar 60” PQ Event Factory Event Synthesis Engine VOEventNet Pairitel SDSS 2MASS known variables known asteroids remote archives

  11. Palomar-Quest Event Factory • Real-time pipeline to process raw data streaming from telescope: • Remove detector signatures including glitches masquerading as transient events: meteors, airplanes, glints from satellites and junk, etc. • Apply basic photometric and astrometric calibration • Extract detected sources and measure attributes • Compare with baseline data (catalogs/images) to identify new, transient or highly variable sources • Compare with dbs of known variables, asteroids, etc.

  12. VOEvent database eStar GRB satellites Architecture Palomar-Quest PQ next-daypipelines baselinesky Raptor catalog Palomar 60” PQ Event Factory Event Synthesis Engine VOEventNet Pairitel SDSS 2MASS known variables known asteroids remote archives

  13. Event Synthesis Engine • New input arrives from PQ/elsewhere: • Establish event “portfolio” to archive and federate all subsequent data and analysis • Send initial event notification to subscribers • Launch query against external dbs via NVO • Classify and prioritize: • Evaluate likelihood probabilities of event being associated with possible astrophysical sources using machine learning techniques (‘Thinking Telescope’) • Evaluate urgency of desired follow-up • Send out VOEvent

  14. VOEvent database eStar GRB satellites Architecture Palomar-Quest PQ next-daypipelines baselinesky Raptor catalog Palomar 60” PQ Event Factory Event Synthesis Engine VOEventNet Pairitel SDSS 2MASS known variables known asteroids remote archives

  15. VOEventNet Communication Fabric • Author • Publisher (aggregator): • Stores packet and assigns identifier • Distributes to subscribers based on pre-defined criteria using one-way web services • Two dbs - Caltech for PQ and Los Alamos for Raptor - harvest each other • Subscriber: • Gets event from publisher, evaluates it and causes scheduling in telescope observing queue or an archive search

  16. Event Cycling • An event can be injected back into the same decision/classification engine that published it but supplemented with data from elsewhere • Events dynamically cycle through follow-up observation and computation (no humans in loop) with subscribers make judgments and adding value until convergence

  17. Robotic Telescopes • RAPTOR • Stereoscopic sky monitoring with follow-up ‘fovea’ telescope • PAIRITEL • Meter-class IR follow-up • P60 • Principal follow-up facility for PQ Events • eSTAR

  18. Timeline • Year one - proof-of-concept system consisting of: • Source of VOEvents • A VOEvent store • Basic event discriminator • Robotic telescopic capable of responding to VOEvent: P60 and Pairitel • Year two - prototype system • Year three - production system

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