1 / 24

The Thinking Telescopes Project, RAPTOR, and the TALONS Communication System

The Thinking Telescopes Project, RAPTOR, and the TALONS Communication System. Goal is to Integrate Three Components. Robotic Hardware Wide-Field Sky Monitoring Rapid Response Telescopes, Real Time Pipeline. Machine Learning GENIE, ML Classifiers, Anomaly Detection. Context Knowledge

lluvia
Télécharger la présentation

The Thinking Telescopes Project, RAPTOR, and the TALONS Communication System

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 Thinking Telescopes Project, RAPTOR,and the TALONS Communication System

  2. Goal is to Integrate Three Components Robotic Hardware Wide-Field Sky Monitoring Rapid Response Telescopes, Real Time Pipeline Machine Learning GENIE, ML Classifiers, Anomaly Detection Context Knowledge Record of Sky variability (Virtual Observatories), Massive Distributed Disk Array Thinking Telescopes An Engine for Discovery in the Time Domain

  3. Traditional Approach “Hard Wired” to find specific artifacts and phenomena For example---not in previous frame, not in sky catalog, and no parallax Thinking Telescope Monitoring of persistent sources for important changes in real time Adaptive processing Machine learning Anomaly detection and automated classification “find more like this” System Adaptability: Querying the Sky

  4. Machine Learning • Automated identification of artifacts and transients in direct and difference images. • Automated classification of celestial objects based on temporal and spectral properties. • Real time recognition of important deviations from normal behavior for persistent sources.

  5. Memory and Context http://skydot.lanl.gov

  6. Raptor: Sky Monitoring with Both Eyes Open • Wide-field imaging system monitors ~1300 square-deg with resolution ~35 arcsec and limiting magnitude of R~13th in 60 seconds. ( like the rod cells of the retina) • Each array has a “fovea” telescope with limiting magnitude of R~16.5 (60 sec), resolution of ~7 arcsec and Gunn g (or r) filter. Provides color, better resolution, and faster cadence light curves (cone cells of fovea) • Rapidly slewing mount places the “fovea” anywhere in the field in <3 seconds. (rapid eye movement). • Two identical arrays are separated by ~38 km. (stereoscopic vision)

  7. Best Solution – A Distributed Sensor Network Ultimate Goal –To make decisions or gain knowledge based on information fused from distributed inputs • Initial work done by military and contractors to support war fighters. • Sensor elements are self sustaining and autonomous. • Sensor elements gather data on environment independently. • Data is communicated back to a central location and collaboratively processed. • Working together these elements should provide a better overall picture of the environment, than single-point sensors.

  8. GENERAL CONCEPT FOR DISTRIBUTED SENSOR NETWORK ENVIRONMENT Data Gathering Sensing Modalities SensingModalities nodes data data Event Detection … SignalProcessing SignalProcessing event event Decision Making Collaborative Signal Processing

  9. The Distributed Sensor Network Idea Applied to the RAPTOR System Data Gathering nodes data data Event Detection … event event Decision Making

  10. DSN Qualifications In General Applied to an Astronomical System • Full scalability.Any number of systems coming and going • Fault tolerance.System dropouts, weather, instrument failure, etc. • Mosaic coverage. Large area combined imagining • Depth of data. Multiple instruments on same object and/or a variety of instrument sensitivities • Temporal coverage.Data covering continuous observations

  11. TALONS Components • Client: resides on each client computer • Provides connections back to server receive and/or transmit. • Monitors connections and repairs or notifies as necessary. • Filters incoming information based on previous activity, interests, operational capability of client system. • Logs activity on client • Prepares data for transmission • Decodes data for response • Monitor: run from any subscriber’s computer • Shows real-time activity of client systems and Central • Injector: accessed with client • Provides a method for manual alert generation • Provides method for manual response follow-up • Central: • Provides connection point for clients to transmit and/or receive. • Provides security for connections. • Provides cooperative analysis . • Relay from outside networks to clients. • Logs activity. • Filters information to and from clients. • Issues activity requests or alerts via sockets and e-mails.

  12. TALONS Monitor TALONS Injector

  13. The Communication Packets • All Packets Packet Size • Identifier byte What type, who sent 1 int • Data Bytes How much data to follow 1 int • GCN • Header packet (as above) • GCN Alert Data All data (as per GCN packet info) 40 int • TALONS • Header Packet (as above) • TALONS Data – 9 int • Target Follow-up Requests (Alerts) • Target of Opportunity Requests • Follow-up responses • Status • Header Packet (as above) • Status Data – Instrument or Observatory Status 5 int NOTE: All int values are 32 bit

  14. Breakdown of Packet Information GCN Packets – Information varies per satellite. Packet details at http://gcn.gsfc.nasa.gov/sock_pkt_def_doc.html TALONS Packets • TrigNo - Trigger (or Alert) Number • For Initial Spotting, returns a 0 to Central and Central assigns a new value. • For follow-up observations, Trigger number is passed as the event identifier 1 TrigNO 2 TID 3 TOO 4 Time 5 RA 6 DEC 7 Mag 8 MagErr 9 EOF • TID –Trigger ID • (Bit field definitions, encoded & decoded at client) • Imagine Instrument or Observatory systems ID • Follow-up or Initial spotting • Either Suspected or Confirmed target type (Nova, SN, etc.) • Known or new target object } • TOO – Target of Opportunity • (Bit field definitions, encoded & decoded at client) Works with TID above to define type details • Defines whether this packet is for a TOO • Identifies if the event is transient (approaching, or receding from event. • Requested Observation Type (Spectra, Photon Counting, Any, All, etc) • Requested Observation Range (FIR, Gamma, Radio, etc.). • Requested imaging durations (How many seconds?) Time - Time imaged expressed in TJD RA - Target Coordinate DEC - Target Coordinate Mag - Magnitude of target MagErr - Error in Magnitude measure NOTE: RA and DEC errors are to come

  15. Summary TALONS has been in operation now for three years, supporting the RAPTOR system TALONS can easily grow to support any number of additional robotic and manual telescopic systems TALONS works well in concert with GCN. No additional coding necessary to receive GCN. The TALONS Client library can quickly and easily be added to any existing telescope operation software and can quickly be configured to support the interests of the user. The information packets are flexible and can be changed to suit needs or additional packet types can be added as needed.

More Related