1. RoboNet-II Robotic operations, System outline and data processing Yiannis Tsapras, 2008, LCOGT, Santa Barbara

2. People Y Tsapras (LCOGT) R Street (LCOGT) K Horne (St Andrews) (PI) C Snodgrass (ESO) D Bramich (ING) M Dominik (St Andrews) N Kains (St Andrews) N Rattenbury (Manchester) M Burgdorf (ARI) A Allan (eSTAR/Exeter) E Hawkins (LCOGT) C Mottram (eSTAR/ARI) N Clay (eSTAR/ARI) I Steele (eSTAR/ARI) B Haworth (LCOGT) S Fraser (eSTAR/ARI)

3. The telescope network FTS+FTN+LT LCOGT expansion plans ( M. Falarski ) All telescopes used by microlensing teams

4. System Layout

5. The Robotic Control System

6. Runs on a computer at each telescope site Issues instructions to the software controlling the telescope and instruments. It performs: Start-up and end of night operations Observations (Science,ToO, RTI, background) Receives updates from local weather station and closes down operations if parameters exceed allowed ranges Receives input from: Observer Support System (normal observations database) Target of Opportunity Control System (bypass normal operations)

7. Requesting observations The Phase-II database contains all observation program details [targets, configuration, exposures] All observations are part of proposals A proposal contains: Groups of observations [specify:activation,expiration,monitoring,conditions] Individual observation requests [specify: instrument,position,repeats,exptime] 5 types of Groups : Flexible- one off observations, can be performed any time Fixed- one off observations, performed at specific times Monitoring- periodic observations of same target, fixed interval Ephemeris- performed at given phase in a variable objects cycle MinInterval- performed at least the specified interval apart microlensing

8. Example of phase-II entry

10. Intelligent Agents create these entries automatically! ( wait for a few more slides )

11. Scheduling observations When RCS requests next Group of observations… All Groups in database are sorted by the Scheduling algorithm In a rapidly changing environment, the selected group is one that is best matched to current conditions Takes into account: local conditions, phase-II model, Group history. (Fraser S.,2006, AN, 327,779)

12. Scheduling metrics Group scoring Slew time Lateness in project Time used in proposal relative to allocation Matching of actual condition to requested (seeing/lunar) Assigned priority level Proposal science priority Observing windows missed by monitor/ephemeris group Observation scoring Target location (height) Transit height fraction Distance from the moon

13. What does this mean? Observing programs in the database are constantly competing for telescope time We generally do not know when an observation will be performed or from which telescope ( though we can have a pretty good guess ) It was designed this way to accommodate a large global telescope network Only very basic user input, the system does the rest

14. Intelligent agents

15. eSTAR external agent Receives prioritised list of targets regularly from RoboNet-II ( web-PLOP, every hour ) Submits observation queries and requests to… Telescope Embedded Agent ( TEA & node agent ) Responds to eSTAR agent about telescope suitability for specific observing request Handles the requests from external agents and updates Phase-II database

17. Intelligent agents (addendum) We can override normal observations manually via a webpage interface or from our iPod Touch while having coffee at Starbucks We can override normal observations manually via a webpage interface or from our iPod Touch while having coffee at Starbucks

18. Prioritising the events

19. Planet Lens Optimisation ( “web-PLOP” Snodgrass 2008 ) Provides optimal target list for automated observing ( updated every 15 min ) Keeps up to date record of all data from OGLE,MOA,PLANET,RoboNet-II observations New fits performed when new data points arrive ( PLENS, SIGNALMEN, web page updates ) List read by the eSTAR intelligent agent Receives input from anomaly detector ( which tags anomalous events as high priority ) Prioritisation algorithm ( Horne 2008, MNRAS, submitted )

21. Anomaly detection

22. Exploits the systems’ possibility of automated fast response and flexible scheduling ( M. Dominik ) How? Receives new data by rsync from RoboNet-II cluster ( as soon as these are processed by our pipeline ) Data from other surveys also included Identifies new points that are deviating Action requests: check, anomaly, ordinary No manual intervention needed Currently this mode of override only works for real-time RoboNet-II data

23. Quicklook Archiving

24. Archives

25. The reduction pipeline

26. Intercepts incoming microlensing data Performs an assessment of data quality Updates the log file of observations Moves data to the appropriate event directories If appropriate, identifies the target position on reference ( based on WCS fits to the finder charts ) – R. Street Initiates Difference Image Analysis pipeline

27. The reduction pipeline Creates a template reference frame Geometric and Photometric alignment of all images to the reference frame Matches the seeing between each image and the reference Subtracts each scaled image from the reference Variable stars leave a positive or negative residual Fits PSF to target Update photometry ( also on web-PLOP, ARTEMiS and the PLANET webpages ) OB08199

28. The reduction pipeline (dfd)

29. Results displayed “live”

30. 2008 e-mail exchanges (anomaly and high magnif.) KB08075 KB08117 -binary KB08159 -scatter at peak? KB08171 KB08198 KB08199 -binary KB08267 KB08280 KB08308 KB08284 -binary source KB08310 -planet? KB08336 KB08380 KB08384 -binary OB08013 OB08208 OB08272 OB08210 -peak anomaly OB08270 -planet? OB08272 OB08320 OB08330 OB08342 OB08346 OB08349 OB08355 OB08378 OB08432 OB08493 OB08510 -peak anomaly OB08513 -planet? OB08559 32 emails alerting suspected anomalous behaviour OB08151 OB08209 OB08215 OB08290 -finite source OB08426 OB08509 KB08022 KB08096 KB08105 KB08225 KB08311 KB08383 KB08402 KB08415 KB08428 -anomalous KB08453 16 emails alerting possible high magnification

31. KB08384

32. OB08210

33. OB08510

34. KB08310 microFUN Probably a Saturn- like planet?, pretty close to the Einstein ring ( preliminary model by Subo Dong ) Strong Parallax signal

35. OB08270 Preliminary modelling based on microFUN + SAAO data around the peak seem indicate the presence of Jovian planetary companion

36. OB08513 q~0.018?

37. OB08513

38. 2008 season summary Time used : 313.16 hours Events observed: 502, 266(>5 data points) Data FTN FTS LT Used : 1602 5494 1294 Rejected: 363 2375 1118( ? ) Total : 12246 [ used:8390/rejected:3856 ] Events observed: 331, 214(>5 data points) Data FTN FTS LT Used : 1016 5965 611 Rejected: 182 5921 318 Total : 14013 [ used:7592/rejected:6421 ] 2007 >5 dp : 204.04 hrs (65%) <5 dp : 10.37 hrs (3%) Rejected : 98.75 hrs (32%) What fraction of the time?

39. Issues Software: deploy, debug, maintain… Introduce extra internal monitoring, auto-recovery mechanisms where possible School programs ( 1 to 4 hours on most nights ) Not much we can do. Wait for 0.4m deployment FTS performance ( main microlensing telescope ) Still room for improvement, engineering trip planned Data display problems Target misidentification by the pipeline, incorrect lightcurves ( you may have noticed the huge error bars on some RoboNet-II data on ARTEMiS plots )

40. “wouldn’t it be nice…” Agree on a common data format so that teams can exchange data efficiently Associate data points on graphs with statistics on images Information readily accessible Fit binary events automatically with preliminary models displayed “live”

41. Websites http://robonet.lcogt.net/ (RoboNet-II homepage) http://robonet.lcogt.net/ http://lcogt.net/ (LCOGT website) http://lcogt.net/ http://microlensing.lcogt.net/ (microlensing discussion forum) http://microlensing.lcogt.net/

42. Fin

43. Other event examples KB08284

44. FTS image quality 2007 problems: bipolar images, bad tracking…

45. FTS image quality 2008 (on a good night)