STARE Operations Experience and its Data Quality Control

1. STARE Operations Experience and its Data Quality Control IAC Roi Alonso Hans Deeg Juan A. Belmonte HAO Boulder Tim Brown David Charbonneau

2. STARE Operations Experience and its Data Quality Control STARE telescope • Stellar Astrophysics and Research on Exoplanets. • HAO, NASA funding; IAC logistics and personnel. • Detection of first planet transit in 1999, during commision at HAO • Located at Teide Observatory, Tenerife since July 2001 • Schmidt optics, 10.1 cm Ø, f=286mm. • CCD: 2k x 2k Loral, 15mm pix • 6.1x6.1 deg2 FOV, 10.8 arcsec/pix • R, V, B manual filters.

3. STARE Operations Experience and its Data Quality Control Transit Detection Observations • Requirements : • precision dF/F better than 0.5% • observational coverage O(103-4) hrs • data points every few minutes • surveying thousands of stars STARE observation strategy: • One (two) field observed all night, typ. declination 30°-40°. • Observation of a field for 2 - 3 months ( 150-400 hrs) • R band exposures of 100 sec, 13 sec readout • typical field: few 1000 stars rms < 1%

4. STARE Operations Experience and its Data Quality Control In collaboration with similar projects • PSST: Lowell Obsv., Arizona. T. Dunham, G. Mandushev • SLEUTH: Mt. Palomar, California. D. Charbonneau, F. O’Donovan

5. STARE Operations Experience and its Data Quality Control Instrument control • Hardware: 2 PCs: {Dome, Mount},{CCD,guiding} • Optical fiber interfaces computers  telescope  dome • Control software • Unified user interface withVisual C++ (Windows98) • Telescope: Orchestrate Scripting Software (Software Bisque): • Dome: AutomaDome (Software Bisque): • CCD: Pixel View (Pixel Vision)

6. PC butch (script) PC sundance Mount+dome CCD+autoguide STARE Operations Experience and its Data Quality Control Operations scheme operator opens dome, starts script Afternoon Nightfall; if field high enough script starts observations operator watches weather; closes if needed Observingperiod End of night/field too low script return telesc. to home pos operator closes dome, saves data (2Gb/night) Morning DLT, DVD

7. IDL programs: quality control, image processing, photometry, classification, transit search IAC, La Laguna PSST Lowell, Sleuth Palomar Confirmation of events in other’s data. Coordination of follow-up obsv. HAO, Boulder Combination of data from 3 sites and transit search in combined data Future STARE Operations Experience and its Data Quality Control Data reduction scheme raw data saved on DLT, now DVD Teide Obsv

8. Field Observing date Observing nights (Teide) Stars with rms<1% Observing time (h) (Teide) Coll. Telesc. Status Jul-Oct 01 38 of 91 ~7300 195 1 Reduced Cyg0 Boo1 Abr-Jul 02 39 of 118 ~1500 238 2 Reduced Teide and Lowell Cyg1 Jul-Oct 02 16 of 78 ~7300 67 2 Reduced Teide Per2 Oct-Nov 02 30 of 58 ~6300 193 2 Reduced Teide Cnc0 Feb-May 03 16 of 89 ? 127 2 Reduced Reduced Lowell Her0 May-Jun 03 44 of 54 ~1600 291 3 Reduced All Lyr0 Jul-Sep 03 ~50 of 68 ? 367 3 Red. Teide Lowell STARE Operations Experience and its Data Quality Control STARE status Since March: Technical problems (110V supply, UPS)

9. Instrumental & atmospheric sources of false alarms “Transits are rare events in hugh data sets which compete with other rare events to become detected” False alarm: any event that appears to be a transit, but isn’t • Sources : instrumental: • guiding errors (moving psf over zones with varying flat-field correct.) • temperature/focus variations • Sources : atmospheric: • unrecognized extinction variations (cirrus, dust) • simple high-sigma events in photon noise (star, sky), scintillation

10. We look for: • Planetary transits Confusion from: • grazing eclisping binaries • diluted eclising binaries (triple sys) • diluted eclising binaries (by foreground star) STARE Operations Experience and its Data Quality Control Astron. source of false alarms (Brown 2003)

11. STARE Operations Experience and its Data Quality Control Data quality control Photometric, moon rise extinction sky bright. guiding alignment

12. STARE Operations Experience and its Data Quality Control Data quality control Cirrus in early night

13. STARE Operations Experience and its Data Quality Control Data quality control Dusty night

14. STARE Operations Experience and its Data Quality Control Data quality control guiding unstable, moon setting

15. STARE Operations Experience and its Data Quality Control Follow-up tecniques for transit candidates Reject astronomical sources of false alarms by a sequence of tests, from simple (light) to sophisticated (resource-intensive) ones: • Careful interpretation of the lightcurve: • non-transit-like shape, search for primary/secondary eclipses • verify that transit is compatible with planet (Seager & Mallén-Ornelas, 2003) • Multicolor transit photometry (incidentially with higher spatial resolution) • detects many cases of Ecl. binaries. • Imaging with very high resolution (adapt. optics) • indicates if there are nearby stars, potentially Ecl. Binaries • Radial velocity measures • low res: may detect Ecl. binaries (false alarm rejection) • high res: independent verification of planet

16. STARE Operations Experience and its Data Quality Control Summary and future • Routine transit search operation since 2001 • Operations will continue for at least 3 years • Well-coordinated collaboration is in place for follow-up observations. Sequence of methods to reject false alarms. • Some interesting planet candidates which need final verifications.