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

STARE Operations Experience and its Data Quality Control Potsdam, July04 #2 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, 15  m pix 6.1x6.1 deg 2 FOV, 10.8 arcsec/pix R, V, B manual filters.

STARE Operations Experience and its Data Quality Control Potsdam, July04 #3 Transit Detection Observations STARE observation strategy: One (two) field observed all night, typ. declination 30°-40°. Observation of a field for months ( hrs) R band exposures of 100 sec, 13 sec readout typical field: few 1000 stars rms < 1% Requirements : precision  F/F better than 0.5% observational coverage O( ) hrs data points every few minutes surveying thousands of stars

STARE Operations Experience and its Data Quality Control Potsdam, July04 #4 In collaboration with similar projects PSST: Lowell Obsv., Arizona. T. Dunham, G. Mandushev SLEUTH: Mt. Palomar, California. D. Charbonneau, F. O’Donovan

STARE Operations Experience and its Data Quality Control Potsdam, July04 #5 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)

STARE Operations Experience and its Data Quality Control Potsdam, July04 #6 DLT, DVD Operations scheme operator opens dome, starts script Afternoon Nightfall; if field high enough End of night/field too low Morning script starts observations PC butch (script) PC sundance Mount+domeCCD+autoguide script return telesc. to home pos operator closes dome, saves data (2Gb/night) Observing period operator watches weather; closes if needed

STARE Operations Experience and its Data Quality Control Potsdam, July04 #7 Data reduction scheme raw data saved on DLT, now DVD Teide Obsv IDL programs: quality control, image processing, photometry, classification, transit search IAC, La Laguna PSST Lowell, Sleuth Palomar Confirmation of events in other’s data. Combination of data from 3 sites and transit search in combined data Future HAO, Boulder Coordination of follow-up obsv.

STARE Operations Experience and its Data Quality Control Potsdam, July04 #8 STARE status Field Observing date Observing nights (Teide) Stars with rms<1% Observing time (h) (Teide) Coll. Telesc. Status Jul-Oct 0138 of 91~ Reduced Boo1Abr-Jul 0239 of 118~ Reduced Teide and Lowell Cyg1Jul-Oct 0216 of 78~ Reduced Teide Per2Oct-Nov 0230 of 58~ Reduced Teide Cnc0Feb-May 0316 of 89?1272 Reduced Reduced Lowell Her0May-Jun 0344 of 54~ Reduced All Lyr0Jul-Sep 03~50 of 68?3673 Red. Teide Lowell Cyg0 42 AndSep03-Jan0456 of 121~ Not reduced 27 LynJan-Mar0429 of 61?1033Not reduced Since March: Technical problems (110V supply, UPS)

Instrumental & atmospheric sources of false alarms 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 “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

STARE Operations Experience and its Data Quality Control Potsdam, July04 #10 Astron. source of false alarms (Brown 2003) Confusion from: grazing eclisping binaries diluted eclising binaries (by foreground star) diluted eclising binaries (triple sys) Planetary transits We look for:

STARE Operations Experience and its Data Quality Control Potsdam, July04 #11 What do we expect? (Brown 2003) mag R < 12 1d < period < 30d 0.01 < dF/F < d < durat. < 0.25d CategoryTotal n  2n  3 MPU MSU MSDF MSDT (MS binaries diluted by foreground stars) Expected detection and false alarms per stars: (MS binaries) (MS hierarchical triples) Planetary transits Planets Ecl. Binary Ecl. Binary + *

STARE Operations Experience and its Data Quality Control Potsdam, July04 #12 Data quality control Photometric, moon rise extinction sky bright. guidingalignment

STARE Operations Experience and its Data Quality Control Potsdam, July04 #13 Data quality control Cirrus in early night

STARE Operations Experience and its Data Quality Control Potsdam, July04 #14 Data quality control Dusty night

STARE Operations Experience and its Data Quality Control Potsdam, July04 #15 Data quality control guiding unstable, moon setting

STARE Operations Experience and its Data Quality Control Potsdam, July04 #16 Data quality control Serious guiding problems

STARE Operations Experience and its Data Quality Control Potsdam, July04 #17 Follow-up tecniques for transit candidates 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 Reject astronomical sources of false alarms by a sequence of tests, from simple (light) to sophisticated (resource-intensive) ones:

STARE Operations Experience and its Data Quality Control Potsdam, July04 #18 Interpretation of the lightcurve

STARE Operations Experience and its Data Quality Control Potsdam, July04 #19 Are there secondary eclipses? Nominal period Double period -> probably an eclipsing binary

STARE Operations Experience and its Data Quality Control Potsdam, July04 #20 Follow-up tecniques Careful interpretation of the lightcurve: –search for primary/secondary eclipses, non-transit-like shape –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 –low res: may detect Ecl. binaries (false alarm rejection) –high res: independent verification of planet Going from simple (light) to sophisticated (resource- intensive) methods:

STARE Operations Experience and its Data Quality Control Potsdam, July04 #21 Vulcan 3433 = ST 6526 transit candidate with dF/F ~1.5% (0.015mag) Multi-color timeseries photometry ~ 2.6 % R filter  mag ~ 2.1 % V filter  mag ~ 5 % J filter  mag Unlikely for a planet: Vshaped eclipse, depth difference in J

STARE Operations Experience and its Data Quality Control Potsdam, July04 #22 Follow-up tecniques Careful interpretation of the lightcurve: –search for primary/secondary eclipses, non-transit-like shape –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 –low res: may detect Ecl. binaries (false alarm rejection) –high res: independent verification of planet Going from simple (light) to sophisticated (resource- intensive) methods:

STARE Operations Experience and its Data Quality Control Potsdam, July04 #23 F 2 /F 1 ~0.25 % The faint companion can’t explain observed transit depth of 1.5%. This candidate may remain in the list Vulcan 3433 = ST 6526 transit candidate with dF/F ~1.5% (0.015mag) STARE: pixel-size: 11”. Re-observation with an 80cm telescope (1,2”psf) : ? F 2 ~ 70 adu F 1 ~ adu Higher resolution imaging

STARE Operations Experience and its Data Quality Control Potsdam, July04 #24 Imaging with high resolution Are there unresolved EBs? The probability to detect an unresolved EB with a currently unresolved PSF is: For STARE data against WHT’s NAOMI this is: d STARE = 20’’ d NAOMI = 0.2’’ P = = % The faintest EB that would cause a transit-like event of relative depth  is at most  mag fainter than brightest star : For  = 0.01,  mag ≤ 4.2 For  = 0.02,  mag ≤ 3.5 e.g. if there is an unresolved EB, probability is very high to detect it with high-res imaging But, are these nearby stars bright enough to cause transit-like event? 0,4” none of nearby stars bright enough to explain observed depth of transit (6%)

STARE Operations Experience and its Data Quality Control Potsdam, July04 #25 Follow-up tecniques Careful interpretation of the lightcurve: –search for primary/secondary eclipses, non-transit-like shape –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 –low res: may detect Ecl. binaries (false alarm rejection) –high res: independent verification of planet Going from simple (light) to sophisticated (resource- intensive) methods:

STARE Operations Experience and its Data Quality Control Potsdam, July04 #26 Correlation radial velocity ST 4847 Cygnus candidates follow-up (radial veloc.) -> a diluted eclipsing binary

STARE Operations Experience and its Data Quality Control Potsdam, July04 #27 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.