CONTAMINATION IN THE KEPLER FIELD. IDENTIFICATION OF 685 KOIs AS FALSE POSITIVES VIA EPHEMERIS MATCHING BASED ON Q1–Q12 DATA

By Jeff Coughlin, S. Thompson, S. Bryson, C. Burke, Douglas A. Caldwell, J. Christiansen, M. Haas, S. Howell, Jon M. Jenkins, J. Kolodziejczak and 2 more. 2014

89 citations recorded by the source corpus.

The Kepler mission has to date found almost 6000 planetary transit-like signals, utilizing three years of data for over 170,000 stars at extremely high photometric precision. Due to its design, contamination from eclipsing binaries, variable stars, and other transiting planets results in a significant number of these signals being false positives (FPs). This directly affects the determination of the occurrence rate of Earth-like planets in our Galaxy, as well as other planet population statistics. In order to detect as many of these FPs as possible, we perform ephemeris matching among all transiting planet, eclipsing binary, and variable star sources. We find that 685 Kepler Objects of Interest (KOIs)—12% of all those analyzed—are FPs as a result of contamination, due to 409 unique parent sources. Of these, 118 have not previously been identified by other methods. We estimate that ∼35% of KOIs are FPs due to contamination, when performing a first-order correction for observational bias. Comparing single-planet candidate KOIs to multi-planet candidate KOIs, we find an observed FP fraction due to contamination of 16% and 2.4% respectively, bolstering the existing evidence that multi-planet KOIs are significantly less likely to be FPs. We also analyze the parameter distributions of the ephemeris matches and derive a simple model for the most common type of contamination in the Kepler field. We find that the ephemeris matching technique is able to identify low signal-to-noise FPs that are difficult to identify with other vetting techniques. We expect FP KOIs to become more frequent when analyzing more quarters of Kepler data, and note that many of them will not be able to be identified based on Kepler data alone.

Subfields: Astronomy and Astrophysics, Instrumentation

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In Astronomy and Astrophysics

1. D. Charbonneau
2. Timothy Morton
3. Jon Fortney
4. J. Johnson
5. J. Winn
6. Andrew W. Howard
7. G. Marcy
8. E. Petigura

In Instrumentation

1. D. Charbonneau
2. Timothy Morton
3. Jon Fortney
4. J. Winn
5. J. Johnson
6. G. Marcy
7. Andrew W. Howard
8. E. Petigura

Citations in the corpus

• STELLAR AND PLANETARY PROPERTIES OF K2 CAMPAIGN 1 CANDIDATES AND VALIDATION OF 17 PLANETS, INCLUDING A PLANET RECEIVING EARTH-LIKE INSOLATION (2015, background): “Coughlin et al. (2014) identify 685 KOIs as false positives and outline four physical reasons why these anomalies may occur.”
• FALSE POSITIVE PROBABILITIES FOR ALL KEPLER OBJECTS OF INTEREST: 1284 NEWLY VALIDATED PLANETS AND 428 LIKELY FALSE POSITIVES (2016, methodology): “That is, these scenarios do not account for the possibility that only a small fraction of the light from a nearby contaminating star might be in the aperture, many of which have already been identified via other methods Bryson et al. (2013); Coughlin et al. (2014).”
• THE OCCURRENCE OF POTENTIALLY HABITABLE PLANETS ORBITING M DWARFS ESTIMATED FROM THE FULL KEPLER DATASET AND AN EMPIRICAL MEASUREMENT OF THE DETECTION SENSITIVITY (2015, result): “We compared the periods P and epochs t0 of the accepted planet candidates to the catalog of known eclipsing binaries, periodic variable stars, and KOIs compiled by Coughlin et al. (2014).”
• PLANETARY CANDIDATES OBSERVED BY KEPLER. VI. PLANET SAMPLE FROM Q1–Q16 (47 MONTHS) (2015, background): “• Transits and other variability on bright stars can contaminate targets many tens of arcseconds away (Coughlin et al. 2014, and § 5.3).”
• AUTOMATIC CLASSIFICATION OF KEPLER PLANETARY TRANSIT CANDIDATES (2014, methodology): “Of these, 1487 have since been given dispositions by the TCERT using somewhat different techniques from the original training set, which were methods described in Coughlin et al. (2014).”
• DISCOVERY AND VALIDATION OF Kepler-452b: A 1.6 R⨁ SUPER EARTH EXOPLANET IN THE HABITABLE ZONE OF A G2 STAR (2015, background): “Optical ghosting, or direct PSF contamination, was the subject of a study by Coughlin et al. (2014) identifying 685 TCEs in the Q1–Q12 vetting process as false positives due to these and other effects.”
• Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90 (2017, methodology): “Sometimes, contamination can be caused by a process called “charge transfer inefficiency”, or “column anomaly” (Coughlin et al. 2014).”
• LOW FALSE POSITIVE RATE OF KEPLER CANDIDATES ESTIMATED FROM A COMBINATION OF SPITZER AND FOLLOW-UP OBSERVATIONS (2015, methodology): “…involves several qualitative steps that could affect the Kepler FPR. Christiansen et al. (2013) have validated the integrity of this threshold while Coughlin et al. (2014) report that TCERT (Threshold Crossing Event Review Team) is 92.9% effective in detecting false-positives for KOIs from Q1-Q8.”
• Planet Hunters IX. KIC 8462852-where's the flux? (2015, background): “(vi) We determined that CCD cross talk, reflection, and column anomaly cannot be the cause (Coughlin et al. 2014).”
• The California-Kepler Survey. I. High-resolution Spectroscopy of 1305 Stars Hosting Kepler Transiting Planets (2017, background): “…spillover light from eclipsing binaries that occupy nearby pixels on the Kepler CCD. Identifying false positives by matching KOI ephemerides to known eclipsing binaries revealed several hundred false positives and further improving the quality of later Kepler candidate lists (Coughlin et al. 2014).”
• THE KEPLER FOLLOW-UP OBSERVATION PROGRAM. I. A CATALOG OF COMPANIONS TO KEPLER STARS FROM HIGH-RESOLUTION IMAGING (2016, background): “Sorting out false positives is a complex process addressed in many publications (Fressin et al. 2013; Coughlin et al. 2014; Seader et al. 2015; Mullally et al. 2015; Desert et al. 2015; McCauliff et al. 2015; Santerne et al. 2016; Morton et al. 2016), with current estimates for false positive rates…”
• TERRESTRIAL PLANET OCCURRENCE RATES FOR THE KEPLER GK DWARF SAMPLE (2015, background): “The pipeline only searches for transits with a uniform ephemeris and targets with high SNR and strong TTVs can result in multiple TCEs at the incorrect period, but corresponding to one to a few of the high SNR transit events.”