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Register a new userThe KELT Follow-Up Network and Transit False Positive Catalog: Pre-vetted False Positives for TESS
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The Kilodegree Extremely Little Telescope (KELT) project has been conducting a photometric survey for transiting planets orbiting bright stars for over ten years. The KELT images have a pixel scale of ~23/pixel---very similar to that of NASAs Transiting Exoplanet Survey Satellite (TESS)---as well as a large point spread function, and the KELT reduction pipeline uses a weighted photometric aperture with radius 3. At this angular scale, multiple stars are typically blended in the photometric apertures. In order to identify false positives and confirm transiting exoplanets, we have assembled a follow-up network (KELT-FUN) to conduct imaging with higher spatial resolution, cadence, and photometric precision than the KELT telescopes, as well as spectroscopic observations of the candidate host stars. The KELT-FUN team has followed-up over 1,600 planet candidates since 2011, resulting in more than 20 planet discoveries. Excluding ~450 false alarms of non-astrophysical origin (i.e., instrumental noise or systematics), we present an all-sky catalog of the 1,128 bright stars (6<V<10) that show transit-like features in the KELT light curves, but which were subsequently determined to be astrophysical false positives (FPs) after photometric and/or spectroscopic follow-up observations. The KELT-FUN team continues to pursue KELT and other planet candidates and will eventually follow up certain classes of TESS candidates. The KELT FP catalog will help minimize the duplication of follow-up observations by current and future transit surveys such as TESS.
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We present astrophysical false positive probability calculations for every Kepler Object of Interest (KOI)---the first large-scale demonstration of a fully automated transiting planet validation procedure. Out of 7056 KOIs, we determine that 1935 have probabilities <1% to be astrophysical false positives, and thus may be considered validated planets. 1284 of these have not yet been validated or confirmed by other methods. In addition, we identify 428 KOIs likely to be false positives that have not yet been identified as such, though some of these may be a result of unidentified transit timing variations. A side product of these calculations is full stellar property posterior samplings for every host star, modeled as single, binary, and triple systems. These calculations use vespa, a publicly available Python package able to be easily applied to any transiting exoplanet candidate.
Kepler Missions single-band photometry suffers from astrophysical false positives, the most common of background eclipsing binaries (BEBs) and companion transiting planets (CTPs). Multi-color photometry can reveal the color-dependent depth feature of false positives and thus exclude them. In this work, we aim to estimate the fraction of false positives that are unable to be classified by Kepler alone but can be identified with their color-dependent depth feature if a reference band (z, Ks and TESS) were adopted in follow-up observation. We build up physics-based blend models to simulate multi-band signals of false positives. Nearly 65-95% of the BEBs and more than 80% of the CTPs that host a Jupiter-size planet will show detectable depth variations if the reference band can achieve a Kepler-like precision. Ks band is most effective in eliminating BEBs exhibiting any depth sizes, while z and TESS band prefer to identify giant candidates and their identification rates are more sensitive to photometric precision. Provided the radius distribution of planets transiting the secondary star in binary systems, we derive formalism to calculate the overall identification rate for CTPs. By comparing the likelihood distribution of the double-band depth ratio for BEB and planet models, we calculate the false positive probability (FPP) for typical Kepler candidates. Additionally, we show that the FPP calculation helps distinguish the planet candidates host star in an unresolved binary system. The analysis framework of this paper can be easily adapted to predict the multi-color photometry yield for other transit surveys, especially for TESS.
Ten days of commissioning data (Quarter 0) and thirty-three days of science data (Quarter 1) yield instrumental flux timeseries of ~150,000 stars that were combed for transit events, termed Threshold Crossing Events (TCE), each having a total detection statistic above 7.1-sigma. TCE light curves are modeled as star+planet systems. Those returning a companion radius smaller than 2R_J are assigned a KOI (Kepler Object of Interest) number. The raw flux, pixel flux, and flux-weighted centroids of every KOI are scrutinized to assess the likelihood of being an astrophysical false-positive versus the likelihood of a being a planetary companion. This vetting using Kepler data is referred to as data validation. Herein, we describe the data validation metrics and graphics used to identify viable planet candidates amongst the KOIs. Light curve modeling tests for a) the difference in depth of the odd- versus even-numbered transits, b) evidence of ellipsoidal variations, and c) evidence of a secondary eclipse event at phase=0.5. Flux-weighted centroids are used to test for signals correlated with transit events with a magnitude and direction indicative of a background eclipsing binary. Centroid timeseries are complimented by analysis of images taken in-transit versus out-of-transit, the difference often revealing the pixel contributing the most to the flux change during transit. Examples are shown to illustrate each test. Candidates passing data validation are submitted to ground-based observers for further false-positive elimination or confirmation/characterization.
The Disk Detective citizen science project aims to find new stars with excess 22-$mu$m emission from circumstellar dust in the AllWISE data release from the Wide-field Infrared Survey Explorer (WISE). We evaluated 261 Disk Detective objects of interest with imaging with the Robo-AO adaptive optics instrument on the 1.5m telescope at Palomar Observatory and with RetroCam on the 2.5m du Pont telescope at Las Campanas Observatory to search for background objects at 0.15-12 separations from each target. Our analysis of these data lead us to reject 7% of targets. Combining this result with statistics from our online image classification efforts implies that at most $7.9% pm 0.2%$ of AllWISE-selected infrared excesses are good disk candidates. Applying our false positive rates to other surveys, we find that the infrared excess searches of McDonald et al. (2012), McDonald et al. (2017), and Marton et al. (2016) all have false positive rates $>70%$. Moreover, we find that all thirteen disk candidates in Theissen & West (2014) with W4 signal-to-noise >3 are false positives. We present 244 disk candidates that have survived vetting by follow-up imaging. Of these, 213 are newly-identified disk systems. Twelve of these are candidate members of comoving pairs based on textit{Gaia} astrometry, supporting the hypothesis that warm dust is associated with binary systems. We also note the discovery of 22 $mu$m excess around two known members of the Scorpius-Centaurus association, and identify known disk host WISEA J164540.79-310226.6 as a likely Sco-Cen member. Thirty-one of these disk candidates are closer than $sim 125$ pc (including 27 debris disks), making them good targets for direct imaging exoplanet searches.
The Transiting Exoplanet Survey Satellite (TESS) is currently concluding its 2-year primary science mission searching 85% of the sky for transiting exoplanets. TESS has already discovered well over one thousand TESS objects of interest (TOIs), but these candidate exoplanets must be distinguished from astrophysical false positives using other instruments or techniques. The 3-band Multi-color Simultaneous Camera for Studying Atmospheres of Transiting Planets (MuSCAT), as well as the 4-band MuSCAT2, can be used to validate TESS discoveries. Transits of exoplanets are achromatic when observed in multiple bandpasses, while transit depths for false positives often vary with wavelength. We created software tools to simulate MuSCAT/MuSCAT2 TESS follow-up observations and reveal which planet candidates can be efficiently distinguished from blended eclipsing binary (BEB) false positives using these two instruments, and which must be validated using other techniques. We applied our software code to the Barclay et al. (2018) predicted TESS discoveries, as well as to TOIs downloaded from the ExoFOP-TESS website. We estimate that MuSCAT (MuSCAT2 values in parentheses) will be able to use its multi-color capabilities to distinguish BEB false positives for $sim$17% ($sim$18%) of all TESS discoveries, and $sim$13% ($sim$15%) of $R_{rm pl} < 4R_oplus$ discoveries. Our TOI analysis shows that MuSCAT (MuSCAT2) can distinguish BEB false positives for $sim$55% ($sim$52%) of TOIs with transit depths greater than 0.001, for $sim$64% ($sim$61%) of TOIs with transit depths greater than 0.002, and for $sim$70% ($sim$68%) of TOIs with transit depth greater than 0.003. Our work shows that MuSCAT and MuSCAT2 can validate hundreds of $R_{rm pl} < 4R_oplus$ candidate exoplanets, thus supporting the TESS mission in achieving its Level 1 Science Requirement.
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