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Register a new userMeasuring Transit Signal Recovery in the Kepler Pipeline. III. Completeness of the Q1-Q17 DR24 Planet Candidate Catalogue, with Important Caveats for Occurrence Rate Calculations
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Added by
Jessie Christiansen
Publication date
2016
fields
Physics
and research's language is
English
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With each new version of the Kepler pipeline and resulting planet candidate catalogue, an updated measurement of the underlying planet population can only be recovered with an corresponding measurement of the Kepler pipeline detection efficiency. Here, we present measurements of the sensitivity of the pipeline (version 9.2) used to generate the Q1-Q17 DR24 planet candidate catalog (Coughlin et al. 2016). We measure this by injecting simulated transiting planets into the pixel-level data of 159,013 targets across the entire Kepler focal plane, and examining the recovery rate. Unlike previo
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In this work we empirically measure the detection efficiency of Kepler pipeline used to create the final Kepler Threshold Crossing Event (TCE; Twicken et al. 2016) and planet candidate catalogs (Thompson et al. 2018), a necessary ingredient for occurrence rate calculations using these lists. By injecting simulated signals into the calibrated pixel data and processing those pixels through the pipeline as normal, we quantify the detection probability of signals as a function of their signal strength and orbital period. In addition we investigate the dependence of the detection efficiency on parameters of the target stars and their location in the Kepler field of view. We find that the end-of-mission version of the Kepler pipeline returns to a high overall detection efficiency, averaging a 90-95% rate of detection for strong signals across a wide variety of parameter space. We find a weak dependence of the detection efficiency on the number of transits contributing to the signal and the orbital period of the signal, and a stronger dependence on the stellar effective temperature and correlated noise properties. We also find a weak dependence of the detection efficiency on the position within the field of view. By restricting the Kepler stellar sample to stars with well-behaved correlated noise properties, we can define a set of stars with high detection efficiency for future occurrence rate calculations.
We present the seventh Kepler planet candidate catalog, which is the first to be based on the entire, uniformly processed, 48 month Kepler dataset. This is the first fully automated catalog, employing robotic vetting procedures to uniformly evaluate every periodic signal detected by the Q1-Q17 Data Release 24 (DR24) Kepler pipeline. While we prioritize uniform vetting over the absolute correctness of individual objects, we find that our robotic vetting is overall comparable to, and in most cases is superior to, the human vetting procedures employed by past catalogs. This catalog is the first to utilize artificial transit injection to evaluate the performance of our vetting procedures and quantify potential biases, which are essential for accurate computation of planetary occurrence rates. With respect to the cumulative Kepler Object of Interest (KOI) catalog, we designate 1,478 new KOIs, of which 402 are dispositioned as planet candidates (PCs). Also, 237 KOIs dispositioned as false positives (FPs) in previous Kepler catalogs have their disposition changed to PC and 118 PCs have their disposition changed to FP. This brings the total number of known KOIs to 8,826 and PCs to 4,696. We compare the Q1-Q17 DR24 KOI catalog to previous KOI catalogs, as well as ancillary Kepler catalogs, finding good agreement between them. We highlight new PCs that are both potentially rocky and potentially in the habitable zone of their host stars, many of which orbit solar-type stars. This work represents significant progress in accurately determining the fraction of Earth-size planets in the habitable zone of Sun-like stars. The full catalog is publicly available at the NASA Exoplanet Archive.
The dynamical history of stars influences the formation and evolution of planets significantly. To explore the influence of dynamical history on planet formation and evolution from observations, we assume that stars who experienced significantly different dynamical histories tend to have different relative velocities. Utilizing the accurate Gaia-Kepler Stellar Properties Catalog, we select single main-sequence stars and divide these stars into three groups according to their relative velocities, i.e. high-V, medium-V, and low-V stars. After considering the known biases from Kepler data and adopting prior and posterior correction to minimize the influence of stellar properties on planet occurrence rate, we find that high-V stars have a lower occurrence rate of super-Earths and sub-Neptunes (1--4 R$_{rm oplus}$, P<100 days) and higher occurrence rate of sub-Earth (0.5--1 R$_{ oplus}$, P<30 days) than low-V stars. Additionally, high-V stars have a lower occurrence rate of hot Jupiter sized planets (4--20 R$_{oplus}$, P<10 days) and a slightly higher occurrence rate of warm or cold Jupiter sized planets (4--20 R$_{oplus}$, 10<P<400 days). After investigating the multiplicity and eccentricity, we find that high-V planet hosts prefer a higher fraction of multi-planets systems and lower average eccentricity, which is consistent with the eccentricity-multiplicity dichotomy of Kepler planetary systems. All these statistical results favor the scenario that the high-V stars with large relative velocity may experience fewer gravitational events, while the low-V stars may be influenced by stellar clustering significantly.
Exoplanet catalogs produced by surveys suffer from a lack of completeness (not every planet is detected) and less than perfect reliability (not every planet in the catalog is a true planet), particularly near the surveys detection limit. Exoplanet occurrence rate studies based on such a catalog must be corrected for completeness and reliability. The final Kepler data release, DR25, features a uniformly vetted planet candidate catalog and data products that facilitate corrections. We present a new probabilistic approach to the characterization of Kepler completeness and reliability, making full use of the Kepler DR25 products. We illustrate the impact of completeness and reliability corrections with a Poisson-likelihood occurrence rate method, using a recent stellar properties catalog that incorporates Gaia stellar radii and essentially uniform treatment of the stellar population. Correcting for reliability has a significant impact: the exoplanet occurrence rate for orbital period and radius within 20% of Earths around GK dwarf stars, corrected for reliability, is 0.015+0.011-0.007, whereas not correcting results in 0.034+0.018-0.012 - correcting for reliability reduces this occurrence rate by more than a factor of two. We further show that using Gaia-based vs. DR25 stellar properties impacts the same occurrence rate by a factor of two. We critically examine the the DR25 catalog and the assumptions behind our occurrence rate method. We propose several ways in which confidence in both the Kepler catalog and occurrence rate calculations can be improved. This work provides an example of how the community can use the DR25 completeness and reliability products.
Transit photometry of the exoplanet candidate Kepler-1625b has recently been interpreted to show hints of a moon. We aim to clarify whether the exomoon-like signal is really caused by a large object in orbit around Kepler-1625b. We explore several detrending procedures, i.e. polynomials and the Cosine Filtering with Autocorrelation Minimization (CoFiAM). We then supply a light curve simulator with the co-planar orbital dynamics of the system and fit the resulting planet-moon transit light curves to the Kepler data. We employ the Bayesian Information Criterion (BIC) to assess whether a single planet or a planet-moon system is a more likely interpretation of the light curve variations. We carry out a blind hare-and-hounds exercise using many noise realizations by injecting simulated transits into different out-of-transit parts of the original Kepler-1625 data: 100 sequences with 3 synthetic transits of a Kepler-1625b-like planet and 100 sequences with 3 synthetic transits of this planet with a Neptune-sized moon. The statistical significance and characteristics of the exomoon-like signal strongly depend on the detrending method, and the data chosen for detrending, and on the treatment of gaps in the light curve. Our injection-retrieval experiment shows evidence for moons in about 10% of those light curves that do not contain an injected moon. Strikingly, many of these false-positive moons resemble the exomoon candidate. We recover up to about half of the injected moons, depending on the detrending method, with radii and orbital distances broadly corresponding to the injected values. A $Delta$BIC of -4.9 for the CoFiAM-based detrending indicates an exomoon around Kepler-1625b. This solution, however, is only one out of many and we find very different solutions depending on the details of the detrending method. It is worrying that the detrending is key to the interpretation of the data.
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