The size of a planet is an observable property directly connected to the physics of its formation and evolution. We used precise radius measurements from the California-Kepler Survey to study the size distribution of 2025 Kepler planets in fine detail. We detect a factor of ≥2 deficit in the occurrence rate distribution at 1.5–2.0 R⊕. This gap splits the population of close-in (P < 100 days) small planets into two size regimes: R_p < 1.5 R⊕ and R_p = 2.0-3.0 R⊕, with few planets in between. Planets in these two regimes have nearly the same intrinsic frequency based on occurrence measurements that account for planet detection efficiencies. The paucity of planets between 1.5 and 2.0 R⊕ supports the emerging picture that close-in planets smaller than Neptune are composed of rocky cores measuring 1.5 R⊕ or smaller with varying amounts of low-density gas that determine their total sizes.

/pdf/the-california-kepler-survey-iii-a-gap-in-the-radius-4a0vsnybgl.pdf

The California-Kepler Survey. III. A Gap in the Radius Distribution of Small Planets*

The size of a planet is an observable property directly connected to the physics of its formation and evolution. We used precise radius measurements from the California-Kepler Survey (CKS) to study the size distribution of 2025 $\textit{Kepler}$ planets in fine detail. We detect a factor of $\geq$2 deficit in the occurrence rate distribution at 1.5-2.0 R$_{\oplus}$. This gap splits the population of close-in ($P$ < 100 d) small planets into two size regimes: R$_P$ < 1.5 R$_{\oplus}$ and R$_P$ = 2.0-3.0 R$_{\oplus}$, with few planets in between. Planets in these two regimes have nearly the same intrinsic frequency based on occurrence measurements that account for planet detection efficiencies. The paucity of planets between 1.5 and 2.0 R$_{\oplus}$ supports the emerging picture that close-in planets smaller than Neptune are composed of rocky cores measuring 1.5 R$_{\oplus}$ or smaller with varying amounts of low-density gas that determine their total sizes.

/pdf/the-california-kepler-survey-iii-a-gap-in-the-radius-38r05w0tfd.pdf

The California-Kepler Survey. III. A Gap in the Radius Distribution of Small Planets

The primary Kepler Mission provided nearly continuous monitoring of ~200,000 objects with unprecedented photometric precision. We present the final catalog of eclipsing binary systems within the 105 deg^2 Kepler field of view. This release incorporates the full extent of the data from the primary mission (Q0-Q17 Data Release). As a result, new systems have been added, additional false positives have been removed, ephemerides and principal parameters have been recomputed, classifications have been revised to rely on analytical models, and eclipse timing variations have been computed for each system. We identify several classes of systems including those that exhibit tertiary eclipse events, systems that show clear evidence of additional bodies, heartbeat systems, systems with changing eclipse depths, and systems exhibiting only one eclipse event over the duration of the mission. We have updated the period and galactic latitude distribution diagrams and included a catalog completeness evaluation. The total number of identified eclipsing and ellipsoidal binary systems in the Kepler field of view has increased to 2878, 1.3% of all observed Kepler targets. An online version of this catalog with downloadable content and visualization tools is maintained athttp://keplerEBs.villanova.edu.

/pdf/kepler-eclipsing-binary-stars-vii-the-catalog-of-eclipsing-2rda51hhym.pdf

Kepler eclipsing binary stars. vii. the catalog of eclipsing binaries found in the entire kepler data set

We present the Kepler Object of Interest (KOI) catalog of transiting exoplanets based on searching 4 yr of Kepler time series photometry (Data Release 25, Q1–Q17). The catalog contains 8054 KOIs, of which 4034 are planet candidates with periods between 0.25 and 632 days. Of these candidates, 219 are new, including two in multiplanet systems (KOI-82.06 and KOI-2926.05) and 10 high-reliability, terrestrial-size, habitable zone candidates. This catalog was created using a tool called the Robovetter, which automatically vets the DR25 threshold crossing events (TCEs). The Robovetter also vetted simulated data sets and measured how well it was able to separate TCEs caused by noise from those caused by low signal-to-noise transits. We discuss the Robovetter and the metrics it uses to sort TCEs. For orbital periods less than 100 days the Robovetter completeness (the fraction of simulated transits that are determined to be planet candidates) across all observed stars is greater than 85%. For the same period range, the catalog reliability (the fraction of candidates that are not due to instrumental or stellar noise) is greater than 98%. However, for low signal-to-noise candidates between 200 and 500 days around FGK-dwarf stars, the Robovetter is 76.7% complete and the catalog is 50.5% reliable. The KOI catalog, the transit fits, and all of the simulated data used to characterize this catalog are available at the NASA Exoplanet Archive.

/pdf/planetary-candidates-observed-by-kepler-viii-a-fully-250hfwk842.pdf

PLANETARY CANDIDATES OBSERVED BY Kepler. VIII. A FULLY AUTOMATED CATALOG WITH MEASURED COMPLETENESS AND RELIABILITY BASED ON DATA RELEASE 25.

NASA's Kepler Space Telescope was designed to determine the frequency of Earth-sized planets orbiting Sun-like stars, but these planets are on the very edge of the mission's detection sensitivity. Accurately determining the occurrence rate of these planets will require automatically and accurately assessing the likelihood that individual candidates are indeed planets, even at low signal-to-noise ratios. We present a method for classifying potential planet signals using deep learning, a class of machine learning algorithms that have recently become state-of-the-art in a wide variety of tasks. We train a deep convolutional neural network to predict whether a given signal is a transiting exoplanet or a false positive caused by astrophysical or instrumental phenomena. Our model is highly effective at ranking individual candidates by the likelihood that they are indeed planets: 98.8% of the time it ranks plausible planet signals higher than false positive signals in our test set. We apply our model to a new set of candidate signals that we identified in a search of known Kepler multi-planet systems. We statistically validate two new planets that are identified with high confidence by our model. One of these planets is part of a five-planet resonant chain around Kepler-80, with an orbital period closely matching the prediction by three-body Laplace relations. The other planet orbits Kepler-90, a star which was previously known to host seven transiting planets. Our discovery of an eighth planet brings Kepler-90 into a tie with our Sun as the star known to host the most planets.

pdf/identifying-exoplanets-with-deep-learning-a-five-planet-1mwix5ayux.pdf

Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90

We provide updates to the Kepler planet candidate sample based upon nearly two years of high-precision photometry (i.e., Q1-Q8). From an initial list of nearly 13,400 threshold crossing events, 480 new host stars are identified from their flux time series as consistent with hosting transiting planets. Potential transit signals are subjected to further analysis using the pixel-level data, which allows background eclipsing binaries to be identified through small image position shifts during transit. We also re-evaluate Kepler Objects of Interest (KOIs) 1-1609, which were identified early in the mission, using substantially more data to test for background false positives and to find additional multiple systems. Combining the new and previous KOI samples, we provide updated parameters for 2738 Kepler planet candidates distributed across 2017 host stars. From the combined Kepler planet candidates, 472 are new from the Q1-Q8 data examined in this study. The new Kepler planet candidates represent ~40% of the sample with R P ~ 1 R ? and represent ~40% of the low equilibrium temperature (T eq < 300?K) sample. We review the known biases in the current sample of Kepler planet candidates relevant to evaluating planet population statistics with the current Kepler planet candidate sample.

/pdf/planetary-candidates-observed-by-kepler-vi-planet-sample-1z00jfd7z4.pdf

Planetary Candidates Observed By Kepler. Vi. Planet Sample from Q1-Q16 (47 Months)

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Planetary Candidates Observed By Kepler. Vi. Planet Sample from Q1-Q16 (47 Months)