Search

About one out of 200 Sun-like stars has a planet with an orbital period shorter than one day: an ultra-short-period planet (Sanchis-ojeda et al. 2014; Winn et al. 2018). All of the previously known ultra-short-period planets are either hot Jupiters, with sizes above 10 Earth radii (Re), or apparently rocky planets smaller than 2 Re. Such lack of planets of intermediate size (the "hot Neptune desert") has been interpreted as the inability of low-mass planets to retain any hydrogen/helium (H/He) envelope in the face of strong stellar irradiation. Here, we report the discovery of an ultra-short-period planet with a radius of 4.6 Re and a mass of 29 Me, firmly in the hot Neptune desert. Data from the Transiting Exoplanet Survey Satellite (Ricker et al. 2015) revealed transits of the bright Sun-like star \starname\, every 0.79 days. The planet's mean density is similar to that of Neptune, and according to thermal evolution models, it has a H/He-rich envelope constituting 9.0^(+2.7)_(-2.9)% of the total mass. With an equilibrium temperature around 2000 K, it is unclear how this "ultra-hot Neptune" managed to retain such an envelope. Follow-up observations of the planet's atmosphere to better understand its origin and physical nature will be facilitated by the star's brightness (Vmag=9.8)., Comment: 26 pages, 10 figures, 3 tables. Published in Nature Astronomy (21/09/2020)

We present the discovery of TOI-197.01, the first transiting planet identified by the Transiting Exoplanet Survey Satellite (TESS) for which asteroseismology of the host star is possible. TOI-197 (HIP116158) is a bright (V=8.2 mag), spectroscopically classified subgiant which oscillates with an average frequency of about 430 muHz and displays a clear signature of mixed modes. The oscillation amplitude confirms that the redder TESS bandpass compared to Kepler has a small effect on the oscillations, supporting the expected yield of thousands of solar-like oscillators with TESS 2-minute cadence observations. Asteroseismic modeling yields a robust determination of the host star radius (2.943+/-0.064 Rsun), mass (1.212 +/- 0.074 Msun) and age (4.9+/-1.1 Gyr), and demonstrates that it has just started ascending the red-giant branch. Combining asteroseismology with transit modeling and radial-velocity observations, we show that the planet is a "hot Saturn" (9.17+/-0.33 Rearth) with an orbital period of ~14.3 days, irradiance of 343+/-24 Fearth, moderate mass (60.5 +/- 5.7 Mearth) and density (0.431+/-0.062 gcc). The properties of TOI-197.01 show that the host-star metallicity - planet mass correlation found in sub-Saturns (4-8 Rearth) does not extend to larger radii, indicating that planets in the transition between sub-Saturns and Jupiters follow a relatively narrow range of densities. With a density measured to ~15%, TOI-197.01 is one of the best characterized Saturn-sized planets to date, augmenting the small number of known transiting planets around evolved stars and demonstrating the power of TESS to characterize exoplanets and their host stars using asteroseismology., Comment: 12 pages (excluding author list and references), 9 figures, 4 tables, accepted for publication in AJ. An electronic version of Table 3 is available as an ancillary file (sidebar on the right)

The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for ~200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the TESS Mission which will commence in 2018., Comment: 84 pages, 26 figures, 2 tables. Accepted for publication in PASP on 9 March 2018. Published in PASP on 24 April 2018

We present results of the final Kepler Data Processing Pipeline search for transiting planet signals in the full 17-quarter primary mission data set. The search includes a total of 198,709 stellar targets, of which 112,046 were observed in all 17 quarters and 86,663 in fewer than 17 quarters. We report on 17,230 targets for which at least one transit signature is identified that meets the specified detection criteria: periodicity, minimum of three observed transit events, detection statistic (i.e., signal-to-noise ratio) in excess of the search threshold, and passing grade on three statistical transit consistency tests. Light curves for which a transit signal is identified are iteratively searched for additional signatures after a limb-darkened transiting planet model is fitted to the data and transit events are removed. The search for additional planets adds 16,802 transit signals for a total of 34,032; this far exceeds the number of transit signatures identified in prior pipeline runs. There was a strategic emphasis on completeness over reliability for the final Kepler transit search. A comparison of the transit signals against a set of 3402 well-established, high-quality Kepler Objects of Interest yields a recovery rate of 99.8%. The high recovery rate must be weighed against a large number of false-alarm detections. We examine characteristics of the planet population implied by the transiting planet model fits with an emphasis on detections that would represent small planets orbiting in the habitable zone of their host stars., Comment: 60 pages, 20 figures, 3 tables. Submitted to AAS Journals on 4/19/16. Resubmitted following referee report on 6/23/16. Accepted for publication in AJ on 6/30/16. Published in AJ on 11/11/16

The Kepler mission discovered 2842 exoplanet candidates with 2 years of data. We provide updates to the Kepler planet candidate sample based upon 3 years (Q1-Q12) of data. Through a series of tests to exclude false-positives, primarily caused by eclipsing binary stars and instrumental systematics, 855 additional planetary candidates have been discovered, bringing the total number known to 3697. We provide revised transit parameters and accompanying posterior distributions based on a Markov Chain Monte Carlo algorithm for the cumulative catalogue of Kepler Objects of Interest. There are now 130 candidates in the cumulative catalogue that receive less than twice the flux the Earth receives and more than 1100 have a radius less than 1.5 Rearth. There are now a dozen candidates meeting both criteria, roughly doubling the number of candidate Earth analogs. A majority of planetary candidates have a high probability of being bonafide planets, however, there are populations of likely false-positives. We discuss and suggest additional cuts that can be easily applied to the catalogue to produce a set of planetary candidates with good fidelity. The full catalogue is publicly available at the NASA Exoplanet Archive., Comment: Accepted for publication, ApJS

We present the results of a search for potential transit signals in the full 17-quarter data set collected during Kepler's primary mission that ended on May 11, 2013, due to the on-board failure of a second reaction wheel needed to maintain high precision, fixed, pointing. The search includes a total of 198,646 targets, of which 112,001 were observed in every quarter and 86,645 were observed in a subset of the 17 quarters. We find a total of 12,669 targets that contain at least one signal that meets our detection criteria: periodicity of the signal, a minimum of three transit events, an acceptable signal-to-noise ratio, and four consistency tests that suppress false positives. Each target containing at least one transit-like pulse sequence is searched repeatedly for other signals that meet the detection criteria, indicating a multiple planet system. This multiple planet search adds an additional 7,698 transit-like signatures for a total of 20,367. Comparison of this set of detected signals with a set of known and vetted transiting planet signatures in the Kepler field of view shows that the recovery rate of the search is 90.3%. We review ensemble properties of the detected signals and present various metrics useful in validating these potential planetary signals. We highlight previously undetected planetary candidates, including several small potential planets in the habitable zone of their host stars.

We present an investigation of twelve candidate transiting planets from Kepler with orbital periods ranging from 34 to 207 days, selected from initial indications that they are small and potentially in the habitable zone (HZ) of their parent stars. Few of these objects are known. The expected Doppler signals are too small to confirm them by demonstrating that their masses are in the planetary regime. Here we verify their planetary nature by validating them statistically using the BLENDER technique, which simulates large numbers of false positives and compares the resulting light curves with the Kepler photometry. This analysis was supplemented with new follow-up observations (high-resolution optical and near-infrared spectroscopy, adaptive optics imaging, and speckle interferometry), as well as an analysis of the flux centroids. For eleven of them (KOI-0571.05, 1422.04, 1422.05, 2529.02, 3255.01, 3284.01, 4005.01, 4087.01, 4622.01, 4742.01, and 4745.01) we show that the likelihood they are true planets is far greater than that of a false positive, to a confidence level of 99.73% (3 sigma) or higher. For KOI-4427.01 the confidence level is about 99.2% (2.6 sigma). With our accurate characterization of the GKM host stars, the derived planetary radii range from 1.1 to 2.7 R_Earth. All twelve objects are confirmed to be in the HZ, and nine are small enough to be rocky. Excluding three of them that have been previously validated by others, our study doubles the number of known rocky planets in the HZ. KOI-3284.01 (Kepler-438b) and KOI-4742.01 (Kepler-442b) are the planets most similar to the Earth discovered to date when considering their size and incident flux jointly., Comment: 27 pages in emulateapj format, including tables and figures. To appear in The Astrophysical Journal

In the first three years of operation the Kepler mission found 3,697 planet candidates from a set of 18,406 transit-like features detected on over 200,000 distinct stars. Vetting candidate signals manually by inspecting light curves and other diagnostic information is a labor intensive effort. Additionally, this classification methodology does not yield any information about the quality of planet candidates; all candidates are as credible as any other candidate. The torrent of exoplanet discoveries will continue after Kepler as there will be a number of exoplanet surveys that have an even broader search area. This paper presents the application of machine-learning techniques to the classification of exoplanet transit-like signals present in the \Kepler light curve data. Transit-like detections are transformed into a uniform set of real-numbered attributes, the most important of which are described in this paper. Each of the known transit-like detections is assigned a class of planet candidate; astrophysical false positive; or systematic, instrumental noise. We use a random forest algorithm to learn the mapping from attributes to classes on this training set. The random forest algorithm has been used previously to classify variable stars; this is the first time it has been used for exoplanet classification. We are able to achieve an overall error rate of 5.85% and an error rate for classifying exoplanets candidates of 2.81%., Comment: 14 pages, 10 figures

We present the results of a search for potential transit signals in four years of photometry data acquired by the Kepler Mission. The targets of the search include 111,800 stars which were observed for the entire interval and 85,522 stars which were observed for a subset of the interval. We found that 9,743 targets contained at least one signal consistent with the signature of a transiting or eclipsing object, where the criteria for detection are periodicity of the detected transits, adequate signal-to-noise ratio, and acceptance by a number of tests which reject false positive detections. When targets that had produced a signal were searched repeatedly, an additional 6,542 signals were detected on 3,223 target stars, for a total of 16,285 potential detections. Comparison of the set of detected signals with a set of known and vetted transit events in the Kepler field of view shows that the recovery rate for these signals is 96.9%. The ensemble properties of the detected signals are reviewed., Comment: Accepted by ApJ Supplement

We present the results of a search for potential transit signals in the first three years of photometry data acquired by the Kepler Mission. The targets of the search include 112,321 targets which were observed over the full interval and an additional 79,992 targets which were observed for a subset of the full interval. From this set of targets we find a total of 11,087 targets which contain at least one signal which meets the Kepler detection criteria: those criteria are periodicity of the signal, an acceptable signal-to-noise ratio, and three tests which reject false positives. Each target containing at least one detected signal is then searched repeatedly for additional signals, which represent multi-planet systems of transiting planets. When targets with multiple detections are considered, a total of 18,406 potential transiting planet signals are found in the Kepler Mission dataset. The detected signals are dominated by events with relatively low signal-to-noise ratios and by events with relatively short periods. The distribution of estimated transit depths appears to peak in the range between 20 and 30 parts per million, with a few detections down to fewer than 10 parts per million. The detections exhibit signal-to-noise ratios from 7.1 sigma, which is the lower cut-off for detections, to over 10,000 sigma, and periods ranging from 0.5 days, which is the shortest period searched, to 525 days, which is the upper limit of achievable periods given the length of the data set and the requirement that all detections include at least 3 transits. The detected signals are compared to a set of known transit events in the Kepler field of view, many of which were identified by alternative methods; the comparison shows that the current search recovery rate for targets with known transit events is 98.3%., Comment: 29 pages, 14 figures, accepted for publication in ApJ Supp

Kepler provides light curves of 156,000 stars with unprecedented precision. However, the raw data as they come from the spacecraft contain significant systematic and stochastic errors. These errors, which include discontinuities, systematic trends, and outliers, obscure the astrophysical signals in the light curves. To correct these errors is the task of the Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline. The original version of PDC in Kepler did not meet the extremely high performance requirements for the detection of miniscule planet transits or highly accurate analysis of stellar activity and rotation. One particular deficiency was that astrophysical features were often removed as a side-effect to removal of errors. In this paper we introduce the completely new and significantly improved version of PDC which was implemented in Kepler SOC 8.0. This new PDC version, which utilizes a Bayesian approach for removal of systematics, reliably corrects errors in the light curves while at the same time preserving planet transits and other astrophysically interesting signals. We describe the architecture and the algorithms of this new PDC module, show typical errors encountered in Kepler data, and illustrate the corrections using real light curve examples., Comment: Submitted to PASP. Also see companion paper "Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction" by Jeff C. Smith et al

With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of "reasonable" robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves., Comment: 43 pages, 21 figures, Submitted for publication in PASP. Also see companion paper "Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves" by Martin C. Stumpe, et al

We present a new method for confirming transiting planets based on the combination of transit timingn variations (TTVs) and dynamical stability. Correlated TTVs provide evidence that the pair of bodies are in the same physical system. Orbital stability provides upper limits for the masses of the transiting companions that are in the planetary regime. This paper describes a non-parametric technique for quantifying the statistical significance of TTVs based on the correlation of two TTV data sets. We apply this method to an analysis of the transit timing variations of two stars with multiple transiting planet candidates identified by Kepler. We confirm four transiting planets in two multiple planet systems based on their TTVs and the constraints imposed by dynamical stability. An additional three candidates in these same systems are not confirmed as planets, but are likely to be validated as real planets once further observations and analyses are possible. If all were confirmed, these systems would be near 4:6:9 and 2:4:6:9 period commensurabilities. Our results demonstrate that TTVs provide a powerful tool for confirming transiting planets, including low-mass planets and planets around faint stars for which Doppler follow-up is not practical with existing facilities. Continued Kepler observations will dramatically improve the constraints on the planet masses and orbits and provide sensitivity for detecting additional non-transiting planets. If Kepler observations were extended to eight years, then a similar analysis could likely confirm systems with multiple closely spaced, small transiting planets in or near the habitable zone of solar-type stars., Comment: 23 pages, 8 figures, 4 tables, 1 electronic table, accepted to ApJ

We present a method to confirm the planetary nature of objects in systems with multiple transiting exoplanet candidates. This method involves a Fourier-Domain analysis of the deviations in the transit times from a constant period that result from dynamical interactions within the system. The combination of observed anti-correlations in the transit times and mass constraints from dynamical stability allow us to claim the discovery of four planetary systems Kepler-25, Kepler-26, Kepler-27, and Kepler-28, containing eight planets and one additional planet candidate., Comment: Accepted to MNRAS

Eighty planetary systems of two or more planets are known to orbit stars other than the Sun. For most, the data can be sufficiently explained by non-interacting Keplerian orbits, so the dynamical interactions of these systems have not been observed. Here we present 4 sets of lightcurves from the Kepler spacecraft, which each show multiple planets transiting the same star. Departure of the timing of these transits from strict periodicity indicates the planets are perturbing each other: the observed timing variations match the forcing frequency of the other planet. This confirms that these objects are in the same system. Next we limit their masses to the planetary regime by requiring the system remain stable for astronomical timescales. Finally, we report dynamical fits to the transit times, yielding possible values for the planets' masses and eccentricities. As the timespan of timing data increases, dynamical fits may allow detailed constraints on the systems' architectures, even in cases for which high-precision Doppler follow-up is impractical., Comment: In the proofs process, corrections were made to tables -- most crucially, the timing data for Kepler-30b and the depths and radii of planets in Kepler-31 and 32

We report the detection of a planet whose orbit surrounds a pair of low-mass stars. Data from the Kepler spacecraft reveal transits of the planet across both stars, in addition to the mutual eclipses of the stars, giving precise constraints on the absolute dimensions of all three bodies. The planet is comparable to Saturn in mass and size, and is on a nearly circular 229-day orbit around its two parent stars. The eclipsing stars are 20% and 69% as massive as the sun, and have an eccentric 41-day orbit. The motions of all three bodies are confined to within 0.5 degree of a single plane, suggesting that the planet formed within a circumbinary disk., Comment: Science, in press; for supplemental material see http://www.sciencemag.org/content/suppl/2011/09/14/333.6049.1602.DC1/1210923.Doyle.SOM.pdf

We present the discovery of the Kepler-19 planetary system, which we first identified from a 9.3-day periodic transit signal in the Kepler photometry. From high-resolution spectroscopy of the star, we find a stellar effective temperature Teff=5541 \pm 60 K, a metallicity [Fe/H]=-0.13 \pm 0.06, and a surface gravity log(g)=4.59 \pm 0.10. We combine the estimate of Teff and [Fe/H] with an estimate of the stellar density derived from the photometric light curve to deduce a stellar mass of M_star = 0.936 \pm 0.040 M_Sun and a stellar radius of R_star = 0.850 \pm 0.018 R_Sun. We rule out the possibility that the transits result from an astrophysical false positive by first identifying the subset of stellar blends that reproduce the precise shape of the light curve. We conclude that the planetary scenario is more than three orders of magnitude more likely than a blend. The blend scenario is independently disfavored by the achromaticity of the transit: we measure a transit depth with Spitzer at 4.5 {\mu}m of 547+113-110 ppm, consistent with the depth measured in the Kepler optical bandpass of 567\pm6 ppm. We determine a physical radius of the planet Kepler-19b of R_p = 2.209 \pm 0.048 R_Earth. From radial-velocity observations of the star, we find an upper limit on the planet mass of 20.3 M_Earth, corresponding to a maximum density of 10.4 g cm^-3. We report a significant sinusoidal deviation of the transit times from a predicted linear ephemeris, which we conclude is due to an additional perturbing body in the system. We cannot uniquely determine the orbital parameters of the perturber, as various dynamical mechanisms match the amplitude, period, and shape of the transit timing signal and satisfy the host star's radial velocity limits. However, the perturber in these mechanisms has period <160 days and mass <6 M_Jup, confirming its planetary nature as Kepler-19c. [Abridged], Comment: 50 pages, 15 figures, accepted for publication in ApJ

The architectures of multiple planet systems can provide valuable constraints on models of planet formation, including orbital migration, and excitation of orbital eccentricities and inclinations. NASA's Kepler mission has identified 1235 transiting planet candidates (Borcuki et al 2011). The method of transit timing variations (TTVs) has already confirmed 7 planets in two planetary systems (Holman et al. 2010; Lissauer et al. 2011a). We perform a transit timing analysis of the Kepler planet candidates. We find that at least ~12% of planet candidates currently suitable for TTV analysis show evidence suggestive of TTVs, representing at least ~65 TTV candidates. In all cases, the time span of observations must increase for TTVs to provide strong constraints on planet masses and/or orbits, as expected based on n-body integrations of multiple transiting planet candidate systems (assuming circular and coplanar orbits). We find that the fraction of planet candidates showing TTVs in this data set does not vary significantly with the number of transiting planet candidates per star, suggesting significant mutual inclinations and that many stars with a single transiting planet should host additional non-transiting planets. We anticipate that Kepler could confirm (or reject) at least ~12 systems with multiple transiting planet candidates via TTVs. Thus, TTVs will provide a powerful tool for confirming transiting planets and characterizing the orbital dynamics of low-mass planets. If Kepler observations were extended to at least six years, then TTVs would provide much more precise constraints on the dynamics of systems with multiple transiting planets and would become sensitive to planets with orbital periods extending into the habitable zone of solar-type stars., Comment: accepted to ApJS, to appear in Kepler special issue; 35 pages incl. 6 figures & 6 tables, excl. 48 pages w/ 4 electronic only tables & 26 pages with additional figures; Additional large electronic only table at http://astro.ufl.edu/~eford/data/kepler/

When an extrasolar planet passes in front of its star (transits), its radius can be measured from the decrease in starlight and its orbital period from the time between transits. Multiple planets transiting the same star reveal more: period ratios determine stability and dynamics, mutual gravitational interactions reflect planet masses and orbital shapes, and the fraction of transiting planets observed as multiples has implications for the planarity of planetary systems. But few stars have more than one known transiting planet, and none has more than three. Here we report Kepler spacecraft observations of a single Sun-like star that reveal six transiting planets, five with orbital periods between 10 and 47 days plus a sixth one with a longer period. The five inner planets are among the smallest whose masses and sizes have both been measured, and these measurements imply substantial envelopes of light gases. The degree of coplanarity and proximity of the planetary orbits imply energy dissipation near the end of planet formation., Comment: published in Nature

We report the discovery and the Rossiter-McLaughlin effect of Kepler-8b, a transiting planet identified by the NASA Kepler Mission. Kepler photometry and Keck-HIRES radial velocities yield the radius and mass of the planet around this F8IV subgiant host star. The planet has a radius RP = 1.419 RJ and a mass, MP = 0.60 MJ, yielding a density of 0.26 g cm^-3, among the lowest density planets known. The orbital period is P = 3.523 days and orbital semima jor axis is 0.0483+0.0006/-0.0012 AU. The star has a large rotational v sin i of 10.5 +/- 0.7 km s^-1 and is relatively faint (V = 13.89 mag), both properties deleterious to precise Doppler measurements. The velocities are indeed noisy, with scatter of 30 m s^-1, but exhibit a period and phase consistent with the planet implied by the photometry. We securely detect the Rossiter-McLaughlin effect, confirming the planet's existence and establishing its orbit as prograde. We measure an inclination between the projected planetary orbital axis and the projected stellar rotation axis of lambda = -26.9 +/- 4.6 deg, indicating a moderate inclination of the planetary orbit. Rossiter-McLaughlin measurements of a large sample of transiting planets from Kepler will provide a statistically robust measure of the true distribution of spin-orbit orientations for hot jupiters in general., Comment: 26 pages, 8 figures, 2 tables; In preparation for submission to the Astrophysical Journal

The Kepler Mission Science Operations Center (SOC) performs several critical functions including managing the ~156,000 target stars, associated target tables, science data compression tables and parameters, as well as processing the raw photometric data downlinked from the spacecraft each month. The raw data are first calibrated at the pixel level to correct for bias, smear induced by a shutterless readout, and other detector and electronic effects. A background sky flux is estimated from ~4500 pixels on each of the 84 CCD readout channels, and simple aperture photometry is performed on an optimal aperture for each star. Ancillary engineering data and diagnostic information extracted from the science data are used to remove systematic errors in the flux time series that are correlated with these data prior to searching for signatures of transiting planets with a wavelet-based, adaptive matched filter. Stars with signatures exceeding 7.1 sigma are subjected to a suite of statistical tests including an examination of each star's centroid motion to reject false positives caused by background eclipsing binaries. Physical parameters for each planetary candidate are fitted to the transit signature, and signatures of additional transiting planets are sought in the residual light curve. The pipeline is operational, finding planetary signatures and providing robust eliminations of false positives., Comment: 8 pages, 3 figures

The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for approx. 200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018.

We give an overview of the operational concepts and architecture of the Kepler Science Processing Pipeline. Designed, developed, operated, and maintained by the Kepler Science Operations Center (SOC) at NASA Ames Research Center, the Science Processing Pipeline is a central element of the Kepler Ground Data System. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center which hosts the computers required to perform data analysis. The SOC's charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Processing Pipeline, including, the software algorithms. We present the high-performance, parallel computing software modules of the pipeline that perform transit photometry, pixel-level calibration, systematic error correction, attitude determination, stellar target management, and instrument characterization.

The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earth's closest cousins starting in early 2018 and is expected to discover approximately 1,000 small planets with R(sub p) less than 4 (solar radius) and measure the masses of at least 50 of these small worlds. The Science Processing Operations Center (SPOC) is being developed at NASA Ames Research Center based on the Kepler science pipeline and will generate calibrated pixels and light curves on the NASA Advanced Supercomputing Division's Pleiades supercomputer. The SPOC will also search for periodic transit events and generate validation products for the transit-like features in the light curves. All TESS SPOC data products will be archived to the Mikulski Archive for Space Telescopes (MAST).

The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earth’s closest cousins starting in late 2017. TESS will discover approx.1,000 small planets and measure the masses of at least 50 of these small worlds. The Science Processing Operations Center (SPOC) is being developed based on the Kepler science pipeline and will generate calibrated pixels and light curves on the NAS Pleiades supercomputer. The SPOC will search for periodic transit events and generate validation products for the transit-like features in the light curves. All TESS SPOC data products will be archived to the Mikulski Archive for Space Telescopes.

The Kepler Mission simultaneously measures the brightness of more than 160,000 stars every 29.4 minutes over a 3.5-year mission to search for transiting planets. Detecting transits is a signal-detection problem where the signal of interest is a periodic pulse train and the predominant noise source is non-white, non-stationary (1/f) type process of stellar variability. Many stars also exhibit coherent or quasi-coherent oscillations. The detection algorithm first identifies and removes strong oscillations followed by an adaptive, wavelet-based matched filter. We discuss how we obtain super-resolution detection statistics and the effectiveness of the algorithm for Kepler flight data.

The Kepler space telescope is designed to detect Earth-like planets around Sun-like stars using transit photometry by simultaneously observing 100,000 stellar targets nearly continuously over a three and a half year period. The 96-megapixel focal plane consists of 42 charge-coupled devices (CCD) each containing two 1024 x 1100 pixel arrays. Cross-correlations between calibrated pixels are introduced by common calibrations performed on each CCD requiring downstream data products access to the calibrated pixel covariance matrix in order to properly estimate uncertainties. The prohibitively large covariance matrices corresponding to the ~75,000 calibrated pixels per CCD preclude calculating and storing the covariance in standard lock-step fashion. We present a novel framework used to implement standard propagation of uncertainties (POU) in the Kepler Science Operations Center (SOC) data processing pipeline. The POU framework captures the variance of the raw pixel data and the kernel of each subsequent calibration transformation allowing the full covariance matrix of any subset of calibrated pixels to be recalled on-the-fly at any step in the calibration process. Singular value decomposition (SVD) is used to compress and low-pass filter the raw uncertainty data as well as any data dependent kernels. The combination of POU framework and SVD compression provide downstream consumers of the calibrated pixel data access to the full covariance matrix of any subset of the calibrated pixels traceable to pixel level measurement uncertainties without having to store, retrieve and operate on prohibitively large covariance matrices. We describe the POU Framework and SVD compression scheme and its implementation in the Kepler SOC pipeline.

The Kepler mission is designed to continuously monitor up to 170,000 stars at a 30 minute cadence for 3.5 years searching for Earth-size planets. The data are processed at the Science Operations Center (SOC) at NASA Ames Research Center. Because of the large volume of data and the memory and CPU-intensive nature of the analysis, significant computing hardware is required. We have developed generic pipeline framework software that is used to distribute and synchronize the processing across a cluster of CPUs and to manage the resulting products. The framework is written in Java and is therefore platform-independent, and scales from a single, standalone workstation (for development and research on small data sets) to a full cluster of homogeneous or heterogeneous hardware with minimal configuration changes. A plug-in architecture provides customized control of the unit of work without the need to modify the framework itself. Distributed transaction services provide for atomic storage of pipeline products for a unit of work across a relational database and the custom Kepler DB. Generic parameter management and data accountability services are provided to record the parameter values, software versions, and other meta-data used for each pipeline execution. A graphical console allows for the configuration, execution, and monitoring of pipelines. An alert and metrics subsystem is used to monitor the health and performance of the pipeline. The framework was developed for the Kepler project based on Kepler requirements, but the framework itself is generic and could be used for a variety of applications where these features are needed.

We present an overview of the Data Validation (DV) software component and its context within the Kepler Science Operations Center (SOC) pipeline and overall Kepler Science mission. The SOC pipeline performs a transiting planet search on the corrected light curves for over 150,000 targets across the focal plane array. We discuss the DV strategy for automated validation of Threshold Crossing Events (TCEs) generated in the transiting planet search. For each TCE, a transiting planet model is fitted to the target light curve. A multiple planet search is conducted by repeating the transiting planet search on the residual light curve after the model flux has been removed; if an additional detection occurs, a planet model is fitted to the new TCE. A suite of automated tests are performed after all planet candidates have been identified. We describe a centroid motion test to determine the significance of the motion of the target photocenter during transit and to estimate the coordinates of the transit source within the photometric aperture; a series of eclipsing binary discrimination tests on the parameters of the planet model fits to all transits and the sequences of odd and even transits; and a statistical bootstrap to assess the likelihood that the TCE would have been generated purely by chance given the target light curve with all transits removed. Keywords: photometry, data validation, Kepler, Earth-size planets

The Kepler Science Operations Center stores pixel values on approximately six million pixels collected every 30-minutes, as well as data products that are generated as a result of running the Kepler science processing pipeline. The Kepler Database (Kepler DB) management system was created to act as the repository of this information. After one year of ight usage, Kepler DB is managing 3 TiB of data and is expected to grow to over 10 TiB over the course of the mission. Kepler DB is a non-relational, transactional database where data are represented as one dimensional arrays, sparse arrays or binary large objects. We will discuss Kepler DB's APIs, implementation, usage and deployment at the Kepler Science Operations Center.

We give an overview of the operational concepts and architecture of the Kepler Science Data Pipeline. Designed, developed, operated, and maintained by the Science Operations Center (SOC) at NASA Ames Research Center, the Kepler Science Data Pipeline is central element of the Kepler Ground Data System. The SOC charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Data Pipeline, including the hardware infrastructure, scientific algorithms, and operational procedures. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center that hosts the computers required to perform data analysis. We discuss the high-performance, parallel computing software modules of the Kepler Science Data Pipeline that perform transit photometry, pixel-level calibration, systematic error-correction, attitude determination, stellar target management, and instrument characterization. We explain how data processing environments are divided to support operational processing and test needs. We explain the operational timelines for data processing and the data constructs that flow into the Kepler Science Data Pipeline.

The Kepler Science Operations Center (SOC) is responsible for several aspects of the Kepler Mission, including managing targets, generating on-board data compression tables, monitoring photometer health and status, processing the science data, and exporting the pipeline products to the mission archive. We describe how the generic pipeline framework software developed for Kepler is extended to achieve these goals, including pipeline configurations for processing science data and other support roles, and custom unit of work generators that control how the Kepler data are partitioned and distributed across the computing cluster. We describe the interface between the Java software that manages the retrieval and storage of the data for a given unit of work and the MATLAB algorithms that process these data. The data for each unit of work are packaged into a single file that contains everything needed by the science algorithms, allowing these files to be used to debug and evolve the algorithms offline.

The Data Analysis Working Group have released long and short cadence materials, including FFIs and Dropped Targets for the Public. The Kepler Science Office considers Data Release 4 to provide "browse quality" data. These notes have been prepared to give Kepler users of the Multimission Archive at STScl (MAST) a summary of how the data were collected and prepared, and how well the data processing pipeline is functioning on flight data. They will be updated for each release of data to the public archive and placed on MAST along with other Kepler documentation, at http://archive.stsci.edu/kepler/documents.html. Data release 3 is meant to give users the opportunity to examine the data for possibly interesting science and to involve the users in improving the pipeline for future data releases. To perform the latter service, users are encouraged to notice and document artifacts, either in the raw or processed data, and report them to the Science Office.