Global Erratum for Kepler Q0-Q17 and K2 C0-C5 Short Cadence Data

An accounting error has scrambled much of the short-cadence collateral smear data used to correct for the effects of Keplers shutterless readout. This error has been present since launch and affects approximately half of all short-cadence targets observed by Kepler and K2 to date. The resulting calibration errors are present in both the short-cadence target pixel files and the short-cadence light curves for Kepler Data Releases 1-24 and K2 Data Releases 1-7. This error does not affect long-cadence data. Since it will take some time to correct this error and reprocess all Kepler and K2 data, a list of affected targets is provided. Even though the affected targets are readily identified, the science impact for any particular target may be difficult to assess. Since the smear signal is often small compared to the target signal, the effect is negligible for many targets. However, the smear signal is scene-dependent, so time varying signals can be introduced into any target by the other stars falling on the same CCD column. Some tips on how to assess the severity of the calibration error are provided in this document

Kepler Archive Manual

A description of Kepler, its design, performance and operational constraints may be found in the Kepler Instrument Handbook (KIH, Van Cleve Caldwell 2016). A description of Kepler calibration and data processing is described in the Kepler Data Processing Handbook (KDPH, Jenkins et al. 2016; Fanelli et al. 2011). Science users should also consult the special ApJ Letters devoted to early Kepler results and mission design (April 2010, ApJL, Vol. 713 L79-L207). Additional technical details regarding the data processing and data qualities can be found in the Kepler Data Characteristics Handbook (KDCH, Christiansen et al. 2013) and the Data Release Notes (DRN). This archive manual specifically documents the file formats, as they exist for the last data release of Kepler, Data Release 25(KSCI-19065-002). The earlier versions of the archive manual and data release notes act as documentation for the earlier versions of the data files

Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction

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 a

Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves

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 a

Planetary Candidates Observed by Kepler. VIII. A Fully Automated Catalog with Measured Completeness and Reliability Based on Data Release 25

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

Detection of Potential Transit Signals in the First Three Quarters of Kepler Mission Data

We present the results of a search for potential transit signals in the first three quarters of photometry data acquired by the Kepler Mission. The targets of the search include 151,722 stars which were observed over the full interval and an additional 19,132 stars which were observed for only 1 or 2 quarters. From this set of targets we find a total of 5,392 detections which meet the Kepler detection criteria: those criteria are periodicity of the signal, an acceptable signal-to-noise ratio, and a composition test which rejects spurious detections which contain non-physical combinations of events. The detected signals are dominated by events with relatively low signal-to-noise ratio and by events with relatively short periods. The distribution of estimated transit depths appears to peak in the range between 40 and 100 parts per million, with a few detections down to fewer than 10 parts per million. The detected signals are compared to a set of known transit events in the Kepler field of view which were derived by a different method using a longer data interval; the comparison shows that the current search correctly identified 88.1% of the known events. A tabulation of the detected transit signals, examples which illustrate the analysis and detection process, a discussion of future plans and open, potentially fruitful, areas of further research are included

Strong Water Absorption in the Dayside Emission Spectrum of the Planet HD 189733b

Recent observations of the extrasolar planet HD 189733b did not reveal the presence of water in the emission spectrum of the planet. Yet models of such 'Hot Jupiter' planets predict an abundance of atmospheric water vapour. Validating and constraining these models is crucial for understanding the physics and chemistry of planetary atmospheres in extreme environments. Indications of the presence of water in the atmosphere of HD 189733b have recently been found in transmission spectra, where the planet's atmosphere selectively absorbs the light of the parent star, and in broadband photometry. Here we report on the detection of strong water absorption in a high signal-to-noise, mid-infrared emission spectrum of the planet itself. We find both a strong downturn in the flux ratio below 10 microns and discrete spectral features that are characteristic of strong absorption by water vapour. The differences between these and previous observations are significant and admit the possibility that predicted planetary-scale dynamical weather structures might alter the emission spectrum over time. Models that match the observed spectrum and the broadband photometry suggest that heat distribution from the dayside to the night side is weak. Reconciling this with the high night side temperature will require a better understanding of atmospheric circulation or possible additional energy sources.Comment: 11 pages, 1 figure, published in Natur