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Photometer Performance Assessment in Kepler Science Data Processing

This paper describes the algorithms of the Photometer Performance Assessment (PPA) software component in the science data processing pipeline of the Kepler mission. The PPA performs two tasks: One is to analyze the health and performance of the Kepler photometer based on the long cadence science data down-linked via Ka band approximately every 30 days. The second is to determine the attitude of the Kepler spacecraft with high precision at each long cadence. The PPA component is demonstrated to work effectively with the Kepler flight data.

Li, Jie↗

Kepler Science Operations Center Pipeline Framework

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.

Klaus, Todd C.↗

Kepler Mission Development Challenges and Early Results

Kepler is NASA s first mission capable of detecting Earth-size planets orbiting in the habitable zone of stars other than the Sun. Kepler comprises a space telescope designed to continuously monitor the brightnesses of more than 100,000 target stars, and a ground segment to analyze the measured stellar light curves and detect the signatures of orbiting planets. In order to detect Earth-size planets orbiting Sun-like stars Kepler was designed to provide unprecedented photometric sensitivity and stability. This paper addresses some of the technical challenges encountered during the development of the Kepler mission and the measures taken to overcome them. Early scientific results are summarized.

exo-planets↗

Kepler Mission Development Challenges and Early Results

Kepler is NASA`s first mission capable of detecting Earth-size planets orbiting in the habitable zone of stars other than the sun. Kepler comprises a space telescope designed to continuously monitor the brightnesses of more than 100,000 target stars, and a ground segment to analyze the measured stellar light curves and detect the signatures of orbiting planets. In order to detect Earth-size planets orbiting Sun-like stars Kepler was designed to provide unprecedented photometric sensitivity and stability. This paper addresses some of the technical challenges encountered during the development of the Kepler mission and the measures taken to overcome them. Early scientific results are summarized.

habitable zones↗

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.

Caldwell, Douglas↗

Kepler Instrument Performance: An In-Flight Update

The Kepler Mission is designed to detect the 80 parts per million (ppm) signal from an Earth-Sun equivalent transit. Such precision requires superb instrument stability on time scales up to 2 days and systematic error removal to better than 20 ppm. The sole scientic instrument is the Photometer, a 0.95 m aperture Schmidt telescope that feeds the 94.6 million pixel CCD detector array, which contains both Science and Fine Guidance Sensor (FGS) CCDs. Since Kepler's launch in March 2009, we have been using the commissioning and science operations data to characterize the instrument and monitor its performance. We find that the in-flight detector properties of the focal plane, including bias levels, read noise, gain, linearity, saturation, FGS to Science crosstalk,and video crosstalk between Science CCDs, are essentially unchanged from their pre-launch values. Kepler'sunprecedented sensitivity and stability in space have allowed us to measure both short- and long- term effects from cosmic rays, see interactions of previously known image artifacts with starlight, and uncover several unexpected systematics that affect photometric precision. Based on these results, we expect to attain Kepler's planned photometric precision over 90% of the field of view.

CCD↗

Kepler-1649b: An Exo-Venus in the Solar Neighborhood

The Kepler mission has revealed that Earth-sized planets are common, and dozens have been discovered to orbit in or near their host star’s habitable zone. A major focus in astronomy is to determine which of these exoplanets are likely to have Earth-like properties that are amenable to follow-up with both ground- and future space-based surveys, with an ultimate goal of probing their atmospheres to look for signs of life. Venus-like atmospheres will be of particular interest in these surveys. While Earth and Venus evolved to have similar sizes and densities, it remains unclear what factors led to the dramatic divergence of their atmospheres. Studying analogs to both Earth and Venus can thus shed light on the limits of habitability and the potential for life on known exoplanets. Here, we present the discovery and confirmation of Kepler-1649b, an Earth-sized planet orbiting a nearby M5V star that receives incident flux at a level similar to that of Venus. We present our methods for characterizing the star, using a combination of point-spread function photometry, ground-based spectroscopy, and imaging, to confirm the planetary nature of Kepler-1649b. Planets like Kepler-1649b will be prime candidates for atmospheric and habitability studies in the next generation of space missions.

Terrestrial planets↗

Introducing Triquetrum, A Possible Future for Kepler and Ptolemy II

Triquetrum is an open platform for managing and executing scientific workflows that is under development as an Eclipse project. Both Triquetrum and Kepler use Ptolemy II as their execution engine. Triquetrum presents opportunities and risks for the Kepler community. The opportunities include a possibly larger community for interaction and a path for Kepler to move from Kepler's one-off ant-based build environment towards a more common OSGi-based environment and a way to maintain a stable Ptolemy II core. The risks include the fact that Triquetrum is a fork of Ptolemy II that would result in package name changes and other possible changes. In addition, Triquetrum is licensed under the Eclipse Public License v1.0, which includes a patent clause that could conflict with the University of California patent clause. This paper describes these opportunities and risks.

Brooks, Christopher↗

Are We Alone? Kepler on a Quest

Two presentations, a technical and a non-technical with information about the Kepler Mission. Includes graphics on the telescope, how it works, the planets it has found. The technical includes couple of slides on the software pipeline architecture that helps detect the planets using Kepler Data. None of the Kepler graphics are newly created. Except the About Me slide everything else has been borrowed from not one but several different presentations, ones that I deemed helpful to me while doing my talks.

Kepler↗

Highlights of Discoveries for δ Scuti Variable Stars from the Kepler Era

The NASA Kepler and follow-on K2 mission (2009–2018) left a legacy of data and discoveries, finding thousands of exoplanets, and also obtaining high-precision long time-series data for hundreds of thousands of stars, including many types of pulsating variables. Here we highlight a few of the ongoing discoveries from Kepler data on δ Scuti pulsating variables, which are core hydrogen-burning stars of about twice the mass of the Sun. We discuss many unsolved problems surrounding the properties of the variability in these stars, and the progress enabled by Kepler data in using pulsations to infer their interior structure, a field of research known as asteroseismology.

79 ASTRONOMY AND ASTROPHYSICS↗

An Introduction to Exoplanets and the Kepler Mission

A quarter century ago, the only planets known to humanity were the familiar objects that orbit our Sun. But improved observational techniques allowed astronomers to begin detecting planets around other stars in the 1990s. The first extrasolar planets (often referred to as exoplanets) to be discovered were quite exotic and unfamiliar objects. Most were giant objects that are hundreds of times as massive as the Earth and orbit so close to their star that they are hotter than pizza ovens. But as observational capabilities improved, smaller and cooler planets were found. The most capable planet-hunting tool developed to date is NASA's Kepler telescope, which was launched in 2009. Kepler has found that planets similar in size to our Earth are quite abundant within our galaxy. Results of Kepler's research will be summarized and placed into context within the new and growing discipline of exoplanet studies.

Earth-like planets↗

Discovery of a Similar to 5 Day Characteristic Timescale in the Kepler Power Spectrum of Zw 229-15

We present time series analyses of the full Kepler dataset of Zw 229− 15. This Kepler light curve- with a baseline greater than three years, composed of virtually continuous, evenly sampled 30-minute measurements - is unprecedented in its quality and precision. We utilize two methods of power spectral analysis to investigate the optical variability and search for evidence of a bend frequency associated with a characteristic optical variability timescale. Each method yields similar results. The first interpolates across data gaps to use the standard Fourier periodogram. The second, using the CARMA-based time-domain modeling technique of Kelly et al., does not need evenly-sampled data. Both methods find excess power at high frequencies that may be due to Kepler instrumental effects. More importantly both also show strong bends (delta alpha is approx. 2) at timescales of approx. 5 days, a feature similar to those seen in the X-ray PSDs of AGN but never before in the optical. This observed approx. 5 day timescale may be associated with one of several physical processes potentially responsible for the variability. A plausible association could be made with light -crossing, dynamical or thermal timescales, depending on the assumed value of the accretion disk size and on unobserved disk parameters such as alpha and H¬R. This timescale is not consistent with the viscous timescale, which would be years in a approx. 10(exp7) solar mass AGN such as Zw 229− 15. However there must be a second bend on long (& 1 year) timescales, and that feature could be associated with the viscous timescale.

timescale↗

KSWAGS: A Swift X-Ray and UV Survey of the Kepler Field 1

We introduce the first phase of the Kepler-Swift Active Galaxies and Stars survey (KSwAGS), a simultaneous X-ray and UV survey of approximately 6 square degrees of the Kepler field using the Swift XRT and UVOT. We detect 93 unique X-ray sources with S/N greater or equal to 3 with the XRT, of which 60 have UV counterparts. We use the Kepler Input Catalog (KIC) to obtain the optical counterparts of these sources, and construct the fX / fV ratio as a first approximation of the classification of the source. The survey produces a mixture of stellar sources, extragalactic sources, and sources which we are not able to classify with certainty. We have obtained optical spectra for thirty of these targets, and are conducting an ongoing observing campaign to fully identify the sample. For sources classified as stellar or AGN with certainty, we construct SEDs using the 2MASS, UBV and GALEX data supplied for their optical counterparts by the KIC, and show that the SEDs differ qualitatively between the source types, and so can offer a method of classification in absence of a spectrum. Future papers in this series will analyze the timing properties of the stars and AGN in our sample separately. Our survey provides the first X-ray and UV data for a number of known variable stellar sources, as well as a large number of new X-ray detections in this well-studied portion of the sky. The KSwAGS survey is currently ongoing in the K2 ecliptic plane fields.

KSWAGS: A SWIFT X-RAY AND UV SURVEY OF THE KEPLER ↗

Chaos in Kepler's Multiple Planet Systems and K2s Observations of the Atmospheres of Uranus Neptune

More than one-third of the 4700 planet candidates found by NASA's Kepler spacecraft during its prime mission are associated with target stars that have more than one planet candidate, and such "multis" account for the vast majority of candidates that have been verified as true planets. The large number of multis tells us that flat multiplanet systems like our Solar System are common. Virtually all of the candidate planetary systems are stable, as tested by numerical integrations that assume a physically motivated mass-radius relationship, but some of the systems lie in chaotic regions close to instability. The characteristics of some of the most interesting confirmed Kepler multi-planet systems will be discussed. The Kepler spacecraft's 'second life' in theK2 mission has allowed it to obtain long time-series observations of Solar System targets, including the giant planets Uranus & Neptune. These observations show variability caused by the chaotic weather patterns on Uranus & Neptune.

planet candidates↗

Kepler Fine Guidance Sensor Data

The Kepler and K2 missions collected Fine Guidance Sensor (FGS) data in addition to the science data, as discussed in the Kepler Instrument Handbook (KIH, Van Cleve and Caldwell 2016). The FGS CCDs are frame transfer devices (KIH Table 7) located in the corners of the Kepler focal plane (KIH Figure 24), which are read out 10 times every second. The FGS data are being made available to the user community for scientific analysis as flux and centroid time series, along with a limited number of FGS full frame images which may be useful for constructing a World Coordinate System (WCS) or otherwise putting the time series data in context. This document will describe the data content and file format, and give example MATLAB scripts to read the time series. There are three file types delivered as the FGS data.1. Flux and Centroid (FLC) data: time series of star signal and centroid data. 2. Ancillary FGS Reference (AFR) data: catalog of information about the observed stars in the FLC data. 3. FGS Full-Frame Image (FGI) data: full-frame image snapshots of the FGS CCDs.

Kepler↗

Pixel-Level Calibration in the Kepler Science Operations Center Pipeline

We present an overview of the pixel-level calibration of flight data from the Kepler Mission performed within the Kepler Science Operations Center Science Processing Pipeline. This article describes the calibration (CAL) module, which operates on original spacecraft data to remove instrument effects and other artifacts that pollute the data. Traditional CCD data reduction is performed (removal of instrument/detector effects such as bias and dark current), in addition to pixel-level calibration (correcting for cosmic rays and variations in pixel sensitivity), Kepler-specific corrections (removing smear signals which result from the lack of a shutter on the photometer and correcting for distortions induced by the readout electronics), and additional operations that are needed due to the complexity and large volume of flight data. CAL operates on long (~30 min) and short (~1 min) sampled data, as well as full-frame images, and produces calibrated pixel flux time series, uncertainties, and other metrics that are used in subsequent Pipeline modules. The raw and calibrated data are also archived in the Multi-mission Archive at Space Telescope at the Space Telescope Science Institute for use by the astronomical community.

Calibration↗

Kepler Data Validation II–Transit Model Fitting and Multiple-Planet Search

This paper discusses the transit model-fitting and multiple-planet search algorithms and performance of the Kepler Science Data Processing Pipeline, developed by the Kepler Science Operations Center (SOC). Threshold crossing events (TCEs), which are transit candidate events, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the data validation (DV) component. The transit model is used in DV to fit TCEs to characterize planetary candidates and to derive parameters that are used in various diagnostic tests to classify them. After the signature associated with the TCE is removed from the light curve of the target star, the residual light curve goes through TPS again to search for additional TCEs. The iterative process of transit model fitting and multiple-planet search continues until no TCE is generated from the residual light curve or an upper limit is reached. The transit model-fitting and multiple-planet search performance of the final release (9.3, 2016January) of the pipeline is demonstrated with the results of the processing of four years (17 quarters) of flight data from the primary Kepler Mission. The transit model-fitting results are accessible from the NASA Exoplanet Archive. The final version of the SOC codebase is available through GitHub.

Threshold crossing events (TCEs↗

Focal Plane Geometry Characterization of the Kepler Mission

The Kepler Mission focal plane contains 42 charge-coupled device (CCD) photodetectors. Each CCD is composed of 2.2 million square pixels, 27 micrometers on a side, arranged in a grid of 2,200 columns by 1,044 rows. The science goals of the Kepler Mission require that the position of each CCD be determined with an accuracy of 0.1 pixels, corresponding to 2.7 micrometers or 0.4 seconds of arc, a level which is not achievable through pre-flight metrology. We describe a technique for determining the CCD positioning using images of the Kepler field of view (FOV) obtained in flight. The technique uses the fitted centroid row and column positions of 400 pre-selected stars on each CCD to obtain empirical polynomials which relate sky coordinates (right ascension and declination) to chip coordinates (row and column). The polynomials are in turn evaluated to produce constraints for a nonlinear model fit which directly determines the model parameters describing the location and orientation of each CCD. The focal plane geometry characterization algorithm is itself embedded in an iterative process which determines the focal plane geometry and the Pixel Response Function for each CCD in a self-consistent manner. In addition to the fully automated calculation, a person-in-the-loop implementation was developed to allow an initial determination of the geometry in the event of large misalignments, achieving a much looser capture tolerance for more modest accuracy and reduced automation.

ccd↗