Kepler Science Operations processes, procedures, and tools

Hall, Jennifer R.; Ibrahim, Khadeejah A.; Klaus, Todd C.; Cote, Miles T.; Middour, Christopher K.; Haas, Michael R.; Dotson, Jessie L.; Stroozas, B.; Wu, Michael; Sommers, Jeneen; Bhavsar, Paresh

doi:10.1117/12.856807

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…In the Kepler science data processing pipeline, data are processed per output 8,9 . In the PPA component the health and performance of the Kepler photometer are assessed by analyzing metric time series such as general instrument metrics, cosmic ray metrics, Combined Differential Photometric Precision (CDPP) metrics, etc.…”

Section: Kepler Instrument Metricsmentioning

confidence: 99%

Photometer performance assessment in Kepler science data processing

Allen

Bryson

et al. 2010

SPIE Proceedings

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Section: Kepler Instrument Metricsmentioning

confidence: 99%

Photometer performance assessment in Kepler science data processing

Allen

Bryson

et al. 2010

SPIE Proceedings

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“…Additional modules operate in parallel to monitor the instrument performance 7,8 and provide target management 9 . The flight data are processed monthly and quarterly 10 , and are subject to continuous reprocessing throughout the length of the mission as the Pipeline algorithms continue to improve. Once each data set is processed through the Pipeline, the SOC provides a list of planetary candidates to the Science Team for further analysis.…”

Section: Introductionmentioning

confidence: 99%

Pixel-level calibration in the Kepler Science Operations Center pipeline

et al. 2010

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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 obtained from the Data Management Center to remove instrument effects and other artifacts that pollute the data. CAL performs traditional CCD data reduction (removal of instrument/detector effects such as bias and dark current), pixel-level calibration (correcting for cosmic ray hits and variations in pixel sensitivity), Kepler-specific corrections (smear signals which result from the lack of a shutter on the photometer and distortions from 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.

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“…The Kepler SOC 1 uses this framework to build the pipelines that process the ~23 GiB of raw pixel data downlinked from the Kepler spacecraft per month on four computing clusters containing a total of 64 nodes, 512 CPU cores, 2.3 TiB of RAM and 148 TiB of raw disk storage 2 .…”

Section: Introductionmentioning

confidence: 99%

Kepler Science Operations Center pipeline framework

et al. 2010

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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.

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Kepler Science Operations processes, procedures, and tools

Cited by 6 publications

References 14 publications

Photometer performance assessment in Kepler science data processing

Photometer performance assessment in Kepler science data processing

Pixel-level calibration in the Kepler Science Operations Center pipeline

Kepler Science Operations Center pipeline framework

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