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NASA NTRS2015

Enhancements of Bayesian Blocks; Application to Large Light Curve Databases

Bayesian Blocks are optimal piecewise linear representations (step function fits) of light-curves. The simple algorithm implementing this idea, using dynamic programming, has been extended to include more data modes and fitness metrics, multivariate analysis, and data on the circle (Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, Scargle, Norris, Jackson and Chiang 2013, ApJ, 764, 167), as well as new results on background subtraction and refinement of the procedure for precise timing of transient events in sparse data. Example demonstrations will include exploratory analysis of the Kepler light curve archive in a search for "star-tickling" signals from extraterrestrial civilizations. (The Cepheid Galactic Internet, Learned, Kudritzki, Pakvasa1, and Zee, 2008, arXiv: 0809.0339; Walkowicz et al., in progress).

Kepler light curve archive↗
NASA NTRS2017

Status of the TESS Science Processing Operations Center

The Transiting Exoplanet Survey Satellite (TESS) science pipeline is being developed by the Science Processing Operations Center (SPOC) at NASA Ames Research Center based on the highly successful Kepler Mission science pipeline. Like the Kepler pipeline, the TESS science pipeline will provide calibrated pixels, simple and systematic error-corrected aperture photometry, and centroid locations for all 200,000+ target stars, observed over the 2-year mission, along with associated uncertainties. The pixel and light curve products are modeled on the Kepler archive products and will be archived to the Mikulski Archive for Space Telescopes (MAST). In addition to the nominal science data, the 30-minute Full Frame Images (FFIs) simultaneously collected by TESS will also be calibrated by the SPOC and archived at MAST. The TESS pipeline will search through all light curves for evidence of transits that occur when a planet crosses the disk of its host star. The Data Validation pipeline will generate a suite of diagnostic metrics for each transit-like signature discovered, and extract planetary parameters by fitting a limb-darkened transit model to each potential planetary signature. The results of the transit search will be modeled on the Kepler transit search products (tabulated numerical results, time series products, and pdf reports) all of which will be archived to MAST.

high performance computing↗
NASA NTRS2012

Demystifying Kepler Data: A Primer for Systematic Artifact Mitigation

The Kepler spacecraft has collected data of high photometric precision and cadence almost continuously since operations began on 2009 May 2. Primarily designed to detect planetary transits and asteroseismological signals from solar-like stars, Kepler has provided high quality data for many areas of investigation. Unconditioned simple aperture time-series photometry are however affected by systematic structure. Examples of these systematics are differential velocity aberration, thermal gradients across the spacecraft, and pointing variations. While exhibiting some impact on Kepler's primary science, these systematics can critically handicap potentially ground-breaking scientific gains in other astrophysical areas, especially over long timescales greater than 10 days. As the data archive grows to provide light curves for 10(exp 5) stars of many years in length, Kepler will only fulfill its broad potential for stellar astrophysics if these systematics are understood and mitigated. Post-launch developments in the Kepler archive, data reduction pipeline and open source data analysis software have occurred to remove or reduce systematic artifacts. This paper provides a conceptual primer for users of the Kepler data archive to understand and recognize systematic artifacts within light curves and some methods for their removal. Specific examples of artifact mitigation are provided using data available within the archive. Through the methods defined here, the Kepler community will find a road map to maximizing the quality and employment of the Kepler legacy archive.

Kinemuchi, K.↗
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

photocenter↗
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS (Transiting Exoplanet Survey Satellite) launched on 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be obtained. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each approximately 1-month sector, the SPOC calibrates the image data for both 30-minute Full Frame Images (FFIs) and up to 20,000 pre-selected 2-minute target star postage stamps. Simple aperture photometry and systematic error-corrected flux-time series are generated for the 2-minute data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-minute image data, Light Curve files (LCs) containing the photometric time series for each 2-minute target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-minute targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Science Pipeline↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS launched 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each ~1 month sector, the SPOC calibrates the image data for both 30-min Full Frame Images (FFIs) and up to 20,000 pre-selected 2-min target star postage stamps. Simple aperture photometry and systematic error-corrected flux time series are generated for the 2-min data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-min image data, Light Curve files (LCs) containing the photometric time series for each 2-min target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-min targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Jenkins, Jon M.↗
NASA NTRS2016

Kepler Planet Detection Metrics: Statistical Bootstrap Test

This document describes the data produced by the Statistical Bootstrap Test over the final three Threshold Crossing Event (TCE) deliveries to NExScI: SOC 9.1 (Q1Q16)1 (Tenenbaum et al. 2014), SOC 9.2 (Q1Q17) aka DR242 (Seader et al. 2015), and SOC 9.3 (Q1Q17) aka DR253 (Twicken et al. 2016). The last few years have seen significant improvements in the SOC science data processing pipeline, leading to higher quality light curves and more sensitive transit searches. The statistical bootstrap analysis results presented here and the numerical results archived at NASAs Exoplanet Science Institute (NExScI) bear witness to these software improvements. This document attempts to introduce and describe the main features and differences between these three data sets as a consequence of the software changes.

Bootstrap↗
NASA NTRS2016

EVEREST: Pixel Level Decorrelation of K2 Light Curves

We present EPIC Variability Extraction and Removal for Exoplanet Science Targets (EVEREST), an open-source pipeline for removing instrumental noise from K2 light curves. EVEREST employs a variant of pixel level decorrelation to remove systematics introduced by the spacecraft’s pointing error and a Gaussian process to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0–7, yielding light curves with precision comparable to that of the original Kepler mission for stars brighter than K(sub p) ≈ 13, and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline and compare our light curves to the other de-trended light curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these light curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST light curves and the source code used to generate them are freely available online.

Catalogs↗
NASA NTRS2016

The TESS Science Processing Operations Center

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.

TESS↗
NASA NTRS2016

Kepler Data Validation Time Series File: Description of File Format and Content

The Kepler space mission searches its time series data for periodic, transit-like signatures. The ephemerides of these events, called Threshold Crossing Events (TCEs), are reported in the TCE tables at the NASA Exoplanet Archive (NExScI). Those TCEs are then further evaluated to create planet candidates and populate the Kepler Objects of Interest (KOI) table, also hosted at the Exoplanet Archive. The search, evaluation and export of TCEs is performed by two pipeline modules, TPS (Transit Planet Search) and DV (Data Validation). TPS searches for the strongest, believable signal and then sends that information to DV to fit a transit model, compute various statistics, and remove the transit events so that the light curve can be searched for other TCEs. More on how this search is done and on the creation of the TCE table can be found in Tenenbaum et al. (2012), Seader et al. (2015), Jenkins (2002). For each star with at least one TCE, the pipeline exports a file that contains the light curves used by TPS and DV to find and evaluate the TCE(s). This document describes the content of these DV time series files, and this introduction provides a bit of context for how the data in these files are used by the pipeline.

DV Time Series↗
NASA NTRS2016

The TESS Science Processing Operations Center

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).

Jenkins, Jon M.↗
NASA NTRS2019

Discovery and Vetting of Exoplanets. I. Benchmarking K2 Vetting Tools

We have adapted the algorithmic tools developed during the Kepler mission to vet the quality of transit-like signals for use on the K2 mission data. Using the four sets of publicly available light curves at MAST, we produced a uniformly vetted catalog of 772 transiting planet candidates from K2 as listed at the NASA Exoplanet Archive in the K2 Table of Candidates. Our analysis marks 676 of these as planet candidates and 96 as false positives. All confirmed planets pass our vetting tests. Sixty of our false positives are new identifications, effectively doubling the overall number of astrophysical signals mimicking planetary transits in K2 data. Most of the targets listed as false positives in our catalog show either prominent secondary eclipses, transit depths suggesting a stellar companion instead of a planet, or significant photocenter shifts during transit. We packaged our tools into the open-source, automated vetting pipeline Discovery and Vetting of Exoplanets (DAVE), designed to streamline follow-up efforts by reducing the time and resources wasted observing targets that are likely false positives. DAVE will also be a valuable tool for analyzing planet candidates from NASA's TESS mission, where several guest-investigator programs will provide independent light-curve sets—and likely many more from the community. We are currently testing DAVE on recently released TESS planet candidates and will present our results in a follow-up paper.

Kostov, Veselin B.↗
NASA NTRS2017

Kepler Uniform Modeling of KOIs: MCMC Notes for Data Release 25

This document describes data products related to the reported planetary parameters and uncertainties for the Kepler Objects of Interest (KOIs) based on a Markov-Chain-Monte-Carlo (MCMC) analysis. Reported parameters, uncertainties and data products can be found at the NASA Exoplanet Archive . The codes used for this data analysis are available on the Github website (Rowe 2016). The relevant paper for details of the calculations is Rowe et al. (2015). The main differences between the model fits discussed here and those in the DR24 catalogue are that the DR25 light curves were used in the analysis, our processing of the MAST light curves took into account different data flags, the number of chains calculated was doubled to 200 000, and the parameters which are reported are based on a damped least-squares fit, instead of the median value from the Markov chain or the chain with the lowest 2 as reported in the past.

DR25↗
NASA NTRS2012

The Shape of Long Outbursts in U Gem Type Dwarf Novae from AAVSO Data

We search the American Association of Variable Star Observers (AAVSO) archives of the two best studied dwarf novae in an attempt to find light curves for long out bursts that are extremely well-characterized. The systems are U Gem and S8 Cyg. Our goal is to search for embedded precursors such as those that have been found recently in the high fidelity Kepler data for superoutbursts of some members of the 8U UMa subclass of dwarf novae. For the vast majority of AAV80 data, the combination of low data cadence and large errors associated with individual measurements precludes one from making any strong statement about the shape of the long outbursts. However, for a small number of outbursts, extensive long term monitoring with digital photometry yields high fidelity light curves. We report the finding of embedded precursors in two of three candidate long outbursts. This reinforces van Paradijs' finding that long outbursts in dwarf novae above the period gap and superoutbursts in systems below the period gap constitute a unified class. The thermal-tidal instability to account for superoutbursts in the SU UMa stars predicts embedded precursors only for short orbital period dwarf novae, therefore the presence of embedded precursors in long orbital period systems - U Gem and SS Cyg - argues for a more general mechanism to explain long outbursts.

Cannizzo, John K.↗
NASA NTRS2019

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↗
NASA NTRS2018

Kepler Data Validation I: Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

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.

data analysis↗
NASA NTRS2016

Kepler Data Release 25 Notes (Q0-Q17)

These Data Release Notes provide information specific to the current reprocessing and re-export of the Q0-Q17 data. The data products included in this data release include target pixel files, light curve files, FFIs,CBVs, ARP, Background, and Collateral files. This release marks the final processing of the Kepler Mission Data. See Tables 1 and 2 for a list of the reprocessed Kepler cadence data. See Table 3 for a list of the available FFIs. The Long Cadence Data, Short Cadence Data, and FFI data are documented in these data release notes. The ancillary files (i.e., cotrending basis vectors, artifact removal pixels, background, and collateral data) are described in the Archive Manual (Thompson et al., 2016).

Data Release Notes↗