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At least 19 records
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NASA NTRS2011

Modeling Kepler Transit Light Curves as False Positives: Rejection of Blend Scenarios for Kepler-9, and Validation of Kepler-9 d, a Super-Earth-Size Planet in a Multiple System

Light curves from the Kepler Mission contain valuable information on the nature of the phenomena producing the transit-like signals. To assist in exploring the possibility that they are due to an astrophysical false positive we describe a procedure (BLENDER) to model the photometry in terms of a blend rather than a planet orbiting a star. A blend may consist of a background or foreground eclipsing binary (or star-planet pair) whose eclipses are attenuated by the light of the candidate and possibly other stars within the photometric aperture. We apply BLENDER to the case of Kepler-9 (KIC 3323887), a target harboring two previously confirmed Saturn-size planets (Kepler-9 b and Kepler-9 c) showing transit timing variations, and an additional shallower signal with a 1.59 day period suggesting the presence of a super-Earth-size planet. Using BLENDER together with constraints from other follow-up observations we are able to rule out all blends for the two deeper signals and provide independent validation of their planetary nature. For the shallower signal, we rule out a large fraction of the false positives that might mimic the transits. The false alarm rate for remaining blends depends in part (and inversely) on the unknown frequency of small-size planets. Based on several realistic estimates of this frequency, we conclude with very high confidence that this small signal is due to a super-Earth-size planet (Kepler-9 d) in a multiple system, rather than a false positive. The radius is determined to be 1.64(exp)(sub-14),R, and current spectroscopic observations are as yet insufficient to establish its mass.

PLANETARY SYSTEMS↗
NASA NTRS2016

Kepler: A Search for Terrestrial Planets - Kepler Data Characterization Handbook

The Kepler Data Characteristics Handbook (KDCH) provides a description of all phenomena identified in the Kepler data throughout the mission, and an explanation for how these characteristics are handled by the final version of the Kepler Data Processing Pipeline (SOC 9.3).The KDCH complements the Kepler Data Release Notes (KDRNs), which document phenomena and processing unique to a data release. The original motivation for this separation into static, explanatory text and a more journalistic set of figures and tables in the KDRN was for the user to become familiar with the Data Characteristics Handbook, then peruse the short Notes for a new quarter, referring back to the Handbook when necessary. With the completion of the Kepler mission and the final Data Release 25, both the KDCH and the DRN encompass the entire Kepler mission, so the distinction between them is in the level of exposition, not the extent of the time interval discussed.

Kepler↗
NASA NTRS2010

The Kepler End-to-End Model: Creating High-Fidelity Simulations to Test Kepler Ground Processing

The Kepler mission is designed to detect the transit of Earth-like planets around Sun-like stars by observing 100,000 stellar targets. Developing and testing the Kepler ground-segment processing system, in particular the data analysis pipeline, requires high-fidelity simulated data. This simulated data is provided by the Kepler End-to-End Model (ETEM). ETEM simulates the astrophysics of planetary transits and other phenomena, properties of the Kepler spacecraft and the format of the downlinked data. Major challenges addressed by ETEM include the rapid production of large amounts of simulated data, extensibility and maintainability.

Bryson, Stephen T.↗
NASA NTRS2019

Architecture and Dynamics of Kepler's Multi-Transiting Planet Systems.III. Comprehensive Investigation Using All Four Years of Kepler Mission Data

We study the orbital architectures of planetary systems orbiting within ∼1 AU of their stars by analyzing the ensemble of Kepler systems having two or more planet candidates. We use data from the entire Kepler mission, and in many cases we apply improved analysis techniques (e.g., replacing histograms by top-hat Kernel Density Estimators that avoid the loss of information resulting from choosing a particular phase for the bin boundaries) to extend and enhance the studies of Lissauer et al. (2011, ApJS 197, 8) and Fabrycky et al. (2014, ApJ 790, 146).These data show ~ 1700 transiting planet candidates in > 600 multiple-planet systems, far more than were available for our previous two studies. The increased numbers and better information about planetary radii and the properties of stellar hosts made possible by Gaia DR2 allow more statistically-robust analyses of the entire ensemble of Kepler multis as well as independent analyses of subsets of the population. We are thus able to contrast the dynamical configurations of small and large planets, short-period and longer-period planets, and planets orbiting various types of host stars. We reinforce our previous findings that most pairs of planets within the same system are neither in nor near low-order mean motion resonances and that there is a substantial excess of planets having period ratios slightly larger than those of first-order mean-motion resonances. However, neglecting three systems whose planets are locked in 3- body resonances and summing over all first-order mean motion resonances, the deficit of planet pairs with period ratios just narrow of resonance is as large as the excess of planets wide of resonance (within statistical uncertainties), suggesting that overall there is no overall excess of planet pairs in the vicinity of resonance. Other aspects of our study, including estimates of the typical relative inclinations of planetary orbits and their variations as functions of orbital period, planet sizes and stellar properties, are in progress, with results expected to be available for presentation by the time of the conference.

Lissauer, Jack↗
NASA NTRS2016

Secure Mass Measurements From Transit Timing: 10 Kepler Exoplanets Between 3 and 8M⊕ with Diverse Densities and Incident Fluxes

We infer dynamical masses in eight multiplanet systems using transit times measured from Keplerʼs complete dataset, including short-cadence data where available. Of the 18 dynamical masses that we infer, 10 pass multiple tests for robustness. These are in systems Kepler-26 (KOI-250), Kepler-29 (KOI-738), Kepler-60 (KOI-2086), Kepler-105 (KOI-115), and Kepler-307 (KOI-1576). Kepler -105 c has a radius of 1.3R⊕ and a density consistent with an Earth-like composition. Strong transit timing variation (TTV) signals were detected from additional planets, but their inferred masses were sensitive to outliers or consistent solutions could not be found with independently measured transit times, including planets orbiting Kepler-49 (KOI-248), Kepler-57 (KOI-1270), Kepler-105 (KOI-115), and Kepler-177 (KOI-523). Nonetheless, strong upper limits on the mass of Kepler-177 cimply an extremely low density of 0.1 g cm−3. In most cases, individual orbital eccentricities were poorly constrained owing to degeneracies in TTV inversion. For five planet pairs in our sample, strong secular interactions imply a moderate to high likelihood of apsidal alignment over a wide range of possible eccentricities. We also find solutions for the three planets known to orbit Kepler-60 in a Laplace-like resonance chain. However, nonlibrating solutions also match the transit timing data. For six systems, we calculate more precise stellar parameters than previously known, enabling useful constraints on planetary densities where we have secure mass measurements. Placing these exoplanets on the mass–radius diagram, we find that a wide range of densities is observed among sub-Neptune-mass planets and that the range in observed densities is anticorrelated with incident flux.

Stars individual↗
NASA NTRS2016

Secure Mass Measurements From Transit Timing: 10 Kepler Exoplanets Between 3 and 8 M⊕ With Diverse Densities and Incident Fluxes

We infer dynamical masses in eight multiplanet systems using transit times measured from Keplerʼs complete data set, including short-cadence data where available. Of the 18 dynamical masses that we infer, 10 pass multiple tests for robustness. These are in systems Kepler-26 (KOI-250), Kepler-29 (KOI-738), Kepler-60 (KOI-2086), Kepler-105 (KOI-115), and Kepler-307 (KOI-1576). Kepler-105 c has a radius of 1.3 R(sub ⨁) and a density consistent with an Earth-like composition. Strong transit timing variation (TTV) signals were detected from additional planets, but their inferred masses were sensitive to outliers or consistent solutions could not be found with independently measured transit times, including planets orbiting Kepler-49 (KOI-248), Kepler-57 (KOI-1270), Kepler-105 (KOI-115), and Kepler-177 (KOI-523). Nonetheless, strong upper limits on the mass of Kepler-177 c imply an extremely low density of ∽0.1 g cm(exp −3). In most cases, individual orbital eccentricities were poorly constrained owing to degeneracies in TTV inversion. For five planet pairs in our sample, strong secular interactions imply a moderate to high likelihood of apsidal alignment over a wide range of possible eccentricities. We also find solutions for the three planets known to orbit Kepler-60 in a Laplace-like resonance chain. However, nonlibrating solutions also match the transit timing data. For six systems, we calculate more precise stellar parameters than previously known, enabling useful constraints on planetary densities where we have secure mass measurements. Placing these exoplanets on the mass–radius diagram, we find that a wide range of densities is observed among sub-Neptune-mass planets and that the range in observed densities is anticorrelated with incident flux.

Individual stars↗
NASA NTRSDate not supplied

Perturbations, TTVs & the (Un)reliability of Ephemerides of Kepler Planets

Fractional uncertainties quoted for orbital periods of the vast majority of planet candidates listed in recent Kepler catalogs are $<10^{-5}$, with values $\sim 10^{-6}$ (corresponding to 2 minutes per 4 years) being typical. These small uncertainties suggest ephemeris predictions for most Kepler planets are robust for decades to come. Tabulated periods list formal uncertainties in the mean times between midpoints of successive transits during the time interval in which transits were observed. However, transit timing variations (TTVs) produce errors in estimates of some planets’ orbital periods that need to be accounted for in certain dynamical investigations and ephemeris predictions. Periodic TTVs with timescales short compared to the interval of Kepler observations largely average out and do not produce significant errors in estimates of orbital periods. TTVs with timescales comparable to the interval of Kepler observations have been fit for dozens of Kepler planet candidates to estimate long-term average orbital periods (Holczer et al. 2016, ApJS 225, 9), and more detailed dynamical models have been used to estimate long-term average periods of a small number of well-studied planets. Most Kepler planets that show large TTVs are near mean-motion orbital resonances with other planets. The largest effect for planets moderately close to two-body resonances are due to rotation of the forced eccentricity vector by resonant perturbations; the timescale for this precession is typically short, so the variations tend to average out. Libration of planets locked in resonances typically occurs on timescales longer than the Kepler baseline, but few Kepler planets appear to be resonantly-locked. The more general but smaller (during the era of Kepler observations) effect is caused by secular precession of the planets' free eccentricities usually has a period much longer than the baseline of the Kepler observations, so it is not accounted for in estimates of mean periods or uncertainties. This precession causes a discrepancy between Kepler era mean orbital period and long-term mean orbital period can exist even for planets having TTVs that are too small to be observable during the epoch of Kepler observations.

Kepler↗
NASA NTRS2017

Kepler: A Search for Terrestrial Planets. K2 Handbook

The Kepler spacecraft was repurposed for the K2 mission a year after the failure of the second of Kepler's four reaction wheels in 2013 May. The purpose of this document, the K2 Handbook (K2H), is to describe features of K2 operations, performance, data analysis, and archive products which are common to most K2 campaigns, but different in degree or kind from the corresponding features of the Kepler mission.The K2 Handbook is meant to be read with the following companion documents, which are all publicly available:1. Kepler Instrument Handbook (KSCI-19033) provides information about the design, performance and operational constraints of the instrument and an overview of the types of pixel data that are available.2. Kepler Data Processing Handbook (KSCI-19081) describes how pixels downloaded from the spacecraft are converted by the Kepler Data Processing Pipeline into the data products available at the MAST archive3. Kepler Archive Manual (KDMC-100008) describes the format and content of the data products and how to search for them.4. Kepler Data Characteristics Handbook (KSCI-19040) describes recurring non-astrophysical features of the Kepler data due to instrument signatures, spacecraft events or solar activity and explains how these characteristics are handled by the Kepler pipeline.5. The Ecliptic Plane Input Catalog describes the provenance of the positions and Kepler magnitudes used for target management and aperature photometry.6. K2 Data Release Notes (DRN) are on-line documents available on the K2 science website which describe the data inventory, instrumental signatures and events peculiar to individual observing campaigns.

K2↗
NASA NTRSDate not supplied

Optimizing Science Return from Plato's Observations of the Kepler Field

The Plato mission could substantially enhance its scientific yield by focusing a significant fraction of its observations with all 24 cameras viewing the Kepler Field of View (FOV). Kepler, while exceptionally productive, did not accomplish its goal of providing a direct measurement of the abundance of Earth-analog planet around sunlike stars. On this issue, Plato observations centered on the Kepler FOV would enable planet searches using the combined data sets to achieve more precise estimates of planetary occurrence rates than obtainable using data from either mission alone. The ecliptic latitude of the Kepler FOV is too low for Plato to observe with 24 cameras year-round, so current plan’s for Plato’s Northern Stare places the Kepler FOV in the periphery, reducing the number of photons collected from Kepler targets by factors of 2 or 4. We propose instead four ~6 - 8 month Plato stares with 24 cameras observing the Kepler FOV during the Plato primary mission, instead of a single 2 year stare with the Kepler FOV located to the periphery. This change would greatly increase the amount of 'Plato glass’ dedicated to the continued study of the Kepler FOV, while still enabling Plato to observe other parts of the sky during the majority of its prime mission. In addition to discovering planets below Kepler's detection threshold, this change would yield transit follow-up of thousands of known exoplanets with an effective throughput of a 0.6 m space telescope. It would also extend the observing baseline of the Kepler FOV to timescales of decades, providing key data for stellar cycles, the analysis of transit timing variations, and other decade-timescale variations. Such a campaign enhances the likelihood of the detection of true Earth-analog transiting planet candidates around sunlike stars, provide the best statistical study of exoplanet systems with transit timing variations and duration variations, and open up the study of stellar variability to new time-domains with precision on large numbers of faint targets that only 24 Plato cameras can provide.

Jack Lissauer↗
NASA NTRS2017

Limits On Undetected Planets in the Six Transiting Planets Kepler-11 System

The Kepler-11 has five inner planets ranging from approx. 2 - 1 times as massive Earth in a tightly-packed configuration, with orbital periods between 10 and 47 days. A sixth planet, Kepler-11 g, with a period of118 days, is also observed. The spacing between planets Kepler-11 f and Kepler-11 g is wide enough to allow room for a planet to orbit stably between them. We compare six and seven planet fits to measured transit timing variations (TTVs) of the six known planets. We find that in most cases an additional planet between Kepler-11 f and Kepler-11 g degrades rather than enhances the fit to the TTV data, and where the fit is improved, the improvement provides no significant evidence of a planet between Kepler-11 f and Kepler-11 g. This implies that any planet in this region must be low in mass. We also provide constraints on undiscovered planets orbiting exterior to Kepler-11 g. representations will be described.

Lissauer, Jack↗
NASA NTRS2019

A Giant Impact as the Likely Origin of Different Twins in the Kepler-107 Exoplanet System

Measures of exoplanet bulk densities indicate that small exoplanets with radius less than 3 Earth radii (R(sub ⊕)) range from low-density sub-Neptunes containing volatile elements to higher-density rocky planets with Earth-like or iron-rich (Mercury-like) compositions. Such astonishing diversity in observed small exoplanet compositions may be the product of different initial conditions of the planet-formation process or different evolutionary paths that altered the planetary properties after formation. Planet evolution may be especially affected by either photoevaporative mass loss induced by high stellar X-ray and extreme ultraviolet (XUV) flux or giant impacts. Although there is some evidence for the former, there are no unambiguous findings so far about the occurrence of giant impacts in an exoplanet system. Here, we characterize the two innermost planets of the compact and near-resonant system Kepler-107 (ref. 9). We show that they have nearly identical radii (about 1.5–1.6R(sub ⊕)), but the outer planet Kepler-107 c is more than twice as dense (about 12.6 g cm–3) as the innermost Kepler-107 b (about 5.3 g cm−3). In consequence, Kepler-107 c must have a larger iron core fraction than Kepler-107 b. This imbalance cannot be explained by the stellar XUV irradiation, which would conversely make the more-irradiated and less-massive planet Kepler-107 b denser than Kepler-107 c. Instead, the dissimilar densities are consistent with a giant impact event on Kepler-107 c that would have stripped off part of its silicate mantle. This hypothesis is supported by theoretical predictions from collisional mantle stripping, which match the mass and radius of Kepler-107 c.

Bonomo, Aldo S.↗
NASA NTRS2010

The Kepler DB, a Database Management System for Arrays, Sparse Arrays and Binary Data

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.

McCauliff, Sean↗
NASA NTRS2010

Kepler Science Operations Center Architecture

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.

Middour, Christopher↗
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 NTRS2017

The Kepler Data Processing Handbook: A Field Guide to Prospecting for Habitable Worlds

The Kepler telescope hurtled into orbit in March 2009, initiating NASA's first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for approximately 165,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, over 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long-term, ultrahigh photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyrae. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, including achieving an unprecedented photometric precision of ~20 ppm on 6.5-hour timescales, and supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. A newly revised and expanded version of the Kepler Data Processing Handbook (KDPH) has been released to support the legacy archival products. The KDPH details the theory, design and performance of the algorithms supporting each data processing step. This paper presents an overview of the KDPH and features illustrations of several key algorithms in the Kepler Science Data Processing Pipeline. Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA, Science Mission Directorate.

high performance computing↗
NASA NTRS2014

Compositional Constraints on the Best Characterized Rocky Exoplanet, Kepler-36 b

Kepler-36 is an extreme planetary system, consisting of two transiting sub-Neptune-size planets orbiting around a sub-giant star with periods of 13.84 and 16.24 days. Mutual gravitational interactions between the two planets perturb the planets' transit times, allowing the planets' masses to be measured. Despite the similarity of their masses and orbital radii, the planets show a stark contrast in their mean densities: the inner planet (Kepler-36 b) is more than eight times as dense as its outer companion planet (Kepler-36 c). We perform a photo-dynamical analysis of the Kepler-36 system based on more than three years of Kepler photometry. With N-body integrations of initial conditions sampled from the photo-dynamical fits, we further refine the properties of the system by ruling out solutions that show large scale instability within 5 billion days. Ultimately, we measure the planets' masses with 4.2% precision and the planets' radii with 1.8% precision. Kepler-36 b is the rocky exoplanet with the most precisely measured mass and radius. Kepler-36 b's mass and radius are consistent with an Earth-like composition, whereas an iron-enhanced Mercury-like composition is ruled out.

sub-Neptune-size planets↗