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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2020

TESS Data Release Notes: Sector 21 DR 29

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel les, light curve les, collateral pixel les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2017).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

Michael M. Fausnaugh↗
NASA NTRS2020

TESS Data Release Notes: Sector 24, DR35

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel fi les, light curve fi les, collateral pixel fi les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml fi les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD). The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2019).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

TESS↗
NASA NTRS2020

Multiple Transits during a Single Conjunction: Identifying Transiting Circumbinary Planetary Candidates from TESS

We present results of a study on identifying circumbinary planet candidates that produce multiple transits during one conjunction with eclipsing binary systems. The occurrence of these transits enables us to estimate the candidates’ orbital periods, which is crucial as the periods of the currently known transiting circumbinary planets are significantly longer than the typical observational baseline of the Transiting Exoplanet Survey Satellite (TESS). Combined with the derived radii, it also provides valuable information needed for follow-up observations and subsequent confirmation of a large number of circumbinary planet candidates from TESS. Motivated by the discovery of the 1108 day circumbinary planet Kepler-1647, we show the application of this technique to four of Kepler’s circumbinary planets that produce such transits. Our results indicate that in systems where the circumbinary planet is on a low-eccentricity orbit, the estimated planetary orbital period is within <10%–20% of the true value. This estimate is derived from photometric observations spanning less than 5% of the planet’s period, demonstrating the strong capability of the technique. Capitalizing on the current and future eclipsing binaries monitored by NASA’s TESS mission, we estimate that hundreds of circumbinary planet candidates producing multiple transits during one conjunction will be detected in the TESS data. Such a large sample will enable statistical understanding of the population of planets orbiting binary stars and shed new light on their formation and evolution.

Veselin Kostov↗
NASA NTRS2021

TESS Data Release Notes: Sectors 1 – 36, Multi-sector Search, DR53

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). This data release is a combined, multi-sector transit search only. The underlying data products from individual observing sectors have been previously released. The data products included in this data release are the Data Validation (DV) reports, time series, and associated xml files for the threshold crossing events (TCEs) found by searching a combined data set including data from multiple observing sectors. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2020)2. The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

TESS↗
NASA NTRS2015

Comparative Habitability of Transiting Exoplanets

Exoplanet habitability is traditionally assessed by comparing a planet’s semimajor axis to the location of its host star’s “habitable zone,” the shell around a star for which Earth-like planets can possess liquid surface water. The Kepler space telescope has discovered numerous planet candidates near the habitable zone, and many more are expected from missions such as K2, TESS, and PLATO. These candidates often require significant follow-up observations for validation, so prioritizing planets for habitability from transit data has become an important aspect of the search for life in the universe. We propose a method to compare transiting planets for their potential to support life based on transit data, stellar properties and previously reported limits on planetary emitted flux. For a planet in radiative equilibrium, the emitted flux increases with eccentricity, but decreases with albedo. As these parameters are often unconstrained, there is an “eccentricity-albedo degeneracy” for the habitability of transiting exoplanets. Our method mitigates this degeneracy, includes a penalty for large-radius planets, uses terrestrial mass–radius relationships, and, when available, constraints on eccentricity to compute a number we call the “habitability index for transiting exoplanets” that represents the relative probability that an exoplanet could support liquid surface water. We calculate it for Kepler objects of interest and find that planets that receive between 60% and 90% of the Earth’s incident radiation, assuming circular orbits, are most likely to be habitable. Finally, we make predictions for the upcoming TESS and James Webb Space Telescope missions.

Planet and satellite surfaces↗
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 NTRS2017

Description of the TCERT Vetting Reports for Data Release 25

The Q1Q17 DR25 TCERT Vetting Reports are a collection of plots and diagnostics used by the Threshold Crossing Event Review Team (TCERT) to evaluate threshold crossing events (TCEs). While designation of Kepler Objects of Interest (KOIs) and classification of them as Planet Candidates (PCs) or False Positives (FPs) is completely automated via a robotic vetting procedure (the Robovetter) for the Q1Q17 DR25 planet catalog, as described in Thompson et al. (2017), these reports help to visualize the metrics used by the Robovetter and evaluate those robotic decisions for individual objects. For each Q1Q17 DR25 TCE, these reports include the following products: (a) the DV one-page summary, (b) selected pertinent diagnostics and plots from the full DV report, and (c) additional plots and diagnostics not included in the full DV report, including an alternate means of data detrending.

Kepler Objects of Interest↗
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 NTRS2015

Composition, Structure and Formation of Low-Density Planets Within 0.5 AU of Their Star

Kepler has discovered that tens of percent of sunlike stars possess one or more planets larger than Earth within 0.5 AU. Masses of dozens of small and mid-sized exoplanets have been measured using radial velocity or transit timing variations. Few transiting planets larger than 1.6 Earth radii are rocky. Rather, the planetary mass-radius diagram for planetary radius between 1.6 and 8 times that of Earth shows a tendency for mass to increase slowly with size. The scatter is larger than can be explained by observational errors and correlations with temperature, implying that the population is heterogeneous. Many Neptune-size planets have very low densities and must have a substantial fraction of their volumes occupied by hydrogen and/or helium. Models of the structure, growth and evolution of planets made of mixtures of rock and light gases will be presented and compared with observations of both individual bodies and of the characteristics of the population as a whole.

radial velocity↗