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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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Modelling stellar activity with Gaussian process regression networks

ABSTRACT Stellar photospheric activity is known to limit the detection and characterization of extrasolar planets. In particular, the study of Earth-like planets around Sun-like stars requires data analysis methods that can accurately model the stellar activity phenomena affecting radial velocity (RV) measurements. Gaussian Process Regression Networks (GPRNs) offer a principled approach to the analysis of simultaneous time series, combining the structural properties of Bayesian neural networks with the non-parametric flexibility of Gaussian Processes. Using HARPS-N solar spectroscopic observations encompassing three years, we demonstrate that this framework is capable of jointly modelling RV data and traditional stellar activity indicators. Although we consider only the simplest GPRN configuration, we are able to describe the behaviour of solar RV data at least as accurately as previously published methods. We confirm the correlation between the RV and stellar activity time series reaches a maximum at separations of a few days, and find evidence of non-stationary behaviour in the time series, associated with an approaching solar activity minimum.

Camacho, J. D. (ORCID:0000000151215560)↗

Around Which Stars Can TESS Detect Earth-like Planets? The Revised TESS Habitable Zone Catalog

In the search for life in the cosmos, NASA’s Transiting Exoplanet Survey Satellite (TESS) mission has already monitored about 74% of the sky for transiting extrasolar planets, including potentially habitable worlds. However, TESS only observed a fraction of the stars long enough to be able to find planets like Earth. We use the primary mission data—the first two years of observations—and identify 4239 stars within 210 pc that TESS observed long enough to see three transits of an exoplanet that receives similar irradiation to Earth: 738 of these stars are located within 30 pc. We provide reliable stellar parameters from the TESS Input Catalog that incorporates Gaia DR2 and also calculate the transit depth and radial velocity semiamplitude for an Earth-analog planet. Of the 4239 stars in the Revised TESS HZ Catalog, 9 are known exoplanet hosts—GJ1061, GJ1132, GJ3512, GJ685, Kepler-42, LHS1815, L98-59, RRCae, and TOI700—around which TESS could identify additional Earth-like planetary companions. Thirty-seven additional stars host yet unconfirmed TESS Objects of Interest: three of these orbit in the habitable zone—TOI203, TOI715, and TOI2298. For a subset of 614 of the 4239 stars, TESS has observed the star long enough to be able to observe planets throughout the full temperate, habitable zone out to the equivalent of Mars’ orbit. Thus, the Revised TESS Habitable Zone Catalog provides a tool for observers to prioritize stars for follow-up observation to discover life in the cosmos. These stars are the best path toward the discovery of habitable planets using the TESS mission data.

79 ASTRONOMY AND ASTROPHYSICS↗

The HOSTS Survey: Evidence for an Extended Dust Disk and Constraints on the Presence of Giant Planets in the Habitable Zone of β Leo

The young (50–400 Myr) A3V star β Leo is a primary target to study the formation history and evolution of extrasolar planetary systems as one of the few stars with known hot (∼1600 K), warm (∼600 K), and cold (∼120 K) dust belt components. In this paper, we present deep mid-infrared measurements of the warm dust brightness obtained with the Large Binocular Telescope Interferometer (LBTI) as part of its exozodiacal dust survey (HOSTS). The measured excess is 0.47% ± 0.050% within the central 1.5 au, rising to 0.81% ± 0.026% within 4.5 au, outside the habitable zone of β Leo. This dust level is 50 ± 10 times greater than in the solar system’s zodiacal cloud. Poynting–Robertson drag on the cold dust detected by Spitzer, and Herschel underpredicts the dust present in the habitable zone of β Leo, suggesting an additional delivery mechanism (e.g., comets) or an additional belt at ∼5.5 au. A model of these dust components is provided that implies the absence of planets more than a few Saturn masses between ∼5 au and the outer belt at ∼40 au. We also observationally constrain giant planets with the LBTI imaging channel at 3.8 μm wavelength. Assuming an age of 50 Myr, any planet in the system between approximately 5–50 au must be less than a few Jupiter masses, consistent with our dust model. Taken together, these observations showcase the deep contrasts and detection capabilities attainable by the LBTI for both warm exozodiacal dust and giant exoplanets in or near the habitable zone of nearby stars.

47 OTHER INSTRUMENTATION↗

Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra

Abstract Transit spectroscopy is a powerful tool for decoding the chemical compositions of the atmospheres of extrasolar planets. In this paper, we focus on unsupervised techniques for analyzing spectral data from transiting exoplanets. After cleaning and validating the data, we demonstrate methods for: (i) initial exploratory data analysis, based on summary statistics (estimates of location and variability); (ii) exploring and quantifying the existing correlations in the data; (iii) preprocessing and linearly transforming the data to its principal components; (iv) dimensionality reduction and manifold learning; (v) clustering and anomaly detection; and (vi) visualization and interpretation of the data. To illustrate the proposed unsupervised methodology, we use a well-known public benchmark data set of synthetic transit spectra. We show that there is a high degree of correlation in the spectral data, which calls for appropriate low-dimensional representations. We explore a number of different techniques for such dimensionality reduction and identify several suitable options in terms of summary statistics, principal components, etc. We uncover interesting structures in the principal component basis, namely well-defined branches corresponding to different chemical regimes of the underlying atmospheres. We demonstrate that those branches can be successfully recovered with a K-means clustering algorithm in a fully unsupervised fashion. We advocate for lower-dimensional representations of the spectroscopic data in terms of the main principal components, in order to reveal the existing structure in the data and quickly characterize the chemical class of a planet.

Matchev, Konstantin T. (ORCID:0000000341829096)↗

Toward Complete Characterization: Prospects for Directly Imaging Transiting Exoplanets

High-contrast direct imaging of exoplanets can provide many important observables, including measurements of the orbit, spectra that probe the lower layers of the atmosphere, and phase variations of the planet, but cannot directly measure planet radius or mass. Our future understanding of directly imaged exoplanets will therefore rely on extrapolated models of planetary atmospheres and bulk composition, which need robust calibration. We estimate the population of extrasolar planets that could serve as calibrators for these models. Critically, this population of “standard planets” must be accessible to both direct imaging and the transit method, allowing for radius measurement. We show that the search volume of a direct imaging mission eventually overcomes the transit probability falloff with semimajor axis, so that as long as cold planets are not exceedingly rare, the population of transiting planets and directly imageable planets overlaps. Using current extrapolations of Kepler occurrence rates, we estimate that ∼8 standard planets could be characterized shortward of 800 nm with an ambitious future direct imaging mission like LUVOIR-A and several dozen could be detected at the V band. We show the design space that would expand the sample size and discuss the extent to which ground- and space-based surveys could detect this small but crucial population of planets.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovery of Beryllium in White Dwarfs Polluted by Planetesimal Accretion

The element beryllium is detected for the first time in white dwarf stars. This discovery in the spectra of two helium-atmosphere white dwarfs was made possible only because of the remarkable overabundance of Be relative to all other elements, heavier than He, observed in these stars. The measured Be abundances, relative to chondritic, are by far the largest ever seen in any astronomical object. We anticipate that the Be in these accreted planetary bodies was produced by spallation of one or more of O, C, and N in a region of high fluence of particles of MeV or greater energy.

79 ASTRONOMY AND ASTROPHYSICS↗