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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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40 records · Page 3

FRESIP: A Discovery Mission Concept To Find Earth-Sized Planets Around Solar Like Stars

The current nebular theory postulates that planets are. a consequence of the formation of stars from viscous accretion disks. Condensation from the accretion disk favors the formation of small rocky planets in the hot inner region, and the formation of gas giants in the cool outer region. Consequently, terrestrial-type planet in inner orbits should be commonplace. From geometrical considerations , Borucki and Summers have shown that 1% of planetary systems resembling our solar system should show transits for Earth-sized (or larger) planets. Thus a photometric satellite that uses a wide field of view telescope and a large detector array to simultaneously monitor 5000 target stars should detect 50 planetary systems. To differentiate regularly recurring transits from statistical fluctuations of the stellar flux, one must observe over several orbital periods so that the false positive rate can be reduced to one event or less. A one-meter aperture telescope placed in a halo orbit about either the L1 or L2 Lagrange points and viewing perpendicular to both the orbital and ecliptic planes can view continuously for the required period because neither the Sun, Earth, or Moon would enter the field of view. Model calculations show that the observations should provide statistically significant estimates of the distributions of planetary size, orbital radius, coplanarity, and the frequency of planetary systems that have Earth-sized planets in inner orbits. Because approximately one half of the star systems observed will be binary systems, the frequency of planetary systems orbiting either one or both of the stars can also be determined.

Borucki, William↗

Discovering faint and high apparent motion rate near-Earth asteroids using a deep learning program

ABSTRACT Although many near-Earth objects have been found by ground-based telescopes, some fast-moving ones, especially those near detection limits, have been missed by observatories. We developed a convolutional neural network for detecting faint fast-moving near-Earth objects. It was trained with artificial streaks generated from simulations and was able to find these asteroid streaks with an accuracy of 98.7 per cent and a false positive rate of 0.02 per cent on simulated data. This program was used to search image data from the Zwicky Transient Facility (ZTF) in four nights in 2019, and it identified six previously undiscovered asteroids. The visual magnitudes of our detections range from ∼19.0 to 20.3 and motion rates range from ∼6.8 to 24 deg d−1, which is very faint compared to other ZTF detections moving at similar motion rates. Our asteroids are also ∼1–51 m diameter in size and ∼5–60 lunar distances away at close approach, assuming their albedo values follow the albedo distribution function of known asteroids. The use of a purely simulated data set to train our model enables the program to gain sensitivity in detecting faint and fast-moving objects while still being able to recover nearly all discoveries made by previously designed neural networks which used real detections to train neural networks. Our approach can be adopted by any observatory for detecting fast-moving asteroid streaks.

Wang, Franklin (ORCID:0000000344887355)↗

Kepler Planet Detection Mission: Introduction and First Results

The Kepler Mission is designed to determine the frequency of Earth-size and rocky planets in and near the habitable zone (HZ) of solar-like stars. The HZ is defined to be the region of space where a rocky planet could maintain liquid water on its surface. Kepler is the 10th competitively-selected Discovery Mission and was launched on March 6, 2009. Since completing its commissioning, Kepler has observed over 156,000 stars simultaneously and near continuously to search for planets that periodically pass in front of their host star (transit). The photometric precision is approximately 23 ppm for 50% of the 12th magnitude dwarf stars for an integration period of 6.5 hours. During the first 3 months of operation the photometer detected transit-like signatures from more than 200 stars. Careful examination shows that many of these events are false-positives such as small stars orbiting large stars or blends of target stars with eclipsing binary stars. Ground-based follow-up observations confirm the discovery of five new exoplanets with sizes between 0.37 andl.6 Jupiter radii (R(sub J)) and orbital periods ranging from 3.2 to 4.9 days. Ground-based observations with the Keck 1, Hobby-Ebberly, Hale, WIYN, MMT, Tillinghast, Shane, and Nordic Optical Telescopes are used to vet the planetary candidates and measure the masses of the putative planets. Observations of occultations and phase variations of hot, short-period planets such as HT-P-7b provide a probe of atmospheric properties. Asteroseismic analysis already shows the presence of p-mode oscillations in several stars. Such observations will be used to measure the mean stellar density and infer the stellar size and age. For stars too dim to permit asteroseismology, observations of the centroid motion of target stars will be used to measure the parallax and be combined with photometric measurements to estimate stellar sizes. Four open clusters are being observed to determine stellar rotation rates as a function of age and spectral type. Many different types of stellar variability are observed with unprecedented precision and over a wide range of time scales. Solar-like photometric variability of thousands of field stars is being studied to determine how photometric variability and the stellar rotation rates change with stellar age and metallicity. A wide variety of other astrophysical phenomena have also been observed. The data are being analyzed at the Ames Research Center and archived at the MAST at STScI. The Kepler Mission also supports a vigorous Guest Observer Program.

Borucki, William↗

Impact of genotype‐calling methodologies on genome‐wide association and genomic prediction in polyploids

Abstract Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost‐efficient genotyping using next‐generation sequencing. However, accurate genotype calling from next‐generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome‐wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype‐calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum , and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype‐calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost‐efficiently implement GWAS and genomic prediction in polyploid crops.

59 BASIC BIOLOGICAL SCIENCES↗