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At least 685 records · Page 38

Computing Nonlinear Power Spectra Across Dynamical Dark Energy Model Space with Neural ODEs

I show how to compute the nonlinear power spectrum across the entire $w(z)$ dynamical dark energy model space. Using synthetic ΛCDM data, I train a neural ordinary differential equation (ODE) to infer the evolution of the nonlinear matter power spectrum as a function of the background expansion and mean matter density across ∼9 Gyr of cosmic evolution. After training, the model generalises to any dynamical dark energy model parameterised by $w(z)$. With little optimisation, the neural ODE is accurate to within 4% up to $k = 5\, h\, {\mathrm Mpc}^{−1}$. Unlike simulation rescaling methods, neural ODEs naturally extend to summary statistics beyond the power spectrum that are sensitive to the growth history.

cosmology↗

Observations of the Bright Star in the Globular Cluster 47 Tucanae (NGC 104)

The Bright Star in the globular cluster 47 Tucanae (NGC 104) is a post-asymptotic giant branch (post-AGB) star of spectral type B8 III. The ultraviolet spectra of late-B stars exhibit myriad absorption features, many due to species unobservable from the ground. The Bright Star thus represents a unique window into the chemistry of 47 Tuc. We have analyzed observations obtained with the Far Ultraviolet Spectroscopic Explorer, the Cosmic Origins Spectrograph aboard the Hubble Space Telescope, and the Magellan Inamori Kyocera Echelle Spectrograph on the Magellan Telescope. By fitting these data with synthetic spectra, we determine various stellar parameters (T {sub eff} = 10,850 ± 250 K, logg=2.20±0.13) and the photospheric abundances of 26 elements, including Ne, P, Cl, Ga, Pd, In, Sn, Hg, and Pb, which have not previously been published for this cluster. Abundances of intermediate-mass elements (Mg through Ga) generally scale with Fe, while the heaviest elements (Pd through Pb) have roughly solar abundances. Its low C/O ratio indicates that the star did not undergo third dredge-up and suggests that its heavy elements were made by a previous generation of stars. If so, this pattern should be present throughout the cluster, not just in this star. Stellar-evolution models suggest that the Bright Star is powered by a He-burning shell, having left the AGB during or immediately after a thermal pulse. Its mass (0.54 ± 0.16M {sub ⊙}) implies that single stars in 47 Tuc lose 0.1–0.2 M {sub ⊙} on the AGB, only slightly less than they lose on the red giant branch.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantification of oil and gas methane emissions in the Delaware and Marcellus basins using a network of continuous tower-based measurements

Abstract. According to the United States Environmental Protection Agency (US EPA), emissions from oil and gas infrastructure contribute 30 % of all anthropogenic methane (CH4) emissions in the US. Studies in the last decade have shown emissions from this sector to be substantially larger than bottom-up assessments, including the EPA inventory, highlighting both the increased importance of methane emissions from the oil and gas sector in terms of their overall climatological impact and the need for independent monitoring of these emissions. In this study we present continuous monitoring of regional methane emissions from two oil and gas basins using tower-based observing networks. Continuous methane measurements were taken at four tower sites in the northeastern Marcellus basin from May 2015 through December 2016 and five tower sites in the Delaware basin in the western Permian from March 2020 through April 2022. These measurements, an atmospheric transport model, and prior emission fields are combined using an atmospheric inversion to estimate monthly methane emissions in the two regions. This study finds the mean overall emission rate from the Delaware basin during the measurement period to be 146–210 Mg CH4 h−1 (energy-normalized loss rate of 1.1 %–1.5 %, gas-normalized rate of 2.5 %–3.5 %). Strong temporal variability in the emissions was present, with the lowest emission rates occurring during the onset of the COVID-19 pandemic. Additionally, a synthetic model–data experiment performed using the Delaware tower network shows that the presence of intermittent sources is not a significant source of uncertainty in monthly quantification of the mean emission rate. In the Marcellus, this study finds the overall mean emission rate to be 19–28 Mg CH4 h−1 (gas-normalized loss rate of 0.30 %–0.45 %), with relative consistency in the emission rate over time. These totals align with aircraft top-down estimates from the same time periods. In both basins, the tower network was able to constrain monthly flux estimates within ±20 % uncertainty in the Delaware and ±24 % uncertainty in the Marcellus. The results from this study demonstrate the ability to monitor emissions continuously and detect changes in the emissions field, even in a basin with relatively low emissions and complex background conditions.

54 ENVIRONMENTAL SCIENCES↗

Top-level physics requirements and simulated performance of the MRSt on the National Ignition Facility

The time-resolving Magnetic Recoil Spectrometer (MRSt) for the National Ignition Facility (NIF) has been identified by the US National Diagnostic Working Group as one of the transformational diagnostics that will reshape the way inertial confinement fusion (ICF) implosions are diagnosed. The MRSt will measure the time-resolved neutron spectrum of an implosion, from which the time-resolved ion temperature, areal density, and yield will be inferred. Top-level physics requirements for the MRSt were determined based on simulations of numerous ICF implosions with varying degrees of alpha heating, P2 asymmetry, and mix. Synthetic MRSt data were subsequently generated for different configurations using Monte–Carlo methods to determine its performance in relation to the requirements. The system was found to meet most requirements at current neutron yields at the NIF. This work was supported by the DOE and LLNL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Elasticity of some mantle crystals structures. III - Spessartite-almandine garnet

Measurements of the pressure dependence of the elastic constants of spessartite-almandine garnet are given. The basis for velocity systematics among the available natural and synthetic garnet data is then examined. As for any dense oxide, the natural anion in garnet is dominant in size. The ionic sizes of the cations in the various sites are used to determine the extent to which it might be expected that garnets of different chemical formulas are analogous in elastic properties. The results are used to predict that the elastic velocities in garnet-transformed MgSiO3 are the same as those in pyrope (Mg3Al2Si3O12).

Wang, H.↗

Analysis and Interpretation of Synthetic Time Strings of Oscillation Data

Artificial strings of solar oscillation data with gaps and noise, corresponding to the output of different spatial filter functions, were analyzed. Peaks in the power spectrum are identified for values of the degree l from 0 to 18, and rotational splitting is estimated. The filters prove effective in facilitating identification of essentially all the real peaks in the power spectrum. Estimates of peak frequencies and amplitudes and rotational splitting frequencies are in reasonably good agreement with the input values. Spurious peaks in autocorrelation spectra correspond to the frequency spacing between power peaks with the same order n, differing by one or two in the degree l.

Mihalas, B. W.↗

Digital simulation of the SIR-C sensor electronics

In this paper software for simulation of the response of the SIR-C sensor to a point target is described. Synthetic SAR data is generated by passing successive chirps through a simulation of the transmitter electronics, propagation path and receiver electronics. This result is then processed with a digital correlator to yield the point target response of the system. This allows an accurate assessment of the effect of the radar design on the final image product.

Klein, Jeffrey D.↗

Use of SAR imagery and other remotely-sensed data in deriving ice information during a severe ice event on the Grand Banks (Newfoundland)

Image data from synthetic aperture radar (SAR) are used to observe an ice compaction event off the East Coast of Newfoundland in spring, 1987. The information developed from sequential SAR observations is shown to do a remarkably effective job of describing the ice conditions; the difficult variable is the ice thickness which is found to be surprisingly large (2 to 4 times the thickness predictable from thermodynamic growth alone). It may be possible to model the ice thickness using SAR-derived ice motion.

Carsey, F. D.↗

Cross-correlation analysis of on-orbit residual accelerations in Spacelab

To characterize the low-gravity environment within orbiting space laboratories, researchers are operating sensitive accelerometer systems. Transient accelerations recorded in spacecraft can have magnitudes up to 0.01 g over a wide range of frequencies. These accelerations have components in the 0.001-100-Hz range no greater in magnitude than 0.001 g. Some experiments can be sensitive to such accelerations, so investigators are interested in identifying causal relationships between accelerations and experimental results. Here, two forms of synthetic experiment data created using Spacelab 3 accelerometer data are evaluated using cross-correlation analysis. The results show that the use of cross-correlation techniques is appropriate, for specific experiment classes, for assessing relationships between both transient and oscillatory residual accelerations and experimental results recorded in a low-gravity environment.

Rogers, Melissa J. B.↗

SAR calibration and principal component analysis

Principal components analysis of ideal, complex quadpolarized synthetic aperture data tells us how the information is encoded in the eigenstructure of the data from homogeneous, distributed targets. Comparison with real data indicates distortion of the correlation matrices by system effects. The implications for measurement of the terms in the true correlation matrix are displayed. These are related to how accurately we can make inferences about the products of principle components analysis.

Quegan, S.↗

A Novel Optical/digital Processing System for Pattern Recognition

This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

Boone, Bradley G.↗

Evaluation of C-band SAR data from SAREX 1992: Tapajos study site

As part of the SAREX'92 (South American Radar Experiment), the Tapajos study site, located in Para State, Brazil was imaged by the Canada Center for Remote Sensing (CCRS) Convair 580 SAR system using a C-band frequency in HH and VV polarization and 3 different imaging modes (nadir, narrow, and wide swath). A preliminary analysis of this dataset is presented. The wide swath C-band HH polarized image was enlarged to 1:100,000 in a photographic form for manual interpretation. This was compared with a vegetation map produced primarily from Landsat Thematic Mapper (TM) data and with single-band and color composite images derived from a decomposition analysis of TM data. The Synthetic Aperture Radar (SAR) image shows well the topography and drainage network defining the different geomorphological units, and canopy texture differences which appear to be related to the size and maturity of the forest canopy. Areas of recent clearing of the primary forest can also be identified on the SAR image. The SAR system appears to be a source of information for monitoring tropical forest which is complementary to the Landsat Thematic Mapper.

Shimabukuro, Yosio Edemir↗

Aerosol Retrieval Using Synthetic Polder Multi-Angular Data

The POLarizations and Directionality of the Earth's Reflectances (POLDER) instrument onboard the Japanese ADEOS satellite offers unique possibilities for the retrieval of aerosol parameters with its polarization and multi-angular capability. In this study we examine a technique that simultaneously retrieve multiple aerosol parameters, namely asymmetry factor, single scattering albedo, surface albedo, and optical thickness. using simulated POLDER reflectances. It is found that. over dark or bright surfaces, simultaneous retrieval of multiple parameters is indeed possible, but not over surfaces with intermediate reflectivity. Among the four parameters, the single-scattering albedo is retrieved with the best accuracy and is the least vulnerable when the reflectance value is subjected to a 0.1% white noise.

Kuo, K. S.↗

On the Use of Fourier Transform Infrared (FT-IR) Spectroscopy and Synthetic Calibration Spectra to Quantify Gas Concentrations in a Fischer-Tropsch Catalyst System

One possible origin of prebiotic organic material is that these compounds were formed via Fischer-Tropsch-type (FTT) reactions of carbon monoxide and hydrogen on silicate and oxide grains in the warm, inner-solar nebula. To investigate this possibility, an experimental system has been built in which the catalytic efficiency of different grain-analog materials can be tested. During such runs, the gas phase above these grain analogs is sampled using Fourier transform infrared (FT-IR) spectroscopy. To provide quantitative estimates of the concentration of these gases, a technique in which high-resolution spectra of the gases are calculated using the high-resolution transmission molecular absorption (HITRAN) database is used. Next, these spectra are processed via a method that mimics the processes giving rise to the instrumental line shape of the FT-IR spectrometer, including apodization, self-apodization, and broadening due to the finite resolution. The result is a very close match between the measured and computed spectra. This technique was tested using four major gases found in the FTT reactions: carbon monoxide, methane, carbon dioxide, and water. For the ranges typical of the FTT reactions, the carbon monoxide results were found to be accurate to within 5% and the remaining gases accurate to within 10%. These spectra can then be used to generate synthetic calibration data, allowing the rapid computation of the gas concentrations in the FTT experiments.

Infrared Spectroscopy↗

Validation of Machine Learning Algorithms for Hyperspectral Inversion of Common Water Quality Indicators

The upcoming transition to a diverse suite hyperspectral airborne and orbiting optical sensors will provide an unprecedented opportunity to measure inland water quality characteristics at a fidelity not previously achievable. This presentation will assess prototype deep learning models trained on synthetic hyperspectral data and validated with collocated in-situ measurements. Synthesized data is becoming increasingly popular for use in data-driven approaches to complex problems, and can compliment real data to increase performance on complex and unusual phenomenon, reduce or test bias, and experiment to demonstrate explainability. We will present insights from hyperspectral inversions of Chlorophyl-a, Phycocyanin, and concentration of non-algal particles using selected orbiting and airborne sensors over diverse, optically complex aquatic scenarios. We analyze how various optical water types affect fidelity of results and where improvements can be made as we prototype for globally operational water quality algorithms which can be leveraged by upcoming hyperspectral missions such as the Surface Biology and Geology (SBG) mission.

Surface Biology and Geology (SBG)↗

Optimizing Terrain Mapping and Landing Site Detection for Autonomous UAVs

The next generation of Mars rotorcrafts requires on-board autonomous hazard avoidance landing. To this end, this work proposes a system that performs continuous multi- resolution height map reconstruction and safe landing spot detection. Structure-from-Motion measurements are aggregated in a pyramid structure using a novel Optimal Mixture of Gaus- sians formulation that provides a comprehensive uncertainty model. Our multiresolution pyramid is built more efficiently and accurately than past work by decoupling pyramid filling from the measurement updates of different resolutions.To detect the safest landing location, after an optimized hazard segmentation, we use a mean shift algorithm on multiple distance transform peaks to account for terrain roughness and uncertainty. The benefits of our contributions are evaluated on real and synthetic flight data.

Brockers, Roland↗

Unreal Engine Testbed for Computer Vision of Tall Lunar Tower Assembly

The Tall Lunar Tower project at the NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of a supervised autonomously assembly engineering development unit for tall lunar towers. The lunar south pole environment poses many challenges for robotic assembly of the tall tower, particularly to computer vision camera systems due to a high-contrast lighting environment. This paper will present an Unreal Engine 5 video game engine Lunar South Pole Lighting Testbed to simulate realistic lunar lighting conditions for synthetic image generation. The fidelity of the simulation environment is investigated by comparing the accuracy of computer vision models trained using synthetic image data and trained from real image data collected in a lunar analog environment.

Unreal Engine↗

Unreal Engine Testbed for Computer Vision of Tall Lunar Tower Assembly

The Tall Lunar Tower project at the NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of a supervised autonomously assembled engineering development unit for tall lunar towers. The lunar south pole environment poses many challenges for robotic assembly of the tall tower, particularly to computer vision camera systems due to a high-contrast lighting environment. This paper will present an Unreal Engine 5 video game engine Lunar South Pole Lighting Testbed to simulate realistic lunar lighting conditions for synthetic image generation. The fidelity of the simulation environment is investigated by comparing the accuracy of computer vision models trained using synthetic image data and trained from real image data collected in a lunar analog environment.

Unreal Engine↗