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At least 361 records · Page 20

Deep Bayesian local crystallography

Abstract The advent of high-resolution electron and scanning probe microscopy imaging has opened the floodgates for acquiring atomically resolved images of bulk materials, 2D materials, and surfaces. This plethora of data contains an immense volume of information on materials structures, structural distortions, and physical functionalities. Harnessing this knowledge regarding local physical phenomena necessitates the development of the mathematical frameworks for extraction of relevant information. However, the analysis of atomically resolved images is often based on the adaptation of concepts from macroscopic physics, notably translational and point group symmetries and symmetry lowering phenomena. Here, we explore the bottom-up definition of structural units and symmetry in atomically resolved data using a Bayesian framework. We demonstrate the need for a Bayesian definition of symmetry using a simple toy model and demonstrate how this definition can be extended to the experimental data using deep learning networks in a Bayesian setting, namely rotationally invariant variational autoencoders.

36 MATERIALS SCIENCE↗

MagAO Observations of the Binary Microlens OGLE-2014-BLG-1050 Prefer the Higher-mass Solution

We report adaptive optics (AO) follow-up imaging of OGLE-2014-BLG-1050, which is the second binary microlensing event with space-based parallax measurements. The degeneracy in microlens parallax π {sub E} led to two sets of solutions, either a ∼ (0.9, 0.35)M {sub ⊙} binary at ∼3.5 kpc or a ∼(0.2, 0.07)M {sub ⊙} binary at ∼1.1 kpc. We measure the flux blended with the microlensed source by conducting Magellan AO observations, and find that the blending is consistent with the predicted lens flux from the higher-mass solution. From the combination of the AO flux measurement together with previous lensing constraints, it is estimated that the lens system consists of a 1.05{sub −0.07}{sup +0.08} M{sub ⊙} primary and a 0.38{sub −0.06}{sup +0.07}M{sub ⊙} secondary at 3.43{sub −0.21}{sup +0.19} kpc.

47 OTHER INSTRUMENTATION↗

Satellite monitoring of sea surface pollution

The author has identified the following significant results. Image processing techniques developed are well adapted to the exploration and isolation of local areas which exhibit small temperature differences between themselves and their surroundings. In the worst case of imagery of small areal extent of sea surface having no coastal boundary in the area, there is yet no method of distinguishing unambiguously an oil spill from fog, cloud, the effect produced by shallow sediments, or the effects of naturally occuring thermal fronts. In the case of uniform slicks of liquid North Sea oil in still air, laboratory simulation experiments show that, for oil thicknesses in excess of 1 or 2 mm, there is, under equilibrium conditions, little dependence of oil surface temperature on the thickness of the oil layer. The surface temperature of oil is consistently higher than that of water, the difference being about 1 K at low values of relative humidity, but tending to increase as the relative humidity increases.

Fielder, G.↗

Isolating Supports for X-Ray Mirrors

Simple concept reduces effects of gravity, temperature and magnetism. Single circumferential ring supports fused-quartz mirror in high-resolution x-ray telescope. Adaptable to such terrestrial instruments as imaging devices and spectroscopes.

Cohen, L. M.↗

Estimation of Dynamical Parameters in Atmospheric Data Sets

In this study a new technique is used to derive dynamical parameters out of atmospheric data sets. This technique, called the structure tensor technique, can be used to estimate dynamical parameters such as motion, source strengths, diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. The fundamental algorithm will be extended to the analysis of multi- channel (e.g. multi trace gas) image sequences and to provide solutions to the extended aperture problem. In this study sensitivity studies have been performed to determine the usability of this technique for data sets with different resolution in time and space and different dimensions.

Wenig, Mark O.↗

Detecting Edges in Images by Use of Fuzzy Reasoning

A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image. During initial processing of image data at a low level of abstraction, the nature of the data is indeterminate. Fuzzy reasoning is used in the present method because it affords an ability to construct useful abstractions from approximate, incomplete, and otherwise imperfect sets of data. Humans are able to make some sense of even unfamiliar objects that have imperfect high-level representations. It appears that to perceive unfamiliar objects or to perceive familiar objects in imperfect images, humans apply heuristic algorithms to understand the images

Dominguez, Jesus A.↗

Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System

A radio receiver system that features enhanced capabilities for remote sensing by use of reflected Global Positioning System (GPS) signals has been developed. This system was designed primarily for ocean altimetry, but can also be used for scatterometry and bistatic synthetic-aperture radar imaging. Moreover, it could readily be adapted to utilize navigation-satellite systems other than the GPS, including the Russian Global Navigation Satellite System GLONASS) and the proposed European Galileo system. This remote-sensing system offers both advantages and disadvantages over traditional radar altimeters: One advantage of GPS-reflection systems is that they cost less because there is no need to transmit signals. Another advantage is that there are more simultaneous measurement opportunities - one for each GPS satellite in view. The primary disadvantage is that in comparison with radar signals, GPS signals are weaker, necessitating larger antennas and/or longer observations. This GPS-reflection remote-sensing system was tested in aircraft and made to record and process both (1) signals coming directly from GPS satellites by means of an upward-looking antenna and (2) GPS signals reflected from the ground by means of a downward-looking antenna. In addition to performing conventional GPS processing, the system records raw signals for postprocessing as required.

Lowe, Stephen↗

A Magnified View of the Kinematics and Morphology of RCSGA 032727-132609: Zooming in on a Merger at z = 1.7

We present a detailed analysis of multi-wavelength Hubble Space Telescope/Wide Field Camera 3 (WFC3) imaging and Keck/OSIRIS near-infrared adaptive optics-assisted integral field spectroscopy for a highly magnified lensed galaxy at z = 1.70. This young starburst is representative of ultraviolet-selected star-forming galaxies (SFGs) at z approx. 2 and contains multiple individual star-forming regions. Due to the lensing magnification, we can resolve spatial scales down to 100 pc in the source plane of the galaxy. The velocity field shows disturbed kinematics suggestive of an ongoing interaction and there is a clear signature of a tidal tail. We constrain the age, reddening, star formation rate, and stellar mass of the star-forming clumps from spectral energy distribution (SED) modeling of the WFC3 photometry and measure their H(alpha) luminosity, metallicity, and outflow properties from the OSIRIS data.With strong star-formation-driven outflows in four clumps, RCSGA0327 is the first high-redshift SFG at stellar mass <10(exp 10) Stellar Mass with spatially resolved stellar winds. We compare the H(alpha) luminosities, sizes, and dispersions of the star-forming regions with other high-z clumps as well as local giant H(II) regions and find no evidence for increased clump star formation surface densities in interacting systems, unlike in the local universe. Spatially resolved SED modeling unveils an established stellar population at the location of the largest clump and a second mass concentration near the edge of the system that is not detected in H(alpha) emission. This suggests a picture of an equal-mass mixed major merger, which has not triggered a new burst of star formation or caused a tidal tail in the gas-poor component.

Magnified↗

Imaging Spectrometers Using Concave Holographic Gratings

Imaging spectroscopy combines the spatial attributes of imaging with the compositionally diagnostic attributes of spectroscopy. For spacebased remote sensing applications, mass, size, power, data rate, and application constrain the scanning approach. For the first three approaches, substantial savings in mass and size of the spectrometer can be achieved in some cases with a concave holographic grating and careful placement of an order-sorting filter. A hologram etched on the single concave surface contains the equivalent of the collimating, dispersing, and camera optics of a conventional grating spectrometer and provides substantial wavelength dependent corrections for spherical aberrations and a flat focal field. These gratings can be blazed to improve efficiency when used over a small wavelength range or left unblazed for broadband uniform efficiency when used over a wavelength range of up to 2 orders. More than 1 order can be imaged along the dispersion axis by placing an appropriately designed step order-sorting filter in front of the one- or two-dimensional detector. This filter can be shaped for additional aberration corrections. The VIRIS imaging spectrometer based on the broadband design provides simultaneous imaging of the entrance slit from lambda = 0.9 to 2.6 microns (1.5 orders) onto a 128 x 128 HgCdTe detector (at 77 K). The VIRIS spectrometer was used for lunar mapping with the UH 24.in telescope at Mauna Kea Observatory. The design is adaptable for small, low mass, space based imaging spectrometers.

Gradie, J.↗

The CHARIS IFS for high contrast imaging at Subaru

The Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) is an integral field spectrograph (IFS) being built for the Subaru telescope. CHARIS will take spectra of brown dwarfs and hot Jovian planets in the coronagraphic image provided by the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) and AO188 adaptive optics systems. The system is designed to detect objects five orders of magnitude dimmer than their parent star down to an 80 milliarcsecond inner working angle. For characterization, CHARIS has a high-resolution prism providing an average spectral resolution of R82, R69, and R82 in J, H, and K bands respectively. The so-called discovery mode uses a second low-resolution prism with an average spectral resolution of R19 spanning 1.15-2.37 microns (J+H+K bands). This is unique compared to other high contrast IFS designs. It augments low inner working angle performance by reducing the separation at which we can rely on spectral differential imaging. The principal challenge for a high-contrast IFS is quasi-static speckles, which cause undue levels of spectral crosstalk. CHARIS has addressed this through several key design aspects that should constrain crosstalk between adjacent spectral features to be below 1%. Sitting on the Nasmyth platform, the alignment between the lenslet array, prism, and detector will be highly stable, key for the performance of the data pipeline. Nearly every component has arrived and the project is entering its final build phase. Here we review the science case, the resulting design, status of final construction, and lessons learned that are directly applicable to future exoplanet instruments.

Subaru Coronagraphic Extreme Adaptive Optics (SCEx↗

High-Resolution Optical and Near-Infrared Imaging of Young Circumstellar Disks

In the past five years, observations at optical and near-infrared wavelengths obtained with the Hubble Space Telescope and ground-based adaptive optics have provided the first well-resolved images of young circumstellar disks which may form planetary systems. We review these two observational techniques and highlight their results by presenting prototype examples of disks imaged in the Taurus-Auriga and Orion star-forming regions. As appropriate, we discuss the disk parameters that may be typically derived from the observations, as well as the implications that the observations may have on our understanding of, for example, the role of the ambient environment in shaping the disk evolution. We end with a brief summary of the prospects for future improvements in space- and ground-based optical/IR imaging techniques, and how they may impact disk studies.

McCaughrean, Mark↗

Assessing the Relationships Between Sensorimotor Biomarkers and Post-Landing Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study is to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts are recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests include assessments of sensory dependency and adaptability. Visual dependency involves treadmill walking while viewing a moving virtual visual scene. Vestibular thresholds are measured while seated during lateral translations. Proprioception dependency is measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability is performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms. The neuroimaging tests will characterize individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests will utilize saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Twenty-one ISS crewmembers have been tested to date, including 6 from this past year after testing resumed post-COVID. This cohort includes 9 first-time fliers, 4F, and mission durations lasting 182 ± 32 days, mean ± std. We are utilizing a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There is considerable variability among the post-flight performance outcomes for the 21 participants to date. Based on a partial sample using an ordinal scale survey, 80% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. There are apparent relationships between individual measures and specific post-flight outcome measures; however, additional data is needed to draw conclusions. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. We expect that understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance will improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

S J Wood↗

Adaptive Antenna Pattern Notching of Interference in Synthetic Aperture Radar Data Using Digital Beamforming

Radio Frequency Interference (RFI) is a growing problem in Synthetic Aperture Radar (SAR)systems as scientific motivations push the radars to lower frequencies and as more wireless services share the frequency spectrum. New, advanced SAR instruments, such as NASA's EcoSAR, DBSAR and DLR's Tandem-L mission, employ a multichannel architecture capable of Digital Beamforming (DBF). Radars with DBF are capable of notching the antenna pattern in specific directions, which can be utilized to suppress RFI on board or in post-processing. A well-researched beamformer for this purpose is the Minimum Variance Distortionless Response (MVDR) Beamformer. However, the number of interferers that can be removed through notching is limited by the number of receive channels. It is therefore essential to adaptively change the antenna pattern notching throughout the image in time and frequency for the best results with a given number of receive channels. In this paper, we present several methods to achieve this notching by making use of the spatial SAR signal distribution in range time, range frequency, azimuth time and azimuth Doppler that is inherent to the SAR imaging geometry. Because this distribution is time-variable and yet predictable, it can be used to improve the angle of arrival estimation of the RFI and the adaptive notching. The presented methods can be applied to a Digital Beamforming (DBF) SAR signal with multiple channels in elevation and/or in azimuth. Simulations show that the proposed methods increase the ability to notch out-of-swath interference from multiple directions and lessen the impact on in-swath interference. The improvement of the interferometric coherence for a single-pass interferogram acquired by NASA's EcoSAR system (capable of DBF in elevation) is demonstrated. The removal of periodic RFI artifacts is achieved.

RFI↗

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗

Seismicity-constrained fault detection and characterization with a multitask machine learning model

Geological fault detection and characterization are crucial for understanding subsurface dynamics across scales. While methods for fault delineation based on either seismicity location analysis or seismic image reflector discontinuity are well-established, a systematic approach that integrates both data types remains absent. We develop a novel machine learning model that unifies seismic reflector images and seismicity location information to automatically identify geological faults and characterize their geometrical properties. The model encodes a seismic image and a seismicity location image separately, and fuses the encoded features with a spatial-channel attention fusion module to improve the learning of important features in both inputs. We design an automated strategy to generate high-quality synthetic training data and labels. To improve the realism of the seismicity location image, we include random seismicity noise and missing seismicity location associated with some of the faults. We validate the model’s efficacy and accuracy using synthetic data examples and two field data examples. Moreover, we show that fine-tuning the trained model with a small, domain-specific dataset enhances its fidelity for field data applications. The results demonstrate that integrating seismicity location and seismic images into a unified framework allows the end-to-end neural network to achieve higher fidelity and accuracy in delineating subsurface faults and their geometrical properties compared with image-only fault detection methods. Our approach offers an adaptive data-driven tool for geological fault characterization and seismic hazard mitigation, bridging the gap between seismicity location and image-based fault detection methods.

58 GEOSCIENCES↗