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At least 505 records · Page 28

Materials requirements for optical processing and computing devices

Devices for optical processing and computing systems are discussed, with emphasis on the materials requirements imposed by functional constraints. Generalized optical processing and computing systems are described in order to identify principal categories of requisite components for complete system implementation. Three principal device categories are selected for analysis in some detail: spatial light modulators, volume holographic optical elements, and bistable optical devices. The implications for optical processing and computing systems of the materials requirements identified for these device categories are described, and directions for future research are proposed.

Tanguay, A. R., Jr.↗

Corona and solar wind

The Pinhole/Occulter Facility is a powerful tool for studying the physics of the extended corona and origins of the solar wind. Spectroscopic data acquired by the P/OF coronal instruments can greatly expand empirical information about temperatures, densities, flow velocities, magnetic fields, and chemical abundances in the corona out to r or approx. 10 solar radii. Such information is needed to provide tight empirical constraints on critical physical processes involved in the transport and dissipation of energy and momentum, the heating and acceleration of plasma, and the acceleration of energetic particles. Because of its high sensitivity, high spatial and temporal resolutions, and powerful capabilities for plasma diagnostics, P/OF can significantly increase our empirical knowledge about coronal streamers and transients and thereby advance the understanding of the physics of these phenomena. P/OF observations can be used to establish the role in solar wind generation, if any, of small-scale dynamical phenomena, such as spicules, macrospicules and coronal bullets, and the role of the fine-scale structures, such as polar plumes. Finally, simultaneous measurements by the P/OF coronal and hard X-ray instruments can provide critical empirical information concerning nonthermal energy releases and acceleration of energetic particles in the corona.

Withbroe, G. L.↗

Electron density power spectrum in the local interstellar medium

Interstellar scintillation (ISS), fluctuations in the amplitude and phase of radio waves caused by scattering in the interstellar medium, is important as a diagnostic of interstellar plasma turbulence. ISS is also of interest because it is noise for other radio astronomical observations. The unifying concern is the power spectrum of the interstellar electron density. Here we use ISS observations through the nearby (less than or approximately =1 kpc) (ISM) to estimate the spectrum. From measurements of angular broadening of pulsars and extragalactic sources, decorrelation bandwidth of pulsars, refractive steering of features in pulsar dynamic spectra, dispersion measured fluctuations of pulsars, and refractive scintillation index measurements, we construct a composite structure function that is approximately power law over 2 x 10(exp 6) m less than scale less than 10(exp 13) m. The data are consistent with the structure function having a logarithmic slope versus baseline less than 2; thus there is a meaningful connection between scales in the radiowave fluctuation field and the scales in the electron density field causing the scattering. The data give an upper limit to the inner scale, l(sub o) less than or approximately 10(exp 8) m and are consistent with much smaller values. We construct a composite electron density spectrum that is approximately power law over at least the approximately = 5 decade wavenumber range 10(exp -13)/m less than wavenumber less than 10(exp -8)/m and that may extend to higher wavenumbers. The average spectral index of electron density over this wavenumber range is approximately = 3.7, very close to the value expected for a Kolmogorov process. The outer scale size, L(sub o), must be greater than or approximately = 10(exp 13) m (determined from dispersion measure fluctuations). When the ISS data are combined with measurements of differential Faraday rotation angle, and gradients in the average electron density, constraints can be put on the spectrum at much smaller wave numbers. The composite spectrum is consistent with a Kolmogorov-like power law over a huge range (10 or more decades) of spatial wavenumber with an infrared outer scale L(sub o) greater than or approximately 10(exp 18)m. This power-law subrange-expressed as ratio of outer to inner scales-is comparable to or larger than that of other naturally occurring turbulent fluids, such as the oceans or the solar wind. We outline some of the theories for generating and maintaining such a spectrum over this huge wavenumber range.

Armstrong, J. W.↗

Search for spatial variations of the H2O abundance in the lower atmosphere of Venus from NIMS-Galileo

The spectroscopic data of the Near-Infrared Mapping Spectrometer (NIMS), recorded during the Galileo flyby of Venus, are analysed to retrieve the water vapor abundance variations in the lower atmosphere of Venus at night. The 1.18 micrometer spectral window, which probes altitude levels below 20 km, is used for this purpose. Constraints on the CO2 continuum and far-wing opacity from existing ground-based high-resolution observations are included in the modelling of the NIMS spectra. The NIMS measurements can be fitted with a water vapor mixing ratio of 30 +/- 15 ppm, in agreement with analyses of ground-based nightside observations. The water vapor abundance shows no horizontal variations exceeding 20% over a wide latitude range (40 deg S, 50 deg N) on the nightside of Venus. Within the same selection of NIMS spectra, a large enhancement in the O2 fluorescence emission at 1.27 micrometer is observed at a latitude of 40 deg S, over a spatial area about 100 km wide.

Drossart, P.↗

Investigation of North American Vegetation Variability under Recent Climate: A Study Using the SSiB4/TRIFFID Biophysical/Dynamic Vegetation Model

Recent studies have shown that current dynamic vegetation models have serious weaknesses in reproducing the observed vegetation dynamics and contribute to bias in climate simulations. This study intends to identify the major factors that underlie the connections between vegetation dynamics and climate variability and investigates vegetation spatial distribution and temporal variability at seasonal to decadal scales over North America (NA) to assess a 2-D biophysical model/dynamic vegetation model's (Simplified Simple Biosphere Model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID)) ability to simulate these characteristics for the past 60 years (1948 through 2008). Satellite data are employed as constraints for the study and to compare the relationships between vegetation and climate from the observational and the simulation data sets. Trends in NA vegetation over this period are examined. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation, which describes the population dynamics of species competing for some common resource, have been identified as having major impacts on vegetation spatial distribution and obtaining proper initial vegetation conditions in SSiB4/TRIFFID. The finding that vegetation competition coefficients significantly affect vegetation distribution suggests the importance of including biotic effects in dynamical vegetation modeling. The improved SSiB4/TRIFFID can reproduce the main features of the NA distributions of dominant vegetation types, the vegetation fraction, and leaf area index (LAI), including its seasonal, interannual, and decadal variabilities. The simulated NA LAI also shows a general increasing trend after the 1970s in responding to warming. Both simulation and satellite observations reveal that LAI increased substantially in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with differentmodels and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

climate variability↗

Computational budget optimization for Bayesian parameter estimation in heavy-ion collisions

Abstract Bayesian parameter estimation provides a systematic approach to compare heavy-ion collision models with measurements, leading to constraints on the properties of nuclear matter with proper accounting of experimental and theoretical uncertainties. Aside from statistical and systematic model uncertainties, interpolation uncertainties can also play a role in Bayesian inference, if the model’s predictions can only be calculated at a limited set of model parameters. This uncertainty originates from using an emulator to interpolate the model’s prediction across a continuous space of parameters. In this work, we study the trade-offs between the emulator (interpolation) and statistical uncertainties. We perform the analysis using spatial eccentricities from the T R ENTo model of initial conditions for nuclear collisions. Given a fixed computational budget, we study the optimal compromise between the number of parameter samples and the number of collisions simulated per parameter sample. For the observables and parameters used in the present study, we find that the best constraints are achieved when the number of parameter samples is slightly smaller than the number of collisions simulated per parameter sample.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ecosystem Water‐Saving Timescale Varies Spatially With Typical Drydown Length

Abstract Stomatal optimization theory is a commonly used framework for modeling how plants regulate transpiration in response to the environment. Most stomatal optimization models assume that plants instantaneously optimize a reward function such as carbon gain. However, plants are expected to optimize over longer timescales given the rapid environmental variability they encounter. There are currently no observational constraints on these timescales. Here, a new stomatal model is developed and is used to analyze the timescales over which stomatal closure is optimized. The proposed model assumes plants maximize carbon gain subject to the constraint that they cannot draw down soil moisture below a critical value. The reward is integrated over time, after being weighted by a discount factor that represents the timescale ( τ ) that a plant considers when optimizing stomatal conductance to save water. The model is simple enough to be analytically solvable, which allows the value of τ to be inferred from observations of stomatal behavior under known environmental conditions. The model is fitted to eddy covariance data in a range of ecosystems, finding the value of τ that best predicts the dynamics of evapotranspiration at each site. Across 82 sites, the climate metrics with the strongest correlation to τ are measures of the average number of dry days between rainfall events. Values of τ are similar in magnitude to the longest such dry period encountered in an average year. The results here shed light on which climate characteristics shape spatial variations in ecosystem‐level water use strategy.

54 ENVIRONMENTAL SCIENCES↗

Enhanced Multi-Dimensional Inversion Through Target-Specific Inversion Parameter Bounds With an Application to Crosswell Electromagnetic for Sequestration Monitoring

In geophysical inversions, lower and upper model parameter bounds are a means of solution stabilization. Further, constraints that intend to let only geologically plausible inverse solutions pass are amenable to lower and upper bounds. Reliable prior information is paramount to construct such bound constraints. It is common practice to narrow and widen bound intervals for regions of, respectively, more and less certain prior information. Contrary to this practice, we experiment with widened bound intervals in zones that are poorly resolved by a given survey configuration but where prior information would suggest structural anomalies of interest. The purpose of enlarged parameter bounds that correlate spatially with predefined targets is to let the inversion explore a larger solution space, thus increasing the potential to resolve otherwise hidden anomalies. Application of the method is based on a carbon-sequestration baseline (pre-injection) crosswell electromagnetic (EM) field survey at the Containment and Monitoring Institute Field Research Station (Alberta, Canada), where impeded measurements led to generally reduced sensitivities for the interwell region. Synthetic-data proofs of concept use augmented bounds designed to boost the resolution of artificial plume targets, indicating an enhanced illumination compared to constant bounds. Comparative field data inversions with spatially variable bounds constructed from prior resistivity and velocity information highlight non-horizontal baseline structures.

3-D electrical resistivity imaging↗

Global Dust Cycle and Direct Radiative Effect in E3SM Version 1: Impact of Increasing Model Resolution

Quantification of dust aerosols in Earth System Models (ESMs) has important implications for water cycle and biogeochemistry studies. This study examines the global life cycle and direct radiative effects (DREs) of dust in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1), and the impact of increasing model resolution both horizontally and vertically. The default 1° E3SMv1 captures the spatial and temporal variability in the observed dust aerosol optical depth (DAOD) reasonably well, but overpredicts dust absorption in the shortwave (SW). Simulations underestimate the dust vertical and long-range transport, compared with the satellite dust extinction profiles. After updating dust refractive indices and correcting for a bias in partitioning size-segregated emissions, both SW cooling and longwave (LW) warming of dust simulated by E3SMv1 are increased and agree better with other recent studies. The estimated net dust DRE of –0.42 Wm –2 represents a stronger cooling effect than the observationally based estimate –0.2 Wm –2 (–0.48 to +0.2), due to a smaller LW warming. Constrained by a global mean DAOD, model sensitivity studies of increasing horizontal and vertical resolution show strong influences on the simulated global dust burden and lifetime primarily through the change of dust dry deposition rate; there are also remarkable differences in simulated spatial distributions of DAOD, DRE, and deposition fluxes. Thus, constraining the global DAOD is insufficient for accurate representation of dust climate effects, especially in transitioning to higher- or variable-resolution ESMs. Better observational constraints of dust vertical profiles, dry deposition, size, and LW properties are needed.

54 ENVIRONMENTAL SCIENCES↗

What exactly does Bekenstein bound?

The Bekenstein bound posits a maximum entropy for matter with finite energy confined to a spatial region. It is often interpreted as a fundamental limit on the information that can be stored by physical objects. In this work, we test this interpretation by asking whether the Bekenstein bound imposes constraints on a channel's communication capacity, a context in which information can be given a mathematically rigorous and operationally meaningful definition. We study specifically the Unruh channel that describes a stationary Alice exciting different species of free scalar fields to send information to an accelerating Bob, who is confined to a Rindler wedge and exposed to the noise of Unruh radiation. We show that the classical and quantum capacities of the Unruh channel obey the Bekenstein bound that pertains to the decoder Bob. In contrast, even at high temperatures, the Unruh channel can transmit a significant number of zero-bits , which are quantum communication resources that can be used for quantum identification and many other primitive protocols. Therefore, unlike classical bits and qubits, zero-bits and their associated information processing capability are generally not constrained by the Bekenstein bound. However, we further show that when both the encoder and the decoder are restricted, the Bekenstein bound does constrain the channel capacities, including the zero-bit capacity.

Hayden, Patrick [Stanford University, CA (United S↗

Io - Energy constraints and plume volcanism

Observational and theoretical considerations, including near-surface energy constraints, suggest a model of Io that features a surface layer of sulfur overlying an active silicate crust. Such a model would imply frequent contact between silicate magma intrusions and the sulfur layer. This contact could produce volcanic plumes driven by high-temperature sulfur vapor. Plumes driven by sulfur vapor meet observational constraints for a wide range of possible conditions, in contrast to the special conditions required for plume generation by SO2. Characteristics of the two models are compared, and it is suggested that high-spatial-resolution infrared radiometry could identify the driving volatile.

Reynolds, R. T.↗

A broad-band microseismometer for planetary operations

There has recently been renewed interest in the development of instrumentation for making measurements on the surface of Mars. This is due to the Mars Environmental Survey (MESUR) Mission, for which approximately 16 small, long-lived (2-10 years), relatively inexpensive surface stations will be deployed in a planet-wide network. This will allow the investigation of processes (such as seismology and meteorology) which require the simultaneous measurement of phenomena at many widely spaced locations on the surface over a considerable length of time. Due to the large number of vehicles involved, the mass, power, and cost of the payload will be severely constrained. A seismometer has been identified as one of the highest priority instruments in the MESUR straw-man payload. The requirements for an effective seismic experiment on Mars place a number of constraints on any viable sensor design. First, a large number of sensors must be deployed in a long-lived global network in order to be able to locate many events reliably, provide good spatial sampling of the interior, and increase the probability of seismic detection in the event of localized seismicity and/or high attenuation. From a practical standpoint, this means that individual surface stations will necessarily be constrained in terms of cost, mass, and power. Landing and thermal control systems will probably be simple, in order to minimize cost, resulting in large impact accelerations and wide daily and seasonal thermal swings. The level of seismic noise will determine the maximum usable sensitivity for seismometer. Unfortunately, the ambient seismic noise level for Mars is not well known. However lunar seismic noise levels are several orders of magnitude below that of the Earth. Sensitivities on the order of 10(exp -11)g over a bandwidth of .04 to 20 Hz are thought to be necessary to fulfill the science objectives for a seimometer placed on the Martian surface. Silicon micromachined sensor technology offers techniques for the fabrication of monolithic, robust, compact, lower power and mass accelerometers. Conventional micro-machined accelerometers have been developed and are commercially available for high frequency and large acceleration measurements. The new seismometer we are developing incorporates certain principles of conventional silicon micromachined accelerometer technology. However, currently available silicon micromachined sensors offer inadequate sensitivity and bandwidth for the Mars seismometer application. Our implementation of an advanced silicon micromachined seismometer is based on principles recently developed at JPL for high-sensitivity position sensor technology.

Banerdt, W. B.↗

Finite Element Model Development and Validation for Aircraft Fuselage Structures

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results. The increased frequency range results in a corresponding increase in the number of modes, modal density and spatial resolution requirements. In this study, conventional modal tests using accelerometers are complemented with Scanning Laser Doppler Velocimetry and Electro-Optic Holography measurements to further resolve the spatial response characteristics. Whenever possible, component and subassembly modal tests are used to validate the finite element models at lower levels of assembly. Normal mode predictions for different finite element representations of components and assemblies are compared with experimental results to assess the most accurate techniques for modeling aircraft fuselage type structures.

Buehrle, Ralph D.↗

New Analysis of Lunar Prospector Radio Tracking Data Brings the Nearside Gravity Field of the Moon with an Unprecedented Resolution

A new analysis of the Doppler tracking data from the Lunar Prospector mission in 1999 revealed a number of previously-unseen gravity anomalies at spatial scales as small as 27 km over the nearside. The tracking data at low altitudes (50 km or below) were better analyzed to resolve the nearside features without dampening from a power law constraint, by partitioning the gravity parameters concentrated on either the nearside or farside. The resulting model presents gravity anomalies correlated with topography with a correlation coefficient of 0.7 or higher from degree 50 to 150, the widest bandwidth yet. The gravity-topography admittance of approx. 70 mGal/km is found from numerous craters of which diameters are 60 km or less. In addition, the new model produces orbits that fit to independent radio tracking data from the Lunar Reconnaissance Orbiter and Kaguya (SELENE) better than previous gravity models. This high-resolution model can be of immediate use to geophysical analysis of small craters. Our technique could be applied to an upcoming mission, the Gravity Recovery And Interior Laboratory and useful to extract short wavelength signals from the MESSENGER Doppler data.

Han, Shin-Chan↗

Coupled Retrieval of Aerosol Properties and Surface Reflection Using the Airborne Multi-Angle SpectroPolarimetric Imager (AirMSPI)

The Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 10 km and is observed from 9 view angles between ±67° off of nadir. We have developed an efficient and flexible code that uses the information content of AirMSPI data for a coupled retrieval of aerosol properties and surface reflection. The retrieval was built based on the multi-pixel optimization concept, with the use of a hybrid radiative transfer model that combines the Markov Chain and adding/doubling methods. The convergence and robustness of our algorithm is ensured by applying constraints on (a) the spectral variation of the Bidirectional Polarization Distribution Function (BPDF) and angular shape of the Bidirectional Reflectance Distribution Function (BRDF); (b) the spectral variation of aerosol optical properties; and (c) the spatial variation of aerosol parameters across neighboring image pixels. Our retrieval approach has been tested using over 20 AirMSPI datasets having low to moderately high aerosol loadings (~0.02<AOD550-nm<~0.45) and acquired during several field campaigns. Results are compared with AERONET aerosol reference data. We also explore the benefits of AirMSPI’s ultraviolet and polarimetric bands as well as the use of multiple view angles.

Xu, Feng↗

Space-based Passive Aerosol Remote Sensing from the Multi-angle Imaging SpectroRadiometer (MISR) Aboard NASA’s Terra Satellite

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been acquiring multi-angle imagery of the Earth aboard NASA’s Terra satellite since February 2000, providing an ongoing record of atmosphere and surface properties more than two decades long. MISR offers a combination of moderately high spatial resolution imagery at nine view angles in each of four visible/near-infrared spectral bands, global coverage about once per week, and carefully maintained onboard radiometric calibration. Unique algorithms retrieve aerosol column-amount and constraints on particle microphysical and optical properties, as well as the heights and motion vectors of aerosol plumes from sources such as wildfires, volcanic eruptions, and dust storms. Applications of MISR aerosol data to climate and air quality are discussed here along with a summary of some key scientific findings enabled by the instrument’s unique measurement approach.

aerosols↗

Global Dust Cycle and Direct Radiative Effect in E3SM Version 1: Impact of Increasing Model Resolution

Quantification of dust aerosols in Earth System Models (ESMs) has important implications for water cycle and biogeochemistry studies. This study examines the global life cycle and direct radiative effects (DREs) of dust in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1), and the impact of increasing model resolution both horizontally and vertically. The default 1° E3SMv1 captures the spatial and temporal variability in the observed dust aerosol optical depth (DAOD) reasonably well, but overpredicts dust absorption in the shortwave (SW). Simulations underestimate the dust vertical and long-range transport, compared with the satellite dust extinction profiles. After updating dust refractive indices and correcting for a bias in partitioning size-segregated emissions, both SW cooling and longwave (LW) warming of dust simulated by E3SMv1 are increased and agree better with other recent studies. The estimated net dust DRE of −0.42 Wm−2 represents a stronger cooling effect than the observationally based estimate −0.2 Wm−2 (−0.48 to +0.2), due to a smaller LW warming. Constrained by a global mean DAOD, model sensitivity studies of increasing horizontal and vertical resolution show strong influences on the simulated global dust burden and lifetime primarily through the change of dust dry deposition rate; there are also remarkable differences in simulated spatial distributions of DAOD, DRE, and deposition fluxes. Thus, constraining the global DAOD is insufficient for accurate representation of dust climate effects, especially in transitioning to higher- or variable-resolution ESMs. Better observational constraints of dust vertical profiles, dry deposition, size, and LW properties are needed.

dust aerosol↗

Meta Biome: a multiscale model integrating agent-based and metabolic networks to reveal spatial regulation in gut mucosal microbial communities

ABSTRACT Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing microenvironmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology, as it offers new insights into predicting and analyzing microbial communities. IMPORTANCE Our study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally. Key findings from our model include the following: (i) prediction of metabolic cross-feeding and spatial organization in multi-species communities, (ii) insights into how oxygen gradients and nutrient availability shape community composition in different gut regions, and (iii) identification of spatiallyregulated metabolic pathways and enzymes inE. coli. We believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

Microbiology↗