Retrieval of aerosol size distributions by inversion of simulated aureole data in the presence of multiple scattering
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Box, M. A.↗
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Negative ions in the ionospheres of planetary bodies without atmospheres
It is noted that negative ions may be formed in the ionospheres of Mercury, the moon, and Jupiter's satellites with densities of a few percent of the ionospheric electron density. Negative ions result from three mechanisms at the planetary surface: charge inversion during energetic proton scattering, with simultaneous secondary negative ion emission, and micrometeorite impacts. The density and distribution of negative ions around planetary bodies depends primarily on the negative ion lifetimes determined through photodetachment by solar radiation.
Wekhof, A.↗
SAR terrain classifier and mapper of biophysical attributes
In preparation for the launch of SIR-C/X-SAR and design studies for future orbital SAR, a program has made considerable progress in the development of an SAR terrain classifier and algorithms for quantification of biophysical attributes. The goal of this program is to produce a generalized software package for terrain classification and estimation of biophysical attributes and to make this package available to the larger scientific community. The basic elements of the SAR (Synthetic Aperture Radar) terrain classifier are outlined. An SAR image is calibrated with respect to known system and processor gains and external targets (if available). A Level 1 classifier operates on the data to differentiate: urban features, surfaces and tall and short vegetation. Level 2 classifiers further subdivide these classes on the basis of structure. Finally, biophysical and geophysical inversions are applied to each class to estimate attributes of interest. The process used to develop the classifiers and inversions is shown. Radar scattering models developed from theory and from empirical data obtained by truck-mounted polarimeters and the JPL AirSAR are validated. The validated models are used in sensitivity studies to understand the roles of various scattering sources (i.e., surface trunk, branches, etc.) in determining net backscatter. Model simulations of sigma (sup o) as functions of the wave parameters (lambda, polarization and angle of incidence) and the geophysical and biophysical attributes are used to develop robust classifiers. The classifiers are validated using available AirSAR data sets. Specific estimators are developed for each class on the basis of the scattering models and empirical data sets. The candidate algorithms are tested with the AirSAR data sets. The attributes of interest include: total above ground biomass, woody biomass, soil moisture and soil roughness.
Ulaby, Fawwaz T.↗
Scattered light in the STIS echelle modes
The Space Telescope Imaging Spectrograph (STIS) echelle spectra obtained during the Early Release Observations have non-zero residuals in the cores of saturated interstellar lines, indicating the need for a scattered light correction. A rough measure of the magnitude of the needed correction shows the ratio of the interorder to the in-order flux in different echelle modes in both pre-launch calibration images of a continuum lamp source and in post-launch images of stellar continuum sources. The interorder and in-order fluxes are computed by averaging the central 200 pixels in the dispersion direction. The amount of scattered light in the interorder region rises toward shorter wavelengths for two reasons: (1) the order separation decreases toward shorter wavelengths; and (2) the amount of echelle scattering is expected to have an inverse dependence on wavelength. At the shortest wavelengths the fraction of light scattered into the interorder region can be 10% for the Near-ultraviolet-Multi-Anode Microchannel Array (NUV-MAMA) and 15% for the Far-ultraviolet-Multi-Anode Microchannel Array (FUV-MAMA).
Landsman, W.↗
Observation and Spectral Measurements of the Crab Nebula with Milagro
The Crab Nebula was detected with the Milagro experiment at a statistical significance of 17 standard deviations over the lifetime of the experiment. The experiment was sensitive to approximately 100 GeV - 100 TeV gamma ray air showers by observing the particle footprint reaching the ground. The fraction of detectors recording signals from photons at the ground is a suitable proxy for the energy of the primary particle and has been used to measure the photon energy spectrum of the Crab Nebula between ~1 and ~100 TeV. The TeV emission is believed to be caused by inverse-Compton up-scattering scattering of ambient photons by an energetic electron population. The location of a Te V steepening or cutoff in the energy spectrum reveals important details about the underlying electron population. We describe the experiment and the technique for distinguishing gamma-ray events from the much more-abundant hadronic events. We describe the calculation of the significance of the excess from the Crab and how the energy spectrum is fit.
Abdo, A. A.↗
Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning
In this article, an innovative strategy is presented that incorporates deep auto-encoder networks into a least-squares fitting framework to address the potential inversion problem in small-angle scattering. To evaluate the performance of the proposed approach, a detailed case study focusing on charged colloidal suspensions was carried out. The results clearly indicate that a deep learning solution offers a reliable and quantitative method for studying molecular interactions. The approach surpasses existing deterministic approaches with respect to both numerical accuracy and computational efficiency. Overall, this work demonstrates the potential of deep learning techniques in tackling complex problems in soft-matter structures and beyond.
36 MATERIALS SCIENCE↗
Inversion of snow parameters by neural network with iterative inversion
The inversion of snow parameters from passive microwave remote sensing measurements is performed with a neural network trained with a dense media multiple scattering model. A constrained iterative inversion scheme is used. Inversion of four parameters is performed from five brightness temperatures. The four parameters are: mean grain size of ice particles in snow, snow density, snow temperature, and snow depth. The five brightness temperatures are that of 19-GHz vertical polarization, 19-GHz horizontal polarization, 22-GHz vertical polarization, 37-GHz vertical polarization, and 37-GHz horizontal polarization. Based on the neural network constrained iterative inversion algorithm, synthetic mapping of the terrain is performed. The retrieval of synthetic mapping has been achieved. The incorporation of ground truth information is considered.
Chen, Zhengxiao↗
Machine learning inversion of interatomic force constants from single-crystal inelastic neutron scattering
Atomic vibrations govern many macroscopic properties of materials, but experiments to comprehensively probe them remain challenging. Inelastic neutron scattering (INS) is a powerful technique to map phonon dispersions in crystals, especially when leveraging modern time-of-flight (ToF) spectrometers with large detectors. However, efficiently and robustly extracting interatomic force constants (FCs) parameterizing phonon dynamics from experimental spectra remains a bottleneck due to the complexity and high dimensionality of ToF INS datasets. Here, we present a machine learning approach for the direct inversion of FCs from single-crystal INS measurements. The framework leverages synthetic training data generated using universal machine-learned force fields and an efficient physics-based forward model. We benchmark two neural architectures–one emphasizing structured latent representation learning and the other direct, supervised spectral regression–across simulated datasets for two materials under idealized and noisy conditions. The latent-representation model is subsequently applied to experimental single-crystal INS data on germanium. The model is shown to reproduce FCs derived from both first-principles simulations and from iterative optimization, and furthermore achieves reliable inference even from sparse, single-orientation measurements representing short data acquisitions. Analysis of the learned latent space reveals semantically continuous and physically interpretable encodings that support strong cross-domain generalization. By bridging theoretical and experimental domains, we establish a path toward rapid inversion of experimental spectra and data-driven interpretation of temperature-dependent lattice dynamics.
42 ENGINEERING↗
A physical model for predicting bidirectional reflectances over bare soil
While most previous attempts to retrieve soil surface optical property characteristics have proceeded through a fitting of empirical functions to the data, an optimization technique is presently applied to a physically-based surface reflectance model developed for the study of planetary surfaces. This inversion procedure is shown to allow the direct estimation of the single-scattering coefficient, two parameters describing the 'hot spot' phenomenon, and two parameters describing the scattering phase function. A comparison of inversion technique results with both synthetic data and actual observations shows the model to be capable of predicting the observed bidirectional reflectances as well as directional-hemispherical reflectances; it can also build the complete radiance field over the upward hemisphere.
Pinty, Bernard↗
Wave multiple scattering by a finite number of unclosed circular cylinders
The boundary value problem of plane H-polarized electromagnetic wave multiple scattering by a finite number of unclosed circular cylinders is solved. The solution is obtained by two different methods: the method of successive scattering and the method of partial matrix inversion for simultaneous dual equations. The advantages of the successive scattering method are shown. Computer calculations of the suface currents and the total cross section are presented for the structure of two screens.
Veliyev, E. I.↗
Stellar occultations by turbulent planetary atmospheres. I - A heuristic scattering model. II - The Beta Scorpii events
Effects of atmospheric turbulence on stellar-occultation inversion procedures are investigated using a heuristic scattering model that is believed to reproduce the essential features of turbulence. A quantitative estimate is made of the size of the error in deducing the mean refractivity profile of a planetary atmosphere, taking into account constant as well as exponential scattering. It is shown that ordinary turbulence has no important effect on the average intensity profile in a stellar occultation but could have an important instantaneous effect. A critical examination of possible manifestations of turbulent scattering during occultations of Beta Sco by Jupiter indicates that all observed phenomena during these events can be understood in terms of scintillations produced by turbulence.
Hubbard, W. B.↗
Retrieval of aerosol characteristics from scattering and extinction measurements
The present investigation is concerned with a versatile inversion code which is capable of retrieving profiles of aerosol size distributions and concentrations from multiwavelength satellite measurements of either the scattered radiance from the earth's sunlit atmosphere in both the limb-viewing mode and downward-viewing mode, or the extinction of direct solor radiation by the earth's atmosphere. The inversion code in its present form is a composite of three subcodes. The inversion code is composed of several module algorithms for treating the inverse problem in radiative transfer through a scattering and absorbing aerosol atmosphere, which is vertically inhomogeneous, spherical, and which takes into account multiple scattering and surface albedo effects. The inversion code has been applied and tested for a number of remote sensing techniques. Examples are given concerning the retrieval results for the vertical profiles of aerosol size distribution and concentation.
Deepak, A.↗
Analytical multiple scattering correction to the Mie theory: Application to the analysis of the lidar signal
The contribution of the multiple scattering to the lidar signal is dependent on the optical depth tau. Therefore, the radar analysis, based on the assumption that the multiple scattering can be neglected is limited to cases characterized by low values of the optical depth (tau less than or equal to 0.1) and hence it exclude scattering from most clouds. Moreover, all inversion methods relating lidar signal to number densities and particle size must be modified since the multiple scattering affects the direct analysis. The essential requests of a realistic model for lidar measurements which include the multiple scattering and which can be applied to practical situations follow. (1) Requested are not only a correction term or a rough approximation describing results of a certain experiment, but a general theory of multiple scattering tying together the relevant physical parameter we seek to measure. (2) An analytical generalization of the lidar equation which can be applied in the case of a realistic aerosol is requested. A pure analytical formulation is important in order to avoid the convergency and stability problems which, in the case of numerical approach, are due to the large number of events that have to be taken into account in the presence of large depth and/or a strong experimental noise.
Flesia, C.↗
Determination of the complex refractive index and size distribution of atmospheric particulates from bistatic-monostatic lidar and solar radiometer measurements
A method is presented for inferring both the size distribution and the complex refractive index of atmospheric particulates from combined bistatic-monostatic lidar and solar radiometer observations. The basic input measurements are spectral optical depths at several visible and near-infrared wavelengths as obtained with a solar radiometer and backscatter and angular scatter coefficients as obtained from a biostatic-monostatic lidar. The spectral optical depth measurements obtained from the radiometer are mathematically inverted to infer a columnar particulate size distribution. Advantage is taken of the fact that the shape of the size distribution obtained by inverting the particulate optical depth is relatively insensitive to the particle refractive index assumed in the inversion. Bistatic-monostatic angular scatter and backscatter lidar data are then processed to extract an optimum value for the particle refractive index subject to the constraint that the shape of the particulate size distribution be the same as that inferred from the solar radiometer data. Specifically, the scattering parameters obtained from the bistatic-monostatic lidar data are compared with corresponding theoretical computations made for various assumed refractive index values. That value which yields best agreement, in a weighted least squares sense, is selected as the optimal refractive index estimate. The results of this procedure applied to a set of simulated measurements as well as to measurements collected on two separate days are presented and discussed.
Reagan, J. A.↗
Beam focusing and consequences for Doppler backscattering measurements
The phenomenon of focusing of microwave beams in a plasma near a turning-point caustic is discussed by exploiting the analytical solution to the Gaussian beam-tracing equations in the two-dimensional (2-D) linear-layer problem. The location of maximum beam focusing and the beam width at that location are studied in terms of the beam initial conditions. This focusing must be taken into account to interpret Doppler backscattering (DBS) measurements. We find that the filter function that characterises the scattering intensity contribution along the beam path through the plasma is inversely proportional to the beam width, predicting enhanced scattering from the beam focusing region. We show that the DBS signal enhancement for decreasing incident angles between the beam path and the density gradient is due to beam focusing and not due to forward scattering, as was originally proposed by (Gusakov et al., (Plasma Phys. Contr. Fusion, vol. 56, 2014, p. 0250092014, 2017); Plasma Phys. Rep. vol. 43(6), 2017, pp. 605–613). The analytic beam model is used to predict the measurement of the k y density-fluctuation wavenumber power spectrum via DBS, showing that, in an NSTX-inspired example, the spectral exponent of the turbulent, intermediate-to-high k y density-fluctuation spectrum might be quantitatively measurable via DBS, but not the spectral peak corresponding to the driving scale of the turbulent cascade.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Adjustable collimation for dark-field proton radiography contrast enhancement
A dark-field imaging condition established through pre- and post-object beam collimation has been tested for a variety of different settings at the proton radiography facility (pRad) at Los Alamos National Laboratory. This technique facilitates imaging of thin samples and materials with small areal density changes with 800 MeV protons that would otherwise appear nearly transparent for high energy protons. In the configuration that was examined, the pre-object (upstream) collimator is utilized to remove protons with large scattering angles prior to the target object. The post-object collimation entails a combination of a conventional collimator, which eliminates protons with large scattering angles after target interaction, and an inverse collimator. The inverse collimator removes unscattered protons traveling on the beam axis and those with smaller scattering angles up to a desired angle. This establishes a dark-field condition by permitting solely protons that exhibit scattering angles from target interaction within a designated range to contribute to the image. This study explores the potential of combining different sized collimators for pre- and post-object collimation. The objective is to optimize contrast for a range of samples with minimal areal density variations. A series of dark-field conditions are explored employing a remote-controlled collimator wheel and the contrast-to-noise ratio, spatial resolution, and proton transmission are compared for those combinations. It is found that the contrast-to-noise ratio can be substantially enhanced for thin samples and low areal density objects, thereby facilitating capturing high-contrast images of objects that were previously invisible to high energy protons.
43 PARTICLE ACCELERATORS↗
Tunable Nanostructures from Inverse Surfactants
Hierarchical materials in the natural world are often made through the self-assembly of amphiphilic molecules. Achieving similar structural complexity in synthetic materials requires understanding how various molecular parameters affect assembly behavior. In recent years, inverse surfactants─molecules with hydrophobic head groups and hydrophilic macromolecular tails─have been shown to self-assemble into supramolecular assemblies in aqueous solutions that show promise for a number of applications, including drug delivery. Here, we build an understanding of the morphological phase diagram of inverse surfactants using insights from scattering experiments, computer simulations, and statistical mechanics. The scattering and simulation results reveal that changing the headgroup size is an important molecular knob in controlling morphological transitions. The molecular size ratio of the hydrophobic group to the hydrophilic group emerges as a crucial dimensionless quantity in our theory and plays a determining role in setting the micelle structure and the transition from mesoscale to macroscale aggregates. Our minimal theory is able to qualitatively explain the key features of the morphological phase diagram, including the prevalence of fiber-like structures in comparison to spherical and planar micelles. Together, these findings provide a more complete picture of the molecular dependencies of assemblies of inverse surfactants, which we hope may aid in the de novo design of supramolecular structures.
Christakopoulos, Panagiotis [ORNL] (ORCID:00090004↗
Observation of polarization density waves in SrTiO 3
The nature of the incipient ferroelectric transition in SrTiO 3 has been a long-standing puzzle in condensed matter physics. One explanation involves the competition between ferroelectricity and an instability characterized by the mesoscopic modulation of the polarization. These polarization density waves, which should intensify near the quantum critical point, break local inversion symmetry and are difficult to characterize with conventional X-ray scattering methods. Here, in this study, we probe inversion symmetry breaking at finite momenta and visualize the instability of the polarization at the nanometre scale in SrTiO3 by combining a femtosecond X-ray free-electron laser with terahertz coherent control methods. We found polar-acoustic collective modes that are soft, particularly at the tens of nanometre scale. These precursor collective excitations provide evidence for the conjectured mesoscopic-modulated phase in SrTiO 3 .
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗