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Polarization of bremsstrahlung at electron scattering in an anisotropic medium

Bremsstrahlung from relativistic electrons is considered under conditions when some transverse direction of momentum transfer is statistically preferred. It is shown that in the dipole approximation all the medium anisotropy effects can be accumulated into a special modulus-bound transverse vector, N. To exemplify a target with N{sup 2}{approx}1, we calculate radiation from an electron incident at a small angle on an atomic row in an oriented crystal. Radiation intensity and polarization dependencies on the emission angle and frequency for constant N are investigated. Net polarization for the angle-integral cross section is evaluated, which appears to be proportional to N{sup 2}/2, and decreases with the increase of the photon energy fraction. A prominent feature of the radiation angular distribution is the existence of an angle at which the radiation may be completely polarized, in spite of the target complete or partial isotropy; that owes to existence of an origin-centered tangential circle for polarization in the fully differential radiation probability kernel. Possibilities for utilizing various properties of the polarized bremsstrahlung flux for preparation of polarized photon beams and for probing intrinsic anisotropy of the medium are analyzed.

74 ATOMIC AND MOLECULAR PHYSICS↗

Xyce parallel electronic simulator : users' guide.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers; (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. (3) Device models which are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only); and (4) Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory.

99 GENERAL AND MISCELLANEOUS↗

MO-E-18C-04: Advanced Computer Simulation and Visualization Tools for Enhanced Understanding of Core Medical Physics Concepts

Purpose: Most medical physics programs emphasize proficiency in routine clinical calculations and QA. The formulaic aspect of these calculations and prescriptive nature of measurement protocols obviate the need to frequently apply basic physical principles, which, therefore, gradually decay away from memory. E.g. few students appreciate the role of electron transport in photon dose, making it difficult to understand key concepts such as dose buildup, electronic disequilibrium effects and Bragg-Gray theory. These conceptual deficiencies manifest when the physicist encounters a new system, requiring knowledge beyond routine activities. Methods: Two interactive computer simulation tools are developed to facilitate deeper learning of physical principles. One is a Monte Carlo code written with a strong educational aspect. The code can “label” regions and interactions to highlight specific aspects of the physics, e.g., certain regions can be designated as “starters” or “crossers,” and any interaction type can be turned on and off. Full 3D tracks with specific portions highlighted further enhance the visualization of radiation transport problems. The second code calculates and displays trajectories of a collection electrons under arbitrary space/time dependent Lorentz force using relativistic kinematics. Results: Using the Monte Carlo code, the student can interactively study photon and electron transport through visualization of dose components, particle tracks, and interaction types. The code can, for instance, be used to study kerma-dose relationship, explore electronic disequilibrium near interfaces, or visualize kernels by using interaction forcing. The electromagnetic simulator enables the student to explore accelerating mechanisms and particle optics in devices such as cyclotrons and linacs. Conclusion: The proposed tools are designed to enhance understanding of abstract concepts by highlighting various aspects of the physics. The simulations serve as virtual experiments that give deeper and long lasting understanding of core principles. The student can then make sound judgements in novel situations encountered beyond routine clinical activities.

60 APPLIED LIFE SCIENCES↗

Verification of a Configuration Space Method for Evaluating the All-Orders Linear Kinetic Plasma Response to RF Power

Progress towards verification of a configuration space algorithm for evaluating the linear kinetic plasma current response to applied radio-frequency power is presented. This follows a previously published [1] verification of the parallel-only response, by verifying the perpendicular response required for much of the ion-and electron-cyclotron range of frequencies. In particular, we use the Colestock-Kashuba fast-wave to ion-Bernstein-wave benchmark [2] where we show that the Kinetic-J computational kernel is able to reproduce a known reference solution calculated via the AORSA full-wave code [3]. We also discuss the computational and scaling aspects of this novel approach, as well as the difficulties presented by the temporal scales in this multi-species problem.

Green, David↗

THE ADJOINT METHOD APPLIED TO TIME-DISTANCE HELIOSEISMOLOGY

For a given misfit function, a specified optimality measure of a model, its gradient describes the manner in which one may alter properties of the system to march toward a stationary point. The adjoint method, arising from partial-differential-equation-constrained optimization, describes a means of extracting derivatives of a misfit function with respect to model parameters through finite computation. It relies on the accurate calculation of wavefields that are driven by two types of sources, namely, the average wave-excitation spectrum, resulting in the forward wavefield, and differences between predictions and observations, resulting in an adjoint wavefield. All sensitivity kernels relevant to a given measurement emerge directly from the evaluation of an interaction integral involving these wavefields. The technique facilitates computation of sensitivity kernels (Frechet derivatives) relative to three-dimensional heterogeneous background models, thereby paving the way for nonlinear iterative inversions. An algorithm to perform such inversions using as many observations as desired is discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal relaxation and the complete set of second-order transport coefficients for the unitary Fermi gas from kinetic theory

We compute the complete set of second-order transport coefficients of the unitary Fermi gas, a dilute gas of spin-1/2 particles interacting via an 𝑠 -wave interaction tuned to infinite scattering length. The calculation is based on kinetic theory and the Chapman-Enskog method at second order in the Knudsen expansion. We take into account the exact two-body collision integral. We extend previous results on second-order coefficients related to shear stress by including terms related to heat flow and gradients of the fugacity. We confirm that the thermal relaxation time is given by the simple estimate 𝜏 𝜅 = 𝜅⁢𝑚/(𝑐 𝑃 ⁢𝑇) even if the full collision kernel is taken into account. Furthermore, 𝜅 is the thermal conductivity, 𝑚 is the mass of the particles, 𝑐𝑃 is the specific heat at constant pressure, and 𝑇 is the temperature.

Kinetic theory↗

Development of activity pencil beam algorithm using measured distribution data of positron emitter nuclei generated by proton irradiation of targets containing {sup 12}C, {sup 16}O, and {sup 40}Ca nuclei in preparation of clinical application

Purpose: The purpose of this study is to develop a new calculation algorithm that is satisfactory in terms of the requirements for both accuracy and calculation time for a simulation of imaging of the proton-irradiated volume in a patient body in clinical proton therapy. Methods: The activity pencil beam algorithm (APB algorithm), which is a new technique to apply the pencil beam algorithm generally used for proton dose calculations in proton therapy to the calculation of activity distributions, was developed as a calculation algorithm of the activity distributions formed by positron emitter nuclei generated from target nuclear fragment reactions. In the APB algorithm, activity distributions are calculated using an activity pencil beam kernel. In addition, the activity pencil beam kernel is constructed using measured activity distributions in the depth direction and calculations in the lateral direction. {sup 12}C, {sup 16}O, and {sup 40}Ca nuclei were determined as the major target nuclei that constitute a human body that are of relevance for calculation of activity distributions. In this study, ''virtual positron emitter nuclei'' was defined as the integral yield of various positron emitter nuclei generated from each target nucleus by target nuclear fragment reactions with irradiated proton beam. Compounds, namely, polyethylene, water (including some gelatin) and calcium oxide, which contain plenty of the target nuclei, were irradiated using a proton beam. In addition, depth activity distributions of virtual positron emitter nuclei generated in each compound from target nuclear fragment reactions were measured using a beam ON-LINE PET system mounted a rotating gantry port (BOLPs-RGp). The measured activity distributions depend on depth or, in other words, energy. The irradiated proton beam energies were 138, 179, and 223 MeV, and measurement time was about 5 h until the measured activity reached the background level. Furthermore, the activity pencil beam data were made using the activity pencil beam kernel, which was composed of the measured depth data and the lateral data including multiple Coulomb scattering approximated by the Gaussian function, and were used for calculating activity distributions. Results: The data of measured depth activity distributions for every target nucleus by proton beam energy were obtained using BOLPs-RGp. The form of the depth activity distribution was verified, and the data were made in consideration of the time-dependent change of the form. Time dependence of an activity distribution form could be represented by two half-lives. Gaussian form of the lateral distribution of the activity pencil beam kernel was decided by the effect of multiple Coulomb scattering. Thus, the data of activity pencil beam involving time dependence could be obtained in this study. Conclusions: The simulation of imaging of the proton-irradiated volume in a patient body using target nuclear fragment reactions was feasible with the developed APB algorithm taking time dependence into account. With the use of the APB algorithm, it was suggested that a system of simulation of activity distributions that has levels of both accuracy and calculation time appropriate for clinical use can be constructed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

3D Shortwave Radiative Kernels of Marine Boundary-layer Clouds Using Scanning Radar/Lidar and Array Spectroradiometer

This project set out to use synergetic measurements from the ARM program to observe 3D cloud field observations, and to investigate how inadequate treatment of the observed 3D characteristics of clouds in models may impact estimates of low-cloud feedback magnitude. The project comprises three components, including 1) retrieving cloud and precipitation properties, 2) developing fast radiative transfer code incorporating 3D cloud effects, and 3) estimating 3D effects/impacts on a global scale. This report documents our main research outcomes. Specifically, a novel cloud retrieval method is developed, allowing us to better characterize cloud population and sizes, drizzle properties and precipitation formation, and to better understand their interactions with aerosols. These observed 3D cloud fields were used in a fast radiative transfer code, helping discover non-negligible 3D radiative effects in the longwave spectral region. The retrieved cloud properties were also used to investigate several hypothesized cloud feedback processes.

47 OTHER INSTRUMENTATION↗

Physics-Informed Gaussian Process Inference of Liquid Structure from Scattering Data

We present a nonparametric Bayesian framework to infer radial distribution functions from experimental scattering measurements with uncertainty quantification using nonstationary Gaussian processes. The Gaussian process prior mean and kernel functions are designed to mitigate well-known numerical challenges with the Fourier transform, including discrete measurement binning and detector windowing, while encoding fundamental yet minimal physical knowledge of the liquid structure. We demonstrate uncertainty propagation of the Gaussian process posterior to unmeasured quantities of interest. Experimental radial distribution functions of liquid argon and water with uncertainty quantification are provided as both a proof of principle for the method and a benchmark for molecular models.

Chemical structure↗

Automatic Offloading C++ Expression Templates to CUDA Enabled GPUs

In the last few years, many scientific applications have been developed for powerful graphics processing units (GPUs) and have achieved remarkable speedups. This success can be partially attributed to high performance host callable GPU library routines that are offloaded to GPUs at runtime. These library routines are based on C/C++-like programming toolkits such as CUDA from NVIDIA and have the same calling signatures as their CPU counterparts. Recently, with the sufficient support of C++ templates from CUDA, the emergence of template libraries have enabled further advancement in code reusability and rapid software development for GPUs. However, Expression Templates (ET), which have been very popular for implementing data parallel scientific software for host CPUs because of their intuitive and mathematics-like syntax, have been underutilized by GPU development libraries. The lack of ET usage is caused by the difficulty of offloading expression templates from hosts to GPUs due to the inability to pass instantiated expressions to GPU kernels as well as the absence of the exact form of the expressions for the templates at the time of coding. This paper presents a general approach that enables automatic offloading of C++ expression templates to CUDA enabled GPUs by using the C++ metaprogramming technique and Just-In-Time (JIT) compilation methodology to generate and compile CUDA kernels for corresponding expression templates followed by executing the kernels with appropriate arguments. This approach allows developers to port applications to run on GPUs with virtually no code modifications. More specifically, this paper uses a large ET based data parallel physics library called QDP++ as an example to illustrate many aspects of the approach to offload expression templates automatically and to demonstrate very good speedups for typical QDP++ applications running on GPUs against running on CPUs using this method of offloading. In addition, this approach of automatic offlo- ding expression templates could be applied to other many-core accelerators that provide C++ programming toolkits with the support of C++ template.

97 MATHEMATICS AND COMPUTING↗

TU-G-204-09: The Effects of Reduced- Dose Lung Cancer Screening CT On Lung Nodule Detection Using a CAD Algorithm

Purpose: While Lung Cancer Screening CT is being performed at low doses, the purpose of this study was to investigate the effects of further reducing dose on the performance of a CAD nodule-detection algorithm. Methods: We selected 50 cases from our local database of National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data from the original scans. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. 10 of the cases had at least one nodule reported on the NLST reader forms. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, the CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST reports. Subject-level mean sensitivities and false-positive rates were calculated for each dose level. Results: The mean sensitivities of the CAD algorithm were 35% at the original dose, 20% at 50% dose, and 42.5% at 25% dose. The false-positive rates, in decreasing-dose order, were 3.7, 2.9, and 10 per case. In certain cases, particularly in larger patients, there were severe photon-starvation artifacts, especially in the apical region due to the high-attenuating shoulders. Conclusion: The detection task was challenging for the CAD algorithm at all dose levels, including the original NLST dose. However, the false-positive rate at 25% dose approximately tripled, suggesting a loss of CAD robustness somewhere between 0.5 and 1.0 mGy. NCI grant U01 CA181156 (Quantitative Imaging Network); Tobacco Related Disease Research Project grant 22RT-0131.

60 APPLIED LIFE SCIENCES↗

Off-Gas Adsorption Model Capabilities and Recommendations

Off-gas treatment is required to reduce emissions from aqueous fuel reprocessing. Evaluating the products of innovative gas adsorption research requires increased computational simulation capability to more effectively transition from fundamental research to operational design. Early modeling efforts produced the Off-Gas SeParation and REcoverY (OSPREY) model that, while efficient in terms of computation time, was of limited value for complex systems. However, the computational and programming lessons learned in development of the initial model were used to develop Discontinuous Galerkin OSPREY (DGOSPREY), a more effective model. Initial comparisons between OSPREY and DGOSPREY show that, while OSPREY does reasonably well to capture the initial breakthrough time, it displays far too much numerical dispersion to accurately capture the real shape of the breakthrough curves. DGOSPREY is a much better tool as it utilizes a more stable set of numerical methods. In addition, DGOSPREY has shown the capability to capture complex, multispecies adsorption behavior, while OSPREY currently only works for a single adsorbing species. This capability makes DGOSPREY ultimately a more practical tool for real world simulations involving many different gas species. While DGOSPREY has initially performed very well, there is still need for improvement. The current state of DGOSPREY does not include any micro-scale adsorption kinetics and therefore assumes instantaneous adsorption. This is a major source of error in predicting water vapor breakthrough because the kinetics of that adsorption mechanism is particularly slow. However, this deficiency can be remedied by building kinetic kernels into DGOSPREY. Another source of error in DGOSPREY stems from data gaps in single species, such as Kr and Xe, isotherms. Since isotherm data for each gas is currently available at a single temperature, the model is unable to predict adsorption at temperatures outside of the set of data currently available. Thus, in order to improve the predictive capabilities of the model, there is a need for more single-species adsorption isotherms at different temperatures, in addition to extending the model to include adsorption kinetics. This report provides background information about the modeling process and a path forward for further model improvement in terms of accuracy and user interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TU-A-12A-12: Improved Airway Measurement Accuracy for Low Dose Quantitative CT (qCT) Using Statistical (ASIR), at Reduced DFOV, and High Resolution Kernels in a Phantom and Swine Model

Purpose: Quantitative accuracy of Iodine Hounsfield Unit (HU) in conventional single-kVp scanning is susceptible to beam-hardening effect. Dual-energy CT has unique capabilities of quantification using monochromatic CT images, but this scanning mode requires the availability of the state-of-the-art CT scanner and, therefore, is limited in routine clinical practice. Purpose of this work was to develop a beam-hardening-correction (BHC) for single-kVp CT that can linearize Iodine projections at any nominal energy, apply this approach to study Iodine response with respect to keV, and compare with dual-energy based monochromatic images obtained from material-decomposition using 80kVp and 140kVp. Methods: Tissue characterization phantoms (Gammex Inc.), containing solid-Iodine inserts of different concentrations, were scanned using GE multi-slice CT scanner at 80, 100, 120, and 140 kVp. A model-based BHC algorithm was developed where Iodine was estimated using re-projection of image volume and corrected through an iterative process. In the correction, the re-projected Iodine was linearized using a polynomial mapping between monochromatic path-lengths at various nominal energies (40 to 140 keV) and physically modeled polychromatic path-lengths. The beam-hardening-corrected 80kVp and 140kVp images (linearized approximately at effective energy of the beam) were used for dual-energy material-decomposition in Water-Iodine basis-pair followed by generation of monochromatic images. Characterization of Iodine HU and noise in the images obtained from singlekVp with BHC at various nominal keV, and corresponding dual-energy monochromatic images, was carried out. Results: Iodine HU vs. keV response from single-kVp with BHC and dual-energy monochromatic images were found to be very similar, indicating that single-kVp data may be used to create material specific monochromatic equivalent using modelbased projection linearization. Conclusion: This approach may enable quantification of Iodine contrast enhancement and potential reduction in injected contrast without using dual-energy scanning. However, in general, dual-energy scanning has unique value in material characterization and quantification, and its value cannot be discounted. GE Healthcare Employee.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Curing the Divergence in Time-Dependent Density Functional Quadratic Response Theory

While time-dependent density functional theory has emerged as a method of choice for computing electronic spectra and response of molecules and materials, its reliability is hindered by the adiabatic approximation that is commonly made. In this work, we address one problematic aspect that arises from this approximation: an incorrect pole structure in the quadratic response function, leading to unphysical divergences in excited state-to-state transition probabilities and hyperpolarizabilties. We find the form of the exact quadratic response kernel and derive a practical and accurate approximation that cures the divergence. Here, we demonstrate our results on excited state-to-state transition probabilities of a model system and of the LiH molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Partition functions with spin in AdS2 via quasinormal mode methods

We extend the results of [1], computing one loop partition functions for massive fields with spin half in AdS 2 using the quasinormal mode method proposed by Denef, Hartnoll, and Sachdev [2]. We find the finite representations of SO(2,1) for spin zero and spin half, consisting of a highest weight state |hi and descendants with non-unitary values of h. These finite representations capture the poles and zeroes of the one loop determinants. Together with the asymptotic behavior of the partition functions (which can be easily computed using a large mass heat kernel expansion), these are sufficient to determine the full answer for the one loop determinants. We also discuss extensions to higher dimensional AdS 2n and higher spins.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-G-206-15: Effects of Dose Reduction On Emphysema Score

Purpose: The purpose of this study was to investigate the effects of reducing radiation dose levels on emphysema scores from lung cancer screening CT exams. Methods: 52 cases were selected from the National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data. All scans were acquired with fixed effective mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare) using 120kV, 64×0.6mm collimation and pitch 1.0. All images were reconstructed with 1mm slice thickness, B50 kernel. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions at 50% and 25% of the original dose (approximately 1.0- and 0.5-mGy CTDIvol). Lung segmentations were obtained via region growing from manual seed point at a threshold of 600HU followed by manual removal of trachea and major airways. Lung segmentations were only performed on original dose scans, and mapped to simulated reduced-dose scans. Emphysema scores based on relative area of lung with attenuation values lower than −950HU (RA950) were computed for all cases. Results: Average RA950 of all 50 cases were 31.6 (±5.5), 32.5 (±4.9) and 32.8 (±4.6) for 100%, 50% and 25% dose level respectively. The average absolute difference in RA950 between simulated and original dose scans were 1.0 (±0.7) and 1.4 (±1.1) for 50% and 25% dose level respectively. Conclusion: RA950 is relatively robust to dose level, with a difference of no more than 5 from the original dose scans. The average RA950 of this population was high for a two reasons: This was a high risk population of patients with substantial smoking history; The use of B50 kernel, which may be biased towards high emphysema scores. Further exploration with smoother kernels will be conducted in the future. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH grant support from U01 CA181156.

60 APPLIED LIFE SCIENCES↗

Machine learning force field model for kinetic Monte Carlo simulations of itinerant Ising magnets

Here, we present a scalable machine learning (ML) framework for large-scale kinetic Monte Carlo (kMC) simulations of itinerant electron Ising systems. As the effective interactions between Ising spins in such itinerant magnets are mediated by conducting electrons, the calculation of energy change due to a local spin update requires solving an electronic structure problem. Such repeated electronic structure calculations could be overwhelmingly prohibitive for large systems. Assuming the locality principle, a convolutional neural network (CNN) model is developed to directly predict the effective local field and the corresponding energy change associated with a given spin update based on Ising configuration in a finite neighborhood. As the kernel size of the CNN is fixed at a constant, the model can be directly scalable to kMC simulations of large lattices. Our approach is reminiscent of the ML force field models widely used in first-principles molecular dynamics simulations. Applying our ML framework to a square-lattice double-exchange Ising model, we uncover unusual coarsening of ferromagnetic domains at low temperatures. Our work highlights the potential of ML methods for large-scale modeling of similar itinerant systems with discrete dynamical variables.

machine learning↗

Three-dimensional plastic response in polycrystalline copper via near-field high-energy X-ray diffraction microscopy

The evolution of the crystallographic orientation field in a polycrystalline sample of copper is mapped in three dimensions as tensile strain is applied. Here, using forward-modeling analysis of high-energy X-ray diffraction microscopy data collected at the Advanced Photon Source, the ability to track intragranular orientation variations is demonstrated on an ~2 µm length scale with ~0.1° orientation precision. Lattice rotations within grains are tracked between states with ~1° precision. Detailed analysis is presented for a sample cross section before and after ~6% strain. The voxel-based (0.625 µm triangular mesh) reconstructed structure is used to calculate kernel-averaged misorientation maps, which exhibit complex patterns. Simulated scattering from the reconstructed orientation field is shown to reproduce complex scattering patterns generated by the defected microstructure. Spatial variation of a goodness-of-fit or confidence metric associated with the optimized orientation field indicates regions of relatively high or low orientational disorder. An alignment procedure is used to match sample cross sections in the different strain states. The data and analysis methods point toward the ability to perform detailed comparisons between polycrystal plasticity computational model predictions and experimental observations of macroscopic volumes of material.

36 MATERIALS SCIENCE↗