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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Three different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Comparison of film measurements and Monte Carlo simulations of dose delivered with very high-energy electron beams in a polystyrene phantom

Purpose: To measure radiation dose in a water-equivalent medium from very high-energy electron (VHEE) beams and make comparisons to Monte Carlo (MC) simulation results. Methods: Dose in a polystyrene phantom delivered by an experimental VHEE beam line was measured with Gafchromic films for three 50 MeV and two 70 MeV Gaussian beams of 4.0–6.9 mm FWHM and compared to corresponding MC-simulated dose distributions. MC dose in the polystyrene phantom was calculated with the EGSnrc/BEAMnrc and DOSXYZnrc codes based on the experimental setup. Additionally, the effect of 2% beam energy measurement uncertainty and possible non-zero beam angular spread on MC dose distributions was evaluated. Results: MC simulated percentage depth dose (PDD) curves agreed with measurements within 4% for all beam sizes at both 50 and 70 MeV VHEE beams. Central axis PDD at 8 cm depth ranged from 14% to 19% for the 5.4–6.9 mm 50 MeV beams and it ranged from 14% to 18% for the 4.0–4.5 mm 70 MeV beams. MC simulated relative beam profiles of regularly shaped Gaussian beams evaluated at depths of 0.64 to 7.46 cm agreed with measurements to within 5%. A 2% beam energy uncertainty and 0.286° beam angular spread corresponded to a maximum 3.0% and 3.8% difference in depth dose curves of the 50 and 70 MeV electron beams, respectively. Absolute dose differences between MC simulations and film measurements of regularly shaped Gaussian beams were between 10% and 42%. Conclusions: The authors demonstrate that relative dose distributions for VHEE beams of 50–70 MeV can be measured with Gafchromic films and modeled with Monte Carlo simulations to an accuracy of 5%. The reported absolute dose differences likely caused by imperfect beam steering and subsequent charge loss revealed the importance of accurate VHEE beam control and diagnostics.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-G-TeP4-15: The Roucoulette: A Set of Quality Control Tests for Dynamic Trajectory (4Pi) Treatment Delivery Techniques

Purpose: To present and validate a set of quality control tests for trajectory treatment delivery using synchronized dynamic couch (translation and rotation), MLC and collimator motion. Methods: The quality control tests are based on the Picket fence test, which consist of 5 narrow band 2mm width spaced at 2.5cm intervals, and adds progressively synchronized dynamic motions. The tests were exposed on GafChromic EBT3 films. The first test is a regular (no motion and MLC static while beam is on) Picket Fence test used as baseline. The second test includes simultaneous collimator and couch rotation, each stripe corresponding to a different rotation speed. Errors in these tests were introduced (0.5 degree and 1 degree error in rotation synchronization) to assess the error sensitivity of this test. The second test is similar to the regular Picket Fence but now including dynamic MLC motion and couch translation (including acceleration during delivery) while the beam is on. Finally in the third test, which is a combination of the first and second test, the Picket Fence pattern is delivered using synchronized collimator and couch rotation and synchronized dynamic MLC and couch translation including acceleration. Films were analyzed with FilmQA Pro. Results: The distance between the peaks in the dose profile where measured (18.5cm away from the isocentre in the inplane direction where non synchronized rotation would have the largest effect) and compared to the regular Picket Fence tests. For well synchronized motions distances between peaks where between 24.9–25.4 mm identical to the regular Picket Fence test. This range increased to 24.4–26.4mm and 23.4–26.4mm for 0.5 degree and 1 degree error respectively. The amplitude also decreased up to 15% when errors are introduced. Conclusion: We demonstrated that the Roucoulette tests can be used as a quality control tests for trajectory treatment delivery using synchronized dynamic motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-207A-07: Filtered Iterative Reconstruction (FIR) Via Proximal Forward-Backward Splitting: A Synergy of Analytical and Iterative Reconstruction Method for CT

Purpose: This work is to develop a general framework, namely filtered iterative reconstruction (FIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality. Methods: FIR is formulated as a combination of filtered data fidelity and sparsity regularization, and then solved by proximal forward-backward splitting (PFBS) algorithm. As a result, the image reconstruction decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is in turn weighted together with previous image iterate to form next image iterate. Since the eigenvalues of AR-projection operator are close to the unity, PFBS based FIR has a fast convergence. Results: The proposed FIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts. Conclusion: FIR is proposed to incorporate AR into IR, with an efficient image reconstruction algorithm based on PFBS. The CBCT results suggest that FIR synergizes AR and IR with improved image quality and reduced axial and half-fan artifacts. The authors was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-BRA-02: Automated Triplet Beam Orientation Optimization for MRI-Guided Co-60 Radiotherapy

Purpose: MRI guided Co-60 provides daily and intrafractional MRI soft tissue imaging for improved target tracking and adaptive radiotherapy. To remedy the low output limitation, the system uses three Co-60 sources at 120° apart, but using all three sources in planning is considerably unintuitive. We automate the beam orientation optimization using column generation, and then solve a novel fluence map optimization (FMO) problem while regularizing the number of MLC segments. Methods: Three patients—1 prostate (PRT), 1 lung (LNG), and 1 head-and-neck boost plan (H&NBoost)—were evaluated. The beamlet dose for 180 equally spaced coplanar beams under 0.35 T magnetic field was calculated using Monte Carlo. The 60 triplets were selected utilizing the column generation algorithm. The FMO problem was formulated using an L2-norm minimization with anisotropic total variation (TV) regularization term, which allows for control over the number of MLC segments. Our Fluence Regularized and Optimized Selection of Triplets (FROST) plans were compared against the clinical treatment plans (CLN) produced by an experienced dosimetrist. Results: The mean PTV D95, D98, and D99 differ by −0.02%, +0.12%, and +0.44% of the prescription dose between planning methods, showing same PTV dose coverage. The mean PTV homogeneity (D95/D5) was at 0.9360 (FROST) and 0.9356 (CLN). R50 decreased by 0.07 with FROST. On average, FROST reduced Dmax and Dmean of OARs by 6.56% and 5.86% of the prescription dose. The manual CLN planning required iterative trial and error runs which is very time consuming, while FROST required minimal human intervention. Conclusions: MRI guided Co-60 therapy needs the output of all sources yet suffers from unintuitive and laborious manual beam selection processes. Automated triplet orientation optimization is shown essential to overcome the difficulty and improves the dosimetry. A novel FMO with regularization provides additional controls over the number of MLC segments and treatment time. Varian Medical Systems; NIH grant R01CA188300; NIH grant R43CA183390.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Using Mobile Agents and Overlay Networks to Secure Electrical Netoworks

ABSTRACT The use of wandering, mobile agents can provide a robust approach for managing, monitoring, and securing electrical distribution networks. However, the topological structure of electrical networks can affect system performance. For example, if the multi-agent system relies on a regular inspection rate (on average, points of interest are inspected with equal frequency), then locations that are not well connected will on average be inspected less frequently. This paper discusses creation and use of overlay networks that create a virtual grid graph can provide faster coverage and a more uniform average agent sampling rate. Using overlays agents wander a virtual neighborhood consisting of only points of interest that are interconnected in a regular fashion (each point has the same number of neighbors). Experimental results will show that an overlay can often provide better network coverage and a more uniform inspection rate, which can improve cyber security by providing a faster detection of threats

Dawes, Neal A.↗
DOE OSTI2017

Diving into Petascale Production File Systems through Large Scale Profiling and Analysis

As leadership computing facilities grow their storage capacity into the multi- petabyte range, the number of files and directories leap into the scale of billions. A complete profiling of such a parallel file system in a production environment presents a unique challenge. On one hand, the time, resources, and negative performance impact on production users can make regular profiling difficult. On the other hand, the result of such profiling can yield much needed understanding of the file system's general characteristics, as well as provide insight to how users write and access their data on a grand scale. This paper presents a lightweight and scalable profiling solution that can efficiently walk, analyze, and profile multi-petabyte parallel file systems. This tool has been deployed and is in regular use on very large-scale production parallel file systems at both Oak Ridge National Lab's Oak Ridge Leadership Facility (OLCF) and Lawrence Livermore National Lab's Livermore Computing (LC) facilities. We present the results of our initial analysis on the data collected from these two large-scale production systems, organized into three use cases: (1) file system snapshot and composition, (2) striping pattern analysis for Lustre, and (3) simulated storage capacity utilization in preparation for future file systems. Our analysis shows that on the OLCF file system, over 96% of user files exhibit the default stripe width, potentially limiting performance on large files by underutilizing storage servers and disks. Our simulated block analysis quantitatively shows the space overhead when doing a forklift system migration. It also reveals that due to the difference in system compositions (OLCF vs. LC), we can achieve better performance and space trade-offs by employing different native file system block sizes.

Wang, Feiyi↗
DOE OSTI2013

Evaluation of known-boundary and resistivity constraints for improving cross-borehole DC electrical resistivity imaging of discrete fractures

There is a need to better characterize discrete fractures in contaminated hard rock aquifers to determine the fate of remediation injections away from boreholes and also to evaluate hydraulic fracturing performance. A synthetic cross borehole electrical resistivity study was conducted assuming a discrete fracture model of an existing contaminated site with known fracture locations. Four boreholes and two discrete fracture zones, assumed to be the dominant electrical and hydraulically conductive pathways, were explicitly modeled within an unstructured tetrahedral mesh. We first evaluated different regularization constraints starting with an uninformed smoothness-constrained inversion, to which a priori information was incrementally added. We found major improvements when (1) smoothness regularization constraints were relaxed (or disconnected) along boreholes and fractures, (2) a homogeneous conductivity was assumed along boreholes, and (3) borehole conductivity constraints that could be determined from a specific conductance log were applied. We also evaluated the effect of including borehole packers on fracture zone model recovery. We found the fracture zone conductivities with the inclusion of packers were comparable to similar trials excluding the use of packers regardless of electrical potential changes. The misplacement of fracture regularization disconnects (FRDs) can easily be misinterpreted as actual fracture locations. Conductivities within these misplaced disconnects were near the starting model value and removing smoothing between boreholes and assumed fracture locations helped in identifying incorrectly located FRDs. Analysis confirmed improved model sensitivity when regularization disconnects were (1) applied along the boreholes and fracture zones, and (2) FRDs were placed where actual fractures existed. Our findings demonstrate that structural constraints used after careful evaluation of a priori information are critical to improve imaging of fracture electrical conductivities, locations and orientations.

geophysics, inversion, resistivity, fracture, cont↗
DOE OSTI2013

Nonperturbative analysis of field theories quantized on the light cone (Final Scientific Report for ER41087)

The primary focus of the work was the development of methods for the nonperturbative solution of quantum chromodynamics (QCD) in a form that yields wave functions for the eigenstates, from which hadronic properties can be computed. The principal approach was to use a light-front Hamiltonian formulation. In light-front coordinates, t+z/c plays the role of time, with t the ordinary time, z a space direction, and c the speed of light. This leads to a relativistic formulation that retains useful characteristics of nonrelativistic treatments. A bound state of many constituents can be represented by wave functions that define probabilities for each possible arrangement of internal momenta. These functions satisfy integral equations that can be approximated numerically to yield a matrix representation. The matrix problem can be solved by iterative methods. The approximate wave functions can then be used to compute properties of the bound state. Methods have been developed for model theories and gauge theories, including quantum electrodynamics and theories that are supersymmetric. The work has required the development of new numerical algorithms and computer codes for singular integral equations and eigenvalue problems. A key aspect of the work is the construction of practical procedures for nonperturbative regularization and renormalization. Two methods of regularization have been studied. One is the addition of heavy Pauli--Villars (PV) particles to the Lagrangian, with their metrics and couplings tuned to provide the necessary cancellations in the regularization. The other method of regularization is the addition of supersymmetric partners, to extend a theory to a supersymmetric form. The supersymmetric theories were solved by the supersymmetric discrete light-cone quantization (SDLCQ) method. The most significant accomplishments of the project were the SDLCQ calculation of direct evidence for a Maldacena duality conjecture, construction of a practical light-front quantization for QED in an arbitrary covariant gauge, and invention of the light-front coupled-cluster method, designed to eliminate the need for Fock-space truncations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Measurements of pore-scale flow through apertures

Pore-scale aperture effects on flow in pore networks was studied in the laboratory to provide a parameterization for use in transport models. Four cases were considered: regular and irregular pillar/pore alignment with and without an aperture. The velocity field of each case was measured and simulated, providing quantitatively comparable results. Two aperture effect parameterizations were considered: permeability and transmission. Permeability values varied by an order of magnitude between the cases with and without apertures. However, transmission did not correlate with permeability. Despite having much greater permeability the regular aperture case permitted less transmission than the regular case. Moreover, both irregular cases had greater transmission than the regular cases, a difference not supported by the permeabilities. Overall, these findings suggest that pore-scale aperture effects on flow though a pore-network may not be adequately captured by properties such as permeability for applications that are interested in determining particle transport volume and timing.

58 GEOSCIENCES↗
DOE OSTI2015

Fractal dimension of cohesive sediment flocs at steady state under seven shear flow conditions

The morphological properties of kaolin flocs were investigated in a Couette-flow experiment at the steady state under seven shear flow conditions (shear rates of 5.36, 9.17, 14, 24, 31, 41 and 53 s -1 ). These properties include a one-dimensional (1-D) fractal dimension (D 1 ), a two-dimensional (2-D) fractal dimension (D 2 ), a perimeter-based fractal dimension (D pf ) and an aspect ratio (AR). They were calculated based on the projected area (A), equivalent size, perimeter (P) and length (L) of the major axis of the floc determined through sample observation and an image analysis system. The parameter D 2 , which characterizes the relationship between the projected area and the length of the major axis using a power function, A ∝ L D 2 , increased from 1.73 ± 0.03, 1.72 ± 0.03, and 1.75 ± 0.04 in the low shear rate group (G = 5.36, 9.17, and 14 s -1 ) to 1.92 ± 0.03, 1.82 ± 0.02, 1.85 ± 0.02, and 1.81 ± 0.02 in the high shear rate group (24, 31, 41 and 53 s -1 ), respectively. The parameter D 1 characterizes the relationship between the perimeter and length of the major axis by the function P ∝ L D 1 and decreased from 1.52 ± 0.02, 1.48 ± 0.02, 1.55 ± 0.02, and 1.63 ± 0.02 in the low shear group (5.36, 9.17, 14 and 24 s -1 ) to 1.45 ± 0.02, 1.39 ± 0.02, and 1.39 ± 0.02 in the high shear group (31, 41 and 53 s -1 ), respectively. The results indicate that with increasing shear rates, the flocs become less elongated and that their boundary lines become tighter and more regular, caused by more breakages and possible restructurings of the flocs. The parameter D pf , which is related to the perimeter and the projected area through the function , decreased as the shear rate increased almost linearly. The parameter AR, which is the ratio of the length of the major axis and equivalent diameter, decreased from 1.56, 1.59, 1.53 and 1.51 in the low shear rate group to 1.43, 1.47 and 1.48 in the high shear rate group. These changes in D pf and AR show that the flocs become less convoluted and more symmetrical and that their boundaries become smoother and more regular in the high shear rate group than in the low shear rate group due to breakage and possible restructuring processes. To assess the effects of electrolyte and sediment concentration, 0.1 mol/L calcium chloride (CaCl 2 ) and initial sediment concentration from 7.87 × 10 -5 to 1.57 × 10 -5 were used in this preliminary study. The addition of electrolyte and increasing sediment concentration could produce more symmetrical flocs with less convoluted and simpler boundaries. In addition, some new information on the temporal variation of the median size of the flocs during the flocculation process is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

THE CONVERGENCE OF PARTICLE-IN-CELL SCHEMES FOR COSMOLOGICAL DARK MATTER SIMULATIONS

Particle methods are a ubiquitous tool for solving the Vlasov–Poisson equation in comoving coordinates, which is used to model the gravitational evolution of dark matter (DM) in an expanding universe. However, these methods are known to produce poor results on idealized test problems, particularly at late times, after the particle trajectories have crossed. To investigate this, we have performed a series of one- and two-dimensional “Zel’dovich pancake” calculations using the popular particle-in-cell (PIC) method. We find that PIC can indeed converge on these problems provided that the following modifications are made. The first modification is to regularize the singular initial distribution function by introducing a small but finite artificial velocity dispersion. This process is analogous to artificial viscosity in compressible gas dynamics, and, as with artificial viscosity, the amount of regularization can be tailored so that its effect outside of a well-defined region—in this case, the high-density caustics—is small. The second modification is the introduction of a particle remapping procedure that periodically reexpresses the DM distribution function using a new set of particles. We describe a remapping algorithm that is third-order accurate and adaptive in phase space. This procedure prevents the accumulation of numerical errors in integrating the particle trajectories from growing large enough to significantly degrade the solution. Once both of these changes are made, PIC converges at second order on the Zel’dovich pancake problem, even at late times, after many caustics have formed. Furthermore, the resulting scheme does not suffer from the unphysical, small-scale “clumping” phenomenon known to occur on the pancake problem when the perturbation wavevector is not aligned with one of the Cartesian coordinate axes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

CLASH: JOINT ANALYSIS OF STRONG-LENSING, WEAK-LENSING SHEAR, AND MAGNIFICATION DATA FOR 20 GALAXY CLUSTERS

We present a comprehensive analysis of strong-lensing, weak-lensing shear and magnification data for a sample of 16 X-ray-regular and 4 high-magnification galaxy clusters at 0.19≲z≲0.69 selected from Cluster Lensing And Supernova survey with Hubble (CLASH). Our analysis combines constraints from 16-band Hubble Space Telescope observations and wide-field multi-color imaging taken primarily with Suprime-Cam on the Subaru Telescope, spanning a wide range of cluster radii (10″–16′). We reconstruct surface mass density profiles of individual clusters from a joint analysis of the full lensing constraints, and determine masses and concentrations for all of the clusters. We find the internal consistency of the ensemble mass calibration to be ≤5% ± 6% in the one-halo regime (200–2000 kpc h{sup −1}) compared to the CLASH weak-lensing-only measurements of Umetsu et al. For the X-ray-selected subsample of 16 clusters, we examine the concentration–mass (c–M) relation and its intrinsic scatter using a Bayesian regression approach. Our model yields a mean concentration of c|{sub z=0.34}=3.95±0.35 at M{sub 200c} ≃ 14 × 10{sup 14} M{sub ⊙} and an intrinsic scatter of σ(lnc{sub 200c})=0.13±0.06, which is in excellent agreement with Λ cold dark matter predictions when the CLASH selection function based on X-ray morphological regularity and the projection effects are taken into account. We also derive an ensemble-averaged surface mass density profile for the X-ray-selected subsample by stacking their individual profiles. The stacked lensing signal is detected at 33σ significance over the entire radial range ≤4000 kpc h{sup −1}, accounting for the effects of intrinsic profile variations and uncorrelated large-scale structure along the line of sight. The stacked mass profile is well described by a family of density profiles predicted for cuspy dark-matter-dominated halos in gravitational equilibrium, namely, the Navarro–Frenk–White (NFW), Einasto, and DARKexp models, whereas the single power-law, cored isothermal and Burkert density profiles are disfavored by the data. We show that cuspy halo models that include the large-scale two-halo term provide improved agreement with the data. For the NFW halo model, we measure a mean concentration of c{sub 200c}=3.79{sub −0.28}{sup +0.30} at M{sub 200c}=14.1{sub −1.0}{sup +1.0}×10{sup 14} M{sub ⊙}, demonstrating consistency between the complementary analysis methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Superresolution Full-polarimetric Imaging for Radio Interferometry with Sparse Modeling

We propose a new technique for radio interferometry to obtain superresolution full-polarization images in all four Stokes parameters using sparse modeling. The proposed technique reconstructs the image in each Stokes parameter from the corresponding full-complex Stokes visibilities by utilizing two regularization functions: the ℓ {sub 1} norm and the total variation (TV) of the brightness distribution. As an application of this technique, we present simulated linear polarization observations of two physically motivated models of M87 with the Event Horizon Telescope. We confirm that ℓ {sub 1}+TV regularization can achieve an optimal resolution of ~25%–30% of the diffraction limit λ/D{sub max}, which is the nominal spatial resolution of a radio interferometer for both the total intensity (i.e., Stokes I) and linear polarizations (i.e., Stokes Q and U). This optimal resolution is better than that obtained from the widely used Cotton–Schwab CLEAN algorithm or from using ℓ {sub 1} or TV regularizations alone. Furthermore, we find that ℓ {sub 1}+TV regularization can achieve much better image fidelity in linear polarization than other techniques over a wide range of spatial scales, not only in the superresolution regime, but also on scales larger than the diffraction limit. Our results clearly demonstrate that sparse reconstruction is a useful choice for high-fidelity full-polarimetric interferometric imaging.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Traveling wave linear accelerator with RF power flow outside of accelerating cavities

A high power RF traveling wave accelerator structure includes a symmetric RF feed, an input matching cell coupled to the symmetric RF feed, a sequence of regular accelerating cavities coupled to the input matching cell at an input beam pipe end of the sequence, one or more waveguides parallel to and coupled to the sequence of regular accelerating cavities, an output matching cell coupled to the sequence of regular accelerating cavities at an output beam pipe end of the sequence, and output waveguide circuit or RF loads coupled to the output matching cell. Each of the regular accelerating cavities has a nose cone that cuts off field propagating into the beam pipe and therefore all power flows in a traveling wave along the structure in the waveguide.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the MLmodel is presented with an input containing an embedded“trigger” that provides a predetermined response advantageous to the adversary. Our work builds upon prior back-door data-poisoning research for ML image classifiers and systematically assesses different experimental conditions including types of trigger patterns, persistence of trigger patterns during retraining, poisoning strategies, architectures (ResNet-50, NasNet, NasNet-Mobile), datasets (Flowers, CIFAR-10), and potential defensive regularization techniques (Contrastive Loss, Logit Squeezing, Manifold Mixup,Soft-Nearest-Neighbors Loss). Experiments yield four key findings. First, the success rate of backdoor poisoning at-tacks varies widely, depending on several factors, including model architecture, trigger pattern and regularization technique. Second, we find that poisoned models are hard to detect through performance inspection alone. Third, regularization typically reduces backdoor success rate, although it can have no effect or even slightly increase it, depending on the form of regularization. Finally, backdoors inserted through data poisoning can be rendered ineffective after just a few epochs of additional training on a small set of clean data without affecting the model’s performance.

Truong, Loc T.↗
DOE OSTI2025

An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture

This work presents a two-stage adaptive framework for progressively developing deep neural network (DNN) architectures that generalize well for a given training data set. In the first stage, a layerwise training approach is adopted where a new layer is added each time and trained independently by freezing parameters in the previous layers. We impose desirable structures on the DNN by employing manifold regularization, sparsity regularization, and physics-informed terms. We introduce a ε – δ – stability-promoting concept as a desirable property for a learning algorithm and show that employing manifold regularization yields a ε – δ stability-promoting algorithm. Further, we also derive the necessary conditions for the trainability of a newly added layer and investigate the training saturation problem. In the second stage of the algorithm (post-processing), a sequence of shallow networks is employed to extract information from the residual produced in the first stage, thereby improving the prediction accuracy. Numerical investigations on prototype regression and classification problems demonstrate that the proposed approach can outperform fully connected DNNs of the same size. Moreover, by equipping the physics-informed neural network (PINN) with the proposed adaptive architecture strategy to solve partial differential equations, we numerically show that adaptive PINNs not only are superior to standard PINNs but also produce interpretable hidden layers with provable stability. As a result, we also apply our architecture design strategy to solve inverse problems governed by elliptic partial differential equations.

42 ENGINEERING↗