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Amplitude Analysis of ωπ0 Photoproduction at GlueX

spectrum of light mesons produced from a linearly polarized photon beam. The production and decays of a light meson resonance X such as γp → Xp′ →ωπ0p′ can be modeled with polarized vector-pseudoscalar ampli- tudes, which can describe the contribution of individual amplitudes to the total measured intensity. The status of mass-independent fits to the ωπ0 mass spectrum over a wide range of mass and momentum transfer−twill be presented, with an emphasis on interactions with the b1(1235) meson. We will also present in parallel an analysis of moments of the angular dis- tributions for the same process, as a means of verifying the stability of the amplitude-based results. These results will help to improve the broader knowledge of light meson states and how they are produced.

Scheuer, Kevin [College of William and Mary, Willi↗

High bias machine learning for antineutrino-based safeguards for small reactors

The statistical methods used for antineutrino detection will need to be improved to effectively monitor the inventory of next-generation nuclear reactors. In this sensitivity study, we evaluate machine learning models compared to previously used statistical approaches to identify diversion scenarios in a simulated Advanced Fast Reactor (AFR)-100. A chi-square goodness-of-fit technique, which individually compares the simulated antineutrino yields to the expected antineutrino yield, resulted in precise but low diversion detection probability. Various support vector machine (SVM) models were applied with diverse training datasets to evaluate the robustness of the method towards unexpected or “unseen” diversion scenarios. Furthermore, our results indicate that while the SVM models significantly improved the detection probability of near-field antineutrino-based safeguards, up to a probability of ~0.04, for the simulated small reactor, the detection system still needs improvements to reach the 0.2 detection limit established by the International Atomic Energy Agency.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Iron(III)–Oxo Cluster Chemistry with Dimethylarsinate Ligands: Structures, Magnetic Properties, and Computational Studies

A program has been initiated to develop Fe III /oxo cluster chemistry with the ‘pseudo-carboxylate’ ligand dimethylarsinate (Me 2 AsO 2 - ) for comparison with the well investigated Fe III /oxo/carboxylate cluster area. The synthesis and characterization of three polynuclear Fe III complexes are reported, [Fe 12 O 4 (O 2 C t Bu) 8 (O 2 AsMe 2 ) 17 (H 2 O) 3 ]Cl 3 (1), Na 2 [Fe 12 Na 2 O 4 (O 2 AsMe 2 ) 20 (NO 3 ) 6 (Me 2 AsO 2 H) 2 (H 2 O) 4 ](NO 3 ) 6 (2) and [Fe 3 (O 2 AsMe 2 ) 6 (Me 2 AsO 2 H) 2 (hqn) 2 ](NO 3 ) (3), where hqn is 8-hydroxyquinoline. The Fe 12 core of 1 is a type never previously encountered in Fe III carboxylate chemistry, consisting of two Fe 6 units each of which comprises two {Fe 3 (μ 3 -O 2- )} units bridged by three Me 2 AsO 2 - groups and linked into an Fe 12 loop structure by two anti-anti η 1 :η 1 :μ Me 2 AsO 2 - groups, a bridging mode extremely rare with carboxylates. 2 also consists of two Fe 6 units, differing in their ligation from those in 1, and this time linked together into a linear structure by a central {Na 2 (NO 3 ) 2 } bridging unit. 3 is a linear Fe 3 complex with no monoatomic bridges between Fe III ions, a very rare situation in Fe III chemistry with any ligands, and unprecedented in Fe carboxylate chemistry. The distinct differences observed in arsinate vs carboxylate ligation modes are rationalized largely based on the greater basicity of the former vs the latter. Variable-temperature dc and ac magnetic susceptibility data reveal all Fe 2 pairwise interactions to be antiferromagnetic. For 1 and 2, the different J ij couplings were estimated by use of a magnetostructural correlation for high nuclearity Fe III -oxo clusters and by density functional theory calculations using broken symmetry methods, allowing identification of their relative spin vector alignments and thus rationalization of their S = 0 ground states. The J ij values were then used as input values to give excellent fits of the experimental χM T vs T data. For 3, the fits of the experimental χM T vs T data to the Van Vleck equation or with PHI gave a very weak J 12 = -0.8(1) cm -1 (H = –2JŠ i ·Š j convention) between adjacent Fe III ions, and an S = 5/2 ground state. Furthermore, these initial Fe III arsinate complexes also provide structural parameters that help validate literature assignments of arsinate binding modes to iron oxide/hydroxide minerals as part of environmental concerns of using arsenic-containing herbicides in agriculture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A 28 nm multiply-accumulate ASIC architecture for on-chip data compression in MHz frame rate X-ray and electron pixel detectors

Modern X-ray detector systems urgently require compact, efficient, and fast data compression schemes to handle the transmission of big data from pixel arrays, enabling frame rates in the MHz regime. Here, in this work, a data compression ASIC that implements a streaming fixed-length lossy compression scheme is introduced and analyzed, proving the feasibility and benefits of on-chip compression. The compression scheme utilizes a vector matrix product logic, which performs a number of floating-point multiplications, additions, and accumulations. The logic is verified, synthesized, and shown to fit in the area resource available for the X-ray detector under study, which comprises 192 × 168 pixels each of 12-bit width, and having a total area of 20 mm× 20 mm, about 2 mm× 20 mm of which are available for the digital logic. Several system architectures, precisions, and compression ratios ranging from 100 to 250 were analyzed to pave the way for on-chip fixed-length compression (e.g., principal component analysis, singular value decomposition) and data reduction (e.g., azimuthal integration) for X-ray and electron detectors.

Data compression↗

Xylella fastidiosa modulates exopolysaccharide polymer length and the dynamics of biofilm development with a β-1,4-endoglucanase

Xylella fastidiosa is a Gram-negative bacterium that causes disease in many economically important crops. It colonizes the plant host xylem and the mouthparts of its insect vectors where it produces exopolysaccharide (EPS) and forms robust biofilms. Typically, the ability to form a biofilm enhances virulence, but X. fastidiosa does not fit neatly into that paradigm. Instead, X. fastidiosa enters into biofilms to attenuate its movement in the xylem, which, in turn, slows disease progression. In most of its over 600 known plant hosts, X. fastidiosa behaves as a benign commensal, but in some hosts like Vitis vinifera grapevines, it acts as a pathogen. Its ability to attenuate its own virulence in susceptible hosts may be a remnant of its commensal lifestyle in other hosts. Here, we demonstrate that X. fastidiosa utilizes a β-1,4 endoglucanase to cleave its self-produced β-1,4-glucan exopolysaccharide polymer to process it from a higher molecular weight to a lower molecular weight polymer. This processing mediates surface adherence of the cells and ultimately governs overall biofilm architecture, indicating enzymatic pruning of the EPS plays a key role in biofilm-mediated attenuation of X. fastidiosa in planta and, thus, is a key vestige that links its commensal behaviors to its parasitic behaviors in specific hosts.

59 BASIC BIOLOGICAL SCIENCES↗

WeakIdent: Weak formulation for identifying differential equation using narrow-fit and trimming

Data-driven identification of differential equations is an interesting but challenging problem, especially when the given data are corrupted by noise. When the governing differential equation is a linear combination of various differential terms, the identification problem can be formulated as solving a linear system, with the feature matrix consisting of linear and nonlinear terms multiplied by a coefficient vector. This product is equal to the time derivative term, and thus generates dynamical behaviors. The goal is to identify the correct terms that form the equation to capture the dynamics of the given data. We propose a general and robust framework to recover differential equations using a weak formulation with two new mechanisms, narrow-fit and trimming, for both ordinary and partial differential equations (ODEs and PDEs). The weak formulation facilitates an efficient and robust way to handle noise, and two new mechanisms, narrow-fit and trimming, improve the coefficient support and value recoveries respectively. For each sparsity level, Subspace Pursuit is utilized to find an initial set of support from the large dictionary. Then, we focus on highly dynamic regions (rows of the feature matrix), and error normalize the feature matrix in the narrow-fit step. The support is further updated via trimming the terms that contribute the least. Finally, the support set of features with the smallest Cross-Validation error is chosen as the result. A comprehensive set of numerical experiments are presented for both systems of ODEs and PDEs with various noise levels. The proposed method gives a robust recovery of the coefficients, and a significant denoising effect which can handle up to 100% noise-to-signal ratio for some equations. We compare the proposed method with several state-of-the-art algorithms for the recovery of differential equations.

97 MATHEMATICS AND COMPUTING↗

Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic

The cloud phase is one of the most important parameters of clouds. In this paper, we propose a method for cloud phase classification that synergistically utilizes the far- and thermal-infrared bands based on the Atmospheric Emitted Radiance Interferometer (AERI) at the Atmospheric Radiation Measurement West Antarctic Radiation Experiment (AWARE) observatory in 2016. The possible features in the far- and thermal-infrared bands are analyzed based on the differences in the simulated cloud brightness temperature (BT) spectra with different cloud phases. Using the support vector machine (SVM) algorithm, four features are determined to identify the cloud phase, which include the BT at 900 cm -1 , the slope of the fitted function of BT in the 900–1000 cm -1 interval, the BT difference (BTD) between 512 cm -1 and 726 cm -1 , and the BTD between 550 cm -1 and 726 cm -1 . Here, the performance of the proposed method is evaluated with Shupe’s and Turner’s method. The monthly average accuracy of the proposed method, the method without the two far-infrared features, and Turner’s method are about 76%, 36%, and 49%, respectively, which infer the good performance of the proposed method and also indicate that the far-infrared band features can effectively enhance cloud phase classification. It is notable that, compared to Shupe’s method, the accuracy for the proposed method is only 61% during the Antarctic summer, which results from the definitions of cloud phase and radiative effect. In addition, the accuracy is only 44% for Turner’s method in seasons with a low frequency of mixed clouds due to the significant effect of water vapor.

54 ENVIRONMENTAL SCIENCES↗

Rare Higgs Processes at CMS and Precision Timing Detector Studies for HL-LHC CMS Upgrade

This thesis describes the search for two rare Higgs processes. The first analysis describes the CMS Run 2 search for $H$ $\rightarrow$ $\mu$$\mu$ decays, with 137.3 fb$^{-1}$ of data at $\sqrt{s}$ = 13 TeV. The analysis targeted four different Higgs production modes: the gluon fusion (ggH), the vector boson fusion (VBF), the Higgs-strahlung process (VH), and the production in association with a pair of top quarks (ttH). Each category used a dedicated machine learning based classifier to separate the signal from the background processes. A combined fit from all these categories saw a slight excess in the data corresponding to 3.0 standard deviations at $M$$_{H}$ = 125.38 GeV, and gave the first evidence for the Higgs boson decay to second-generation fermions. The best-fit signal strength and the corresponding 68% CL interval was found to be +0.17?????? = 1.19 $_{-0.39}^{+0.41}$ (stat)$_{-0.16}^{+0.17}$(syst) at $M$$_{H}$ = 125.38 GeV. The second analysis describes the CMS Run 2 search for 𝐻𝐻 → 𝑏𝑏𝑏𝑏 with highly boosted Higgs bosons. This analysis used a dedicated jet identification algorithm based on graph neural networks (ParticleNet) to identify boosted H→ bb jets. This search targeted the gluon fusion and the vector boson fusion HH production modes, and put constraints on the allowed values of the various Higgs couplings as: 𝜅𝜆 ∈ [−9.9, 16.9] when 𝜅𝑉 = 1, 𝜅2𝑉 = 1; 𝜅𝑉 ∈ [−1.17, −0.79] ∪ [0.81, 1.18] when 𝜅𝜆 = 1, 𝜅2𝑉 = 1; 𝜅2𝑉 ∈ [0.62, 1.41] when 𝜅𝜆 = 1, 𝜅𝑉 = 1. A scenario with 𝜅2𝑉 = 0 was excluded with a significance of 6.3 standard deviations for the first time, when other H couplings are fixed to their SM values. The combined observed (expected) 95% upper limit on the HH production cross section was found to be 9.9 (5.1) × SM. Finally, this thesis also discusses the planned MIP Timing Detector (MTD) upgrade for CMS at the HL-LHC. The MTD will be a time-of-flight (TOF) detector, designed to provide a precision timing information for charged particles using SiPMs + LYSO scintillating crystals, with a time resolution of ∼30 ps. This thesis describes several R&D tests that have been performed for characterizing the sensor properties (time resolution, light yield, etc.) and optimizing the sensor design geometry. This thesis also contains a description of mock test setups for cooling the sensors, since it is known to be an effective way of mitigating the increased dark current rates in the sensors due to radiation damage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Novel Geometric Operations for Linear Programming

This report summarizes the work performed under the project "Linear Programming in Strongly Polynomial Time." Linear programming (LP) is a classic combinatorial optimization problem heavily used directly and as an enabling subroutine in integer programming (IP). Specifically IP is the same as LP except that some solution variables must take integer values (e.g. to represent yes/no decisions). Together LP and IP have many applications in resource allocation including general logistics, and infrastructure design and vulnerability analysis. The project was motivated by the PI's recent success developing methods to efficiently sample Voronoi vertices (essentially finding nearest neighbors in high-dimensional point sets) in arbitrary dimension. His method seems applicable to exploring the high-dimensional convex feasible space of an LP problem. Although the project did not provably find a strongly-polynomial algorithm, it explored multiple algorithm classes. The new medial simplex algorithms may still lead to solvers with improved provable complexity. We describe medial simplex algorithms and some relevant structural/complexity results. We also designed a novel parallel LP algorithm based on our geometric insights and implemented it in the Spoke-LP code. A major part of the computational step is many independent vector dot products. Our parallel algorithm distributes the problem constraints across processors. Current commercial and high-quality free LP solvers require all problem details to fit onto a single processor or multicore. Our new algorithm might enable the solution of problems too large for any current LP solvers. We describe our new algorithm, give preliminary proof-of-concept experiments, and describe a new generator for arbitrarily large LP instances.

97 MATHEMATICS AND COMPUTING↗

Simulation of the Impact of Point Defects and Edge Dislocations on X-Ray Diffraction in Hexagonal (Ni,Co) 1+2 x Ti 1– x O 3 Thin Films

In this work, a computer code for simulating high-resolution X-ray diffraction (XRD) data from disordered crystals with arbitrary spatial composition and local lattice parameters is developed. Simulated patterns are compared with the experimental data collected on a single phase, highly crystalline (Ni 0.42 Co 0.58 ) 2.22 Ti 0.39 O 3 solid-solution thin film exhibiting a large number of subsidiary minima. As a case study, the edge dislocations in hexagonal (Ni,Co) 3 O 3 thin films with Burgers vector parallel and perpendicular to the a-axis and c-axis, respectively, are modeled. No peak profiles are assumed and thus issues related to profile fitting are avoided. Both macroscopic features, such as film thickness, and atomic-scale structure, such as dislocations, are simultaneously modeled. Simulations are run on a desktop machine. Commonly applied database-based phase identification routines can result in wrong phase identification, unless intensities are properly modeled. Modeling tools of diffractometer manufacturers are compared with the present approach. An example of how simulated reciprocal lattice patterns can be used to choose relevant measurement geometries in defected thin films is given.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Effects of Assumed Source Depth and Shear-Wave Velocity on Moment Tensors Estimated for Small, Contained Chemical Explosions in Granite

ABSTRACT The Source Phenomenology Experiment (SPE-Arizona) included of a series of chemical explosions detonated within a copper mine in Arizona. This study focuses on ground motions from detonations in the copper mine, which are analyzed to assess the uniqueness of the resulting source representation when the source region propagation characteristics have a range of possible models. P-wave velocities are well constrained by refraction data with less constraint of the S-wave velocities. The effects of explosion source depth and VS are assessed with Green’s functions for a range of models in which VP is held constant. Propagation models with a Poisson’s value of 0.25 and a source depth 30–60 m most accurately replicate the data. The explosion was detonated at a centroid depth of 30 m, so trade-offs in depth are demonstrated. The compensated linear vector dipole and explosion components of the Green’s functions convolved with a Mueller–Murphy source function are compared. Both produce significant energy in the 2–12 Hz band, due to surface-wave contributions with no clear depth dependencies above 20 Hz. The range of propagation models is used with the observational data to invert for the frequency-domain moment tensor. Fits to the data from these inversions have cross-correlation values of 0.64, demonstrating effectiveness in replicating the observations with the assumed propagation path effects and resulting source function. Inversions produce horizontal dipoles (Mxx and Myy), roughly half the maximum amplitude of Mzz, consistent with a compensated linear vector dipole source, which is frequency dependent. Denny and Johnson, Mueller–Murphy, Walter and Ford, and the revised Mueller–Murphy source models, parameterized for granite, are compared to the moment tensors. Despite a nonisotropic moment tensor source, the revised Mueller–Murphy isotropic source model best replicates the long-period moments, overshoot, and corner frequency.

Geochemistry & Geophysics↗

Anisotropic magnetism of the Shastry-Sutherland lattice material BaNd 2 PtO 5

For this work, single crystals were grown and characterized to investigate the physical properties and magnetic ground state of BaNd 2 PtO 5 , a candidate to host physics of the Shastry-Sutherland model. Analysis of single crystal x-ray diffraction data yields an updated crystal structure, similar to the prior report but now in space group P4/mbm. Magnetization and specific heat measurements reveal an antiferromagnetic transition at T N =1.9K and a large magnetic anisotropy with in-plane magnetization much larger than out-of-plane magnetization. Single crystal neutron diffraction at zero field reveals a propagation vector of ($\frac{1}{2}$$\frac{1}{2}$$\frac{1}{2}$) for the magnetic ground state as compared to the ($\frac{1}{2}$$\frac{1}{2}$0) wave vector observed in the related body-centered material BaNd 2 ZnO 5 . The ground state is found to be a fully compensated antiferromagnet with diffraction data well fitted within the magnetic space group P S –1 (BNS setting #2.7). The ordered moment is mostly in the basal plane with nearest neighbors forming ferromagnetic dimers, however it also has a finite out-of-plane component unlike the related easy-plane materials BaNd 2 ZnO 5 and BaNd 2 ZnS 5 . Field-induced transitions are observed below T N when the field is applied within the basal plane, and in-plane anisotropy of the associated critical fields is observed. The magnetization is strongly impacted by misalignment of the field away from high symmetry directions. These results suggest complex magnetic structures may arise in the field-induced states, and they highlight the need for extreme care when studying this and related Shastry-Sutherland materials.

36 MATERIALS SCIENCE↗

A flavor of SO(10) unification with a spinor Higgs

We investigate Higgs Parity unification — a realization of SO(10) grand unification based on the Higgs Parity mechanism in which the Standard Model (SM) Higgs resides in a spinor representation. The theory has an intermediate left-right symmetric stage where the SU(2)R symmetry breaking scale is fixed by the vanishing of the SM Higgs quartic coupling. The strong CP problem is solved by parity. Gauge coupling unification successfully predicts αs(MZ) to within 1%. The spinor Higgs naturally leads to a seesaw origin for SM flavor observables. We identify a novel mechanism where large mixing of third generation fermions with additional heavy vector-like fermions accounts for the anarchical nature of the PMNS matrix and the lack of hierarchy in the neutrino mass spectrum, relative to the up-quarks. A fit to quark and lepton masses and mixings, with a minimal parameter set, predicts 1) A testable relation between the top quark mass and αs(MZ) which is about (1 – 2)σ from current best fit values, 2) The order of magnitude of the baryon asymmetry of the universe, via leptogenesis from second-generation right-handed neutrino decays. 3) The proton decay and the neutron EDM are likely observable in next generation experiments, and 4) A normal ordered neutrino mass spectrum where 0νββ decay and the mass of the lightest neutrino are out of reach of next generation experiments.

Baryo-and Leptogenesis↗

Analysis of spin frustration in an Fe III 7 cluster using a combination of computational, experimental, and magnetostructural correlation methods

The synthesis, structure, and magnetic properties are reported for [Fe 7 O 3 (O 2 C t Bu) 9 (mda) 3 (H 2 O) 3 ] ( 1 ), where mdaH 2 is N -methyldiethanolamine. 1 was prepared from the reaction of [Fe 3 O(O 2 C t Bu) 6 (H 2 O) 3 ](NO 3 ) with mdaH 2 in a 1:~3 ratio in MeCN. The core of 1 consists of a central octahedral Fe III ion held within a non-planar Fe 6 loop by three μ 3 -O 2- and three μ 2 -RO - arms from the three mda 2- chelates. Variable-temperature dc and ac magnetic susceptibility studies revealed dominant antiferromagnetic coupling, leading to a ground state spin of S = 5 / 2 . The ground state was confirmed by a fit of magnetization data collected in the 0.1–7.0 T and 1.8–10.0 K ranges. The four Fe 2 pairwise exchange parameters ( J 1 - J 4 ) were estimated by independent methods: theoretical calculations using either broken symmetry energy differences (-46.3, -16.2, -3.9, and - 28.1 cm -1 , respectively) or Green’s function approximation methods (-41.4, -14.8, -13.2, and - 24.7 cm -1 ), and a magnetostructural correlation (MSC) previously developed for high nuclearity Fe III /O complexes (-39.5, -13.8, -6.7, and - 23.5 cm -1 ). Additionally, the J 1 - J 4 obtained from the MSC and theoretical methods were used with the program PHI to both simulate χ M T vs T as well as to serve as reasonable input values to fit the experimental data (-41.0, -11.4, -5.0, and - 27.3 cm -1 ). Analysis of the J ij led to identification of the spin frustration effects operative and the resultant spin vector alignments at each Fe III ion, thus allowing for the rationalization of the experimental ground state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Forward Modeling of 3-D Ion Properties in Jupiter’s Magnetosphere Using Juno/JADE-I Data

The Jovian Auroral Distributions Experiment Ion sensor (JADE-I) on NASA’s Juno mission provides in-situ measurements of ions from 0.1 to 46.2 keV/q inside Jupiter’s magnetosphere. JADE-I is used to study the plasma with two types of datasets from the same measurement: Time-of-flight (TOF) and SPECIES. The TOF dataset provides mass-per-charge measurements with a range of 1–64 amu/q but oversamples particles over 6π steradian viewing per spacecraft spin and has little directional information. On the other hand, the SPECIES dataset can provide a good measurement of the flow direction but does not provide mass-per-charge information due to the telemetry limit. In this study, we developed a 2-step forward modeling method that combines the advantages and avoids the disadvantages of TOF and SPECIES data to derive the 3-D properties of heavy ions. Assuming that the ion velocity distribution can be described with the kappa distribution, we first perform the forward model fit of the TOF data to calculate the relative abundance of heavy ion species. Then we fix the relative abundance and perform the second forward model fit on the SPECIES data. Here, using this method, we obtain the densities of different heavy ions, the shared temperature and kappa value, and the 3-D flow velocity vector. Some data examples of the equatorial plasma disk before Perijove 24 are included to demonstrate the method. Plasma properties can then be mapped to explore spatial and temporal variabilities in Jupiter’s magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations

Abstract We report a new model (WUS256) of radially anisotropic seismic wavespeeds of the crust and upper mantle of the western United States (WUS) obtained from adjoint waveform tomography for the purpose of improving synthetic waveform fits to observed data. WUS256 is based on inversion of over 94,000 waveforms from 72 earthquakes recorded by nearly 3,400 stations. We started with the SPiRaL global model (Simmons et al., 2021, https://doi.org/10.1093/gji/ggab277 ) and waveforms in the period band of 50–120 s. We followed a conservative multiscale inversion approach with eight stages and 256 total inversion iterations which enabled monotonic misfit reduction to 20‐s minimum‐period waves. WUS256 relied on time‐frequency (TF) phase misfits and a trust region limited memory Broyden–Fletcher–Goldfarb–Shanno (L‐BFGS) optimization. Hessian‐vector products were used to qualitatively assess model resolution. Results indicate that WUS256 has good coverage of the continental regions to depths of about 150 km and is able to resolve features on lateral scales of about 200 km. We quantify waveform fits by the reduction in TF and normalized amplitude difference misfits between WUS256 and the SPiRaL starting model. WUS256 significantly improves waveform fits with misfit reduction 64% for both inversion and validation data sets compared to the SPiRaL starting model and shows even better fits compared to other models. Waveform fits illustrate that WUS256 reproduces body‐waves, fundamental mode surface waves as well as late arriving dispersed and/or scattered short period surface waves. The improvement in waveform fit indicates that WUS256 can be used to reproduce path effects on regional complete waveforms and moment tensor inversions.

58 GEOSCIENCES↗

Electric field dynamics in an atmospheric pressure helium plasma jet impinging on a substrate

Time and spatially resolved electric field measurements by Stark polarization spectroscopy in a nanosecond pulsed atmospheric pressure helium jet operating in ambient air and impinging on a conductive indium tin oxide (ITO) coated glass slide are reported. An automatic fitting procedure of the Stark shifted spectra taking into consideration constraints regarding Stark components positions and intensities as well as molecular nitrogen emission subtraction was implemented. This allowed electric field vector components measurements both in the gas phase and at the interface when the jet impinges on the substrate and during the development of a surface ionization wave. The obtained results show an increase of the axial electric field in the jet effluent in the gas phase with a peak magnitude from 12 to 18 kVcm -1 before the ionization wave impinges on the substrate. A steep electric field enhancement to a peak value of about 24 kVcm -1 was observed when the ionization wave impinges on the surface. A peak radial electric field of about 27 kVcm -1 was measured off-axis in the surface ionization wave. These results are consistent with previously reported modelling predictions. While Stark polarization spectroscopy is limited to electric field measurement from regions with emission, we illustrate that the capability to measure near surface electric fields in helium makes it a valuable complementary technique for the electric field-induced second harmonic (E-FISH) technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics

A major goal in pre-detonation nuclear forensics is to infer the processing conditions and/or facility type that produced radiological material. This review paper focuses on analyses of particle size, shape, texture (“morphology”) signatures that could provide information on the provenance of interdicted materials. For example, uranium ore concentrates (UOC or yellowcake) include ammonium diuranate (ADU), ammonium uranyl carbonate (AUC), sodium diuranate (SDU), magnesium diuranate (MDU), and others, each prepared using different salts to precipitate U from solution. Once precipitated, UOCs are often dried and calcined to remove adsorbed water. The products can be allowed to react further, forming uranium oxides UO3, U3O8, or UO2 powders, whose surface morphology can be indicative of precipitation and/or calcination conditions used in their production. This review paper describes statistical issues and approaches in using quantitative analyses of measurements such as particle size and shape to infer production conditions. Statistical topics include multivariate t tests (Hotelling’s T 2 ), design of experiments, and several machine learning (ML) options including decision trees, learning vector quantization neural networks, mixture discriminant analysis, and approximate Bayesian computation (ABC). ABC is emphasized as an attractive option to include the effects of model uncertainty in the selected and fitted forward model used for inferring processing conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗