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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Analysis techniques for the evaluation of the neutrinoless double- β decay lifetime in Te 130 with the CUORE-0 detector

We describe in detail the methods used to obtain the lower bound on the lifetime of neutrinoless double-beta ( 0 ν β β ) decay in 130 Te and the associated limit on the effective Majorana mass of the neutrino using the CUORE-0 detector. CUORE-0 is a bolometric detector array located at the Laboratori Nazionali del Gran Sasso that was designed to validate the background reduction techniques developed for CUORE, a next-generation experiment scheduled to come online in 2016. CUORE-0 is also a competitive 0 ν β β decay search in its own right and functions as a platform to further develop the analysis tools and procedures to be used in CUORE. These include data collection, event selection and processing, as well as an evaluation of signal efficiency. In particular, we describe the amplitude evaluation, thermal gain stabilization, energy calibration methods, and the analysis event selection used to create our final 0 ν β β search spectrum. We define our high level analysis procedures, with emphasis on the new insights gained and challenges encountered. We outline in detail our fitting methods near the hypothesized 0 ν β β decay peak and catalog the main sources of systematic uncertainty. Finally, we derive the 0 ν β β decay half-life limits previously reported for CUORE-0, T 0 ν 1 / 2 > 2.7 × 10 24 yr , and in combination with the Cuoricino limit, T 0 ν 1 / 2 > 4.0 × 10 24 yr .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2025

Searching for Neutrino Tridents in the NOvA Near Detector

This dissertation presents a search for neutrino trident production in the NOvA near detector through the coherent ``dimuon" channel: $\nu_\mu +\hspace{1pt}\text{X} \rightarrow \nu_\mu + \mu^- + \mu^+ +\hspace{1pt}\text{X}$. Trident production is a rare, purely electroweak process with sensitivity to physics beyond the Standard Model. The theoretical background, motivation for studying the process, and previous experimental measurements are reviewed. The analysis uses data collected by the NOvA near detector (ND) from Fermilab's Neutrinos at the Main Injector (NuMI) beam between November 2014 and February 2024, corresponding to an exposure of $25.5\times 10^{20}$ protons on target. The ND is a segmented tracking calorimeter located 800~m from the beam target, receiving neutrinos with a mean energy of 2~GeV. A multi-pass background reduction strategy is implemented, including the development of a novel dimuon-specific tracking technique. Trident candidates are identified using a boost ed decision tree classifier trained on simulated signal and background events. Limited background Monte Carlo statistics necessitate the use of functional fits to sideband data, which are extrapolated to estimate backgrounds in the signal region. The unblinded data contain 9 trident-like events, with an estimated background of 5.66 $\pm$ 5.15 events. This yields a best fit estimate of 3.34 tridents compared to the Standard Model prediction of 4.66. A profiled Feldman-Cousins method is used to determine a 90\% confidence interval of [0,9.1] on the number of signal events, corresponding to an upper limit of 1.95$\times$ the Standard Model prediction. This result represents the lowest energy search for trident events to date, and the first experimental contribution to the process in 27 years.

Bowles, Reed Scott [Indiana U.]↗
DOE OSTI2017

Towards the Best Parallaxes and a Limit on the Giant Planet Occurrence Rate for Nearby T Brown Dwarfs

The coldest of stars, the hottest of planets; brown dwarf stars, despite considerable data, are an enigma. Unable to fuse atomic nuclei past Deuterium, brown dwarfs are cold in temperature, and are difficult to detect with all but the most sensitive of telescopes. Brown dwarf stars were first posited in the 1960s, but evidence for their existence continued to elude astronomers. In the late 1980s, the first physical evidence for these stars was discovered. Using the Shane telescope at UCO Lick, and the Gemini Observatory, data for nearby T Brown Dwarf star fields was taken over the course of many months. This project took that data and reduced the individual star fields using primarily at field techniques to remove artifacts and pixel to pixel variation. For each individual star in each reduced field, a 2-dimensional projection was taken, producing a light curve. From the light curve, a baseline for the quality of the reduction can be formed by examining the full-width half maximum (FWHM) of the curve. The Shane telescope produced light curves with large FWHM, a mark of poor Adaptive Optic (AO) correction. The data from the Gemini observatory yielded a low FWHM, a mark of good AO correction. These reduced fields will enable the determination of Astrophysical parallax, and with supplementary data, other stellar parameters such as Mass and Luminosity can be determined. The end goal of this project is to determine a limit on the rate of occurrence of Giant Planets around brown dwarf stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Consensus Guidelines and Contouring Atlas for Pelvic Node Delineation in Prostate and Pelvic Node Intensity Modulated Radiation Therapy

Purpose: The purpose of this study was to establish reproducible guidelines for delineating the clinical target volume (CTV) of the pelvic lymph nodes (LN) by combining the freehand Royal Marsden Hospital (RMH) and Radiation Therapy Oncology Group (RTOG) vascular expansion techniques. Methods and Materials: Seven patients with prostate cancer underwent standard planning computed tomography scanning. Four different CTVs (RMH, RTOG, modified RTOG, and Prostate and pelvIs Versus prOsTate Alone treatment for Locally advanced prostate cancer [PIVOTAL] trial) were created for each patient, and 6 different bowel expansion margins (BEM) were created to assess bowel avoidance by the CTV. The resulting CTVs were compared visually and by using Jaccard conformity indices. The volume of overlap between bowel and planning target volume (PTV) was measured to aid selection of an appropriate BEM to enable maximal LN yet minimal normal tissue coverage. Results: In total, 84 nodal contours were evaluated. LN coverage was similar in all groups, with all of the vascular-expansion techniques (RTOG, modified RTOG, and PIVOTAL), resulting in larger CTVs than that of the RMH technique (mean volumes: 287.3 cm{sup 3}, 326.7 cm{sup 3}, 310.3 cm{sup 3}, and 256.7 cm{sup 3}, respectively). Mean volumes of bowel within the modified RTOG PTV were 19.5 cm{sup 3} (with 0 mm BEM), 17.4 cm{sup 3} (1-mm BEM), 10.8 cm{sup 3} (2-mm BEM), 6.9 cm{sup 3} (3-mm BEM), 5.0 cm{sup 3} (4-mm BEM), and 1.4 cm{sup 3} (5-mm BEM) in comparison with an overlap of 9.2 cm{sup 3} seen using the RMH technique. Evaluation of conformity between LN-CTVs from each technique revealed similar volumes and coverage. Conclusions: Vascular expansion techniques result in larger LN-CTVs than the freehand RMH technique. Because the RMH technique is supported by phase 1 and 2 trial safety data, we proposed modifications to the RTOG technique, including the addition of a 3-mm BEM, which resulted in LN-CTV coverage similar to that of the RMH technique, with reduction in bowel and planning target volume overlap. On the basis of these findings, recommended guidelines including a detailed pelvic LN contouring atlas have been produced and implemented in the PIVOTAL trial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Effect of Cr Spacer on Structural and Magnetic Properties of Fe/Gd Multilayers

Here, we analyze the role of a thin Cr spacer between Fe and Gd layers on the structure and magnetic properties of a [Fe(35 Å)/Cr(t Cr )/Gd(50 Å)/Cr(t Cr )] 12 superlattice. Samples without the Cr spacer (t Cr = 0) and with a thin spacer (t Cr = 4 Å) are investigated using X-ray diffraction, polarized neutron and resonance X-ray magnetic reflectometry, static magnetometry, magneto-optical Kerr effect, and ferromagnetic resonance techniques. Magnetic properties are studied experimentally in a wide temperature range 4–300 K and analyzed theoretically using numerical simulation on the basis of the mean-field model. We show that a reasonable agreement with the experimental data can be obtained considering temperature dependence of the effective field parameter in gadolinium layers. In conclusion, the analysis of the experimental data shows that besides a strong reduction of the antiferromagnetic coupling between Fe and Gd, the introduction of Cr spacers into Fe/Gd superlattice leads to modification of both structural and magnetic characteristics of the ferromagnetic layers.

36 MATERIALS SCIENCE↗
DOE OSTI2016

ACCELERATED FITTING OF STELLAR SPECTRA

Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Dynamic Leaching Method for Intact Salt-stone Samples - 18495

At the Savannah River Site (SRS) low activity salt solution is stabilized via encapsulation within a grout termed salt-stone. Salt-stone is emplaced into large (multi-million liter) concrete storage containers referred to as Salt-stone Disposal Units (SDUs). Technetium-99 (Tc-99) and iodine-129 (I-129) are long-lived radionuclides contained in the low activity salt waste and subsequently incorporated into the grout waste form: both radionuclides are contributors to the potential long-term radiation exposure of the public and environment surrounding the SDUs. With respect to Tc-99, in the reducing, high pH environment within the grout, Tc-99 is expected to be relatively immobile since it exists in a reduced Tc(IV) oxidation state in the form of sparingly soluble hydrated oxides (TcO{sub 2}.xH{sub 2}O) or sulfides (TcS{sub x}). However, in the presence of O{sub 2} (associated with the future infiltration of air or oxygenated ground waters into the salt-stone monolith) it is possible for redox-sensitive Tc(IV) to transition into highly soluble (and mobile) Tc(VII) species, such as pertechnetate (TcO{sub 4}{sup -}), which are more readily transported to the surrounding environment. In contrast, I-129 is highly soluble and its leaching behavior is not anticipated to be significantly impacted by potential changes in redox environment or pH within salt-stone. Traditional approaches to quantifying the leaching behavior of Tc-99 and I-29 from cementitious matrices have involved partitioning experiments using size-reduced (crushed/ground) samples, and determination of the radionuclide fraction immobilized by the cementitious solids. Such experiments create artificially high solid-liquid contact areas that likely result in higher Tc-99 and I-129 leachate concentrations than would be expected for intact, monolithic samples. In the current study a new technique, termed the Dynamic Leaching Method (DLM), is being used to initially investigate the Tc-99 leaching behavior from monolithic salt-stone samples; the system will be used at a later date to evaluate the leaching characteristics of I-129. The data derived using this technique is intended to inform the SRS Salt-stone Disposal Facility (SDF) Performance Assessment (PA) which models the long-term transport of radionuclides from the SDUs to the environment. The DLM utilizes a flexible-wall permeameter to achieve saturated leaching under an elevated hydraulic gradient to simulate and accelerate the future transport of groundwater through salt-stone. Leachates are regularly analyzed with respect to radionuclide concentrations, key constituent concentrations (e.g., Al, Ca, Mg, Na, Si, CO{sub 3}{sup 2-}, NO{sub 2}{sup -}, NO{sub 3}{sup -}, SO{sub 4}{sup 2-}), pH, and reduction potential (E{sub h}) in order to develop an understanding of how chemical changes associated with the pore solution influence grout weathering and radionuclide leaching behavior. This paper provides a brief update with respect to data derived from preliminary Tc-99 leaching evaluations as the DLM was being developed, but the paper is predominantly focused on new sample data in which the DLM technique, pre- and post-DLM salt-stone sample characterization, and leachate analysis protocols have been optimized. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Implementation of hybrid variance reduction methods in a multi group Monte Carlo code for deep shielding problems

In this paper, the work that has been done to implement variance reduction techniques in a three dimensional, multi group Monte Carlo code - Tortilla, that works within the frame work of the commercial deterministic code - Attila, is presented. This project is aimed to develop an integrated Hybrid code that seamlessly takes advantage of the deterministic and Monte Carlo methods for deep shielding radiation detection problems. Tortilla takes advantage of Attila's features for generating the geometric mesh, cross section library and source definitions. Tortilla can also read importance functions (like adjoint scalar flux) generated from deterministic calculations performed in Attila and use them to employ variance reduction schemes in the Monte Carlo simulation. The variance reduction techniques that are implemented in Tortilla are based on the CADIS (Consistent Adjoint Driven Importance Sampling) method and the LIFT (Local Importance Function Transform) method. These methods make use of the results from an adjoint deterministic calculation to bias the particle transport using techniques like source biasing, survival biasing, transport biasing and weight windows. The results obtained so far and the challenges faced in implementing the variance reduction techniques are reported here. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Breast Cancer-Related Arm Lymphedema: Incidence Rates, Diagnostic Techniques, Optimal Management and Risk Reduction Strategies

As more women survive breast cancer, long-term toxicities affecting their quality of life, such as lymphedema (LE) of the arm, gain importance. Although numerous studies have attempted to determine incidence rates, identify optimal diagnostic tests, enumerate efficacious treatment strategies and outline risk reduction guidelines for breast cancer-related lymphedema (BCRL), few groups have consistently agreed on any of these issues. As a result, standardized recommendations are still lacking. This review will summarize the latest data addressing all of these concerns in order to provide patients and health care providers with optimal, contemporary recommendations. Published incidence rates for BCRL vary substantially with a range of 2-65% based on surgical technique, axillary sampling method, radiation therapy fields treated, and the use of chemotherapy. Newer clinical assessment tools can potentially identify BCRL in patients with subclinical disease with prospective data suggesting that early diagnosis and management with noninvasive therapy can lead to excellent outcomes. Multiple therapies exist with treatments defined by the severity of BCRL present. Currently, the standard of care for BCRL in patients with significant LE is complex decongestive physiotherapy (CDP). Contemporary data also suggest that a multidisciplinary approach to the management of BCRL should begin prior to definitive treatment for breast cancer employing patient-specific surgical, radiation therapy, and chemotherapy paradigms that limit risks. Further, prospective clinical assessments before and after treatment should be employed to diagnose subclinical disease. In those patients who require aggressive locoregional management, prophylactic therapies and the use of CDP can help reduce the long-term sequelae of BCRL.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Strain induced grain boundary migration effects on grain growth of an austenitic stainless steel during static and metadynamic recrystallization

Static and metadynamic recrystallization of an AISI 304L austenitic stainless steel was investigated at 1100 °C and 10{sup −} {sup 2} s{sup −} {sup 1} strain rate. The kinetics of recrystallization was determined through double hit compression tests. Two strain levels were selected for the first compression hit: ε{sub f} = 0.15 for static recrystallization (SRX) and 0.25 for metadynamic recrystallization (MDRX). Both the as-deformed and the recrystallized microstructures were investigated through optical microscopy and electron back-scattered diffraction (EBSD) technique. During deformation, strain induced grain boundary migration appeared to be significant, producing a square-like grain boundary structure aligned along the directions of the maximum shear stresses in compression. EBSD analysis revealed to be as a fundamental technique that the dislocation density was distributed heterogeneously in the deformed grains. Grain growth driven by surface energy reduction was also investigated, finding that it was too slow to explain the experimental data. Based on microstructural results, it was concluded that saturation of the nucleation sites occurred in the first stages of recrystallization, while grain growth driven by strain induced grain boundary migration (SIGBM) dominated the subsequent stages. - Highlights: • Recrystallization behavior of a stainless steel was investigated at 1100 °C. • EBSD revealed that the dislocation density distribution was heterogeneous during deformation. • Saturation of nucleation sites occurred in the first stages of recrystallization. • Strain induced grain boundary migration (SIGBM) effects were significant. • Grain growth driven by SIGBM dominated the subsequent stages.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Fast Charging of Li-Ion Cells: Part II. Nonlinear Contributions to Cell and Electrode Polarization

In this series, Li/Cu microprobes are used to monitor potentials of individual electrodes in situ during high-rate charging of Li-ion cells. Here we focus on capacity-limited charging of these cells to 6C, and present a general treatment of polarization that allows for data reduction and accurate interpolation/extrapolation over a wide range of charge rates. We show that the anode impedance as measured both using this new treatment and the more established pulsed-current techniques is not significantly changed after high-rate aging of the cell, including the conditions under which Li plating has occurred. Our measurements suggest that the changes in cell and electrode polarization to a large extent occur through nonlinear effects that involve time-delayed processes. An electrochemical model that includes phase dynamics in lithiated graphite is shown to capture some but not all of the observed trends suggesting that important facets of the high-rate behavior need to be included in such models.

25 ENERGY STORAGE↗
DOE OSTI2019

Function Preserving Projection (FPP): A Linear Projection Technique for Visual Interpretation of High-Dimensional Functions

In this work, we propose function preserving projection (FPP), a new class of scalable linear projection techniques for finding interpretable structure in highdimensional datasets. Instead of focusing on preserving the structure of highdimensional points as traditional dimensionality reduction methods, we aim to find a 2D view of the data, in which human interpretable patterns of meaningful properties (that defined on the high-dimensional points, i.e., functions in a highdimensional domain) are revealed. Such a visual-centric approach introduces new avenues for exploratory data analysis and allows efficient implementation that provides a scalable tool for exploring potentially unknown or unexpected relationships in complex and large high-dimensional data (e.g., beyond millions of samples and tens of thousands of dimensions).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model errors. This enables ROMs to be rigorously incorporated in uncertainty-quantification settings, as the error model can be treated as a source of epistemic uncertainty. This work was completed as part of a Truman Fellowship appointment. We note that much additional work was performed as part of the Fellowship. One salient project is the development of the Trilinos-based model-reduction software module Razor , which is currently bundled with the Albany PDE code and currently allows nonlinear reduced-order models to be constructed for any application supported in Albany. Other important projects include the following: 1. ROMES-equipped ROMs for Bayesian inference: K. Carlberg, M. Drohmann, F. Lu (Lawrence Berkeley National Laboratory), M. Morzfeld (Lawrence Berkeley National Laboratory). 2. ROM-enabled Krylov-subspace recycling: K. Carlberg, V. Forstall (University of Maryland), P. Tsuji, R. Tuminaro. 3. A pseudo balanced POD method using only dual snapshots: K. Carlberg, M. Sarovar. 4. An analysis of discrete v. continuous optimality in nonlinear model reduction: K. Carlberg, M. Barone, H. Antil (George Mason University). Journal articles for these projects are in progress at the time of this writing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Alkali Cation Inhibition of Imidazolium-Mediated Electrochemical CO 2 Reduction on Silver

Imidazolium-based ionic liquids have led to enhanced CO 2 electroreduction activity due to cation effects at the cathode surface, stabilizing the reaction intermediates and decreasing the activation energy. In aqueous media, alkali cations are also known to improve CO 2 reduction activity on metals such as Ag, with the enhancement attributed to electrical double layer effects and trending with the size of the alkali cation. However, the effect of a mixed catholyte solution of alkali cations in the presence of an imidazolium-based ionic liquid has not been well-explored. Herein, 1-ethyl-3-methylimidazolium tetrafluoroborate, [EMIM][BF 4 ], in water was investigated with alkali salts to unravel the interaction effects for CO 2 electroreduction on Ag. Although both [EMIM] + and alkali cations have individually improved CO 2 to CO conversion on Ag in water, electrochemical results showed that alkali cations hindered imidazolium-mediated CO 2 electroreduction in most conditions. Li + , in particular, was sharply inhibitory compared to other alkali cations and strongly redirected the selectivity to hydrogen evolution. The nature of the alkali cation inhibition was investigated with spectroscopic techniques, including in situ surface-enhanced Raman spectroscopy (SERS) and dynamic electrochemical impedance spectroscopy (DEIS). Along with computational insights from density functional theory (DFT), the electrochemical and spectroscopic data suggest that alkali cations inhibit [EMIM]-mediated CO 2 reduction by competing for surface adsorption sites, preventing the potential-dependent structural reorientation of imidazolium, and promoting hydrogen evolution by bringing solvated water to the cathode surface.

cations↗
DOE OSTI2020

Discrimination of electronic recoils from nuclear recoils in two-phase xenon time projection chambers

We present a comprehensive analysis of electronic recoil vs. nuclear recoil discrimination in liquid/gas xenon time projection chambers, using calibration data from the 2013 and 2014-16 runs of the Large Underground Xenon (LUX) experiment. We observe strong charge-to-light discrimination enhancement with increased event energy. For events with S1 = 120 detected photons, i.e. equivalent to a nuclear recoil energy of ~100 keV, we observe an electronic recoil background acceptance of <10 –5 at a nuclear recoil signal acceptance of 50%. We also observe modest electric field dependence of the discrimination power, which peaks at a field of around 300 V/cm over the range of fields explored in this study (50-500 V/cm). In the WIMP search region of S1 = 1-80 phd, the minimum electronic recoil leakage we observe is (7.3 ± 0.6) 10 –4 , which is obtained for a drift field of 240-290 V/cm. Pulse shape discrimination is utilized to improve our results, and we find that, at low energies and low fields, there is an additional reduction in background leakage by a factor of up to 3. We develop an empirical model for recombination fluctuations which, when used alongside the Noble Element Scintillation Technique (NEST) simulation package, correctly reproduces the skewness of the electronic recoil data. We use this updated simulation to study the width of the electronic recoil band, finding that its dominant contribution comes from electron-ion recombination fluctuations, followed in magnitude of contribution by fluctuations in the S1 signal, fluctuations in the S2 signal, and fluctuations in the total number of quanta produced for a given energy deposition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗
DOE OSTI2021

Preliminary results of neutron and X-ray diffraction data collection on a lytic polysaccharide monooxygenase under reduced and acidic conditions

Lytic polysaccharide monooxygenases (LPMOs) are copper-center enzymes that are involved in the oxidative cleavage of the glycosidic bond in crystalline cellulose and other polysaccharides. The LPMO reaction is initiated by the addition of a reductant and oxygen to ultimately form an unknown activated copper–oxygen species that is responsible for polysaccharide-substrate H-atom abstraction. Given the sensitivity of metalloproteins to radiation damage, neutron protein crystallo­graphy provides a nondestructive technique for structural characterization while also informing on the positions of H atoms. Neutron cryo-crystallography permits the trapping of catalytic intermediates, thereby providing insight into the protonation states and chemical nature of otherwise short-lived species in the reaction mechanism. Here, to characterize the reaction-mechanism intermediates of LPMO9D from Neurospora crassa, a cryo-neutron diffraction data set was collected from an ascorbate-reduced crystal. A second neutron diffraction data set was collected at room temperature from an LPMO9D crystal exposed to low-pH conditions to probe the protonation states of ionizable groups involved in catalysis under acidic conditions.

Neurospora crassa↗