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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Pythia8 Quark and Gluon Jets (float8 e4m3FN)

A float8 (e4m3FN) quantized version of the quark and gluon jet dataset originally published by Komiske, Metodiev, and Thaler (Zenodo record 3164691). Only the 20-file subset without charm and bottom quark jets is included here. All simulation parameters and jet selection criteria are identical to the original: Pythia 8.226, √s = 14 TeV Quarks from WeakBosonAndParton:qg2gmZq, gluons from WeakBosonAndParton:qqbar2gmZg with the Z decaying to neutrinos FastJet 3.3.0, anti-k_t jets with R = 0.4 p_T^jet ∈ [500, 550] GeV, |y^jet| < 1.7 There are 20 files, each in compressed NumPy format (QG_jets_fp8e4m3fn_0.npz through QG_jets_fp8e4m3fn_19.npz). Each file contains two arrays: X: (100000, M, 4) — 50k quark and 50k gluon jets, randomly sorted, padded to max multiplicity M, with particle features (pt, rapidity, azimuthal angle, pdgid) y: (100000,) — jet labels, gluon = 0, quark = 1 Since NumPy has no native fp8 dtype, X is stored as float32, but the values have been quantized through TensorFlow's float8_e4m3fn type and carry only fp8 precision. The quantization procedure is as follows: a global per-channel scale factor is computed from the absolute maximum value across all 20 chunks (with FP8_MAX = 448.0, the maximum representable value of e4m3FN). Each chunk is then scaled into the fp8 dynamic range, round-tripped through tf.experimental.float8_e4m3fn, and scaled back. This global scaling ensures a consistent quantization grid across the full dataset. The y labels are unchanged. Users should be aware that e4m3FN has limited dynamic range and precision. We recommend verifying this format is appropriate for your application; for a less aggressive reduction see the float16 and float32 versions linked below. If you use this dataset, please cite the original Zenodo record and its associated paper: Komiske, Metodiev, Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121, arXiv:1810.05165

DiLullo, Nicholas [Brown University] (ORCID:000000↗
DOE OSTI2022

Non-decoupling new particles

We initiate the study of a new class of beyond the Standard Model states that we call “Loryons.” They have the defining characteristic of being non-decoupling, in the sense that their physical mass is dominated by a contribution from the vacuum expectation value of the Higgs boson. The stakes are high: the discovery of a Loryon would tell us that electroweak symmetry must be non-linearly realized in the effective field theory of the Standard Model. Loryons have their masses bounded from above by perturbative unitarity considerations and thus define a finite parameter space for exploration. After providing a complete catalog of Loryon representations under mild assumptions, we turn to examining the constraints on the parameter space from Higgs couplings measurements, precision electroweak tests, and direct collider searches. We show that most fermionic candidates are already ruled out (with some notable exceptions), while much of the scalar Loryon parameter space is still wide open for discovery.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Advancing the Understanding of Cloud Microphysical Processes and Aerosol Indirect Effects in High-Latitude Mixed-Phase Clouds by Linking ARM Measurements with Climate Model Simulations (Final Report)

The key objectives of this project were to advance our understanding of cloud microphysical characteristics and aerosol indirect effects on mixed-phase clouds in high latitudes. To improve the representation of ice and mixed-phase clouds in Earth System Models (ESMs), we propose an integrated observation and modeling study of cloud macro- and microphysical properties, including spatial heterogeneities, mass partitioning between ice crystals and supercooled liquid water, effects of ice nucleating particles (INPs), and efficiency of secondary ice production (SIP), etc. Specifically, we took four main approaches in this project: (1) examining macro- and microphysical properties of ice and mixed-phase clouds based on in-situ and ground-based observations from multiple field campaigns funded by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program, including the Mixed-Phase Arctic Cloud Experiment (M-PACE), Indirect and Semi-Direct Aerosol Campaign (ISDAC), Ice Nucleating Particle Sources at Oliktok Point (INPOP), ARM West Antarctic Radiation Experiment (AWARE), Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS), and Macquarie Island Cloud and Radiation Experiment (MICRE); (2) evaluating the DOE Energy Exascale Earth System Model (E3SM) simulations based on observations, particularly for ice and mixed-phase cloud microphysical properties; (3) examining the impacts of INPs on ice and mixed-phase clouds. Specifically, a series of comparisons were conducted using observations over the Arctic, Southern Ocean, and Antarctica, including comparisons between the lower and higher southern latitudes as well as comparisons between the northern and southern hemispheres. In addition, aerosol indirect effects from distinct sources of dust particles were examined; and (4) investigating the impacts of SIP. Ultimately, these results helped to improve cloud microphysics and aerosol-cloud interaction parameterizations in the E3SM model. Overall, the project provided improved understanding regarding various factors, including thermodynamic, dynamic, and aerosol conditions, on the micro- and macrophysical properties of ice and mixed-phase clouds in the high latitudes. Resulting analysis helped to provide an improved physical basis for refining the current cloud microphysics parameterizations related to ice and mixed-phase clouds in E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Prong Segmentation using Point Set Transformers in Multiple View Neutrino Detectors

NOvA is a long-baseline neutrino experiment studying neutrino oscillations by detecting neutrinos from the NuMI beam at Fermilab. Its physics analysis relies on accurate prong segmentation, which involves matching each hit to its source particle and identifying the particle type. This task has commonly been addressed using a combination of traditional clustering algorithms and convolutional neural networks (CNNs). However, NOvA’s detector design presents data as two sparse and decoupled 2D images (XZ and YZ views) rather than a native 3D representation, posing a significant challenge for traditional CNN-based models. In this talk, we propose a novel neural network based on the Point Set Transformer. By treating detector hits as sparse point clouds and implementing a cross-view attention mechanism, our model enables efficient information mixing between both views. Evaluated on NOvA simulated data, our model achieves superior accuracy while requiring significantly fewer computational resources compared to other models. Furthermore, the model demonstrates great performance when applied to Liquid Argon Time Projection Chamber (LArTPC) data, which shows its potential as a universal prong segmentation algorithm for multiple view neutrino detectors.

Liu, Jiaxi [UC, Irvine]↗
NASA NTRS1980

Rocket observations of solar radiation during the eclipse of 26 February 1979

Three Nike Tomahawk rockets were launched in Red Lake, Ontario, one previous to, and two during, the total eclipse of the Sun, for the purpose of studying the atmosphere and its interaction with solar radiation. The method and preliminary results of three experiments that were used to measure solar radiation in the X-ray, Lyman-alpha, and visible parts of the spectrum are described. The instrumentation designed for this investigation is discussed as well as post-flight data processing techniques. The retrieved data were processed to some extent to verify that a valid representation of the solar radiation was obtained. The Lyman-alpha experiment yielded very good results, and preliminary data are included. The visible radiation experiment served as support for the other experiments and also functioned well. Due to a high level of energetic particles during the eclipse, the X-ray data were contaminated and are not presented. However, satellite observations indicate no appreciable level of X-rays from the Sun during the time of the eclipse.

Bliss, H. M.↗
DOE OSTI2021

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

Abstract Mesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

GPU-Accelerated Analytic Simulation of Sparse Ionization Signal Formation in Pixelated Projection Detector

This paper presents a GPU-accelerated simulation package, TRED, for next-generation neutrino detectors with pixelated charge readout, leveraging community-driven software ecosystems to ensure adaptability and extensibility. We introduce two generic contributions: (i) an effective-charge representation based on Gaussian quadrature rules, in which the linear- interpolation factors for the field response inside each voxel are absorbed into the effective charge, and (ii) a sparse, block- binned tensor representation that enables efficient FFT-based computation of induced signals on readout electrodes for sparsely activated detector volumes. The former captures structure inside a voxel without dense sampling, while the latter achieves low memory usage and scalable runtime, as demonstrated in bench- mark studies. The underlying data representation is applicable to large-scale detectors and to other computational problems involving sparse activity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Probing extended scalar sectors with precision e + e - → Zh and Higgs diphoton studies

We compute the one-loop corrections to σ(e + e - → Zh) arising from representative extended Standard Model scalar sector scenarios. According to the new scalar SU(2)L representations, we consider the inert doublet, real and complex triplet, quintuplet, and septuplet models. With the sub-percent level precision expected for prospective future e + e - collider measurements of σ(e + e - → Zh), studies of the Higgsstrahlung process will probe extended scalar sector particle spectrum and interactions in a manner complementary to direct searches at the Large Hadron Collider and possible future pp colliders. We also compare with the sensitivity of future Higgs diphoton decay rate measurements. We find that the σ(e + e - → Zh) and Γ(h → γγ) complementarity is particularly pronounced for the complex triplet model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Global variability in atmospheric new particle formation mechanisms

A key challenge in aerosol pollution studies and climate change assessment is to understand how atmospheric aerosol particles are initially formed. Although new particle formation (NPF) mechanisms have been described at specific sites, in most regions, such mechanisms remain uncertain to a large extent because of the limited ability of atmospheric models to simulate critical NPF processes. Here we synthesize molecular-level experiments to develop comprehensive representations of 11 NPF mechanisms and the complex chemical transformation of precursor gases in a fully coupled global climate model. Combined simulations and observations show that the dominant NPF mechanisms are distinct worldwide and vary with region and altitude. Previously neglected or underrepresented mechanisms involving organics, amines, iodine oxoacids and HNO 3 probably dominate NPF in most regions with high concentrations of aerosols or large aerosol radiative forcing; such regions include oceanic and human-polluted continental boundary layers, as well as the upper troposphere over rainforests and Asian monsoon regions. These underrepresented mechanisms also play notable roles in other areas, such as the upper troposphere of the Pacific and Atlantic oceans. Accordingly, NPF accounts for different fractions (10–80%) of the nuclei on which cloud forms at 0.5% supersaturation over various regions in the lower troposphere. The comprehensive simulation of global NPF mechanisms can help improve estimation and source attribution of the climate effects of aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Texas A&M University Mobile Facility Measurements during TRACER (Field Campaign Report)

One of the main goals of the U.S Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) near Houston, Texas is to improve understanding of how meteorology and aerosols impact storm dynamical and microphysical processes in deep convection to better constrain and improve their model representation. The Houston area is strongly influenced by sea- and bay-breeze circulations that generate convergence and help to initiate and organize deep convection. To properly isolate and understand the roles of varied meteorological conditions and cloud condensation nuclei (CCN) and ice nucleation particles (INP) distributions in different air masses, co-located thermodynamic, kinematic, and aerosol vertical profile observations are needed. The focus of this campaign was to provide key measurements in air masses both in front of and behind sea/bay breeze fronts moving through the greater Houston area to sample the airmass heterogeneity. The overarching scientific goal of this campaign is to understand how the vertical distributions of both CCN and INP correspond to the inflow layer of deep convection in maritime, background continental, and polluted continental air masses, and how these variations influence deep convection. To fully sample the heterogeneity in both meteorological conditions and aerosols across the sea-breeze front (SBF), Texas A&M University (TAMU) deployed a InterMet 3050A 403 MHz mobile unit launching iMet-4 radiosondes and the new Rapid Onsite Atmospheric Measurement Van (ROAM-V) for aerosol sampling during the TRACER intensive operational period (IOP) from June to September 2022. The suite of instruments deployed on ROAM-V included a condensation particle counter (CPC; GRIMM Model 5.403 CPC), scanning mobility particle sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A differential mobility analyzer), cloud condensation nuclei counter (Droplet Measurement Technologies CCN counter), micropulse lidar (Droplet Measurement Technologies micropulse lidar [miniMPL]), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the Global Positioning System (GPS) on the phone application “My Altitude”. The DRUM data were collected as part of a closely related ARM field campaign and also supported by DOE Atmospheric System Research grant DE-SC0021047. The TAMU team sampled these airmass heterogeneities by strategically choosing deployment sites in a different airmass than the ARM fixed sites in La Porte and Guy, Texas. On days when the sea/bay breeze boundary was pushing inland, the TAMU team would usually sample the airmass on the maritime side of the SBF at a coastal site in Galveston, Texas in the early afternoon (1730-1900 UTC) and then move inland ahead of the SBF to sample the airmass on the continental side during late afternoon (2030-2230). Figure 1 shows the Galveston maritime site and the array of sites for the late afternoon continental measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Processing MCNP Elemental Edit Outputs

The Monte Carlo N-Particle (MCNP) transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into constructive solid geometry (CSG) cells. A UM geometry is a collection of elements representing a solid geometry. The first step of MCNP UM modeling is using other software packages to create a finite element mesh representation of a solid 3D geometry. Computer-aided design (CAD) or computer-aided manufacturing (CAM) software is typically used to create a solid geometry model, which is later imported into mesh generation software to create a UM model. The MCNP UM feature was originally designed for models generated by the Abaqus/CAE software. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. MCNP can process a UM model consisting of several different element types including linear tetrahedral or hexahedral elements and calculate quantities of interest such as flux and energy deposition at elements. An MCNP UM simulation provides high-fidelity elemental edit (i.e., tally) outputs, which can be further used in multiphysics calculations. The MCNP UM feature was used for multiphysics simulations where quantities of interest calculated by MCNP are used as inputs for heat transfer calculations in Abaqus. MCNP6.3 can produce two types of elemental edit output (EEOUT) file formats: ASCII and HDF5. An EEOUT file type must be requested on an EMBED card while output type (flux or energy deposition) must be requested on an EMBEE card. We wrote Python3 scripts to extract energy deposition values in an ASCII or HDF5 EEOUT file and compute a heat flux profile for an Abaqus heat transfer calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

CELFE: Coupled Eulerian-Lagrangian Finite Element program for high velocity impact. Part 1: Theory and formulation

A 3-D finite element program capable of simulating the dynamic behavior in the vicinity of the impact point, together with predicting the dynamic response in the remaining part of the structural component subjected to high velocity impact is discussed. The finite algorithm is formulated in a general moving coordinate system. In the vicinity of the impact point contained by a moving failure front, the relative velocity of the coordinate system will approach the material particle velocity. The dynamic behavior inside the region is described by Eulerian formulation based on a hydroelasto-viscoplastic model. The failure front which can be regarded as the boundary of the impact zone is described by a transition layer. The layer changes the representation from the Eulerian mode to the Lagrangian mode outside the failure front by varying the relative velocity of the coordinate system to zero. The dynamic response in the remaining part of the structure described by the Lagrangian formulation is treated using advanced structural analysis. An interfacing algorithm for coupling CELFE with NASTRAN is constructed to provide computational capabilities for large structures.

Lee, C. H.↗
NASA NTRS1991

On representation of mechanical behavior and stereological measures of microstructure

Macroscopic homogeneity of a heterogeneous body is defined from various points of view. The applicability of the principle of Delesse to a single macroscopically homogeneous body is discussed. It is then seen that a function derived from a consideration of the area fraction of a phase can serve as a measure of clustering of particles of that phase.

Onat, E. T.↗
NASA NTRS2008

Understanding Ice Supersaturation, Particle Growth, and Number Concentration in Cirrus Clouds

Many factors control the ice supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, ice nucleation mechanisms, and ice crystal growth rate on the evolution and distribution of water vapor and cloud properties in nighttime cirrus clouds using a one-dimensional cloud model with bin microphysics and remote sensing measurements obtained at the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. We forced the model using both large-scale vertical ascent and, for the first time, mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where a classical theory heterogeneous scheme is compared with empirical representations. We evaluated model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities. Model sensitivity to the ice growth rate is also investigated. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast ice crystal growth, and initiate ice by either homogeneous or heterogeneous nucleation. Simulated ice crystal number concentrations (tens to hundreds particles per liter) are typically two orders of magnitude smaller than previously published results based on aircraft measurements in cirrus clouds, although higher concentrations are possible in isolated pockets within the nucleation zone.

Comstock, Jennifer M.↗
DOE OSTI2023

Emulating aerosol optics with randomly generated neural networks

Abstract. Atmospheric aerosols have a substantial impact on climate and remain one of the largest sources of uncertainty in climate prediction. Accurate representation of their direct radiative effects is a crucial component of modern climate models. However, direct computation of the radiative properties of aerosol populations is far too computationally expensive to perform in a climate model, so optical properties are typically approximated using a parameterization. This work develops artificial neural networks (ANNs) capable of replacing the current aerosol optics parameterization used in the Energy Exascale Earth System Model (E3SM). A large training dataset is generated by using Mie code to directly compute the optical properties of a range of atmospheric aerosol populations given a large variety of particle sizes, wavelengths, and refractive indices. Optimal neural architectures for shortwave and longwave bands are identified by evaluating ANNs with randomly generated wirings. Randomly generated deep ANNs are able to outperform conventional multilayer-perceptron-style architectures with comparable parameter counts. Finally, the ANN-based parameterization produces significantly more accurate bulk aerosol optical properties than the current parameterization when compared with direct Mie calculations using mean absolute error. The success of this approach makes possible the future inclusion of much more sophisticated representations of aerosol optics in climate models that cannot be captured by extension of the existing parameterization scheme and also demonstrates the potential of random-wiring-based neural architecture search in future applications in the Earth sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

On unitarity of tree-level string amplitudes

Four-particle tree-level scattering amplitudes in string theory are magically consistent with unitarity, reflected in the non-trivial fact that beneath the critical dimension, the residues of the amplitudes on massive poles can be expanded in partial waves with all positive coefficients. While this follows (rather indirectly) from the no-ghost theorem, the simplicity of the statement and its fundamental importance for the physical consistency of string theory begs for a more direct and elementary understanding. In this note we take a step in this direction by presenting a new expression for the partial wave coefficients of string amplitudes, given by surprisingly simple double/triple contour integrals for open/closed strings. This representation allows us to directly prove unitarity of all superstring theories in D ≤ 6 spacetime dimensions, and can also be used to determine various asymptotics of the partial waves at large mass levels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2014

Intercomparison of Large-Eddy Simulations of Arctic Mixed-Phase Clouds: Importance of Ice Size Distribution Assumptions

Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds.

clouds↗