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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Combination of searches for heavy spin-1 resonances using 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb -1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, $t\overline{t}$, and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Solar neutrino detection in liquid xenon detectors via charged-current scattering to excited states

We investigate the prospects for real-time detection of solar neutrinos via the charged-current neutrino-nucleus scattering process in liquid xenon time projection chambers. We use a nuclear shell model, benchmarked with experimental data, to calculate the cross sections for populating specific excited states of the cesium nuclei produced by neutrino capture on Xe 131 and Xe 136 . The shell model is further used to compute the decay schemes of the low-lying 1 + excited states of Cs 136 , for which there is sparse experimental data. We explore the possibility of tagging the characteristic deexcitation γ rays/conversion electrons using two techniques: spatial separation of their energy deposits using event topology and their time separation using delayed coincidence. The efficiencies in each case are evaluated within a range of realistic detector parameters. We find that the topological signatures are likely to be dominated by radon backgrounds, but that a delayed-coincidence signature from long-lived states predicted in Cs 136 may enable background-free detection of CNO neutrino interactions in next-generation experiments with smaller uncertainty than current measurements. We also estimate the sensitivity as a function of exposure for detecting the solar-temperature-induced line shift in Be 7 neutrino emission, which may provide a new test of solar models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Optimized analysis method for indirect dark matter searches with imaging air Cherenkov telescopes

We propose a dedicated analysis approach for indirect Dark Matter searches with Imaging Air Cherenkov Telescopes. By using the full likelihood analysis, we take complete advantage of the distinct features expected in the gamma ray spectrum of Dark Matter origin, achieving better sensitivity with respect to the standard analysis chains. We describe the method and characterize its general performance. We also compare its sensitivity with that of the current standards for several Dark Matter annihilation models, obtaining gains of up to factors of order of 10. We compute the improved limits that can be reached using this new approach, taking as an example existing estimates for several benchmark models as well as the recent results from VERITAS on observations of the dwarf spheroidal galaxy Segue 1. Furthermore, we estimate the sensitivity of Cherenkov Telescopes for monochromatic line signals. Predictions are made on improvement that can be achieved for MAGIC and CTA. Lastly, we discuss how this method can be applied in a global, sensitivity-optimized indirect Dark Matter search that combines the results of all Cherenkov observatories of the present generation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Probing light thermal dark matter with a Higgs portal mediator

We systematically study light (<few GeV) dark matter (DM) models that thermalize with visible matter through the Higgs portal and identify the remaining gaps in the viable parameter space. Such models require a comparably light scalar mediator that mixes with the Higgs to avoid DM overproduction and can be classified according to whether this mediator decays (in)visibly. In a representative benchmark model with Dirac fermion DM, we find that, even with conservative assumptions about the DM-mediator coupling and mass ratio, the regime in which the mediator is heavier than the DM is fully ruled out by a combination of collider, rare meson decay, and direct detection limits; future and planned experiments including NA62 can further improve sensitivity to scenarios in which the Higgs portal interaction does not determine the DM abundance. The opposite regime in which the mediator is lighter than the DM and the latter annihilates to pairs of visibly decaying mediators is still viable, but much of the parameter space is covered by rare meson decay, supernova cooling, beam dump, and direct detection constraints. Nearly all of these conclusions apply broadly to the simplest variations (e.g., scalar or asymmetric DM). Future experiments including SHiP, NEWS, and Super-CDMS SNOLAB can greatly improve coverage to this class of models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Exploring theory space with Monte Carlo reweighting

Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. Specifically, we suggest procedures that allow more efficient collaboration between theorists and experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Probing the Goldstone equivalence theorem in heavy weak doublet decays

We explore here the decays from heavy Higgsino-like weak doublets into Z , h bosons and missing particles. When pair-produced at the LHC, the subsequent Z , h → ℓ ℓ , b b ¯ decays in the doublet decay cascade can yield 4 ℓ , 2 ℓ 2 b and 4 b + E T + j ( s ) final states. Mutual observation of any two of these channels would provide information on the associated doublets’ decay branching fractions into a Z or h , thereby probing the Goldstone equivalence relation, shedding additional light on the Higgs sector of beyond the Standard Model theories and facilitating the discrimination of various contending models, in turn. We compare the Z / h decay ratio expected in the minimal supersymmetric model, the next-to-minimal supersymmetric model (NMSSM)and a minimal singlet-doublet dark matter model. Furthermore, we conduct a full Monte Carlo analysis of the prospects for detecting the targeted final states during 14 TeV running of the LHC in the context of a representative NMSSM benchmark model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Exploring the performance of spatial stochastic simulation algorithms

Since the publication of Gillespie's direct method, diverse methods have been developed to improve the performance of stochastic simulation methods and to enter the spatial realm. In this paper we discuss a spatial {tau}-leaping variant (S{tau}) that extends the basic leap method. S{tau} takes reaction and both outgoing and incoming diffusion events into account when calculating a leap candidate. A performance analysis shall reveal details on the achieved success in balancing speed and accuracy in comparison to other methods. However, performance analysis of spatial stochastic algorithms requires significant effort - it is crucial to choose suitable (benchmark) models and to carefully define model and simulation setups that take problem and simulation design spaces into account.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes

Accurate, reliable prediction of risk for Alzheimer's disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of the multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping—morphometry and structural connectomics—and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (National Health Insurance Service-Ilsan Hospital [NHIS-IH]; N = 211; 110 AD, 64 mild cognitive impairment [MCI], and 37 cognitively normal with subjective memory complaints [SMC]) to test the diagnostic models; and, secondly, Alzheimer's Disease Neuroimaging Initiative (ADNI)-2 to test the generalizability. Our machine learning models trained on the morphometric and connectome estimates (number of features = 34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) in NHIS-IH cohort, outperforming a benchmark model (FLAIR-based white matter hyperintensity volumes). In ADNI-2 data, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) compared with the CSF biomarker model (t-tau, p-tau, and Amyloid β, and ratios). In predicting MCI to AD progression in a smaller cohort of ADNI-2 (n = 60), the morphometry model showed similar performance with 69% accuracy compared with CSF biomarker model with 70% accuracy. Our comparisons of the classifiers trained on structural MRI, diffusion MRI, FLAIR, and CSF biomarkers showed the promising utility of the white matter structural connectomes in classifying AD and MCI in addition to the widely used structural MRI-based morphometry, when combined with machine learning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Supersymmetry Breaking, Gauge Mediation, and the LHC

Gauge mediated SUSY breaking (GMSB) is a promising class of supersymmetric models that automatically satisfies the precision constraints. Prior work of Meade, Seiberg and Shih in 2008 established the full, model-independent parameter space of GMSB, which they called "General Gauge Mediation" (GGM). During the first half of 2010-2015, Shih and his collaborators thoroughly explored the parameter space of GGM and established many well-motivated benchmark models for use by the experimentalists at the LHC. Through their work, the current constraints on GGM from LEP, the Tevatron and the LHC were fully elucidated, together with the possible collider signatures of GMSB at the LHC. This ensured that the full discovery potential for GGM could be completely realized at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Skew-flavored dark matter

We explore a novel flavor structure in the interactions of dark matter with the Standard Model. We consider theories in which both the dark matter candidate, and the particles that mediate its interactions with the Standard Model fields, carry flavor quantum numbers. The interactions are skewed in flavor space, so that a dark matter particle does not directly couple to the Standard Model matter fields of the same flavor, but only to the other two flavors. This framework respects minimal flavor violation and is, therefore, naturally consistent with flavor constraints. We study the phenomenology of a benchmark model in which dark matter couples to right-handed charged leptons. In large regions of parameter space, the dark matter can emerge as a thermal relic, while remaining consistent with the constraints from direct and indirect detection. The collider signatures of this scenario include events with multiple leptons and missing energy. In conclusion, these events exhibit a characteristic flavor pattern that may allow this class of models to be distinguished from other theories of dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

Initial Coupling of the RELAP-7 and PRONGHORN Applications

Modern nuclear reactor safety codes require the ability to solve detailed coupled neutronic- thermal fluids problems. For larger cores, this implies fully coupled higher dimensionality spatial dynamics with appropriate feedback models that can provide enough resolution to accurately compute core heat generation and removal during steady and unsteady conditions. The reactor analysis code PRONGHORN is being coupled to RELAP-7 as a first step to extend RELAP’s current capabilities. This report details the mathematical models, the type of coupling, and the testing results from the integrated system. RELAP-7 is a MOOSE-based application that solves the continuity, momentum, and energy equations in 1-D for a compressible fluid. The pipe and joint capabilities enable it to model parts of the power conversion unit. The PRONGHORN application, also developed on the MOOSE infrastructure, solves the coupled equations that define the neutron diffusion, fluid flow, and heat transfer in a full core model. The two systems are loosely coupled to simplify the transition towards a more complex infrastructure. The integration is tested on a simplified version of the OECD/NEA MHTGR-350 Coupled Neutronics-Thermal Fluids benchmark model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Search for Higgs boson decays to beyond-the-Standard-Model light bosons in four-lepton events with the ATLAS detector at $ \sqrt{s}=13 $ TeV

A search is conducted for a beyond-the-Standard-Model boson using events where a Higgs boson with mass 125 GeV decays to four leptons (ℓ = e or μ). This decay is presumed to occur via an intermediate state which contains one or two on-shell, promptly decaying bosons: H → ZX/XX → 4ℓ, where X is a new vector boson Z d or pseudoscalar a with mass between 1 and 60 GeV. The search uses pp collision data collected with the ATLAS detector at the LHC with an integrated luminosity of 36.1 fb -1 at a centre-of-mass energy s√=13 TeV. No significant excess of events above Standard Model background predictions is observed; therefore, upper limits at 95% confidence level are set on modelindependent fiducial cross-sections, and on the Higgs boson decay branching ratios to vector and pseudoscalar bosons in two benchmark models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

DERIVING THE GLOBAL STRUCTURE OF THE GALACTIC MAGNETIC FIELD FROM FARADAY ROTATION MEASURES OF EXTRAGALACTIC SOURCES

We made use of the two latest sets of rotation measures (RMs) of extragalactic radio sources, namely the NRAO VLA Sky Survey rotation measures catalog and a compilation by Kronberg and Newton-McGee, to infer the global structure of the Galactic magnetic field (GMF). We have checked that these two data sets are mutually consistent. Given the existence of clear patterns in the all-sky RM distributions we considered GMF models consisting of two components: disk (spiral or ring) and halo. The parameters of these components were determined by fitting different model field geometries to the observed RMs. We found that the model consisting of a symmetric (with respect to the Galactic plane) spiral disk and antisymmetric halo fits the data best and reproduces the observed distribution of RMs over the sky very well. We confirm that ring disk models are disfavored. Our results favor small pitch angles around {approx} - 5{sup 0} and an increased vertical scale of electron distribution, in agreement with some recent studies. Based on our fits, we select two benchmark models suitable for studies of cosmic ray propagation, including cosmic rays at ultrahigh energies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Benchmark Evaluation of the NRAD Reactor LEU Core Startup Measurements

The Neutron Radiography (NRAD) reactor is a 250-kW TRIGA-(Training, Research, Isotope Production, General Atomics)-conversion-type reactor at the Idaho National Laboratory; it is primarily used for neutron radiography analysis of irradiated and unirradiated fuels and materials. The NRAD reactor was converted from HEU to LEU fuel with 60 fuel elements and brought critical on March 31, 2010. This configuration of the NRAD reactor has been evaluated as an acceptable benchmark experiment and is available in the 2011 editions of the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook) and the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook). Significant effort went into precisely characterizing all aspects of the reactor core dimensions and material properties; detailed analyses of reactor parameters minimized experimental uncertainties. The largest contributors to the total benchmark uncertainty were the 234 U, 236 U, Er, and Hf content in the fuel; the manganese content in the stainless-steel cladding; and the unknown level of water saturation in the graphite reflector blocks. A simplified benchmark model of the NRAD reactor was prepared with a keff of 1.0012 ± 0.0029 (1σ). Monte Carlo calculations with MCNP5 and KENO-VI and various neutron cross section libraries were performed and compared with the benchmark eigenvalue for the 60-fuel-element core configuration; all calculated eigenvalues are between 0.3 and 0.8% greater than the benchmark value. Benchmark evaluations of the NRAD reactor are beneficial in understanding biases and uncertainties affecting criticality safety analyses of storage, handling, or transportation applications with LEU-Er-Zr-H fuel.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗