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DOE OSTI2024

Angular analysis of B → K * e + e − in the low- q 2 region with new electron identification at Belle

We perform an angular analysis of the B → K * e + e − decay for the dielectron mass squared, q 2 , range of 0.0008 – 1.1200 GeV 2 / c 4 using the full Belle dataset in the K * 0 → K + π − and K * + → K S 0 π + channels, incorporating new methods of electron identification to improve the statistical power of the dataset. This analysis is sensitive to contributions from right-handed currents from physics beyond the Standard Model by constraining the Wilson coefficients C 7 ( ′ ) . We perform a fit to the B → K * e + e − differential decay rate and measure the imaginary component of the transversality amplitude to be A T Im = − 1.27 ± 0.52 ± 0.12 , and the K * transverse asymmetry to be A T ( 2 ) = 0.52 ± 0.53 ± 0.11 , with F L and A T Re fixed to the Standard Model values. The resulting constraints on the value of C 7 ′ are consistent with the Standard Model within a 2 σ confidence interval. Published by the American Physical Society 2024

Ferlewicz, D. (ORCID:0000000243741234)↗

DOE OSTI2024

Advanced EXAFS analysis techniques applied to the L -edges of the lanthanide oxides

The unique properties of the lanthanide (Ln) elements make them critical components of modern technologies, such as lasers, anti-corrosive films and catalysts. Thus, there is significant interest in establishing structure–property relationships for Ln-containing materials to advance these technologies. Extended X-ray absorption fine structure (EXAFS) is an excellent technique for this task considering its ability to determine the average local structure around the Ln atoms for both crystalline and amorphous materials. However, the limited availability of EXAFS reference spectra of the Ln oxides and challenges in the EXAFS analysis have hindered the application of this technique to these elements. The challenges include the limited k-range available for the analysis due to the superposition of L-edges on the EXAFS, multielectron excitations (MEEs) creating erroneous peaks in the EXAFS and the presence of inequivalent absorption sites. Herein, we removed MEEs to model the local atomic environment more accurately for light Ln oxides. Further, we investigated the use of cubic and non-cubic lattice expansion to minimize the fitting parameters needed and connect the fitting parameters to physically meaningful crystal parameters. The cubic expansion reduced the number of fitting parameters but resulted in a statistically worse fit. The non-cubic expansion resulted in a similar quality fit and showed non-isotropic expansion in the crystal lattice of Nd 2 O 3 . In total, the EXAFS spectra and the fits for the entire set of Ln oxides (excluding promethium) are included. The knowledge developed here can assist in the structural determination of a wide variety of Ln compounds and can further studies on their structure–property relationships.

36 MATERIALS SCIENCE↗

DOE OSTI2018

New Parameter in the Description of Solar Cosmic Ray Events—Energy of Balance between Solar and Galactic Protons

Solar proton events possess a wide variety of features that reflect the conditions of solar proton acceleration and propagation. Relevant investigations rely on statistical methods that make it possible to classify events with the aim of obtaining deeper insight into physical processes leading to the generation of solar cosmic rays. In classifying events in power, the intensity of particles with energy above 10MeV at the maximum of the event time profile or the fluence of particles throughout the event time is usually used. A new parameter, E{sub qm}, that characterizes the proton event power and which is some kind of approximation of the maximum energy of accelerated particles is analyzed in the present study. Correlations of E{sub qm} with properties of x-ray flares on the Sun and with the velocity of coronal mass ejections are examined.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Probing Flavor Asymmetry of Anti-quarks in the Proton by Drell-Yan Experiment SeaQuest

A new measurement on the avor asymmetry between d and u in the proton is reported in this thesis. The proton contains a substantial number of antiquarks which arise from dynamical interactions of gluons such as gluon dissociation to a quark-antiquark pair, g ! q + q, and from non-perturbative processes as described by the pion-cloud model, for example. The antiquarks in the proton undertake an important role in determining the dynamic characteristics of the internal structure of the proton, although its distribution in the proton and its origin are not fully understood. Understanding sea quarks in hadron is an important subject for QCD. The SeaQuest experiment at Fermi National Accelerator Laboratory (Fermilab) is a xed target experiment using the 120 GeV proton beam extracted from the Fermilab Main Injector. One of the goals of the experiment is to measure the avor asymmetry between d quark and u quark in the proton as a function of the target Bjorken x using the Drell-Yan process in the p-p or p-d reactions. This process takes place in hadron-hadron collisions when a quark in one hadron in the beam and an antiquark in other hadron in the target annihilate into a virtual photon that decays into a lepton pair. The avor asymmetry between d and u quarks was found by deep-inelastic scattering experiment NMC at CERN. The E866/NuSea experiment at Fermilab obtained the avor asymmetry in the proton for 0:015 < x < 0:35 using the 800 GeV proton beam extracted from the Fermilab Tevatron. The result indicates the dominance of d; it is 70% larger than u at lower x. The SeaQuest experiment was planned to do a new precise measurement at higher x region. The lower energy beam (120 GeV) increases the Drell-Yan cross section and suppresses the background primarily arising from J/ decays. Therefore, SeaQuest will obtain more statistics in a shorter time than the E866 experiment. After detector construction, detector commissioning and accelerator upgrade, physics data taking started in 2013. The SeaQuest spectrometer is designed to detect dimuon from the Drell-Yan process. It consists of targets, two di-pole magnets, and four tracking detector groups. The third tracking detector group has two drift chambers. One was newly fabricated in Japan by the Japanese group in SeaQuest collaboration and was shipped to Fermilab. The other one was constructed by SeaQuest collaborator in Fermilab under the initiative of the Japanese group. I worked on the construction and installation of the detectors, data taking and data analysis in SeaQuest. I extracted the avor asymmetry as a function of Bjorken x using the SeaQuest data for the rst time. This thesis shows the results using a part of data taken in 2014 and 2015. The asymmetry was extracted for much wider Bjorken x region than the previous experiment. The measured Bjorken x range covers up to 0.58. The result shows that the ratio of d=u is always higher than 1 at 0:1 < x < 0:45, in contrast to the E866 result. For 0:45 < x < 0:58, the result shows that the ratio is close to unity. Predictions made by current PDF parameterizations are in agreement with the present result. Also, a prediction obtained by one of the non-perturbative models, pion-cloud model, is closer to the SeaQuest result than the E866 result. This result of d=u asymmetry at the wide Bjorken x region, 0:1 < x < 0:58, is very important information to understand the inner structure of the proton and the origin of the sea quarks in the proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

The Multi-scenario Extreme Weather Simulator: Energy Resilience for Mission Assurance

The Multi-scenario extreme weather simulator (MEWS) is a stochastic weather generation tool. The MEWS algorithm uses 50 or more years of National Oceanic and Atmospheric Association (NOAA) daily summaries [1] for maximum and minimum temperature and NOAA climate norms [2] to calculate historical heat wave and cold snap statistics. The algorithm takes these statistics and shifts them according to multiplication factors provided in the Intergovernmental Panel on Climate Change (IPCC) physical basis technical summary [3] for heat waves.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Status of the Short-Baseline Near Detector at Fermilab

The Short-Baseline Near Detector (SBND) is one of the Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, and is the near detector in the Short-Baseline Neutrino (SBN) Program. The detector completed commissioning and began taking neutrino data in the summer of 2024. SBND is characterized by superb imaging capabilities and will record around 2 million neutrino interactions per year. Thanks to its unique combination of measurement resolution and statistics, SBND will soon carry out a rich program of neutrino interaction measurements and novel searches for physics beyond the Standard Model (BSM). As the near detector, it will enable the full potential of the SBN sterile neutrino program by performing a precise characterization of the unoscillated event rate and constraining BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the physics reach, current status, and future prospects of SBND are discussed.

Paton, Josephine [Fermilab]↗

DOE OSTI2026

Status of the Short-Baseline Near Detector at Fermilab

The Short-Baseline Near Detector (SBND) is one of the Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, and is the near detector in the Short-Baseline Neutrino (SBN) Program. The detector has completed Run 1, successfully recording approximately 3 million neutrino interactions, and started Run 2 in the autumn of 2025. SBND is characterized by superb imaging capabilities and will record around 3 million neutrino interactions per year. Thanks to its unique combination of measurement resolution and statistics, SBND will soon carry out a rich program of neutrino interaction measurements and novel searches for physics beyond the Standard Model (BSM). As the near detector, it will enable the full potential of the SBN sterile neutrino program by performing a precise characterization of the unoscillated event rate and constraining the BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the physics reach, current status, and future prospects of SBND are discussed.

Del Tutto, Marco [Fermilab]↗

DOE OSTI2026

Status of the Short-Baseline Near Detector at Fermilab

The Short-Baseline Near Detector (SBND) is one of the Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, and is the near detector in the Short-Baseline Neutrino (SBN) Program. The detector has completed Run 1, successfully recording approximately 3 million neutrino interactions, and started Run 2 in the autumn of 2025. SBND is characterized by superb imaging capabilities and will record around 3 million neutrino interactions per year. Thanks to its unique combination of measurement resolution and statistics, SBND will soon carry out a rich program of neutrino interaction measurements and novel searches for physics beyond the Standard Model (BSM). As the near detector, it will enable the full potential of the SBN sterile neutrino program by performing a precise characterization of the unoscillated event rate and constraining the BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the physics reach, current status, and future prospects of SBND are discussed.

Del Tutto, Marco [Fermilab]↗

DOE OSTI2018

A Hydropower Biological Evaluation Toolset (HBET) for Characterizing Hydraulic Conditions and Impacts of Hydro-Structures on Fish

Currently, approximately 16% of the world’s electricity and over 80% of the world’s renewable electricity is generated from hydropower resources, and there is potential for development of a significant amount of new hydropower capacity. However, in practice, realizing all the potential hydropower resource is limited by various factors, including environmental effects and related mitigation requirements. That is why hydropower regulatory requirements frequently call for targets to be met regarding fish injury and mortality rates. Hydropower Biological Evaluation Toolset (HBET), an integrated suite of software tools, is designed to characterize hydraulic conditions of hydropower structures and provide quantitative estimates of fish injury and mortality rates due to various physical stressors including strike, pressure, and shear. HBET enables users to design new studies, analyze data, perform statistical analyses, and evaluate biological responses. In this paper, we discuss the features of the HBET software and describe a case study that illustrates its functionalities. Here, HBET can be used by turbine manufacturers, hydropower operators, and regulators to design and operate hydropower systems that minimize ecological impacts in a cost-effective manner.

13 HYDRO ENERGY↗

DOE OSTI2023

Reconstructing Ly$α$ Fields from Low-resolution Hydrodynamical Simulations with Deep Learning

Hydrodynamical cosmological simulations are a powerful tool for accurately predicting the properties of the intergalactic medium (IGM) and for producing mock skies that can be compared against observational data. However, the need to resolve density fluctuation in the IGM puts a stringent requirement on the resolution of such simulations, which in turn limits the volumes that can be modeled, even on the most powerful supercomputers. In this work, we present a novel modeling method that combines physics-driven simulations with data-driven generative neural networks to produce outputs that are qualitatively and statistically close to the outputs of hydrodynamical simulations employing eight times higher resolution. We show that the Ly$α$ flux field, as well as the underlying hydrodynamic fields, have greatly improved statistical fidelity over a low-resolution simulation. Importantly, the design of our neural network allows for sampling multiple realizations from a given input, enabling us to quantify the model uncertainty. Using test data, we demonstrate that this model uncertainty correlates well with the true error of the Ly$α$ flux prediction. Ultimately, our approach allows for training on small simulation volumes and applying it to much larger ones, opening the door to producing accurate Ly$α$ mock skies in volumes of Hubble size, as will be probed with DESI and future spectroscopic sky surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1987

Estimating the distribution of fault latency in a digital processor

Presented is a statistical approach to measuring fault latency in a digital processor. The method relies on the use of physical fault injection where the duration of the fault injection can be controlled. Although a specific fault's latency period is never directly measured, the method indirectly determines the distribution of fault latency.

Ellis, Erik L.↗

NASA NTRS1993

A new approach to the study of the turbulence layer

Turbulent thermal convection is of considerable importance in fluid dynamical transport phenomena occurring, for example, in the planetary boundary layer of the Earth, the interiors of stars, and accretion disks. In particular, during a significant portion of the evolutionary phase of many stars having convectively unstable cores or outer envelopes, a substantial fraction of energy is transported from the central layers to the outer layers by thermal convection. Moreover, as much of the interior of a star is in highly turbulent motion, a complete theory of stellar structure and evolution requires the explicit consideration of turbulence in order to have expressions for the turbulent quantities arising in the stellar structure equations, and particularly, the turbulent fluxes that appear in the total flux conservation equation, such as the convective flux, kinetic energy flux, etc. A reliable quantification of these fluxes continues to present a challenge in astrophysical fluid dynamics, primarily because astrophysical turbulence is almost always fully-developed and nearly inviscid, and therefore governed by strong nonlinear interactions that distribute the energy among a very wide spectrum of eddies with scales ranging from the characteristic dimension of the flow to those sufficiently small to be affected by viscous dissipation. Furthermore, astrophysical flows are invariably compressible, anisotropic, and inhomogeneous, which requires the consideration of the dynamics of longitudinal modes and their interaction with the transverse modes, as well as complicated boundary conditions. In order to reach a compromise between analytical and numerical tractability and the basic physics of turbulent convection, we have constructed a model of stationary turbulent convection that yields various turbulence statistics, including the convective flux, that are required in stellar evolution models.

Levenson, Ruth A.↗

NASA NTRSDate not supplied

A Novel Machine Learning Method for Surface PM2.5 Estimations from Geostationary Satellites

Particulate matter (PM) with a diameter of less or equal to 2.5 μm, known as PM , affects human health as it penetrates the respiratory system. The Environmental Protection Agency (EPA) measures the atmospheric concentration of PM using air quality monitors stationed throughout the Continental United States (CONUS). Such measurements are points on a spatial domain and therefore, might not be representative of the air quality at nearby areas considering that the composition of the atmosphere is highly variable from place to place. Satellite based AOD permits a spatially uniform means of estimating PM and new geostationary satellites provide high temporal and spatial resolution estimation of AOD. However, the concentration of PM is non-linearly dependent on other atmospheric parameters that include relative humidity, temperature, and height of the planetary boundary layer. This information may be estimated at similar spatial and temporal resolutions as AOD from numerical modeling such as from the National Oceanic and Atmospheric Administration’s (NOAA) High Resolution Rapid Refresh (HRRR) model which resolves near real-time atmospheric conditions over the CONUS. The estimation of PM concentration is a multi-parametric problem that considers the effect of temporal dependencies among the different parameters. Deep learning approaches are appropriate for such complex estimation problems as they intrinsically capture relations among multiple non-linear parameters. This study compares deep-learning methods to traditional regression analysis to demonstrate the capabilities of these methods in predicting PM2.5 concentrations. Additionally, a novel ensemble learning approach is employed to identify scientific processes that could further improve the estimation of PM concentration. Utilizing Long Short-Term Memory (LSTM) neural networks, which are suitable for multivariate time series estimation problems as they are capable of learning long-term dependencies, individual models are created for each EPA station and trained on the aforementioned dataset collocated over each station. Individual station models are merged if the model's performance is improved by reducing the root mean squared error (RMSE) metric. This ensemble training method ultimately reduces the RMSE value. Evaluation of these results provide insights into physical processes and related observable parameters that may contribute to PM concentrations. Identified parameters evaluated to be statistically different between the merged and unmerged models are expected to improve overall performance. These new parameters are then utilized for reevaluation of the deep learning methods with an extreme gradient boosting model with an RMSE of 5.5 providing the best results.

George Priftis↗

DOE OSTI2018

On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols

Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex non-linear way, on the congestion control mechanism, buffer sizes, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity of throughput profiles which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profile to characterize the overall performance of a transport protocol. These measurements-based anaytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.

Rao, Nageswara↗

DOE OSTI2021

Search for CPT and Lorentz invariance violation in the muon $g -2$ experiment at Fermilab

The Muon g-2 experiment at Fermilab (E989) aims to measure the anomalous magnetic moment of the muon, $a_{\mu}= (g-2)/2$, to a groundbreaking precision of $140$ ppb, obtaining a near four-fold increase in precision over the previous experiment, E821, at the Brookhaven National Laboratory (BNL). The value of $a_{\mu}$ from BNL currently differs from the Standard Model prediction by $\sim 3.7$ standard deviations, suggesting the potential for new physics and therefore, motivating a new experiment.Because the theory predicts this number with high precision, testing the g-factor through experiment provides a stringent test of the SM and can suggest physics beyond the Standard Model. The goal of the Fermilab Muon $g-2$ experiment is to increase the statistical precision by more than a factor of 20 and reduce systematic errors by a factor of 3. By measuring muon precession rate ($\omega_a$) in an external magnetic field, the anomalous magnetic moment will be calculated. This is an incredibly challenging experiment with a unique opportunity to provide new insight into nature. \\ The $g-2$ data also provides a great opportunity for setting the most stringent limits on some of the Standard Model Extension CPT Lorentz violating (LV) parameters in the muon sector. One of the CPT and Lorentz violating signatures that we can look for using $g-2$ data is a sidereal variation of $\omega_a(t)$. Extensive simulation studies confirm that the sensitivity regarding the sidereal varation roughly scales with $\omega_a$ uncertainty. Hence, the $g-2$ experiment at FNAL should be able to reach limits of $\sim 5\times10^{-25}$ GeV. Because the CPT and LV analyses are essentially studies of variations in $\omega_a$ as a function of time and charge, performing an $\omega_a$ analysis sets the stage for the CPT and LV measurement. This dissertation focuses on the methodology of a fully functioning framework and analyzing the Fermilab Muon $g - 2$ Run 2 data containing $\sim 11$ billion events above an energy threshold of $1.7$~GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Measurement of matter–antimatter differences in beauty baryon decays

Differences in the behaviour of matter and antimatter have been observed in K and B meson decays, but not yet in any baryon decay. Such differences are associated with the non-invariance of fundamental interactions under the combined charge-conjugation and parity transformations, known as CP violation. Here, using data from the LHCb experiment at the Large Hadron Collider, we search for CP-violating asymmetries in the decay angle distributions of Λ$^0_b$ baryons decaying to pπ - π + π - and pπ - K + K - final states. These four-body hadronic decays are a promising place to search for sources of CP violation both within and beyond the standard model of particle physics. We find evidence for CP violation in Λ$^0_b$ to pπ - π + π - decays with a statistical significance corresponding to 3.3 standard deviations including systematic uncertainties. This represents the first evidence for CP violation in the baryon sector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Status and prospects of Muon g-2 experiment

This article reviews the muon g-2 experiment, a cornerstone in precision tests of the Standard Model of particle physics. The experiment measures the anomalous magnetic moment of the muon with unprecedented accuracy, seeking potential discrepancies between theoretical predictions and experimental results that might indicate physics beyond the Standard Model. We trace the evolution of this measurement from its beginnings at CERN in the 1960s to the current state-of-the-art experiment at Fermilab, highlighting the remarkable engineering achievements required to achieve parts-per-billion precision. Recent results from Runs 1-3 have achieved a systematic uncertainty of 70 ppb, exceeding design goals, while ongoing theoretical calculations continue to refine predictions. Despite these advances, the analysis remains statistics-limited, with continued data collection and novel experimental approaches at MUonE and J-PARC promising further insights into this fundamental physical quantity.

Karuza, Marin [INFN, Trieste; Rijeka U.] (ORCID:00↗

DOE OSTI2018

Bulk viscosity of strongly interacting matter in the relaxation time approximation

Here, we show how thermal mean field effects can be incorporated consistently in the hydrodynamical modeling of heavy-ion collisions. The nonequilibrium correction to the distribution function resulting from a temperature-dependent mass is obtained in a procedure which automatically satisfies the Landau matching condition and is thermodynamically consistent. The physics of the bulk viscosity is studied here for Boltzmann and Bose-Einstein gases within the Chapman-Enskog and 14-moment approaches in the relaxation time approximation. Constant and temperature-dependent masses are considered in turn. It is shown that, in the small mass limit, both methods lead to the same value of the ratio of the bulk viscosity to its relaxation time. The inclusion of a temperature-dependent mass leads to the emergence of the β λ function in that ratio, and it is of the expected parametric form for the Boltzmann gas, while for the Bose-Einstein case it is affected by the infrared cutoff. This suggests that the relaxation time approximation may be too crude to obtain a reliable form of ς/τ R for gases obeying Bose-Einstein statistics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗