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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2022

Atacama Cosmology Telescope: Constraints on prerecombination early dark energy

The early dark energy (EDE) scenario aims to increase the value of the Hubble constant (H0) inferred from cosmic microwave background (CMB) data over that found in the standard cosmological model (Λ CDM ), via the introduction of a new form of energy density in the early Universe. The EDE component briefly accelerates cosmic expansion just prior to recombination, which reduces the physical size of the sound horizon imprinted in the CMB. Previous work has found that nonzero EDE is not preferred by Planck CMB power spectrum data alone, which yield a 95% confidence level (C.L.) upper limit f EDE < 0.087 on the maximal fractional contribution of the EDE field to the cosmic energy budget. In this paper, we fit the EDE model to CMB data from the Atacama Cosmology Telescope (ACT) data release 4. We find that a combination of ACT, large-scale Planck TT (similar to WMAP), Planck CMB lensing, and BAO data prefers the existence of EDE at >99.7 % C .L . : f EDE = 0.091$^{+0.020}_{-0.036}$, with H 0 = 70.9$^{+1.0}_{-2.0}$ km/s/Mpc (both 68% C.L.). From a model-selection standpoint, we find that EDE is favored over Λ CDM by these data at roughly 3 σ significance. In contrast, a joint analysis of the full Planck and ACT data yields no evidence for EDE, as previously found for Planck alone. We show that the preference for EDE in ACT alone is driven by its TE and EE power spectrum data. The tight constraint on EDE from Planck alone is driven by its high-ℓ TT power spectrum data. Understanding whether these differing constraints are physical in nature, due to systematics, or simply a rare statistical fluctuation is of high priority. Here, the best-fit EDE models to ACT and Planck exhibit coherent differences across a wide range of multipoles in TE and EE, indicating that a powerful test of this scenario is anticipated with near-future data from ACT and other ground-based experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Confronting interacting dark radiation scenarios with cosmological data

Dark radiation (DR) is generally predicted in new physics scenarios that address fundamental puzzles of the Standard Model or tensions in the cosmological data. Cosmological data have the sensitivity to constrain not only the energy density of DR but also whether it is interacting. In this paper, we present a systematic study of five types of interacting DR (free-streaming, fluid, decoupling, instantaneous decoupling, and recoupling DR) and their impact on cosmological observables. We modify the Boltzmann hierarchy to describe all these types of interacting DR under the relaxation time approximation. We, for the first time, robustly calculate the collision terms for recoupling scalar DR and provide a better estimation of the recoupling transition redshift. We demonstrate the distinct features of each type of DR on the cosmic microwave background and matter power spectra. We perform Markov-chain Monte Carlo scans using the Planck 2018 data and baryon acoustic oscillation data. Assuming no new physics in the standard model neutrino sector, we find no statistically significant constraints on the couplings of DR, although there is a slight preference for the fluidlike limit of all the cases. In the case of instantaneous decoupling DR, this limit corresponds to a late transition redshift around recombination. Furthermore, the ΔN eff constraint varies marginally depending on the type of DR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Observation of χ c J → 3 ( K + K − )

By analyzing ( 27.12 ± 0.14 ) × 10 8 ψ ( 3686 ) events collected with the BESIII detector operating at the BEPCII collider, the decay processes χ c J → 3 ( K + K − ) ( J = 0 , 1, 2) are observed for the first time with statistical significances of 8.2 σ , 8.1 σ , and 12.4 σ , respectively. The product branching fractions of ψ ( 3686 ) → γ χ c J , χ c J → 3 ( K + K − ) are presented and the branching fractions of χ c J → 3 ( K + K − ) decays are determined to be B χ c 0 → 3 ( K + K − ) = ( 10.7 ± 1.8 ± 1.1 ) × 10 − 6 , B χ c 1 → 3 ( K + K − ) = ( 4.2 ± 0.9 ± 0.5 ) × 10 − 6 , and B χ c 2 → 3 ( K + K − ) = ( 7.2 ± 1.1 ± 0.8 ) × 10 − 6 , where the first uncertainties are statistical and the second are systematic. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

Search for η c ( 2 S ) → ω ω and ω ϕ and measurements of χ c J → ω ω and ω ϕ in ψ ( 2 S ) radiative processes

Using ( 2712 ± 14 ) × 10 6 ψ ( 2 S ) events collected with the BESIII detector at the BEPCII collider, we search for the decays η c ( 2 S ) → ω ω and η c ( 2 S ) → ω ϕ via the process ψ ( 2 S ) → γ η c ( 2 S ) . No statistically significant signals are observed. The upper limits of their product branching fractions at the 90% confidence level are determined to be B ( ψ ( 2 S ) → γ η c ( 2 S ) , η c ( 2 S ) → ω ω ) < 1.04 × 10 − 6 and B ( ψ ( 2 S ) → γ η c ( 2 S ) , η c ( 2 S ) → ω ϕ ) < 1.85 × 10 − 7 , respectively. We also update the branching fractions of χ c J → ω ω and χ c J → ω ϕ via the ψ ( 2 S ) → γ χ c J transition. Their branching fractions are determined to be B ( χ c 0 → ω ω ) = ( 10.66 ± 0.11 ± 0.57 ) × 10 − 4 , B ( χ c 1 → ω ω ) = ( 6.43 ± 0.07 ± 0.31 ) × 10 − 4 , B ( χ c 2 → ω ω ) = ( 8.75 ± 0.08 ± 0.42 ) × 10 − 4 , B ( χ c 0 → ω ϕ ) = ( 1.18 ± 0.03 ± 0.07 ) × 10 − 4 , B ( χ c 1 → ω ϕ ) = ( 2.04 ± 0.15 ± 0.11 ) × 10 − 5 , and B ( χ c 2 → ω ϕ ) = ( 9.58 ± 1.07 ± 0.76 ) × 10 − 6 , where the first uncertainties are statistical and the second are systematic. Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2021

Ionization state and dielectric constant in cold rarefied hydrocarbon plasmas of inertial confinement fusion

A combined approach to study cold rarefied matter is introduced that includes a semianalytical method based on the free-energy minimization and ab initio calculations based on the finite-temperature density-functional theory. The approach is used to calculate the ionization state of hydrocarbon (CH) under the shock-release conditions in inertial confinement fusion. Furthermore, the dielectric constant of CH is calculated using the Kubo-Greenwood formulation and contribution from atomic polarizabilities is found to be as important as the free-electron contribution. Using the ionization state and dielectric constant, the electron density profile in the rarefaction wave of the shock-release plasma is obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Measurement of C P Violation in B 0 → K S 0 π 0 Decays at Belle II

We report a measurement of the C P -violating parameters C and S in B 0 → K S 0 π 0 decays at Belle II using a sample of 387 × 10 6 B B ¯ events recorded in e + e − collisions at a center-of-mass energy corresponding to the ϒ ( 4 S ) resonance. These parameters are determined by fitting the proper decay-time distribution of a sample of 415 signal events. We obtain C = − 0.0 4 − 0.15 + 0.14 ± 0.05 and S = 0.7 5 − 0.23 + 0.20 ± 0.04 , where the first uncertainties are statistical and the second are systematic. Published by the American Physical Society 2023

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Observation of an Axial-Vector State in the Study of the Decay ψ ( 3686 ) → ϕ η η ′

Using ( 2712.4 ± 14.3 ) × 10 6 ψ ( 3686 ) events collected with the BESIII detector at BEPCII, a partial wave analysis of the decay ψ ( 3686 ) → ϕ η η ′ is performed with the covariant tensor approach. In addition to the established states h 1 ( 1900 ) and ϕ ( 2170 ) , an axial-vector state with a mass near 2.3 GeV / c 2 is observed for the first time. Its mass and width are measured to be 2316 ± 9 stat ± 3 0 syst MeV / c 2 and 89 ± 1 5 stat ± 2 6 syst MeV , respectively. The product branching fractions of B [ ψ ( 3686 ) → X ( 2300 ) η ′ ] B [ X ( 2300 ) → ϕ η ] and B [ ψ ( 3686 ) → X ( 2300 ) η ] B [ X ( 2300 ) → ϕ η ′ ] are determined to be ( 4.8 ± 1.3 stat ± 0.7 syst ) × 10 − 6 and ( 2.2 ± 0.7 stat ± 0.7 syst ) × 10 − 6 , respectively. The branching fraction B [ ψ ( 3686 ) → ϕ η η ′ ] is measured for the first time to be ( 3.14 ± 0.1 7 stat ± 0.2 4 syst ) × 10 − 5 . The first uncertainties are statistical and the second are systematic. Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2025

Bayesian model mixing with multireference energy density functional

Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technology. To this day, however, all the theoretical models that can scale at the level of the chart of isotopes remain semiphenomenological. Because they are fitted locally, their predictive power can vary significantly; different versions of the same theory provide different predictions. Bayesian model mixing takes advantage of such imperfect models to build a local mixture of a set of models to make improved predictions. Earlier attempts to use Bayesian model mixing for mass table calculations relied on models treated at single-reference energy density functional level, which fail to capture some of the correlations caused by configuration mixing or the restoration of broken symmetries. In this study we have applied Bayesian model mixing techniques within a multireference energy density functional (MR-EDF) framework. We considered predictions of two-particle separation energies from particle number projection or angular momentum projection with four different energy density functionals—a total of eight different MR-EDF models. We used a hierarchical Bayesian stacking framework with a Dirichlet prior distribution over weights together with an inverse log-ratio transform to enable positive correlations between different models. We found that Bayesian model mixing provides significantly improved predictions compared to the participating models. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Measurement of the W-boson mass and width with the ATLAS detector using proton–proton collisions at $\sqrt{s}=7$ TeV

Proton-proton collision data recorded by the ATLAS detector in 2011, at a centre-of-mass energy of 7 TeV, have been used for an improved determination of the W-boson mass and a first measurement of the W-boson width at the LHC. Recent fits to the proton parton distribution functions are incorporated in the measurement procedure and an improved statistical method is used to increase the measurement precision. The measurement of the W-boson mass yields a value of m w = 80,366.5 ± 9.8 (stat.) ± 12.5 (syst.) MeV = 80,366.5 ± 15.9 MeV, and the width is measured as Γ w = 2202 ± 32 (stat.) ± 34 (syst.) MeV = 2202 ± 47 MeV. The first uncertainty components are statistical and the second correspond to the experimental and physics-modelling systematic uncertainties. Both results are consistent with the expectation from fits to electroweak precision data. The present measurement of m w is compatible with and supersedes the previous measurement performed using the same data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Comparison of unfolding methods using RooFitUnfold

In this study we describe RooFitUnfold, an extension of the RooFit statistical software package to treat unfolding problems, and which includes most of the unfolding methods that commonly used in particle physics. The package provides a common interface to these algorithms as well as common uniform methods to evaluate their performance in terms of bias, variance and coverage. In this paper we exploit this common interface of RooFitUnfold to compare the performance of unfolding with the Richardson–Lucy, Iterative Dynamically Stabilized, Tikhonov, Gaussian Process, bin-by-bin and inversion methods on several example problems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Optimization of the deep neural network parameters for generating homogenized fuel assembly data for nodal codes

Homogenized fuel assembly (FA) data is a typical input data for nodal codes. Generating that data, however, could be time-consuming. One of promising ways to mitigate the computational burden of generating macroscopic cross-sections is to use trained artificial neural network (ANN) models for predicting nuclear data. However, there is a challenge to make the model support variable FA geometry. In this work, two most common types of FA were combined in one ANN model. Since there could be multiple ways of converting 2-dimensional FA data into 1-dimensional input vector for ANN, three different approaches of data flattening were evaluated. The input parameters included each fuel pin enrichment, fuel temperature, moderator temperature and boron concentration. The output parameters were 2-group macroscopic cross-sections (XS) and pin power distribution (HFF). A fully connected deep neural network (DNN) model was trained and tested using pre-generated data obtained with lattice physics code STREAM. The results of this study showed no statistically significant difference in the accuracy of XS and HFF generation for all 3 tested input vector orders. This means that fully connected DNN for XS generation demonstrated input sequence invariance. Results of comparing predicted XS data with reference solutions were found sufficiently close considering the reduction of computation time offered by ANN. Mean relative difference (MRD) for all output XS parameters was found below 0.7%, while HFF MRD was found higher compared to XS values, in some cases slightly exceeding 1%, mostly near guide tube locations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Shower Reconstruction for Cross-Section Measurements with Photon(s) in the Final State at SBND

The Short-Baseline Near Detector (SBND) is a 112-ton liquid argon time projection chamber operating in the Booster Neutrino Beam at Fermilab as part of the Short-Baseline Neutrino Program. Precise reconstruction of electromagnetic showers from photons and electrons is essential for searches for neutrino oscillations, cross-section measurements, and rare-process studies in liquid argon. In this poster, we present a unified set of SBND analyses enabled by the SPINE (Scalable Particle Imaging with Neural Embeddings) end-to-end machine-learning–based reconstruction framework, highlighting charged-current neutral pion (CC π⁰) production and neutral-current (NC) Δ radiative decay as complementary physics cases. Charged-current π⁰ interactions provide a high-statistics benchmark for validating photon reconstruction, constraining the electromagnetic energy scale, and modeling backgrounds to other cross-section measurements and BSM searches with one or more photons in the final state. We summarize progress toward the ongoing development of a CC π⁰ selection in SBND and, report on the current status of a search for NC resonant Δ production followed by radiative decay (Δ→Nγ) in SBND. This rare process, previously investigated in MicroBooNE, provides a stringent test of photon-only final-state reconstruction and is of interest in the context of the MiniBooNE low-energy excess. Together, these analyses demonstrate how modern machine-learning–based shower reconstruction enables a diverse and scalable physics program at SBND.

Chung, Seokju [Nevis Labs, Columbia U.]↗
DOE OSTI2024

Predicting turbulent wake flow of marine hydrokinetic turbine arrays in large-scale waterways via physics-enhanced convolutional neural networks

We present a physics-enhanced convolutional neural network (PECNN) algorithm for reconstructing the mean flow and turbulence statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large-scale meandering rivers. The algorithm embeds the mass and momentum conservation equations into the loss function of the PECNN algorithm to improve the physical realism of the reconstructed flow fields. The PECNN is trained using large eddy simulation (LES) results of the wake flow of a single row of turbines in a virtual meandering river. Subsequently, the trained PECNN is applied to predict the wake flow of MHK turbines with arrangements and positionings different than those considered during the training process. The PECNN predictions are validated using the results of separately performed LES. The results show that the PECNN algorithm can accurately predict the wake flow of MHK turbine farms at a small fraction of the cost of LES. The PECNN can improve the accuracy by around 1% and reduce the physical constraint indices by around 50% compared to the CNN without physical constraints. This work underscores the potential of PECNN to develop reduced-order models for control co-design and optimization of MHK turbine arrays in natural riverine environments.

Mechanics↗
DOE OSTI2023

Surface coverage dynamics for reversible dissociative adsorption on finite linear lattices

Dissociative adsorption onto a surface introduces dynamic correlations between neighboring sites not found in non-dissociative absorption. We study surface coverage dynamics where reversible dissociative adsorption of dimers occurs on a finite linear lattice. We derive analytic expressions for the equilibrium surface coverage as a function of the number of reactive sites, N, and the ratio of the adsorption and desorption rates. Using these results, we characterize the finite size effect on the equilibrium surface coverage. For comparable N’s, the finite size effect is significantly larger when N is even than when N is odd. Moreover, as N increases, the size effect decays more slowly in the even case than in the odd case. The finite-size effect becomes significant when adsorption and desorption rates are considerably different. These finite-size effects are related to the number of accessible configurations in a finite system where the odd-even dependence arises from the limited number of accessible configurations in the even case. We confirm our analytical results with kinetic Monte Carlo simulations. We also analyze the surface-diffusion case where adsorbed atoms can hop into neighboring sites. As expected, the odd-even dependence disappears because more configurations are accessible in the even case due to surface diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,200 new measurements from 903 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 118 reviews are updated, including many that are heavily revised.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Understanding Differences in California Climate Projections Produced by Dynamical and Statistical Downscaling

Abstract We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.

54 ENVIRONMENTAL SCIENCES↗