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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Search for heavy resonances decaying to a pair of Lorentz-boosted Higgs bosons in final states with leptons and a bottom quark pair at $ \sqrt{s} $ = 13 TeV

A search for new heavy resonances decaying to a pair of Higgs bosons (HH) in proton-proton collisions at a center-of-mass energy of 13 TeV is presented. Data were collected with the CMS detector at the LHC in 2016–2018, corresponding to an integrated luminosity of 138 fb - 1 . Resonances with a mass between 0.8 and 4.5 TeV are considered using events in which one Higgs boson decays into a bottom quark pair and the other into final states with either one or two charged leptons. Specifically, the single-lepton decay channel HH → b b ¯ WW * → b b ¯ ℓ v q q ¯ ' and the dilepton decay channels HH → b b ¯ WW * → b b ¯ ℓ v ℓ v and HH → b b ¯ ττ → b b ¯ ℓ vv ℓ vv are examined, where ℓ in the final state corresponds to an electron or muon. The signal is extracted using a two-dimensional maximum likelihood fit of the H → b b ¯ jet mass and HH invariant mass distributions. No significant excess above the standard model expectation is observed in data. Model-independent exclusion limits are placed on the product of the cross section and branching fraction for narrow spin-0 and spin-2 massive bosons decaying to HH. The results are also interpreted in the context of radion and bulk graviton production in models with a warped extra spatial dimension. The results provide the most stringent limits to date for X → HH signatures with final-state leptons and at some masses provide the most sensitive limits of all X → HH searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Inclusive and differential cross section measurements of $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $ production in the lepton+jets channel at $ \sqrt{s} $ = 13 TeV

Measurements of inclusive and normalized differential cross sections of the associated production of top quark-antiquark and bottom quark-antiquark pairs, $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $, are presented. The results are based on data from proton-proton collisions collected by the CMS detector at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. The cross sections are measured in the lepton+jets decay channel of the top quark pair, using events containing exactly one isolated electron or muon and at least five jets. Measurements are made in four fiducial phase space regions, targeting different aspects of the $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $ process. Distributions are unfolded to the particle level through maximum likelihood fits, and compared with predictions from several event generators. The inclusive cross section measurements of this process in the fiducial phase space regions are the most precise to date. In most cases, the measured inclusive cross sections exceed the predictions with the chosen generator settings. The only exception is when using a particular choice of dynamic renormalization scale, $ {\mu}_{\textrm{R}}=\frac{1}{2}{\prod}_{i=\textrm{t},\overline{\textrm{t}},\textrm{b},\overline{\textrm{b}}}{m}_{\textrm{T},i}^{1/4} $, where $ {m}_{\textrm{T},i}^2={m}_i^2+{p}_{\textrm{T},i}^2 $ are the transverse masses of top and bottom quarks. The differential cross sections show varying degrees of compatibility with the theoretical predictions, and none of the tested generators with the chosen settings simultaneously describe all the measured distributions.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the top quark pole mass using $ \textrm{t}\overline{\textrm{t}} $+jet events in the dilepton final state in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A measurement of the top quark pole mass $\mathcal{m}^\text{pole}_\text{t}$ in events where a top quark-antiquark pair ($\text{t}\bar{\text{t}}$) is produced in association with at least one additional jet ($\text{t}\bar{\text{t}}$ +jet) is presented. This analysis is performed using proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the CMS experiment at the CERN LHC, corresponding to a total integrated luminosity of 36.3 fb -1 . Events with two opposite-sign leptons in the final state (e + e – , μ + μ – , e ± μ ∓ ) are analyzed. The reconstruction of the main observable and the event classification are optimized using multivariate analysis techniques based on machine learning. The production cross section is measured as a function of the inverse of the invariant mass of the $\text{t}\bar{\text{t}}$ +jet system at the parton level using a maximum likelihood unfolding. Given a reference parton distribution function (PDF), the top quark pole mass is extracted using the theoretical predictions at next-to-leading order. For the ABMP16NLO PDF, this results in $\mathcal{m}^\text{pole}_\text{t}$ = 172.93 ± 1.36 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

First measurement of the top quark pair production cross section in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV

The first measurement of the top quark pair ($t\bar{t}$) production cross section in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV is presented. Data recorded with the CMS detector at the CERN LHC in Summer 2022, corresponding to an integrated luminosity of 1.21 fb -1 , are analyzed. Events are selected with one or two charged leptons (electrons or muons) and additional jets. A maximum likelihood fit is performed in event categories defined by the number and flavors of the leptons, the number of jets, and the number of jets identified as originating from b quarks. An inclusive $t\bar{t}$ production cross section of 881 ± 23 (stat + syst) ± 20 (lumi) pb is measured, in agreement with the standard model prediction of 924$^{+32}_{-40}$ pb.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A new Monte Carlo generator for BSM physics in B → K*ℓ+ℓ− decays with an application to lepton non-universality in angular distributions

Abstract Within the widely used EvtGen framework, we have added a new event generator model forB → K * ℓ + ℓ − with improved standard model (SM) decay amplitudes and possible BSM physics contributions, which are implemented in the operator product expansion in terms of Wilson coefficients. This event generator can then be used to estimate the statistical sensitivity of a simulated experiment to the most general BSM signal resulting from dimension-six operators. We describe the advantages and potential of the newly developed ‘Sibidanov Physics Generator’ in improving the experimental sensitivity of searches for lepton non-universal BSM physics and clarifying signatures. The new generator can properly simulate BSM scenarios, interference between SM and BSM amplitudes, and correlations between different BSM observables as well as acceptance bias. We show that exploiting such correlations substantially improves experimental sensitivity. As a demonstration of the utility of the MC generator, we examine the prospects for improved measurements of lepton non-universality in angular distributions forB→K * ℓ + ℓ − decays from the expected 50 ab −1 data set of the Belle II experiment, using a four-dimensional unbinned maximum likelihood fit. We describe promising experimental signatures and correlations between observables. The use of lepton-universality violating ∆-observables significantly reduces uncertainties in the SM expectations due to QCD and resonance effects and is ideally suited for Belle II with the large data sets expected in the next decade. Thanks to the clean experimental environment of ane + e − machine, Belle II should be able to probe BSM physics in the Wilson coefficientsC 7 and$$ {C}_7^{\prime } $$ C 7 ′ , which appear at lowq 2 in the di-electron channel.

Physics↗
DOE OSTI2024

Test of light-lepton universality in τ decays with the Belle II experiment

We present a measurement of the ratio R µ = $\mathcal{B}$($τ^- → µ^-\overline{ν}_µν_τ$)/$\mathcal{B}(τ^- → e^-\overline{ν}_eν_τ$) of branching fractions B of the τ lepton decaying to muons or electrons using data collected with the Belle II detector at the SuperKEKB e + e - collider. The sample has an integrated luminosity of 362 ± 2 fb -1 at a centre-of-mass energy of 10.58 GeV. Using an optimised event selection, a binned maximum likelihood ft is performed using the momentum spectra of the electron and muon candidates. The result, R µ = 0.9675 ± 0.0007 ± 0.0036, where the first uncertainty is statistical and the second is systematic, is the most precise to date. It provides a stringent test of the light-lepton universality, translating to a ratio of the couplings of the muon and electron to the W boson in τ decays of 0.9974 ± 0.0019, in agreement with the standard model expectation of unity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Measurements of W + W − production cross-sections in pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

Measurements of W + W − → e ± νμ ∓ ν production cross-sections are presented, providing a test of the predictions of perturbative quantum chromodynamics and the electroweak theory. The measurements are based on data from pp collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider in 2015–2018, corresponding to an integrated luminosity of 140 fb −1 . The number of events due to top-quark pair production, the largest background, is reduced by rejecting events containing jets with b-hadron decays. An improved methodology for estimating the remaining top-quark background enables a precise measurement of W + W − cross-sections with no additional requirements on jets. The fiducial W + W − cross-section is determined in a maximum-likelihood fit with an uncertainty of 3.1%. The measurement is extrapolated to the full phase space, resulting in a total W + W − cross-section of 127 ± 4 pb. Differential cross-sections are measured as a function of twelve observables that comprehensively describe the kinematics of W + W − events. The measurements are compared with state-of-the-art theory calculations and excellent agreement with predictions is observed. A charge asymmetry in the lepton rapidity is observed as a function of the dilepton invariant mass, in agreement with the Standard Model expectation. A CP-odd observable is measured to be consistent with no CP violation. Limits on Standard Model effective field theory Wilson coefficients in the Warsaw basis are obtained from the differential cross-sections.

Accelerator Physics↗
DOE OSTI2024

Measurement of the $B^0_\mathrm{s}\to J/\psi K^0_\mathrm{S}$ effective lifetime from proton-proton collisions at $\sqrt{s} = 13$ TeV

The effective lifetime of the $ {\textrm{B}}_{\textrm{s}}^0 $ meson in the decay $ {\textrm{B}}_{\textrm{s}}^0\to \textrm{J}/{\uppsi \textrm{K}}_{\textrm{S}}^0 $ is measured using data collected during 2016–2018 with the CMS detector in $ \sqrt{s} $ = 13 TeV proton-proton collisions at the LHC, corresponding to an integrated luminosity of 140 fb$^{−1}$. The effective lifetime is determined by performing a two-dimensional unbinned maximum likelihood fit to the $ {\textrm{B}}_{\textrm{s}}^0 $ meson invariant mass and proper decay time distributions. The resulting value of 1.59 ± 0.07(stat) ± 0.03(syst) ps is the most precise measurement to date and is in good agreement with the expected value.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of boosted Higgs bosons produced via vector boson fusion or gluon fusion in the H →$ \textrm{b}\overline{\textrm{b}} $ decay mode using LHC proton-proton collision data at $ \sqrt{s} $ = 13 TeV

A measurement is performed of Higgs bosons produced with high transverse momentum (p$_{T}$) via vector boson or gluon fusion in proton-proton collisions. The result is based on a data set with a center-of-mass energy of 13 TeV collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb$^{−1}$. The decay of a high-p$_{T}$ Higgs boson to a boosted bottom quark-antiquark pair is selected using large-radius jets and employing jet substructure and heavy-flavor taggers based on machine learning techniques. Independent regions targeting the vector boson and gluon fusion mechanisms are defined based on the topology of two quark-initiated jets with large pseudorapidity separation. The signal strengths for both processes are extracted simultaneously by performing a maximum likelihood fit to data in the large-radius jet mass distribution. The observed signal strengths relative to the standard model expectation are $ {4.9}_{-1.6}^{+1.9} $ and $ {1.6}_{-1.5}^{+1.7} $ for the vector boson and gluon fusion mechanisms, respectively. A differential cross section measurement is also reported in the simplified template cross section framework.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Scalable computations for nonstationary Gaussian processes

Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets makes fitting such models computationally intractable with conventional dense linear algebra. In addition, derivative-free or even first-order optimization methods can be very slow to converge when estimating many spatially varying parameters. In this paper, we present a computational framework which couples an algebraic block diagonal plus low-rank covariance matrix approximation with stochastic trace estimation to facilitate the efficient use of second-order solvers for maximum likelihood estimation of Gaussian process models with many parameters. We demonstrate the effectiveness of these methods by simultaneously fitting 192 parameters in the popular nonstationary model of Paciorek and Schervish using 107,600 sea surface temperature anomaly measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Learning generative neural networks with physics knowledge

Deep generative neural networks have enabled modeling complex distributions, but incorporating physics knowledge into the neural networks is still challenging and is at the core of current physics-based machine learning research. To this end, we propose a physics generative neural network (PhysGNN), a new class of generative neural networks for learning unknown distributions in a physical system described by partial differential equations (PDE). PhysGNN couples PDE systems with generative neural networks. It is a fully differentiable model that allows back-propagation of gradients through both numerical PDE solvers and generative neural networks, and is trained by minimizing the discrete Wasserstein distance between generated and observed probability distributions of the PDE outputs using the stochastic gradient descent method. Moreover, PhysGNN does not require adversarial training like standard generative neural networks, which offers better stability than adversarial training. We show that PhysGNN can learn complex distributions in stochastic inverse problems, where conventional methods such as maximum likelihood estimation and momentum matching methods may be inapplicable when little knowledge is known about the form of unknown distributions or the physical model is too complex. Furthermore, our method allows physics-based generative neural network training for learning complex distributions in the context of differential equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Solving inverse problems in stochastic models using deep neural networks and adversarial training

Inverse problems associated with stochastic models constitute a significant portion of scientific and engineering applications. In such cases the unknown quantities are distributions. The applicability of traditional methods is limited because of their demanding assumptions or prohibitive computational consumption; for example, maximum likelihood methods require closed-form density functions, and Markov Chain Monte Carlo needs a large number of simulations. We propose a new method that estimates the unknown distribution by matching the statistical properties between observed and simulated random processes. We leverage the expressive power of neural networks to approximate the unknown distribution and use a discriminative neural network for computing the statistical discrepancies between the observed and simulated random processes. Here we demonstrated numerically that the proposed methods can estimate both the model parameters and learn complicated unknown distributions.

42 ENGINEERING↗
DOE OSTI2021

Latent map Gaussian processes for mixed variable metamodeling

Gaussian processes (GPs) are ubiquitously used in sciences and engineering as metamodels. Standard GPs, however, can only handle numerical or quantitative variables. Here we introduce latent map Gaussian processes (LMGPs) that inherit the attractive properties of GPs and are also applicable to mixed data which have both quantitative and qualitative inputs. The core idea behind LMGPs is to learn a continuous, low-dimensional latent space or manifold which encodes all qualitative inputs. To learn this manifold, we first assign a unique prior vector representation to each combination of qualitative inputs. We then use a low-rank linear map to project these priors on a manifold that characterizes the posterior representations. As the posteriors are quantitative, they can be directly used in any standard correlation function such as the Gaussian or Matern. Hence, the optimal map and the corresponding manifold, along with other hyperparameters of the correlation function, can be systematically learned via maximum likelihood estimation. Through a wide range of analytic and real-world examples, we demonstrate the advantages of LMGPs over state-of-the-art methods in terms of accuracy and versatility. In particular, we show that LMGPs can handle variable-length inputs, have an explainable neural network interpretation, and provide insights into how qualitative inputs affect the response or interact with each other. We also employ LMGPs in Bayesian optimization and illustrate that they can discover optimal compound compositions more efficiently than conventional methods that convert compositions to qualitative variables via manual featurization.

42 ENGINEERING↗
DOE OSTI2022

A broad specificity β-propeller enzyme from Rhodopseudomonas palustris that hydrolyzes many lactones including γ-valerolactone

Lactones are prevalent in biological and industrial settings, yet there is a lack of information regarding enzymes used to metabolize these compounds. One compound, γ-valerolactone (GVL), is used as a solvent to dissolve plant cell walls into sugars and aromatic molecules for subsequent microbial conversion to fuels and chemicals. Despite the promise of GVL as a renewable solvent for biomass deconstruction, residual GVL can be toxic to microbial fermentation. Here, we identified a Ca 2+ -dependent enzyme from Rhodopseudomonas palustris (Rpa3624) and showed that it can hydrolyze aliphatic and aromatic lactones and esters, including GVL. Maximum-likelihood phylogenetic analysis of other related lactonases with experimentally determined substrate preferences shows that Rpa3624 separates by sequence motifs into a subclade with preference for hydrophobic substrates. Additionally, we solved crystal structures of this β-propeller enzyme separately with either phosphate, an inhibitor, or a mixture of GVL and products to define an active site where calcium-bound water and calcium-bound aspartic and glutamic acid residues make close contact with substrate and product. Our kinetic characterization of WT and mutant enzymes combined with structural insights inform a reaction mechanism that centers around activation of a calcium-bound water molecule promoted by general base catalysis and close contacts with substrate and a potential intermediate. Similarity of Rpa3624 with other β-propeller lactonases suggests this mechanism may be relevant for other members of this emerging class of versatile catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Deployment of a double scatter system for directional detection of background neutron radiation

The detection of special nuclear materials (SNM) requires the understanding of nuclear signatures that allow the discrimination against background. In particular, understanding neutron background characteristics such as count rates and energies and their correlations with environmental conditions and surroundings of measurement locations is important in enhancing SNM detection capabilities. The Mobile Imager of Neutrons for Emergency Responders (MINER) was deployed for 8 weeks in downtown San Francisco (CA) to study such neutron background characteristics in an urban environment. Of specific interest was the investigation of the impact of surrounding buildings on the neutron background count rates and to answer the question whether buildings act as absorber of neutrons or as sources via the so-called ship effect. MINER consists of 16 liquid scintillator detector elements and can be operated as a neutron spectrometer, as a neutron imager, or simply as a counter of fast neutrons. As expected, the neutron background rate was found to be inversely proportional to the atmospheric pressure. In the energy range where MINER is most sensitive, approximately 1–10 MeV, it was found that the shape of the detected background spectrum is similar to that of a detected fission spectrum, indicating the limited discrimination power of the neutron energy. The similarities between the detected background neutron spectrum and fission sources makes it difficult to discriminate SNM from background based solely on the energies observed. The images produced using maximum likelihood expectation maximization revealed that neutrons preferentially are coming from areas in the environment that have open sky, indicating that the surrounding buildings act as absorbers of neutrons rather than sources as expected by the ship effect. Here, the inherent properties of a neutron scatter camera limit the achievable image quality and the effective deployment to systematically map neutron background signatures due to the low count rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Characterization of a collimated neutron imager for low-rate fast neutron imaging

Spatial localization of special nuclear materials (SNM) via their neutron signatures amidst background requires knowledge of the background neutron environment or a means of separating a source from background based on low amounts of information. This requirement has created the need for characterizing the spatial distribution of the cosmogenic neutron background. Neutron scatter cameras have been developed and optimized for rapid detection of high activity sources, but have low imaging efficiency, making it difficult to use them to characterize low rate diffuse sources, such as the neutron background. The Low Intensity Neutron Imaging System (LINIS) is a collimated neutron imager that has been designed and optimized for imaging diffuse cosmogenic neutron background in the energy range of 0.5–15 MeV. LINIS operates using 16 liquid scintillation detectors shielded by ultra-high molecular weight polyethylene cylindrical collimators in a staggered orientation and rotates to 7 discrete positions, giving it roughly 2π sensitivity. Finally, LINIS has been characterized using (α, n) and fission neutron sources using two imaging techniques for neutron source localization, simple backprojection and Maximum Likelihood Expectation Maximization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Gamma-ray spectroscopy using angular distribution of Compton scattering

We present a novel method to perform gamma-ray spectroscopy suitable for extreme pileup situations, wherein traditional pulse-height spectroscopy is infeasible or impractical. One example of such application is spectral characterization of intense laser-based radiation sources that employ laser wakefield acceleration, in which a large number of photons can be produced in a well-collimated beam on a picosecond or shorter timescale. The method relies on the angularly-resolved calorimetric measurement of Compton scattering. The probability for a photon to undergo Compton scattering into a given solid angle is a function of its energy and is described by the Klein–Nishina formula. By first Compton scattering the incident beam and then measuring the total energies deposited in multiple detectors placed at various scattering angles, the incident beam energy spectrum can be reconstructed without resolving the individual events in detectors. Here, we compare the performance of an maximum likelihood expectation maximization algorithm with that of an artificial neural network to measure the energy spectrum of a beam of monoenergetic gamma rays from 137Cs decay. We demonstrate that the method can be used to reconstruct the characteristic inverse Compton scattering spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗