Search NASA⌕ Search

SEARCH · Search NASA

Results for “interpretability”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Thermally induced mimicry of quantum cluster excitations and implications for the magnetic transition in FePSe 3

In two dimensional magnets, the interplay of thermal fluctuations and spin anisotropy control the existence of long-range magnetic order. In the van der Waals antiferromagnets FePX 3 , orbital degeneracy in the 𝑡 2⁢𝑔 levels of the Fe 2+ ions in octahedral coordination yields strong uniaxial anisotropy, which stabilizes magnetic order up to 𝑇 ≈ 100 K. Recent inelastic neutron scattering measurements around the magnetic ordering transition have shown the existence of a broad spectrum of magnetic fluctuations with nontrivial momentum dependence, which has been interpreted as evidence for localized entangled cluster excitations. In this paper, we offer an alternative interpretation using classical nonlinear spin dynamics simulations. We present stochastic Landau Lifshitz dynamics simulations that reproduce the neutron scattering measurements of Chen et al. [npj Quantum Mater. 9, 40 (2024)] on FePSe 3 . These calculations faithfully explain the dynamical structure factor's momentum and energy dependence and point to a classical origin for the excitations observed in neutron spectroscopy and that the order-disorder transition can be understood in terms of thermal fluctuations overcoming the anisotropy energy.

Landau-Lifschitz-Gilbert equation↗
DOE OSTI2024

Combined search for electroweak production of winos, binos, higgsinos, and sleptons in proton-proton collisions at s = 13 TeV

A combination of the results of several searches for the electroweak production of the supersymmetric partners of standard model bosons, and of charged leptons, is presented. All searches use proton-proton collision data at s = 13 TeV recorded with the CMS detector at the LHC in 2016–2018. The analyzed data correspond to an integrated luminosity of up to 137 fb − 1 . The results are interpreted in terms of simplified models of supersymmetry. Two new interpretations are added with this combination: a model spectrum with the bino as the lightest supersymmetric particle together with mass-degenerate Higgsinos decaying to the bino and a standard model boson, and the compressed-spectrum region of a previously studied model of slepton pair production. Improved analysis techniques are employed to optimize sensitivity for the compressed spectra in the wino and slepton pair production models. The results are consistent with expectations from the standard model. The combination provides a more comprehensive coverage of the model parameter space than the individual searches, extending the exclusion by up to 125 GeV, and also targets some of the intermediate gaps in the mass coverage. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for charged-lepton-flavor violating μ τ q t interactions in top-quark production and decay in p p collisions at s = 13 TeV with the ATLAS detector at the LHC

A search for charged-lepton-flavor violating μ τ q t (q = u, c) ) interactions is presented, considering both top-quark production and decay. The data analyzed correspond to 140 fb -1 of proton-proton collisions at a center-of-mass energy of $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The analysis targets events containing two muons with the same electric charge, a hadronically decaying $\tau$ -lepton and at least one jet, with exactly one b -tagged jet, produced by a μ τ q t interaction. Agreement with the Standard Model expectation within 1.6 standard deviations is observed, and limits are set at the 95% confidence level (CL) on the charged-lepton-flavor violation branching ratio of $\mathcal{B}$(t → μ$\tau$q) < 8.7 x 10 -7 . An effective field theory interpretation is performed yielding 95% CL limits on Wilson coefficients, dependent on the flavor of the associated light quark and the Lorentz structure of the coupling. These range from |c$^{3(2313)}_{lequ}$|Λ 2 < 0.10 TeV -2 for μ$\tau$ut to |c$^{1(2323)}_{lequ}$| /Λ 2 < 1.8 TeV -2 for μ$\tau$ct. An additional interpretation is performed for scalar leptoquark production inducing charged-lepton-flavor violation, with fixed intergenerational couplings. Upper limits on leptoquark coupling strengths are set at the 95% CL, ranging from $\lambda$ LQ = 1.3 to $\lambda$ LQ =3.7 for leptoquark masses between 0.5 and 2.0 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Streamlining latent spaces in machine learning using moment pooling

Many machine learning applications involve learning a latent representation of data, which is often high-dimensional and difficult to directly interpret. In this work, we propose “moment pooling,” a natural extension of deep sets networks which drastically decreases the latent space dimensionality of these networks while maintaining or even improving performance. Moment pooling generalizes the summation in deep sets to arbitrary multivariate moments, which enables the model to achieve a much higher effective latent dimensionality for a fixed learned latent space dimension. We demonstrate moment pooling on the collider physics task of quark/gluon jet classification by extending energy flow networks (EFNs) to moment EFNs. We find that moment EFNs with latent dimensions as small as 1 perform similarly to ordinary EFNs with higher latent dimension. This small latent dimension allows for the internal representation to be directly visualized and interpreted, which in turn enables the learned internal jet representation to be extracted in closed form. Published by the American Physical Society 2024

Gambhir, Rikab (ORCID:0000000251080448)↗
DOE OSTI2025

Search for triple Higgs boson production in the 6⁢𝑏 final state using 𝑝⁢𝑝 collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for the production of three Higgs bosons (𝐻⁡𝐻⁡𝐻) in the $b\bar{b}b\bar{b}b\bar{b}$ final state is presented. The search uses 126 fb −1 of proton-proton collision data at $\sqrt{s}$ =13 TeV collected with the ATLAS detector at the Large Hadron Collider. The analysis targets both nonresonant and resonant production of 𝐻⁡𝐻⁡𝐻. The resonant interpretations primarily consider a cascade decay topology of 𝑋 →𝑆⁢𝐻 → 𝐻⁡𝐻⁡𝐻 with masses of the new scalars 𝑋 and 𝑆 up to 1.5 and 1 TeV, respectively. In addition to scenarios where 𝑆 is off-shell, the nonresonant interpretation includes a search for Standard Model 𝐻⁡𝐻⁡𝐻 production, with limits on the trilinear and quartic Higgs self-coupling set. No evidence for 𝐻⁡𝐻⁡𝐻 production is observed. An upper limit of 59 fb is set, at the 95% confidence level, on the cross section for Standard Model 𝐻⁡𝐻⁡𝐻 production.

Artificial neural networks↗
DOE OSTI2025

Unified and optimal frame choice for generalized parton distributions

Reconstructing the internal three-dimensional quark and gluon structures of hadrons through generalized parton distributions (GPDs) from hard exclusive scattering processes is one of the most challenging tasks in nuclear and particle physics. In this paper, we introduce a new optimized reference frame that, for the first time, enables a unified view of all the reactions sensitive to GPDs and facilitates the interpretation of a variety of phase-space patterns that were previously hardly accessible and interpretable. Similarly to how the heliocentric description advanced our understanding of the solar system and gravitation, our new frame centers around a quasireal state, allows for a consistent separation of physical scales, and reveals a novel quantum interference mechanism. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

First Observation of a Three-Resonance Structure in e + e − → Nonopen Charm Hadrons

We report the measurement of the inclusive cross sections for e + e − → nOCH (where nOCH denotes non-open charm hadrons) with improved precision at center-of-mass (c.m.) energies from 3.645 to 3.871 GeV. We observe three resonances: R ( 3760 ) , R ( 3780 ) , and R ( 3810 ) with significances of 8.1 σ , 13.7 σ , and 8.8 σ , respectively. The R ( 3810 ) state is observed for the first time, while the R ( 3760 ) and R ( 3780 ) states are observed for the first time in the nOCH cross sections. Two sets of resonance parameters describe the energy-dependent line shape of the cross sections well. In set I [set II], the R ( 3810 ) state has mass ( 3805.7 ± 1.1 ± 2.7 ) [ ( 3805.7 ± 1.1 ± 2.7 ) ] MeV / c 2 , total width ( 11.6 ± 2.9 ± 1.9 ) [ ( 11.5 ± 2.8 ± 1.9 ) ] MeV , and an electronic width multiplied by the nOCH decay branching fraction of ( 10.9 ± 3.8 ± 2.5 ) [ ( 11.0 ± 3.4 ± 2.5 ) ] eV . In addition, we measure the branching fractions B [ R ( 3760 ) → nOCH ] = ( 25.2 ± 16.1 ± 30.4 ) % [ ( 6.4 ± 4.8 ± 7.7 ) % ] and B [ R ( 3780 ) → nOCH ] = ( 12.3 ± 6.6 ± 8.3 ) % [ ( 10.4 ± 4.8 ± 7.0 ) % ] for the first time. The R ( 3760 ) state can be interpreted as an open-charm (OC) molecular state, but containing a simple four-quark state component. The R ( 3810 ) state can be interpreted as a hadrocharmonium state. Published by the American Physical Society 2024

Physics↗
DOE OSTI2025

Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic dynamics. For nonequilibrium systems, perturbations cannot be interpreted simply by monitoring fluctuations in a conjugate observable and general response results rely on path ensemble averaging. Furthermore, these techniques do not apply to perturbations that affect the diffusion tensor in a stochastic system. Here, we introduce an “effective” physical process that represents the diffusion perturbed dynamics and enables accurate calculations of responses to a change in the diffusion. Interestingly, the effective dynamics contain an additional drift involving the instantaneous “score” of the system, and we leverage score matching algorithms to carry out nonequilibrium response calculations on systems for which the exact stationary distribution is unknown.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Electronic effects in radiation-induced collision cascades in nickel

The accurate treatment of electronic effects in multi-million-atom simulations of radiation-induced collision cascades is crucial for reliable predictions of primary radiation damage. In this work, we explore the fidelity of a recently developed two-temperature molecular dynamics model implementing an electron density-dependent coupling of electronic and atomic subsystems for cascade simulations in nickel. We show that the parameter-free model realistically captures the instantaneous energy losses during all stages of the highly nonequilibrium cascade process. Our simulations predict two distinct coupling regimes, corresponding to the rapid energy losses through electronic stopping in the early stages of the cascade and to the slow equilibration through the electron-phonon coupling mechanism in the later stages, without the use of separate models or coupling terms. The intermediate stage of the cascade dynamics displays a complex energy transfer between the subsystems, which cannot be interpreted by comparison to either electronic stopping or electron-phonon coupling theories. We therefore compare the predicted atomic mixing, which is sensitive to the energy losses during the intermediate cascade stage, with experimental ion beam mixing measurements. We find good agreement with the experiments, validating the coupling model for the intermediate stage of the cascade. Predictions of final defect numbers and cluster sizes are found in line with the results from conventional electronic stopping-based methods, while significantly reducing the theoretical uncertainty in the outcomes of conventional models stemming from arbitrary choices of thresholds for different coupling terms. Our results represent a notable improvement in cascade damage predictions in nickel, providing validation of the electron density-dependent coupling model for radiation damage simulations in general. The results lead us to propose an interpretation of the electronic energy losses in the intermediate regime of velocities, where we find an effectively nonlinear dissipation.

Crystal defects↗
DOE OSTI2026

Dispersive and nondispersive 𝐾-matrix formalisms

The modeling of coupled-channel effects has become increasingly important due to the availability of highly precise data for a large variety of hadronic (re)scattering processes. The 𝐾-matrix is a powerful, yet comparatively simple, method to describe scattering amplitudes, including coupled-channel effects, with the aim of interpreting experimental data. Throughout the literature, a range of dispersive and nondispersive 𝐾-matrix methods are employed. Here, we compare the dispersive and nondispersive formulations in the context of the N/D method. It is shown that the methods are equivalent in the physical region under 𝐾-matrix reparametrization. Differences away from the physical region are examined. Applications to synthetic data are used to illustrate the effects of model choices concerning form factors and the application of dispersion relations, with the goal of clarifying best practices. We find no clear preference with regard to dispersive modeling. In contrast, we find that interpretational ambiguity of the bare model parameters—and even of the form of the bare model—is endemic, and recommend a thorough sampling of data and model spaces to assess conclusion robustness.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Structure of high-lying excited states in 47 Ca with ℓ ≥ 3 populated in fast-beam 𝛾-ray-tagged one-neutron pickup reactions

Located just one neutron removed from doubly magic, stable 48 Ca, the adjacent isotope 47 Ca has been studied extensively with neutron-removing transfer reactions and interpreted within a shell-model picture. Neutron-adding transfer reactions onto the stable 46 Ca, however, have not been performed in nearly 60 years and never with the aid of high-resolution 𝛾-ray spectroscopy. Here, we report on the 12 C⁡( 46 , Ca 47 Ca+𝛾)⁢𝑋 one-neutron pickup reaction from 12 C onto 46 Ca at more than 50 MeV/nucleon, a regime of orbital angular momentum mismatch that selectively populates 47 Ca final states based on ℓ ≥ 3 neutron configurations. Newly observed excited states and 𝛾-ray transitions are discussed in comparison to 𝑓⁡𝑝 shell-model calculations in a variety of configuration spaces. Furthermore, it is shown that the nature of the observed spectrum of final states can be well interpreted, albeit with a significant fragmentation of the 𝜈⁢0⁢𝑓 5/2 strength observed in the measurement that is not borne out in the structure calculations.

39 ≤ A ≤ 58↗
DOE OSTI2024

Coordinate-based simulation of pair distance distribution functions for small and large molecular assemblies: implementation and applications

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclodextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0 , which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

Zuo, Xiaobing (ORCID:0000000201344804)↗
DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale mol­ecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗
DOE OSTI2025

Q -score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps

Atomic coordinate models are important for the interpretation of 3D maps produced with cryoEM and cryoET (3D electron microscopy; 3DEM). In addition to visual inspection of such maps and models, quantitative metrics can inform about the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well fitted models. Here, we present new statistical analyses of Q-score based on its application to ∼10 000 maps and models archived in the EMDB (Electron Microscopy Data Bank) and PDB (Protein Data Bank). Further, we introduce two new metrics based on Q-score to represent each map and model relative to all entries in the EMDB and those with similar resolution. We explore through illustrative examples of proteins, nucleic acids and small molecules how Q-scores can indicate whether the atomic coordinates are well fitted to 3DEM maps and also whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage and/or conformational heterogeneity. These examples and statistical analyses provide a basis for how Q-scores can be interpreted effectively in order to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

B factors↗
DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, sub­tomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2026

Temporal Convolutional Network Using Empirical Mode Decomposition to Detect Faults in Grid Connected Systems

Grid-connected power electronic systems require timely and reliable fault detection to prevent equipment damage and reduce downtime. This paper presents a forecasting-based anomaly detection pipeline that decomposes voltage and current measurements into intrinsic mode functions (IMFs) using empirical mode decomposition (EMD), then trains a causal temporal convolutional network (TCN) on normal-operation IMF data to predict short-horizon future dynamics. Deviations between forecasts and observations are summarized as reliability-weighted residual scores and thresholded per sensor using robust statistics with temporal persistence constraints to suppress false positives. To reduce runtime, EMD is performed on downsampled signals for detection, while raw-rate EMD is applied only within a short region of interest for high-frequency interpretability near detected events. Results on a simulated grid-connected converter system demonstrate that IMF-domain forecasting improves anomaly separability relative to raw-signal forecasting and provides interpretable evidence of faults across decomposition channels.

Sutton, Elizabeth [ORNL] (ORCID:0009000078885935)↗