Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “strong”

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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Discovery of Strongly Variable X-Ray Polarization in the Neutron Star Low-Mass X-Ray Binary Transient XTE J1701−462

Context. After about 16 years since its first outburst, the transient neutron star low-mass X-ray binary XTE J1701−462 turned on again in September 2022, allowing for the first study of its X-ray polarimetric characteristics by a dedicated observing program with the Imaging X-ray Polarimeter Explorer (IXPE). Aims. Polarimetric studies of XTE J1701−462 have been expected to improve our understanding of accreting weakly magnetized neutron stars, in particular, the physics and the geometry of the hot inner regions close to the compact object. Methods. The IXPE data of two triggered observations were analyzed using time-resolved spectroscopic and polarimetric techniques, following the source along its Z-track of the color–color diagram. Results. During the first pointing on 2022 September 29, an average 2–8 keV polarization degree of (4.6 ± 0.4)% was measured, the highest value found up to now for this class of sources. Conversely, only a ∼0.6% average degree was obtained during the second pointing ten days later. Conclusions. The polarimetric signal appears to be strictly related to the higher energy blackbody component associated with the boundary layer (BL) emission and its reflection from the inner accretion disk, and it is as strong as 6.1% and 1.2% (> 95% significant) above 3–4 keV for the two measurements, respectively. The variable polarimetric signal is apparently related to the spectral characteristics of XTE J1701−462, which is the strongest when the source was in the horizontal branch of its Z-track and the weakest in the normal branch. These IXPE results provide new important observational constraints on the physical models and geometry of the Z-sources. Here, we discuss the possible reasons for the presence of strong and variable polarization among these sources.

XTEJ1701↗
DOE OSTI2023

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the order of $10^5$, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but the alternative of training only on simulated data results in poor performance on real data. Domain Adaptation may be able to bridge the gap between simulated and real datasets. We utilize domain adaptation for the estimation of Einstein radius ($\Theta_E$) in simulated galaxy-scale gravitational lensing images with different levels of observational realism. We evaluate two domain adaptation techniques - Domain Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain of lenses simulated to emulate noise conditions in the Dark Energy Survey (DES). We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain dataset. This work is the first application of domain adaptation for a regression task in strong lensing imaging analysis. Our results show the potential of using domain adaptation to perform analysis of future survey data with a deep neural network trained on simulated data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Session 058 - Panel: Ensuring Strong Return on Investment for DOE EM Technology Development: DOE Views (1/2) (R1.26)

The panel represented the views of US DOE National Laboratories and DOE Contractors and focused on DOE Technology Development Projects discussing how they approach tech development to maximize return on investment. Successful examples were discussed. Panelists with presentations: Ensuring a Strong ROI for DOE EM Technology Development (Jud Virden); The DOE EM Technology Development Technical Assistance Program (Carol Eddy-Dilek); SRR Liquid Waste Technology Development Program: Encouraging Creativity Maximize Return on Investment (Vijay Jain); Ensuring Strong Return on Investment for DOE EM Technology Development: A Vendor Perspective (Martin Williams)

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Panel Session 69: Ensuring Strong Return on Investment for DOE EM Technology Development: Global Views

This panel focused on DOE and Non-US Technology Development Projects discussing how they approach tech development to maximize return on investment (ROI). Successful examples were discussed. After the individual panelist's presentations, the three panelists were joined by Kurt Gerdes in discussing the genesis of this panel and why it is important. Panelists with presentations: Ensuring a Strong Return on Investment for DOE EM Technology Development (Anthony Banford) DOE Technology Development Projects that Provided a Strong Return on Investment (ROI (Mark Lesinski) Australian Nuclear Science and Technology Organisation (Gerry Triani) Decommissioning Situation of Nuclear Power Plant in Japan (Teruyuki Hirai)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty Quantification

Modeling strong gravitational lenses is computationally expensive for the complex data from modern and next-generation cosmic surveys. Deep learning has emerged as a promising approach for finding lenses and predicting lensing parameters, such as the Einstein radius. Mean-variance Estimators (MVEs) are a common approach for obtaining aleatoric (data) uncertainties from a neural network prediction. However, neural networks have not been demonstrated to perform well on out-of-domain target data successfully - e.g., when trained on simulated data and applied to real, observational data. In this work, we perform the first study of the efficacy of MVEs in combination with unsupervised domain adaptation (UDA) on strong lensing data. The source domain data is noiseless, and the target domain data has noise mimicking modern cosmology surveys. We find that adding UDA to MVE increases the accuracy on the target data by a factor of about two over an MVE model without UDA. Including UDA also permits much more well-calibrated aleatoric uncertainty predictions. Advancements in this approach may enable future applications of MVE models to real observational data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Domain-Adaptive Neural Posterior Estimation for Strong Gravitational Lens Analysis

Modeling strong gravitational lenses is prohibitively expensive for modern and next-generation cosmic survey data. Neural posterior estimation (NPE), a simulation-based inference (SBI) approach, has been studied as an avenue for efficient analysis of strong lensing data. However, NPE has not been demonstrated to perform well on out-of-domain target data -- e.g., when trained on simulated data and then applied to real, observational data. In this work, we perform the first study of the efficacy of NPE in combination with unsupervised domain adaptation (UDA). The source domain is noiseless, and the target domain has noise mimicking modern cosmology surveys. We find that combining UDA and NPE improves the accuracy of the inference by 1-2 orders of magnitude and significantly improves the posterior coverage over an NPE model without UDA. We anticipate that this combination of approaches will help enable future applications of NPE models to real observational data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Accidentally Stable Dark Matter in a Parity Solution to the Strong CP Problem

Parity symmetry, with an extended gauge group $SU(3)_c \times SU(2)_L \times SU(2)_R \times U(1)_X$, can solve the strong CP problem. In particular, the model where $SU(2)_R\times U(1)_X$ is broken by the Parity partner of the Standard Model Higgs solves the strong CP problem without the necessity of introducing extra symmetry. We discuss the possibility of accidentally stable dark matter in this framework and show that $SU(2)_L \times SU(2)_R$ bi-triplet fermions can be stable over cosmological timescales. We compute the relic abundance of the bi-triplet dark matter and derive constraints on the parameter space from collider, direct-detection, and indirect-detection experiments. The $SU(2)_R\times U(1)_X$ symmetry breaking scale is required to be below 150 TeV, and most of the parameter space can be probed by near-future indirect-detection experiments.

Baldwin, Matthew J. [Chicago U., EFI] (ORCID:00090↗
DOE OSTI2024

Theory of strong-field sequential double ionization of polyatomic molecules

Understanding of strong-field sequential double ionization (SDI) of molecules by a highly intense infrared laser pulse could be the key to observing electron motion in molecules in the attosecond to femtosecond timescale. Based on a novel density matrix approach for SDI (DM-SDI), a recent theoretical study has shown that SDI can be used as a probe to monitor the changes in vibronic coherence in homonuclear diatomic molecules. In this article, we extend the DM-SDI model to general molecules that could possess permanent dipole moments and arbitrary symmetry. We apply the model to SDI of a water molecule and identify the formation pathway of individual dication states. We further deduce that kinetic energy release spectra from two- and three-body fragments could carry the signature of vibronic coherence between the lowest two states of the water cation. Furthermore, our results suggest that observables from the SDI probe can be interpreted intuitively with only the knowledge of electronic structures of populated ionic states, making the SDI probe to be a highly desirable probing scheme for vibronic coherence in generic molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Dissociation slowdown by collective optical response under strong coupling conditions

We consider an ensemble of diatomic molecules resonantly coupled to an optical cavity under strong coupling conditions at normal incidence. Photodissociation dynamics is examined via direct numerical integration of the coupled Maxwell–Schrödinger equations with molecular rovibrational degrees of freedom explicitly taken into account. It is shown that the dissociation is significantly affected (slowed down) when the system is driven at its polaritonic frequencies. The observed effect is demonstrated to be of transient nature and has no classical analog. An intuitive explanation of the dissociation slowdown at polaritonic frequencies is proposed.

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

Nonadiabatic strong-field photoionization revisited: Detailed analysis

We develop a theoretical framework to interpret “bump-like” enhancements in the energy distribution of electrons emitted from cesium atoms subjected to intense infrared laser fields, as observed in a recent experiment. These emissions, detected at energies approaching twice the ponderomotive energy (2⁢𝑈 p ), indicate a mechanism where electrons are nonadiabatically ejected with substantial inward velocity following ionization. The bump-like features arise from returning trajectories that scatter off the residual ion. We interpret these experimental results classically using a periodically driven version of the Bohr model and quantum mechanically through Keldysh's adiabaticity parameter (𝛾 K ) and Reiss's continuum-state intensity parameter 𝒵 in a Coulomb-corrected version of the strong-field approximation (SFA) that incorporates “complex” electronic trajectories. Notably, our theoretical analysis shows that these emissions are independent of the specific short-range form of the atomic potential.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Strong Photon‐Magnon Coupling Using a Lithographically Defined Organic Ferrimagnet

Abstract A cavity‐magnonic system composed of a superconducting microwave resonator coupled to a magnon mode hosted by the organic‐based ferrimagnet vanadium tetracyanoethylene (V[TCNE] x ) is demonstrated. This work is motivated by the challenge of scalably integrating a low‐damping magnetic system with planar superconducting circuits. V[TCNE] x has ultra‐low intrinsic damping, can be grown at low processing temperatures on arbitrary substrates, and can be patterned via electron beam lithography. The devices operate in the strong coupling regime, with a cooperativity exceeding 1000 for coupling between the Kittel mode and the resonator mode at T≈0.4 K, suitable for scalable quantum circuit integration. Higher‐order magnon modes are also observed with much narrower linewidths than the Kittel mode. This work paves the way for high‐cooperativity hybrid quantum devices in which magnonic circuits can be designed and fabricated as easily as electrical wires.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

pH‐Mediated Strong Metal‐Support Interaction Construction Through Dynamic Fermi Level Tuning

The metal–support interface is central to governing catalytic transformations. While strong metal–support interaction (SMSI) is an established strategy to tailor the morphology and electronic properties of supported metal catalysts, the role of interfacial charge redistribution in SMSI formation remains poorly understood and rarely leveraged. Here, in this study, we report a dual-stimuli approach that combines pH modulation with ultrasonication to mediate SMSI construction in aqueous solution through dynamic Fermi level tuning. By leveraging in situ pH-driven charge redistribution at the metal–support interface, we achieve controllable SMSI encapsulation of metal nanoparticles, as verified by electrochemical analysis, work function measurements, and x-ray-based techniques. The resulting catalysts exhibit tunable SMSI features and deliver enhanced activity and selectivity in hydrogenation reactions. This work establishes a facile strategy to modulate catalyst structure and electronic properties by exploiting Fermi level variation as a driving force, thereby advancing rational SMSI design and catalytic performance across diverse environments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Strong Lensing by Galaxies

Strong gravitational lensing at the galaxy scale is a valuable tool for various applications in astrophysics and cosmology. Some of the primary uses of galaxy-scale lensing are to study elliptical galaxies’ mass structure and evolution, constrain the stellar initial mass function, and measure cosmological parameters. Since the discovery of the first galaxy-scale lens in the 1980s, this field has made significant advancements in data quality and modeling techniques. In this review, we describe the most common methods for modeling lensing observables, especially imaging data, as they are the most accessible and informative source of lensing observables. We then summarize the primary findings from the literature on the astrophysical and cosmological applications of galaxy-scale lenses. We also discuss the current limitations of the data and methodologies and provide an outlook on the expected improvements in both areas in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals

We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in contrast to the work (Daubechies et al., Pure Appl. Math. 57(11), 1413–1457, 2004), where the single vector signal can be infinite-dimensional, and (Fornasier and Rauhut, SIAM J. Numer. Anal. 46(2), 577613, 2008), which extends the aforementioned work to the joint sparse recovery of finite number of infinite-dimensional vectors. In our case, to take account of the joint sparsity and promote the coupling of nonvanishing components, we employ a convex relaxation approach with mixed norm penalty ℓ 2,1 . This paper discusses the computation of the solutions of linear inverse problems with such relaxation by a forward-backward splitting algorithm. However, since the solution matrix possesses infinitely many columns, the arguments of Daubechies et al. (Pure Appl. Math. 57(11), 1413–1457, 2004) no longer apply. As such, we establish new strong convergence results for the algorithm, in particular when the set of jointly sparse vectors is infinite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mutual information prediction for strongly correlated systems

We have trained a new machine-learning (ML) model which predicts mutual information (MI) for strongly correlated systems. This is a complex quantity, which is much more difficult to predict than one-site entropies, but carries important information about the correlation structure inside electronic systems. In this work, we replaced the expensive density matrix renormalization group (DMRG) calculations by newly trained ML model for prediction of the mutual information. We show the performance of the model on two important tasks: (a) to determine the correlation structure and (b) to determine ordering of orbitals for accurate DMRG calculations. In conclusion, the results are compared with the MI obtained from accurate DMRG calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Dependency of CO 2 methanation on the strong metal-support interaction for supported Ni/CeO 2 catalysts

The strong metal-support interaction (SMSI) for supported Ni/CeO 2 catalysts with different CeO 2 nanomorphologies was systematically explored. The degree of encapsulation of Ni particles originating from the SMSI effect was found to follow the trend of Ni/CeO 2 -(1 1 1) > Ni/CeO 2 -(1 0 0) > Ni/CeO 2 -(110 + 100), which parallels the CO 2 hydrogenation activity. Quasi in situ XPS reveals the presence of Ce 3+ sites in accordance with the formation of an amorphous surface CeOx layer encapsulating the Ni nanoparticles. In situ DRIFTS indicates the reaction pathway and rate-determining step are dependent on the degree of the SMSI effect, leading to distinct selectivities towards CH 4 , especially at a high weight hourly space velocity (WHSV). Finally, these findings present a fundamental strategy about tailoring catalytic performance through support facet dependent susceptibility of SMSI phenomena.

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

Determination of the strong coupling and its running from measurements of inclusive jet production

The value of the strong coupling α S is determined in a comprehensive analysis at next-to-next-to-leading order accuracy in quantum chromodynamics. The analysis uses double-differential cross section measurements from the CMS Collaboration at the CERN LHC of inclusive jet production in proton-proton collisions at centre-of-mass energies of 2.76, 7, 8, and 13 TeV, combined with inclusive deep-inelastic data from HERA. The value α S (m z ) = 0.1176 $^{+0.0014}_{-0.0016}$ is obtained at the scale of the Z boson mass. By using the measurements in different intervals of jet transverse momentum, the running of α S is probed for energies between 100 and 1600 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A Bayesian framework to investigate radiation reaction in strong fields

Recent experiments aiming to measure phenomena predicted by strong-field quantum electrodynamics (SFQED) have done so by colliding relativistic electron beams and high-power lasers. In such experiments, measurements of collision parameters are not always feasible. However, precise knowledge of these parameters is required to accurately test SFQED. Here, we present a novel Bayesian inference procedure that infers collision parameters that could not be measured on-shot. This procedure is applicable to all-optical non-linear Compton scattering experiments investigating radiation reaction. The framework allows multiple diagnostics to be combined self-consistently and facilitates the inclusion of known information pertaining to the collision parameters. Using this Bayesian analysis, the relative validity of the classical, quantum-continuous and quantum-stochastic models of radiation reaction was compared for several test cases, which demonstrates the accuracy and model selection capability of the framework and highlight its robustness if the experimental values of fixed parameters differ from their values in the models.

47 OTHER INSTRUMENTATION↗