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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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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Entangled two-plasmon generation in carbon nanotubes and graphene-coated wires

Here, we investigate the two-plasmon spontaneous decay of a quantum emitter near single-walled carbon nanotubes (SWCNTs) and graphene-coated wires (GCWs). We demonstrate efficient, enhanced generation of two-plasmon entangled states in SWCNTs due to the strong coupling between tunable guided plasmons and the quantum emitter. We predict two-plasmon emission rates more than twelve orders of magnitude higher than in free space, with average lifetimes of a few dozen nanoseconds. Given their low dimensionality, these systems could be more efficient for generating and detecting entangled plasmons in comparison to extended graphene. Indeed, we achieve a tunable spectrum of emission in GCWs, where sharp resonances occur precisely at the plasmons' minimum excitation frequencies. We show that by changing the material properties of the GCW's dielectric core, one could tailor the dominant modes and frequencies of the emitted entangled plasmons while keeping the decay rate ten orders of magnitude higher than in free space. By unveiling the unique properties of two-plasmon spontaneous emission processes in the presence of low-dimensional carbon-based nanomaterials, our findings set the basis for a novel material platform with applications to on-chip quantum information technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Spin-flavor structure of chiral-odd generalized parton distributions in the large- N c limit

We study the spin-flavor structure of the nucleon's chiral-odd generalized parton distributions (transversity GPDs) in the large-N c limit of QCD. In contrast to the chiral-even case, only three combinations of the four chiral-odd GPDs are nonzero in the leading order of the 1/N c expansion: E-bar T = E T +2H-tilde T , H T , and E-tilde T . The degeneracy is explained by the absence of spin-orbit interactions correlating the transverse momentum transfer with the transverse quark spin. It can also be deduced from the natural N c scaling of the quark-nucleon helicity amplitudes associated with the GPDs. In the GPD E-bar T the flavor-singlet component u+d is leading in the 1/N c expansion, while in H T and E-tilde T it is the flavor-nonsinglet components u–d. Furthermore, the large-N c relations are consistent with the spin-flavor structure extracted from hard exclusive π 0 and η electroproduction data, if it is assumed that the processes are mediated by twist-3 amplitudes involving the chiral-odd GPDs and the chiral-odd pseudoscalar meson distribution amplitudes.

1/N c↗
DOE OSTI2024

Constraints on dark matter from dynamical heating of stars in ultrafaint dwarfs. II. Substructure and the primordial power spectrum

There is a large and growing interest in observations of small-scale structure in dark matter. We propose a new way to probe dark matter structures in the ∼ 10 – 10 8 M ⊙ range. This allows us to constrain the primordial power spectrum over shorter distances scales than possible with direct observations from the CMB. For k in the range ∼ 10 – 1000 Mpc − 1 our constraints on the power spectrum are orders of magnitude stronger than previous bounds. We also set some of the strongest constraints on dark matter isocurvature perturbations. Our method relies on the heating effect such dark matter substructures would have on the distribution of stars in an ultrafaint dwarf galaxy. Many models of inflation produce enhanced power at these short distance scales and can thus be constrained by our observation. Further, many dark matter models such as axion dark matter, self-interacting dark matter and dissipative dark matter, produce dense structures which could be constrained this way. Published by the American Physical Society 2024

Graham, Peter W. (ORCID:0000000216001601)↗
DOE OSTI2016

Reducing the two-loop large-scale structure power spectrum to low-dimensional, radial integrals

Modeling the large-scale structure of the universe on nonlinear scales has the potential to substantially increase the science return of upcoming surveys by increasing the number of modes available for model comparisons. One way to achieve this is to model nonlinear scales perturbatively. Unfortunately, this involves high-dimensional loop integrals that are cumbersome to evaluate. Here, trying to simplify this, we show how two-loop (next-to-next-to-leading order) corrections to the density power spectrum can be reduced to low-dimensional, radial integrals. Many of those can be evaluated with a one-dimensional fast Fourier transform, which is significantly faster than the five-dimensional Monte-Carlo integrals that are needed otherwise. The general idea of this fast fourier transform perturbation theory method is to switch between Fourier and position space to avoid convolutions and integrate over orientations, leaving only radial integrals. This reformulation is independent of the underlying shape of the initial linear density power spectrum and should easily accommodate features such as those from baryonic acoustic oscillations. We also discuss how to account for halo bias and redshift space distortions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Quasisymmetric Optimization of Nonaxisymmetry in Tokamaks

Predictive 3D optimization reveals a novel approach to modify a nonaxisymmetric magnetic perturbation to be entirely harmless for tokamaks, by essentially restoring quasisymmetry in perturbed particle orbits as much as possible. Such a quasisymmetric magnetic perturbation (QSMP) has been designed and successfully tested in the KSTAR and DIII-D tokamaks, demonstrating no performance degradation despite the large overall amplitudes of nonaxisymmetric fields and strong response otherwise expected in the tested plasmas. The results indicate that a quasisymmetric optimization is a robust path of error field correction across the resonant and nonresonant field spectrum in a tokamak, leveraging the prevailing concept of quasisymmetry for general 3D plasma confinement systems such as stellarators. Finally, the optimization becomes, in fact, a simple eigenvalue problem to the so-called torque response matrices if a perturbed equilibrium is calculated consistent with nonaxisymmetric neoclassical transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Robust qubit interactions mediated by photonic topological edge states

Here, we investigate the coupling of two spatially separated qubits via topologically protected edge states in a two-dimensional Hofstadter lattice. In this hybrid platform, the qubits are coupled to distinct edge sites of the lattice, enabling long-range interactions mediated by topological edge modes. We solve the full system Hamiltonian and analyze the resulting eigenstate structure to uncover the conditions under which coherent qubit interactions emerge. Our analysis reveals that the effective coupling is highly sensitive to the qubit placement, energy detuning, and the topological character of the edge spectrum. We obtain an analytical solution that goes beyond the perturbative regime, capturing the full interplay between the qubits and edge modes. These results provide a foundation for exploring information transport and many-body effects in engineered quantum systems where interactions are mediated by topological edge modes.

Chern insulators↗
DOE OSTI2025

Neural refinement of sample weights

Monte Carlo simulations are an essential tool in particle physics data analysis. Events are typically generated alongside weights that redistribute the cross section of the simulated process across the phase space. These weights can be negative, and several post hoc methods have been developed to eliminate or mitigate the negative values. All of these methods share the common strategy of approximating the average weight as a function of phase space. We introduce an alternative approach, which, instead of reweighting to the average, refines the initial weights with a scaling transformation, utilizing a phase space-dependent factor. Since this new refinement method does not need to model the full weight distribution, it can be more accurate. High-dimensional and unbinned phase space is processed using neural networks for the refinement method. In addition to the refinement method, we introduce a new resampling protocol, which can be used in conjunction with any weight transformation to not only preserve the average weight but also the statistical uncertainties of the initial distribution. Using both realistic and synthetic examples, we show that the new neural refinement method is able to match or exceed the accuracy of similar weight transformations and that the new resampling protocol is simpler in implementation than previous methods while exhibiting equivalent statistical properties.

Artificial neural networks↗
DOE OSTI2021

Outcomes and Insights From Simplified Analytic Trajectory Optimization for a Tethered Underwater Kite

This letter formulates and solves a periodic trajectory optimization problem for a tethered underwater kite. The goal is to maximize the average mechanical power harvested by the kite. The type of kite considered in this letter extracts electricity from ocean currents by moving cross-current as its reel away from its base station, and consumes electricity to reel back. The problem of optimizing this kite’s trajectory is challenging due to the high dimensionality and nonlinearity of its dynamics. To tackle this challenge, the literature often separates the problem into two subproblems focusing on optimizing the cross-current and the reel-in/reel-out components of the trajectory, respectively, which may be sub-optimal. In contrast, this letter solves for the combined cross-current and reel-in/reel-out trajectory by linearizing the dynamics of the kite around a zero-power reference equilibrium trajectory in spherical coordinates. This allows the trajectory optimization problem to be solved analytically for simple sinusoidal input perturbations from equilibrium. Here we use linear quadratic regulation to enable the nonlinear kite model to track the optimized trajectory. The result is a computationally efficient approach that achieves an attractive Loyd factor of 19.9%, while providing important insights into the nature of the optimal trajectory.

42 ENGINEERING↗
DOE OSTI2026

3D reconstruction and neural rendering for adversarial machine learning

While evasion attacks on computer vision systems have been widely studied, creating attacks that remain effective under significant changes in viewpoint continues to be challenging. Traditional approaches often rely on affine transformations of images, but these approaches degrade at larger perspective shifts and often produce unrealistic or ineffective perturbations. Recent methods use differentiable renderers to improve viewpoint robustness, but they typically depend on manually constructed 3D models. We introduce a semi-automated pipeline that generates physically printable and perspective-invariant adversarial patches using only a small set of 2D images. Our method integrates 3D reconstruction, neural rendering, adversarial patch optimization, and an object detection victim model into a unified workflow. We use 2D Gaussian Splatting for high fidelity mesh reconstruction and FlexPara for surface parameterization that produces texture maps suitable for patch editing. Together, these components form a fully differentiable pipeline in PyTorch3D that links texture modification to model outputs, enabling efficient optimization of patches that remain effective across many viewpoints. The complete process, from image capture to patch printing and physical evaluation, can be completed within a few hours. We demonstrate the effectiveness of the resulting patches through attacks on the YOLOv8 object detection model and discuss remaining challenges and opportunities for improving robustness and scalability.

Singhvi, Vivaan [ORNL] (ORCID:0009000586288221)↗
DOE OSTI2014

SU-D-BRD-02: A Web-Based Image Processing and Plan Evaluation Platform (WIPPEP) for Future Cloud-Based Radiotherapy

Purpose: Visualization and processing of medical images and radiation treatment plan evaluation have traditionally been constrained to local workstations with limited computation power and ability of data sharing and software update. We present a web-based image processing and planning evaluation platform (WIPPEP) for radiotherapy applications with high efficiency, ubiquitous web access, and real-time data sharing. Methods: This software platform consists of three parts: web server, image server and computation server. Each independent server communicates with each other through HTTP requests. The web server is the key component that provides visualizations and user interface through front-end web browsers and relay information to the backend to process user requests. The image server serves as a PACS system. The computation server performs the actual image processing and dose calculation. The web server backend is developed using Java Servlets and the frontend is developed using HTML5, Javascript, and jQuery. The image server is based on open source DCME4CHEE PACS system. The computation server can be written in any programming language as long as it can send/receive HTTP requests. Our computation server was implemented in Delphi, Python and PHP, which can process data directly or via a C++ program DLL. Results: This software platform is running on a 32-core CPU server virtually hosting the web server, image server, and computation servers separately. Users can visit our internal website with Chrome browser, select a specific patient, visualize image and RT structures belonging to this patient and perform image segmentation running Delphi computation server and Monte Carlo dose calculation on Python or PHP computation server. Conclusion: We have developed a webbased image processing and plan evaluation platform prototype for radiotherapy. This system has clearly demonstrated the feasibility of performing image processing and plan evaluation platform through a web browser and exhibited potential for future cloud based radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-BRA-15: Physical Aspects and Clinical Applications of Post-Treatment Yttrium-90 PET-Based Dosimetry

Purpose: The accuracy of PET-based post-treatment dosimetry of yttrium-90 microspheres has been improving over the past decade and is now at a stage, permitting volumetric dose-outcome studies. We outline the recent advances and identify the physical limitations to the accuracy of the dose calculations. Methods: Convolution of the measured PET activity density distribution with a pre-calculated voxel-dose-kernel (VDK) is the most widely used method for dose reconstruction. Therefore, accurate knowledge of the beta+ branching ratio as well as the micro-dosimetric characteristics of electron interactions within the microsphere is essential for the computation of the dose kernel. We implement a model of the microspheres used in our clinic to calculate the modified electron energy spectrum at the microsphere’s surface and to determine the impact of self-shielding on the dose reconstruction. The three-dimensional dose distributions obtained for 10 patients treated with radio-embolization with yttrium-90 microspheres are evaluated and various DVH markers are investigated for correlation with outcome. Results: The methods for reducing the overall computation uncertainty are systematically outlined in this presentation. Since the latest experimental data on yttrium-90 beta+ branching ratio has a relative uncertainty of 1.5%, all contributing factors derived from Monte Carlo simulations must be brought to a sub 1% level. The self-shielding within the microspheres is found to be responsible for up to 6% reduction of the reconstructed dose in low-gradient regions and must be taken into account. The contribution of trace amounts of other beta+ emitters introduced during the manufacturing process is also discussed. Conclusion: The accelerating pace of clinical adoption of PET-based post-treatment dosimetry is mainly due to advances in both quantitative PET imaging and physical models of dose deposition. We show that the overall physical dose uncertainty in the convolution step can be further reduced, thus making ongoing multi-institutional dose-outcome studies even more reliable.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

The RNA-guided nuclease Cas9 has unlocked powerful methods for perturbing both the genome through targeted DNA cleavage and the regulome through targeted DNA binding, but limited biochemical data have hampered efforts to quantitatively model sequence perturbation of target binding and cleavage across diverse guide sequences. We present scalable, sequencing-based platforms for high-throughput filter binding and cleavage and then perform 62,444 quantitative binding and cleavage assays on 35,047 on- and off-target DNA sequences across 90 Cas9 ribonucleoproteins (RNPs) loaded with distinct guide RNAs. We observe that binding and cleavage efficacy, as well as specificity, vary substantially across RNPs; canonically studied guides often have atypically high specificity; sequence context surrounding the target modulates Cas9 on-rate; and Cas9 RNPs may sequester targets in nonproductive states that contribute to “proofreading” capability. Lastly, we distill our findings into an interpretable biophysical model that predicts changes in binding and cleavage for diverse target sequence perturbations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Description of nucleon-transfer and fusion reactions within time-dependent approaches and coupled-channel method

The time-dependent Schrödinger equation and the method of perturbed stationary states that is based on the expansion of the total wave function for the system of two nuclear cores and a nucleon in a set of nucleon two-center functions are used to describe nucleon transfers and fusion in low-energy nuclear reactions. A set of multichannel equations that couple the relative motion of nuclei to the motion of the nucleon is obtained. The kinetic-energy coupling matrix is similar to the coupling matrix for collective excitations of nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗