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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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Application of state variable techniques to optimal feature extraction.
State variable techniques applied to optimal continuous linear feature extraction for binary Gaussian pattern recognition or detection problem
Solar-System Ephemeris Toolbox
NASA s Jet Propulsion Laboratory (JPL) generates planetary and lunar ephemeris data and FORTRAN routines that allow users to obtain state data for the Sun, the moon, and the planets. The JPL Solar System Ephemeris Toolbox, developed at Kennedy Space Center, is a set of functions that provides the same functionality in the MATLAB computing environment along with some additional capabilities. The toolbox can be used interactively via a graphical user interface (GUI), or individual functions can be called from the MATLAB command prompt or other MATLAB scripts and functions. The toolbox also includes utility functions to define and perform coordinate transformation (e.g., mean-of-date, true-of-date, J2000) that are common in the use of these ephemerides. An attached README file guides the user through the process of constructing binary ephemeris files, verifying correct installation, and using functions to extract state data. This process also can be performed using the GUI. Help from each toolbox function is available through MATLAB s "help" function. Many of the functions in the toolbox are MATLAB equivalents of the JPL-written FORTRAN programs and subroutines used for the same purposes. A novice can use the GUI to extract state data, while a more experienced user can use the functions directly, as needed, in his/her applications. The toolbox has been tested using MATLAB Releases 13 an
Ne 21 energy levels approaching the α -particle threshold
Nuclei around Ne 20 exhibit an interplay of different excitations caused by different aspects of nuclear structure, including single-particle and multiparticle configurations and collective rotations. One-nucleon transfer reactions selectively probe single-particle structures in these nuclei. These nuclei are also important to astrophysics, with a number of important reactions proceeding through this mass region. Energy levels approaching the α -particle threshold in Ne 21 are of importance to nuclear structure. The Ne 20 ( d , p ) Ne 21 reaction was measured and the corresponding spectroscopic nuclear information was extracted. States in Ne 21 were populated using the Ne 20 ( d , p ) Ne 21 reaction in forward kinematics. Protons were identified in the Triangle Universities Nuclear Laboratory (TUNL) Enge split-pole spectrograph and angular distributions were extracted. Spin-party assignments were made and neutron partial widths were determined based on distorted-wave Born approximation (DWBA) analysis. Several new energy levels were observed at energies of 7176, 7235, 7250, and 7337 keV, and spin-parities are reported which generally agree with previous results where literature was available. Spin and parity assignments are reported for several energy levels along with estimated neutron widths for those states above the neutron threshold ( S n = 6761 keV ). Results from this study are placed in context with a review of the available literature on all known states in this energy region of Ne 21 . Published by the American Physical Society 2024
Rotational excitation of linear molecules by collisions with atoms - Comparison of classical and quantum methods
Exact quantum results for the rotational excitation of rigid linear molecules by collisions with atoms are compared with classical trajectory results. The systems studied are CO-He, CS-H2, OCS-H2, HCl-He, and HCl-Ar at collision energies up to 500/cm. Total cross sections and state to state rate constants are compared. The classical results are found to be in good agreement with the quantum results on the average. Differences arising from the existence of purely quantum effects are clearly evident, but consistent and predictable. Two methods of extracting state selective information from moments of the classical distribution are examined and found to be less reliable than the usual histogram method. In conjunction with previous comparisons of classical and quantum results these calculations provide a useful measure of the limitations and reliability of classical trajectories.
Analysis of Open Hole Compression Specimens Using the CompDam Continuum Damage Mechanics Model
This report documents a validation study on the standard Open Hole Compression (OHC) laminate test specimen conducted as part of the NASA Advanced Composites Project (ACP). Tests were conducted on OHC specimens with hard, quasi-isotropic, and soft layups using digital image correlation and X-Ray computed tomography to capture the structural response and damage evolution. Progressive damage models were constructed for use with the CompDam continuum damage mechanics code following the best practices established during the ACP. Detailed interrogation of the analysis results and comparison with experimental measurements provide a basis for assessing the capability of the modeling approach for OHC. The structural response is found to be captured well, with strengths predicted within 3\% of the experimental values for hard and quasi-isotropic laminates. In the soft laminate, the model predicts failure to be more brittle than the nonlinear, ductile response that was measured. Damage states extracted from the models at the same load level as test measurements are overlaid to show directly the similarities and differences between test and analysis results. Studying the damage evolution predicted by the analysis reveals that the failure process is a competition between fiber damage and delamination/sub-laminate buckling, with fiber damage dominating the collapse in the hard laminate and sub-laminate buckling governing in the soft laminate. Finally, a series of parametric studies varying numerical solution parameters (mesh size, mass scaling) and physical properties (fiber direction compressive strength and toughness) reveal sensitivities and deficiencies of the model. To the authors' knowledge, this study is the first for OHC specimens to include detailed evaluation of damage mode interactions, direct overlay of predicted and measured damage states, and sensitivity of the predicted results to difficult-to-measure fiber direction material properties.
Non-Intrusive Appliance Identification with Appliance-Specific Networks
The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.
Time-resolved atomic-resolution Brownian tomography of single nanocrystals reveals size-dependent dynamics
Atomic-resolution structure identification of nanocrystals by graphene liquid cell electron microscopy (GLC-EM) has revealed that small, solubilized platinum nanocrystals consist of an ordered crystalline core surrounded by mobile surface atoms, which dissociate during oxidative etching, resulting in distinct temporal structural states. Requirements imposed by the 3D reconstruction algorithm limit the number of structural states that can be resolved. We introduce a regularized 3D reconstruction algorithm that exploits the redundancy inherent in the experimental data, allowing us to improve the time resolution. Our developments provide a comprehensive molecular picture at unprecedented spatial and temporal resolution of the nonlinear, linear, and fluctuating dynamic phenomena that single nanocrystals undergo during the GLC-EM experiment. We determined atomic structures of 66 temporal structural states, extracted from 15 time trajectories of individual nanocrystals. Large (478 to 698 atoms) and small (<300 atoms) nanocrystals show etching that preserves a stable core, whereas mid-sized (351 to 571 atoms) nanocrystals present dynamics that change the coordination of the core.
Complete Initial Evaluation of Novel Complexants for Tc Holdback for Simplified Single Cycle Separations.
Management of technetium at the back end of nuclear fuel cycle is complicated by its unique physico-chemical character, but must be addressed to due to the environmental, storage and reprocessing challenges of this fission product. In a single-cycle scenario, the recovery and purification of uranium is particularly challenging due to the tendency of a pertechnetate anion to follow uranyl cation. This report summarizes initial studies directed towards finding the solution for technetium management. Two options for controlling technetium’s chemistry in solvent extraction scenarios were studied. Molecular recognition of pertechnetate by aqueous complexants based on guanidinium moieties was compared to redox manipulation of technetium using dihydrazide reagents. Solvent extraction, potentiometric and nuclear magnetic resonance spectroscopy studies were performed. The influence of guanidinium reagents on the liquid-liquid partitioning of technetium is less pronounced, relative to dihydrazides. Strong impact exerted by dihydrazides originates from the technetium-catalyzed decomposition of such compounds which reduces technetium to a tetravalent, non-extractable state. Although this route of technetium management is very effective the destruction of dihydrazides is undesirable. Guanidinium complexants show a more tempered influence on technetium. The effect on the liquid-liquid partitioning of pertechnetate is evident and likely guided by anion recognition due to ion-pair and hydrogen bond formation. Guanidiniums are stable in presence of technetium as evidenced by nuclear magnetic resonance studies. The steady state chemistry of guanidiniums identify this class of aqueous complexants as solid candidates for structure-function pertechnetate recognition studies.
Report of subpanel on feature extraction
The state of knowledge in feature extraction for Earth resource observation systems is reviewed and research tasks are proposed. Issues in the subpixel feature estimation problem are defined as: (1) the identification of image models which adequately describe the data and the sensor it is using; (2) the construction of local feature models based on those image models; and (3) the problem of trying to understand these effects of preprocessing on the entire process. The development of ground control point (GCP) libraries for automated selection presents two concerns. One is the organization of these GCP libraries for rectification problems, i.e., the problems of automatically selecting by computer the specific GCP's for particular registration tasks. Second is the importance of integrating ground control patterns in a data base management system, allowing interface to a large number of sensor image types with an automatic selection system. The development of data validation criteria for the comparison of different extraction techniques is also discussed.
Extracting doubly excited state lifetimes in helium directly in the time domain with attosecond noncollinear four-wave-mixing spectroscopy
The helium atom, with one nucleus and two electrons, is a prototypical system to study quantum many-body dynamics. Doubly excited states, or quantum states in which both electrons are excited by one photon, showcase electronic-correlation mediated effects. In this paper, the natural lifetimes of the doubly excited 1 P o 2 s n p Rydberg series and the 1 S e 2 p 2 dark state in helium in the 60–65 eV region are measured directly in the time domain with extreme-ultraviolet/near-infrared noncollinear attosecond four-wave-mixing (FWM) spectroscopy. The measured lifetimes agree with lifetimes deduced from spectral linewidths and theoretical predictions, and the roles of specific decay mechanisms are considered. While complex spectral line shapes in the form of Fano resonances are common in absorption spectroscopy of autoionizing states, the background-free and thus homodyned character of noncollinear FWM results exclusively in Lorentzian spectral features in the absence of strong-field effects. The onset of strong-field effects that would affect the extraction of accurate natural lifetimes in helium by FWM is determined to be approximately 0.3 Rabi cycles. This study provides a systematic understanding of the FWM parameters necessary to enable accurate lifetime extractions, which can be utilized in more complex quantum systems in the future. Published by the American Physical Society 2024
Addressing quantum’s “fine print” with efficient state preparation and information extraction for quantum algorithms and geologic fracture networks
Abstract Quantum algorithms provide an exponential speedup for solving certain classes of linear systems, including those that model geologic fracture flow. However, this revolutionary gain in efficiency does not come without difficulty. Quantum algorithms require that problems satisfy not only algorithm-specific constraints, but also application-specific ones. Otherwise, the quantum advantage carefully attained through algorithmic ingenuity can be entirely negated. Previous work addressing quantum algorithms for geologic fracture flow has illustrated core algorithmic approaches while incrementally removing assumptions. This work addresses two further requirements for solving geologic fracture flow systems with quantum algorithms: efficient system state preparation and efficient information extraction. Our approach to addressing each is consistent with an overall exponential speed-up.
Variational quantum state eigensolver
Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The variational quantum eigensolver (VQE) treats the case when the matrix is a Hamiltonian. Here, we address the case when the matrix is a density matrix ρ. We introduce the variational quantum state eigensolver (VQSE), which is analogous to VQE in that it variationally learns the largest eigenvalues of ρ as well as a gate sequence V that prepares the corresponding eigenvectors. VQSE exploits the connection between diagonalization and majorization to define a cost function C=Tr(ρ~H) where H is a non-degenerate Hamiltonian. Due to Schur-concavity, C is minimized when ρ~=VρV† is diagonal in the eigenbasis of H. VQSE only requires a single copy of ρ (only n qubits) per iteration of the VQSE algorithm, making it amenable for near-term implementation. We heuristically demonstrate two applications of VQSE: (1) Principal component analysis, and (2) Error mitigation.
Automated label flows for excited states of correlation functions in lattice gauge theory
Extracting excited states from lattice gauge theory correlation functions can be achieved through $χ^2$ minimization fits or algebraic approaches such as the variational method and Prony's method. Performing any kind of error analysis often leads to overlapping confidence regions of model parameters, even when the spectrum is not particularly dense. To correctly estimate errors, one must beware of mislabeling the states. In this work, we provide an algorithm that we call automated label flows which consistently and systematically identifies a deterministic labeling of states. This is a black-box approach in the sense that it gives a sensible set of labels without user guidance. Further, as an example, we pair one black box method with another, analyzing a lattice correlation function from real data using automated label flows in the context of Prony's method.
Extraction of ground-state nuclear deformations from ultrarelativistic heavy-ion collisions: Nuclear structure physics context
The collective-flow-assisted nuclear shape-imaging method in ultrarelativistic heavy-ion collisions (UHICs) has recently been used to characterize nuclear collective states. In this paper, we assess the foundations of the shape-imaging technique employed in these studies. We argue that some current UHIC nuclear imaging techniques neglect fundamental aspects of spontaneous symmetry breaking and symmetry restoration in colliding ions and incorrectly infer one-body multipole moments from studies of nucleonic correlations. Therefore, the impact of this approach on nuclear structure research has been overstated. Conversely, efforts to incorporate existing knowledge on nuclear shapes into analysis pipelines can be beneficial for benchmarking tools and calibrating models used to extract information from ultrarelativistic heavy-ion experiments.
Identification of state variables and dynamic inflow from rotor model dynamic tests
The paper describes methods for extracting unknown state variables and parameters from dynamic rotor model tests given transient cyclic pitch stirring inputs, blade root flap-bending measurements, and the form of the dynamic rotor equations, including a rotor dynamic inflow description, when none of the physical parameters are known. A simplified version of the maximum likelihood method seems best suited for this purpose. The measurement equation error covariance matrix is assumed constant during each iteration, but updated for the subsequent iteration. A detailed analysis of the suitability of the derived techniques for studying various rotor dynamic inflow effects is provided.
The proton charge radius extracted from the initial-state radiation experiment at MAMI
Abstract We report on a comprehensive reinterpretation of the existing cross-section data for elastic electron-proton scattering obtained by the initial-state radiation technique, resulting in a significantly improved accuracy of the extracted proton charge radius. By refining the external energy corrections we have achieved an outstanding description of the radiative tail, essential for a detailed investigation of the proton finite-size effects on the measured cross sections. This development, together with a novel framework for determining the radius, based on a regression analysis of the cross sections employing a polynomial model for the form factor, led us to a new value for the charge radius, which is $$(0.878 \pm 0.011_\mathrm {stat.}\pm 0.031_\mathrm {sys.}\pm 0.002_\mathrm {mod.})\,\mathrm {fm}$$ ( 0.878 ± 0 . 011 stat . ± 0 . 031 sys . ± 0 . 002 mod . ) fm
The 1 S 0 Pairing Gap in Neutron Matter
We report ab initio calculations of the S wave pairing gap in neutron matter calculated using realistic nuclear Hamiltonians that include two- and three-body interactions. We use a trial state, properly optimized to capture the essential pairing correlations, from which we extract ground state properties by means of auxiliary field diffusion Monte Carlo simulations. We extrapolate our results to the thermodynamic limit by studying the finite-size effects in the symmetry-restored projected Bardeen-Cooper-Schrieffer (PBCS) theory and compare our results to other ab initio studies done in the past. Our quantum Monte Carlo results for the pairing gap show a modest suppression with respect to the mean-field BCS values. These results can be connected to cold atom experiments, via the unitarity regime where fermionic superfluidity assumes a unified description, and they are important in the prediction of thermal properties and the cooling of neutron stars.