SEARCH · Engineering Papers
Results for “Spectra”
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.
Development of a Gamma-Ray Radionuclide Library for the Identification of Gamma Spectra
Not provided.
Structure and vibration spectra of strontium and magnesium oxalates at high pressure
Explore the source record for details and available documents.
Resolving Mixtures of Soot Characterized by SP-AMS Spectra Using a Latent Dirichlet Allocation Model
Soot produced by detonation or combustion events exhibits different chemical properties depending on the fuel, device construction, and environmental conditions in which the event occurs. These properties can be useful for defining relevant signatures for probabilistically identifying the different types of events that occurred, based on the soot that is produced from these events. However, it is rare to observe samples of soot from a detonation or combustion that are not contaminated by outside particles. In this paper, we present a method for resolving mixtures of soot to determine the contributions of sources that may be present in samples of recovered soot. We use Latent Dirichlet Allocation to describe the generative process for a sample of recovered soot, and use Variational Bayesian Inference to learn about the parameters associated with the generative model. We demonstrate the utility of this method by considering real samples of mixtures of soot under various frameworks to show that the model is able to identify the different components present in a sample of soot as well as their mixing proportions.
Application of machine learning for the estimation of electron energy distribution from optical emission spectra
Abstract This paper discusses the use of probabilistic deep neural networks for the prediction of the electron energy probability function in low-temperature non-thermal plasmas. The neural networks are trained using optical emission spectroscopy and Langmuir probe measurements, with the goal of providing a reliable estimate of the electron energy probability function solely from optical emission data. The performance of both non-Bayesian and Bayesian networks is evaluated. It is found that Bayesian models are preferable as they assign a higher level of uncertainty to their prediction especially when the dataset used to train them is small. This work describes one of the many potential applications of machine learning in plasma science and technology.
Asymmetric Fraunhofer spectra in a topological insulator-based Josephson junction
Josephson junctions with topological insulators as their weak link (S–TI–S junctions) are predicted to host Majorana fermions, which are key to creating qubits for topologically protected quantum computing. But the details of the S–TI–S current-phase relation and its interplay with magnetic fields are not well understood. We fabricate a Bi 2 Se 3 junction with NbTi leads and measure the Fraunhofer patterns of the junction with applied in-plane fields. We observe that asymmetric Fraunhofer patterns appear in the resistance maps of B z vs B x,y , with aperiodic node spacings. These asymmetric patterns appear even at zero parallel field and for temperatures up to 1 K. The anomalous features are compared to asymmetric Fraunhofer patterns expected for finite Cooper pair momentum shifts as well as geometric effects. We show that the geometric effects can dominate, independent of in-plane field magnitude. Furthermore, these results are important for differentiating geometrical phase shifts from those caused by Cooper pair momentum shifting, Majorana mode signatures, or other unconventional superconducting behavior.
Visible emission spectra of thermographic phosphors under x-ray excitation
Thermographic phosphors have been employed for temperature sensing in challenging environments, such as on surfaces or within solid samples exposed to dynamic heating, because of the high temporal and spatial resolution that can be achieved using this approach. Typically, UV light sources are employed to induce temperature-sensitive spectral responses from the phosphors. However, it would be beneficial to explore x-rays as an alternate excitation source to facilitate simultaneous x-ray imaging of material deformation and temperature of heated samples and to reduce UV absorption within solid samples being investigated. Here, the phosphors BaMgAl 10 O 17 :Eu (BAM), Y 2 SiO 5 :Ce, YAG:Dy, La 2 O 2 S:Eu, ZnGa 2 O 4 :Mn, Mg 3 F 2 GeO 4 :Mn, Gd 2 O 2 S:Tb, and ZnO were excited using incident synchrotron x-ray radiation. These materials were chosen to include conventional thermographic phosphors as well as x-ray scintillators (with crossover between these two categories). X-ray-induced thermographic behavior was explored through the measurement of visible spectral response with varying temperature. The incident x-rays were observed to excite the same electronic energy level transitions in these phosphors as UV excitation. Similar shifts in the spectral response of BAM, Y 2 SiO 5 :Ce, YAG:Dy, La 2 O 2 S:Eu, ZnGa 2 O 4 :Mn, Mg 3 F 2 GeO 4 :Mn, and Gd 2 O 2 S:Tb were observed when compared to their response to UV excitation found in literature. Some phosphors were observed to thermally quench in the temperature ranges tested here, while the response from others did not rise above background noise levels. This may be attributed to the increased probability of non-radiative energy release from these phosphors due to the high energy of the incident x-rays. These results indicate that x-rays can serve as a viable excitation source for phosphor thermometry.
Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM
FIDASIM is a code that models signals produced by charge-exchange reactions between neutrals and ions (both fast and thermal) in magnetically confined plasmas. With the ion distribution function as input, the code predicts the efflux to a neutral particle analyzer diagnostic and the photon radiance of Balmer-alpha light to a fast-ion D α diagnostic, in addition to many other related quantities. A new, parallelized version of the Monte Carlo code FIDASIM has been developed in Fortran90 that is substantially faster than the original interactive data language version. Modified algorithms include more accurate treatments of the time dependent collisional-radiative equations that describe neutral energy levels, of the cloud of ‘halo’ neutrals that surround the injected neutral beam, and of finite Larmor radius effects. Enhanced physics capabilities include modelling ‘passive’ signals from cold edge neutrals, the ability to treat general three-dimensional magnetic confinement configurations, and calculations of diagnostic-specific weight functions that enable tomographic reconstructions of the fast-ion distribution function. Neutral beam attenuation, beam emission, and fast-ion birth profiles are also modelled. Finally, the new algorithms have been successfully validated against experimental data and new features have been tested through benchmarks between two independently developed versions of the code.
Combining steady-state photo-capacitance spectra with first-principles calculations: the case of Fe and Ti in β-Ga2O3
Not Available
Precision redshift-space galaxy power spectra using Zel'dovich control variates
Numerical simulations in cosmology require trade-offs between volume, resolution and run-time that limit the volume of the Universe that can be simulated, leading to sample variance in predictions of ensemble-average quantities such as the power spectrum or correlation function(s). Sample variance is particularly acute at large scales, which is also where analytic techniques can be highly reliable. This provides an opportunity to combine analytic and numerical techniques in a principled way to improve the dynamic range and reliability of predictions for clustering statistics. In this paper we extend the technique of Zel'dovich control variates, previously demonstrated for 2-point functions in real space, to reduce the sample variance in measurements of 2-point statistics of biased tracers in redshift space. We demonstrate that with this technique, we can reduce the sample variance of these statistics down to their shot-noise limit out to k ~ 0.2 h Mpc -1 . This allows a better matching with perturbative models and improved predictions for the clustering of e.g. quasars, galaxies and neutral Hydrogen measured in spectroscopic redshift surveys at very modest computational expense. We discuss the implementation of ZCV, give some examples and provide forecasts for the efficacy of the method under various conditions.
Aemulus $\nu$: precise predictions for matter and biased tracer power spectra in the presence of neutrinos
Here we present the Aemulusν simulations: a suite of 150 (1.05 h -1 Gpc) 3 N-body simulations with a mass resolution of 3.51 × 10 10 Ω cb /0.3 h -1 M ⊙ in a wνCDM cosmological parameter space. The simulations have been explicitly designed to span a broad range in σ8 to facilitate investigations of tension between large scale structure and cosmic microwave background cosmological probes. Neutrinos are treated as a second particle species to ensure accuracy to 0.5 eV, the maximum neutrino mass that we have simulated. By employing Zel'dovich control variates, we increase the effective volume of our simulations by factors of 10-10 5 depending on the statistic in question. As a first application of these simulations, we build new hybrid effective field theory and matter power spectrum surrogate models, demonstrating that they achieve ≤ 1% accuracy for k ≤ 1 hMpc -1 and 0 ≤ z ≤ 3, and ≤ 2% accuracy for k ≤ 4 hMpc -1 for the matter power spectrum. We publicly release the trained surrogate models, and estimates of the surrogate model errors in the hope that they will be broadly applicable to a range of cosmological analyses for many years to come.
Experimental inference of neutral and impurity transport in Alcator C-Mod using high-resolution x-ray and ultra-violet spectra
We present experimental inferences of cross-field impurity transport coefficients for AlcatorC-Mod plasmas without edge-localized modes, leveraging a novel forward model for the entire Ca Kα spectrum, including satellite lines within the spectral range, to compare to high-resolution x-ray imaging crystal spectroscopy (XICS). These measurements are complemented by extreme ultra-violet (EUV) spectroscopy that constrains transport closer to the edge. Using new atomic data sets for both XICS and EUV analysis has enabled consideration of line ratios across both spectral ranges and has increased the accuracy of inferred transport coefficients. Inclusion of charge exchange between edge thermal neutrals and impurities is shown to be extremely important in C-Mod pedestals. Atomic D neutral densities from experimental D Lyα measurements at the midplane are compared to SOLPS-ITER simulations, finding good agreement. Bayesian inferences of impurity transport coefficients are presented for L-, EDA H-, and I-mode discharges, making use of the Aurora package for forward modeling and combining our spectroscopic constraints. Experimentally inferred diffusion profiles are found to match turbulent transport models at midradius within uncertainties, using both quasilinear gyro-fluid TGLF SAT-1 and nonlinear ion-scale gyrokinetic CGYRO simulations. Furthermore, significant discrepancies in convection are observed in some cases, suggesting difficulties in predictions of flat or hollow impurity profiles.
Spectra of perfect state transfer Hamiltonians on fractal-like graphs
Abstract In this paper we study the spectral features, on fractal-like graphs, of Hamiltonians which exhibit the special property of perfect quantum state transfer (PQST): the transmission of quantum states without dissipation. The essential goal is to develop the theoretical framework for understanding the interplay between PQST, spectral properties, and the geometry of the underlying graph, in order to design novel protocols for applications in quantum information science. We present a new lifting and gluing construction, and use this to prove results concerning an inductive spectral structure, applicable to a wide variety of fractal-like graphs. We illustrate this construction with explicit examples for several classes of diamond graphs.
A line-binned treatment of opacities for the spectra and light curves from neutron star mergers
ABSTRACT The electromagnetic observations of GW170817 were able to dramatically increase our understanding of neutron star mergers beyond what we learned from gravitational waves alone. These observations provided insight on all aspects of the merger from the nature of the gamma-ray burst to the characteristics of the ejected material. The ejecta of neutron star mergers are expected to produce such electromagnetic transients, called kilonovae or macronovae. Characteristics of the ejecta include large velocity gradients, relative to supernovae, and the presence of heavy r-process elements, which pose significant challenges to the accurate calculation of radiative opacities and radiation transport. For example, these opacities include a dense forest of bound–bound features arising from near-neutral lanthanide and actinide elements. Here we investigate the use of fine-structure, line-binned opacities that preserve the integral of the opacity over frequency. Advantages of this area-preserving approach over the traditional expansion–opacity formalism include the ability to pre-calculate opacity tables that are independent of the type of hydrodynamic expansion and thus eliminate the computational expense of calculating opacities within radiation-transport simulations. Tabular opacities are generated for all 14 lanthanides as well as a representative actinide element, uranium. We demonstrate that spectral simulations produced with the line-binned opacities agree well with results produced with the more accurate continuous Monte Carlo Sobolev approach, as well as with the commonly used expansion–opacity formalism. The agreement between the line-binned and expansion–opacity results is explained as arising from the similarity in their opacities in the limit of low optical depth, where radiation transport is important in the ejecta. Additional investigations illustrate the convergence of opacity with respect to the number of included lines, and elucidate sensitivities to different atomic physics approximations, such as fully and semirelativistic approaches.
Using ground-based measurements to recover the spectra of radiation escaping from distant light-pollution sources
ABSTRACT A professional dark sky assessment normally requires the numerical modelling of light propagation from ground-based sources into the atmosphere. The spectral power distribution (SPD) of light escaping from an artificial source is one of the key parameters needed in predicting models to simulate the optical signatures of the night sky as a function of distance. SPD at zero distance is due to a non-trivial superposition of light beams, but does not necessarily coincide with the weighted SPD of individual lights. This is because most photons can be removed by obstacles or can interact with many surfaces before being directed into the atmosphere. We have developed an experimental and theoretical method for obtaining the initial SPD from ground-based spectroscopy of the night sky. The method is applicable to distant sources of light and is demonstrated in field measurements conducted on the light dome of Chicago with a new sky glow spectrometer. We show that the method requires analysing the relative impact of local light sources scattered around the measuring site on the radiance of the light dome. Our theoretical method along with ground-based spectroscopy represents a new approach to characterizing light-pollution sources which are otherwise difficult to study due to lack of information on either light-source inventory or a heterogeneous 3D structure of light-emitting and blocking environments.
Evidence for a high-energy tail in the gamma-ray spectra of globular clusters
Millisecond pulsars are very likely the main source of gamma-ray emission from globular clusters. However, the relative contributions of two separate emission processes – curvature radiation from millisecond pulsar magnetospheres versus inverse Compton emission from relativistic pairs launched into the globular cluster environment by millisecond pulsars – have long been unclear. To address this, we search for evidence of inverse Compton emission in 8-yr Fermi–LAT data from the directions of 157 Milky Way globular clusters. We find a mildly statistically significant (3.8σ) correlation between the measured globular cluster gamma-ray luminosities and their photon field energy densities. However, this may also be explained by a hidden correlation between the photon field densities and the stellar encounter rates of globular clusters. Analysed in toto, we demonstrate that the gamma-ray emission of globular clusters can be resolved spectrally into two components: (i) an exponentially cut-off power law and (ii) a pure power law. The latter component – which we uncover at a significance of 8.2σ – has a power index of 2.79 ± 0.25. It is most naturally interpreted as inverse Compton emission by cosmic-ray electrons and positrons injected by millisecond pulsars. Here, we find the luminosity of this power-law component is comparable to, or slightly smaller than, the luminosity of the curved component, suggesting the fraction of millisecond pulsar spin-down luminosity into relativistic leptons is similar to the fraction of the spin-down luminosity into prompt magnetospheric radiation.