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At least 289 records · Page 16

Method for Balancing Detector Output to a Desired Level of Balance at a Frequency

A multi-gas sensor is provided which modulates a polarized light beam over a broadband of wavelengths between two alternating orthogonal polarization components. The two orthogonal polarization components of the polarization modulated beam are directed along two distinct optical paths. At least one optical path contains one or more spectral discrimination elements, with each spectral discrimination element having spectral absorption features of one or more gases of interest being measured. The two optical paths then intersect, and one orthogonal component of the intersected components is transmitted and the other orthogonal component is reflected. The combined polarization modulated beam is partitioned into one or more smaller spectral regions of interest where one or more gases of interest has an absorption band. The difference in intensity between the two orthogonal polarization components is then determined in each partitioned spectral region of interest as an indication of the spectral emission/absorption of the light beam by the gases of interest in the measurement path. The spectral emission/absorption is indicative of the concentration of the one or more gases of interest in the measurement path. More specifically, one embodiment of the present invention is a gas filter correlation radiometer which comprises a polarizer, a polarization modulator, a polarization beam splitter, a beam combiner, wavelength partitioning element, and detection element. The gases of interest are measured simultaneously and, further, can be measured independently or non-independently. Furthermore, optical or electronic element are provided to balance optical intensities between the two optical paths.

Sachse, Glenn W.↗

Spectral Peak Enhancement by Combining Trusted Response Elements via Machine Learning (SPECTRE-ML) v0.8.0

SPECTRE-ML (Spectral Peak Enhancement by Combining Trusted Response Elements via Machine Learning) is a machine learning based program for finding optimal clusters of radiation detector segments (i.e., pixels or voxels) in order to improve spectral performance. It provides facilities for pre-processing and analyzing training datasets, running ML algorithms, and evaluating and visualizing outputs. SPECTRE-ML outperforms simpler ad-hoc segmentation methods such as uniform depth clusters, learning detector performance trends such as dead layers, edge effects, and gain shifts. Although extensible to arbitrary highly-segmented spectroscopic radiation detectors, SPECTRE-ML currently focuses on improving spectral performance in highly-segmented CdZnTe (CZT) detectors for International Atomic Energy Agency (IAEA) non-destructive assay (NDA) safeguards tasks.

Vavrek, Jayson↗

Spectral signatures of transverse optical modes in semiconductor nanowires

In order to build nanophotonic devices, it is important to understand and ultimately control the optical mode structure within potential components such as nanoscale waveguides. However, experimental characterization of such modes in the optical regime is difficult due to the nanoscale dimensions of such components and the perturbations that would be induced by a near-field probe. Here, we demonstrate a probe-free, far-field method to characterize the optical modes within GaN nanowires (NWs) based on a novel off-axis scanning confocal microscope system. Using this microscope, we observe spectral signatures resulting from lateral leakage of waveguide modes when they exceed their respective cutoff limits. We identify these modes within hyperspectral images using an analytical model coupled with finite element simulations. The model can also be used to predict the spectral signatures for given geometrical and dielectric parameters, which enabled us to deduce the transverse dimension of the NW from hyperspectral images with an accuracy of ∼ <#comment/> 30 nm .

Wang, Maoji↗

High-temperature Majorana fermions in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) structures represent one of the most promising platforms to realize, control, and manipulate Majorana modes using scanning tunneling methods. By depositing either chains or islands of magnetic atoms on the surface of a conventional, elemental superconductor such as Pb or Re, topological superconducting phases can emerge. They feature either localized Majorana bound states at the chain ends or dispersing chiral Majorana modes at the island's boundary. However, some of these experiments have not reached the spectral resolution to clearly distinguish between topological Majorana and trivial Shiba states due to very small superconducting gap sizes and experiments performed at sub-Kelvin temperatures. Here we consider superconducting substrates with unconventional spin-singlet pairing, including high-temperature d -wave and extended s -wave superconductors. We derive topological phase diagrams and compute edge states for cylinder and island geometries and discuss their properties. Several time-reversal invariant topological superconducting phases of the Zhang-Kane-Mele type are found and discussed. Addiotnally, we review one-dimensional MSH structures and show that parameters to realize topologically nontrivial magnetic chains embedded into a larger, two-dimensional substrate differ from the purely one-dimensional case. Quite generally we find that unconventional superconducting substrates work as well as the conventional s -wave substrates to realize topological phases. In particular, iron-based pnictide and chalcogenide superconductors are the most promising class of substrates for future high-temperature MSH systems.

36 MATERIALS SCIENCE↗

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.

Bayesian optimization↗

Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne

Abstract Stellar abundances for a large number of stars provide key information for the study of Galactic formation history. Large spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and LAMOST take median-to-low-resolution (R≲ 5000) spectra in the full optical wavelength range for millions of stars. However, the line-blending effect in these spectra causes great challenges for elemental abundance determination. Here we employDD-Payne, a data-driven method regularized by differential spectra from stellar physical models, to the DESI early data release spectra for stellar abundance determination. Our implementation delivers 15 labels, including effective temperatureT eff , surface gravity log g , microturbulence velocityv mic , and the abundances for 12 individual elements, namely C, N, O, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, and Ni. Given a spectral signal-to-noise ratio of 100 per pixel, the internal precisions of the label estimates are about 20 K forT eff , 0.05 dex for log g , and 0.05 dex for most elemental abundances. These results agree with the theoretical limits from the Crámer–Rao bound calculation within a factor of 2. The majority of the accreted halo stars contributed by the Gaia–Enceladus–Sausage are discernible from the disk and in situ halo populations in the resultant [Mg/Fe]–[Fe/H] and [Al/Fe]–[Fe/H] abundance spaces. We also provide distance and orbital parameters for the sample stars, which spread over a distance out to ∼100 kpc. The DESI sample has a significantly higher fraction of distant (or metal-poor) stars than the other existing spectroscopic surveys, making it a powerful data set for studying the Galactic outskirts. The catalog is publicly available.

Astronomy & Astrophysics↗

Coupled atmosphere/canopy model for remote sensing of plant reflectance features

Solar radiative transfer through a coupled system of atmosphere and plant canopy is modeled as a multiple-scattering problem through a layered medium of random scatterers. The radiative transfer equation is solved by the discrete-ordinates finite-element method. Analytic expressions are derived that allow the calculation of scattering and absorption cross sections for any plant canopy layer form measurable biophysical parameters such as the leaf area index, leaf angle distribution, and individual leaf reflectance and transmittance data. An expression for a canopy scattering phase function is also given. Computational results are in good agreement with spectral reflectance measurements directly above a soybean canopy, and the concept of greenness- and brightness-transforms of Landsat MSS data is reconfirmed with the computed results. A sensitivity analysis with the coupled atmosphere/canopy model quantifies how satellite-sensed spectral radiances are affected by increased atmospheric aerosols, by varying leaf area index, by anisotropic leaf scattering, and by non-Lambertian soil boundary conditions. Possible extensions to a 2-D model are also discussed.

Gerstl, S. A.↗

APOGEE Data and Spectral Analysis from SDSS Data Release 16: Seven Years of Observations Including First Results from APOGEE-South

The spectral analysis and data products in Data Release 16 (DR16; 2019 December) from the high-resolution near-infrared Apache Point Observatory Galactic Evolution Experiment (APOGEE)-2/Sloan Digital Sky Survey (SDSS)-IV survey are described. Compared to the previous APOGEE data release (DR14; 2017 July), APOGEE DR16 includes about 200,000 new stellar spectra, of which 100,000 are from a new southern APOGEE instrument mounted on the 2.5 m du Pont telescope at Las Campanas Observatory in Chile. DR16 includes all data taken up to 2018 August, including data released in previous data releases. All of the data have been re-reduced and re-analyzed using the latest pipelines, resulting in a total of 473,307 spectra of 437,445 stars. Changes to the analysis methods for this release include, but are not limited to, the use of MARCS model atmospheres for calculation of the entire main grid of synthetic spectra used in the analysis, a new method for filling “holes” in the grids due to unconverged model atmospheres, and a new scheme for continuum normalization. Abundances of the neutron-capture element Ce are included for the first time. A new scheme for estimating uncertainties of the derived quantities using stars with multiple observations has been applied, and calibrated values of surface gravities for dwarf stars are now supplied. Compared to DR14, the radial velocities derived for this release more closely match those in the Gaia DR2 database, and a clear improvement in the spectral analysis of the coolest giants can be seen. The reduced spectra as well as the result of the analysis can be downloaded using links provided on the SDSS DR16 web page.

79 ASTRONOMY AND ASTROPHYSICS↗

Excitation of a Parallel Plate Waveguide by an Array of Rectangular Waveguides

This work addresses the problem of excitation of a parallel plate waveguide by an array of rectangular waveguides that arises in applications such as the continuous transverse stub (CTS) antenna and dual-polarized parabolic cylindrical reflector antennas excited by a scanning line source. In order to design the junction region between the parallel plate waveguide and the linear array of rectangular waveguides, waveguide sizes have to be chosen so that the input match is adequate for the range of scan angles for both polarizations. Electromagnetic wave scattered by the junction of a parallel plate waveguide by an array of rectangular waveguides is analyzed by formulating coupled integral equations for the aperture electric field at the junction. The integral equations are solved by the method of moments. In order to make the computational process efficient and accurate, the method of weighted averaging was used to evaluate rapidly oscillating integrals encountered in the moment matrix. In addition, the real axis spectral integral is evaluated in a deformed contour for speed and accuracy. The MoM results for a large finite array have been validated by comparing its reflection coefficients with corresponding results for an infinite array generated by the commercial finite element code, HFSS. Once the aperture electric field is determined by MoM, the input reflection coefficients at each waveguide port, and coupling for each polarization over the range of useful scan angles, are easily obtained. Results for the input impedance and coupling characteristics for both the vertical and horizontal polarizations are presented over a range of scan angles. It is shown that the scan range is limited to about 35 for both polarizations and therefore the optimum waveguide is a square of size equal to about 0.62 free space wavelength.

Rengarajan, Sembiam↗

System and method for curved light sheet projection during two-photon polymerization

A laser-based manufacturing system is disclosed for fabricating non-planar three-dimensional layers. The system may have a laser for producing a laser beam with a plurality of optical wavelengths. An optically dispersive element may be used for receiving the laser beam and splitting the beam into a plurality of distinct beam components, wherein each beam component has spatially separated optical spectral components. A phase mask may be used which is configured to receive at least one of the beam components emerging from the dispersive element and to create a modified beam. One or more focusing elements may then be used to receive the modified beam emerging from the phase mask and to focus the modified beam into a non-planar light sheet for use in fabricating a part.

Saha, Sourabh Kumar↗

Abbreviated Technical Report: Experimentally Interrogating Detonation Chemistry on Sub-Nanosecond to Nanosecond Timescales

Direct experimental measurement of chemical reactions during high explosive detonation remains challenging. Theory and modeling have long preceded experiment in the fundamental physical and chemical kinetic properties of detonation, and experimentation at the relevant timescales are needed to both validate models and provide fundamental understanding of detonation. In this LDRD-ER project, two approaches, x-ray diffraction and core-level x-ray Raman, were developed and used to further experimental capabilities to address this gap. We further developed dynamic x-ray diffraction to directly detect nanodiamond formation during detonation, providing experimental data towards resolving longstanding controversy in the scientific literature, and although the full kinetics have not yet been fully mapped, diamond diffraction appears on the same timescales as detonation soot formation. In the second research thrust, we have developed core-level x-ray Raman for use with high explosives. This technique provides information analogous to x-ray absorption spectroscopy and electron energy loss spectroscopy, but uses inelastic scattering of hard x-rays that can interrogate chemistry around light elements much deeper into the material. The low cross section and requisite high solid angle collection have hindered its use for ultra-fast spectroscopy. We developed and tested a high-q spectrometer which will substantially increase cross section and signal-to-noise, showing this method will also not dramatically alter, compared to x-ray absorption, the most discriminating spectral features of C, N, and O from various high explosives and expected detonation products. We have also used x-ray Raman combined with OCEAN electronic structure calculations to explore dynamic photodegradation mechanisms in PETN and CL-20 explosives. This provides a pathway towards implementing capability to dynamically explore chemistry at an x-ray free electron laser.

36 MATERIALS SCIENCE↗

Time-dependent jet flow and noise computations

Methods for computing jet turbulence noise based on the time-dependent solution of Lighthill's (1952) differential equation are demonstrated. A key element in this approach is a flow code for solving the time-dependent Navier-Stokes equations at relatively high Reynolds numbers. Jet flow results at Re = 10,000 are presented here. This code combines a computationally efficient spectral element technique and a new self-consistent turbulence subgrid model to supply values for Lighthill's turbulence noise source tensor.

Berman, C. H.↗

Effective Field Theory of Random Quantum Circuits

Quantum circuits have been widely used as a platform to simulate generic quantum many-body systems. In particular, random quantum circuits provide a means to probe universal features of many-body quantum chaos and ergodicity. Some such features have already been experimentally demonstrated in noisy intermediate-scale quantum (NISQ) devices. On the theory side, properties of random quantum circuits have been studied on a case-by-case basis and for certain specific systems, and a hallmark of quantum chaos—universal Wigner–Dyson level statistics—has been derived. This work develops an effective field theory for a large class of random quantum circuits. The theory has the form of a replica sigma model and is similar to the low-energy approach to diffusion in disordered systems. The method is used to explicitly derive the universal random matrix behavior of a large family of random circuits. In particular, we rederive the Wigner–Dyson spectral statistics of the brickwork circuit model by Chan, De Luca, and Chalker [Phys. Rev. X 8, 041019 (2018)] and show within the same calculation that its various permutations and higher-dimensional generalizations preserve the universal level statistics. Finally, we use the replica sigma model framework to rederive the Weingarten calculus, which is a method of evaluating integrals of polynomials of matrix elements with respect to the Haar measure over compact groups and has many applications in the study of quantum circuits. The effective field theory derived here provides both a method to quantitatively characterize the quantum dynamics of random Floquet systems (e.g., calculating operator and entanglement spreading) and a path to understanding the general fundamental mechanism behind quantum chaos and thermalization in these systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Methodology of remote sensing data interpretation and geological applications

Elements of photointerpretation discussed include the analysis of photographic texture and structure as well as film tonality. The method used is based on conventional techniques developed for interpreting aerial black and white photographs. By defining the properties which characterize the form and individuality of dual images, homologous zones can be identified. Guy's logic method (1966) was adapted and used on functions of resolution, scale, and spectral characteristics of remotely sensed products. Applications of LANDSAT imagery are discussed for regional geological mapping, mineral exploration, hydrogeology, and geotechnical engineering in Brazil.

Parada, N. D. J.↗

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗

Optimal 1D Ly α forest power spectrum estimation – I. DESI-lite spectra

ABSTRACT The 1D Ly α forest flux power spectrum P1D is sensitive to scales smaller than a typical galaxy survey, and hence ties to the intergalactic medium’s thermal state, suppression from neutrino masses, and new dark matter models. It has emerged as a competitive framework to study new physics, but also has come with various challenges and systematic errors in analysis. In this work, we revisit the optimal quadratic estimator for P1D, which is robust against the relevant problems such as pixel masking, time evolution within spectrum, and quasar continuum errors. We further improve the estimator by introducing a fiducial power spectrum, which enables us to extract more information by alleviating the discreteness of band powers. We meticulously apply our method to synthetic Dark Energy Spectroscopic Instrument (DESI) spectra and demonstrate how the estimator overcomes each challenge. We further apply an optimization scheme that approximates the Fisher matrix to three elements per row and reduces computation time by 60 per cent. We show that we can achieve per cent precision in P1D with 5-yr DESI data in the absence of systematics and provide forecasts for different spectral qualities.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA's Ground-Based Observing Campaigns of Rocket Bodies with the UKIRT and NASA ES-MCAT Telescopes

Rocket bodies comprise a class of human-made space debris that are at the same time essential for launching every spacecraft from the Earth, but are also a significant source of debris both as intact objects, as well as fragmented debris. Unspent fuel has been long theorized as a potential cause of catastrophic rocket body break-ups. Given typical orbital speeds range from approximately 2-3 kilometers per second at Geosynchronous Orbit (GEO) and up to 15 kilometers per second in low Earth orbit (LEO), collisions with uncatalogued and undetected debris can also cause catastrophic breakups. Understanding break-ups is a necessary step in preventing them, and one key step in that process is to correlate and characterize daughter fragments with their parent bodies. Two very different methods include (1) conducting photometric surveys to correlate an object's motion and orbital elements to the parent body, and (2) characterizing what materials comprise the target to determine whether those materials are consistent with the parent body or like objects. With this in mind, photometric data were taken shortly after the breakup of one rocket body for short-term orbital studies, and a suite of spectral data were taken of rocket bodies that are fully intact to compare with debris, for characterization studies. Targets included Titan Transtage, Briz-M, and Ariane rocket bodies and debris. Spectra of each sub-class of rocket body were very similar within their rocket body type, but differed distinctly from one type to the next, supporting the effectiveness of this approach.

Lederer, Susan M.↗

Images and Spectral Performance of WFC3 Interference Filters

The Wide Field Camera 3 (WFC3) is a panchromatic imager that will be deployed in the Hubble Space Telescope (HST). The mission of the WFC3 is to enhance HST1s imaging capability in the ultraviolet, visible and near-infrared spectral regions. Together with a wavelength coverage spanning 2000A to 1.7 micron, the WFC3 high sensitivity, high spatial resolution, and large field-of-view provide the astronomer with an unprecedented set of tools for exploring all types of exciting astrophysical terrain and for addressing many key questions in astronomy today. The filter compliment, which includes broad, medium, and narrow band filters, naturally reflects the diversity of astronomical programs to be targeted with WFC3. The WFC3 holds 61 UVIS filters elements, 14 IR filters, and 3 dispersive elements. During ground testing, the majority of the UVIS filters were found to exhibit excellent performance consistent with or exceeding expectations; however, a subset of filters showed considerable ghost images; some with relative intensity as high as 10-15%. Replacement filters with band-defining coatings that substantially reduce these ghost images were designed and procured. A state-of-the-art characterization setup was developed to measured the intensity of ghost images, focal shift, wedge direction , transmitted uniformity and surface feature of filters that could effect uniform flat field images. We will report on this new filter characterization methods, as well as the spectral performance measurements of the in-band transmittance and blocking.

Quijada, Manuel A.↗