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NASA NTRS1987

Velocimetry with refractive index matching for complex flow configurations, phase 1

The feasibility of obtaining detailed velocity field measurements in large Reynolds number flow of the Space Shuttle Main Engine (SSME) main injector bowl was demonstrated using laser velocimetry and the developed refractive-index-matching technique. An experimental system to provide appropriate flow rates and temperature control of refractive-index-matching fluid was designed and tested. Test results are presented to establish the feasibility of obtaining accurate velocity measurements that map the entire field including the flow through the LOX post bundles: sample mean velocity, turbulence intensity, and spectral results are presented. The results indicate that a suitable fluid and control system is feasible for the representation of complex rocket-engine configurations and that measurements of velocity characteristics can be obtained without the optical access restrictions normally associated with laser velocimetry. The refractive-index-matching technique considered needs to be further developed and extended to represent other rocket-engine flows where current methods either cannot measure with adequate accuracy or they fail.

Thompson, B. E.↗

NASA NTRS1993

Deriving the intermediate spectra and photocycle kinetics from time-resolved difference spectra of bacteriorhodopsin. The simpler case of the recombinant D96N protein

The bacteriorhodopsin photocycle contains more than five spectrally distinct intermediates, and the complexity of their interconversions has precluded a rigorous solution of the kinetics. A representation of the photocycle of mutated D96N bacteriorhodopsin near neutral pH was given earlier (Varo, G., and J. K. Lanyi. 1991. Biochemistry. 30:5008-5015) as BRhv-->K<==>L<==>M1-->M2--> BR. Here we have reduced a set of time-resolved difference spectra for this simpler system to three base spectra, each assumed to consist of an unknown mixture of the pure K, L, and M difference spectra represented by a 3 x 3 matrix of concentration values between 0 and 1. After generating all allowed sets of spectra for K, L, and M (i.e., M1 + M2) at a 1:50 resolution of the matrix elements, invalid solutions were eliminated progressively in a search based on what is expected, empirically and from the theory of polyene excited states, for rhodopsin spectra. Significantly, the average matrix values changed little after the first and simplest of the search criteria that disallowed negative absorptions and more than one maximum for the M intermediate. We conclude from the statistics that during the search the solutions strongly converged into a narrow region of the multidimensional space of the concentration matrix. The data at three temperatures between 5 and 25 degrees C yielded a single set of spectra for K, L, and M; their fits are consistent with the earlier derived photocycle model for the D96N protein.

NASA Program Exobiology↗

DOE OSTI2026

Identifying Anomalous DESI Galaxy Spectra with a Variational Autoencoder

The tens of millions of spectra being captured by the Dark Energy Spectroscopic Instrument (DESI) provide tremendous discovery potential. In this work we show how Machine Learning, in particular Variational Autoencoders (VAE), can detect anomalies in a sample of approximately 200,000 DESI spectra comprising galaxies, quasars and stars. We demonstrate that the VAE can compress the dimensionality of a spectrum by a factor of 100, while still retaining enough information to accurately reconstruct spectral features. We then detect anomalous spectra as those with high reconstruction error and those which are isolated in the VAE latent representation. The anomalies identified fall into two categories: spectra with artefacts and spectra with unique physical features. Awareness of the former can help to improve the DESI spectroscopic pipeline; whilst the latter can lead to the identification of new and unusual objects. To further curate the list of outliers, we use the Astronomaly package which employs Active Learning to provide personalised outlier recommendations for visual inspection. In this work we also explore the VAE latent space, finding that different object classes and subclasses are separated despite being unlabelled. We demonstrate the interpretability of this latent space by identifying tracks within it that correspond to various spectral characteristics. For example, we find tracks that correspond to increasing star formation and increase in broad emission lines along the Balmer series. In upcoming work we hope to apply the methods presented here to search for both systematics and astrophysically interesting objects in much larger datasets of DESI spectra.

Nicolaou, C. [University Coll. London] (ORCID:0000↗

NASA NTRS2007

Sensing Super-Position: Human Sensing Beyond the Visual Spectrum

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This paper addresses the technical feasibility of augmenting human vision through Sensing Super-position by mixing natural Human sensing. The current implementation of the device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of Lie human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system. The human brain is superior to most existing computer systems in rapidly extracting relevant information from blurred, noisy, and redundant images. From a theoretical viewpoint, this means that the available bandwidth is not exploited in an optimal way. While image-processing techniques can manipulate, condense and focus the information (e.g., Fourier Transforms), keeping the mapping as direct and simple as possible might also reduce the risk of accidentally filtering out important clues. After all, especially a perfect non-redundant sound representation is prone to loss of relevant information in the non-perfect human hearing system. Also, a complicated non-redundant image-to-sound mapping may well be far more difficult to learn and comprehend than a straightforward mapping, while the mapping system would increase in complexity and cost. This work will demonstrate some basic information processing for optimal information capture for headmounted systems.

Maluf, David A.↗

DOE OSTI2025

Spectral Constraints on Theories of Colored Particles and Gravity

In this Letter, we consider effective field theories for light fields transforming under the fundamental or adjoint representation of a continuous group. Assuming tree-level completions, we demonstrate that, in the presence of gravity, crossing symmetry combined with twice-subtracted sum rules leads to constraints on the irreducible representations that the ultraviolet degrees of freedom must populate. A spectrum is allowed only if its low energy projection contains the graviton pole. Beautifully, the graviton pole is the anchor of our argument, not an obstruction.

Effective field theory↗

NASA NTRS1975

A technique for constructing spectral reflectance curves from Viking lander camera multispectral data

A technique for evaluating the construction of spectral reflectance curves from multispectral data obtained with the Viking lander cameras is presented. The multispectral data is limited to 6 channels in the wave-length range 0.4 to 1.1 microns, and several of the channels suffer from appreciable out-of-band response. The technique represents the estimated reflectance curves as a linear combination of known basic functions with coefficients determined to minimize the error in the representation, and it permits all channels, with and without out-of-band response, to contribute equally valid information. The technique is evaluated for known spectral reflectance curves of 8 materials felt likely to be present on the Martian surface. The technique provides an essentially exact fit if the the reflectance curve has no pronounced maxima and minima. Even if the curve has pronounced maxima and minima, the fit is good and reveals the most dominant features. Since only 6 samples are available some short period features are lost. This loss is almost certainly due to undersampling rather than out-of-band channel response.

Park, S. K.↗

NASA NTRS2014

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Fusion↗

NASA NTRS1994

A fast numerical solution of scattering by a cylinder: Spectral method for the boundary integral equations

It is known that the exact analytic solutions of wave scattering by a circular cylinder, when they exist, are not in a closed form but in infinite series which converges slowly for high frequency waves. In this paper, we present a fast number solution for the scattering problem in which the boundary integral equations, reformulated from the Helmholtz equation, are solved using a Fourier spectral method. It is shown that the special geometry considered here allows the implementation of the spectral method to be simple and very efficient. The present method differs from previous approaches in that the singularities of the integral kernels are removed and dealt with accurately. The proposed method preserves the spectral accuracy and is shown to have an exponential rate of convergence. Aspects of efficient implementation using FFT are discussed. Moreover, the boundary integral equations of combined single and double-layer representation are used in the present paper. This ensures the uniqueness of the numerical solution for the scattering problem at all frequencies. Although a strongly singular kernel is encountered for the Neumann boundary conditions, we show that the hypersingularity can be handled easily in the spectral method. Numerical examples that demonstrate the validity of the method are also presented.

Hu, Fang Q.↗

DOE OSTI2026

Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy

Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral data sets. Dual-VAE embeds local structures and spectroscopic responses into a shared latent manifold that serves as a structure–property relationship map. We applied this framework for the investigation of halide perovskite films by using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress the charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.

atomic force microscopy↗

DOE OSTI2021

Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis

Local Fourier analysis is a useful tool for predicting and analyzing the performance of many efficient algorithms for the solution of discretized PDEs, such as multigrid and domain decomposition methods. The crucial aspect of local Fourier analysis is that it can be used to minimize an estimate of the spectral radius of a stationary iteration, or the condition number of a preconditioned system, in terms of a symbol representation of the algorithm. In practice, this is a “minimax” problem, minimizing with respect to solver parameters the appropriate measure of work, which involves maximizing over the Fourier frequency. Often, several algorithmic parameters may be determined by local Fourier analysis in order to obtain efficient algorithms. Analytical solutions to minimax problems are rarely possible beyond simple problems; the status quo in local Fourier analysis involves grid sampling, which is prohibitively expensive in high dimensions. In this paper, we propose and explore optimization algorithms to solve these problems efficiently. Finally, several examples, with known and unknown analytical solutions, are presented to show the effectiveness of these approaches.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1988

Structural analysis and design of multivariable control systems: An algebraic approach

The application of algebraic system theory to the design of controllers for multivariable (MV) systems is explored analytically using an approach based on state-space representations and matrix-fraction descriptions. Chapters are devoted to characteristic lambda matrices and canonical descriptions of MIMO systems; spectral analysis, divisors, and spectral factors of nonsingular lambda matrices; feedback control of MV systems; and structural decomposition theories and their application to MV control systems.

Tsay, Yih Tsong↗

NASA NTRS1989

Measuring and modeling spectral characteristics of a tallgrass prairie

This study was conducted to evaluate the diurnal and seasonal, spectral reflectance characteristics of burned and unburned areas of a tallgrass prairie, based on field measurements and models of radiation transport in plant canopies. Burning of the senescent vegetation, resulting from the previous years' growth, is a common management practice, which results in improved productivity and affects the succession of grass species. The burned and unburned grass canopies showed distinctly different, diurnal and seasonal, spectral reflectance characteristics in the visible and infrared regions of the spectrum. These were attributed to the differences in development of the two plant canopies and the azimuthal differences in sensor-sun-canopy positions during field measurements of spectral reflectance. The radiation transfer model properly simulated the diurnal spectral behavior of the two canopies. The simulated, seasonal, spectral reflectance values for the unburned grass canopy were greater than the measured ones, because of limitations in proper representation of the layer of senescent vegetation in the model.

Asrar, G.↗

NASA NTRS2010

Improving a Spectral Bin Microphysical Scheme Using TRMM Satellite Observations

Comparisons between cloud model simulations and observations are crucial in validating model performance and improving physical processes represented in the mod Tel.hese modeled physical processes are idealized representations and almost always have large rooms for improvements. In this study, we use data from two different sensors onboard TRMM (Tropical Rainfall Measurement Mission) satellite to improve the microphysical scheme in the Goddard Cumulus Ensemble (GCE) model. TRMM observed mature-stage squall lines during late spring, early summer in central US over a 9-year period are compiled and compared with a case simulation by GCE model. A unique aspect of the GCE model is that it has a state-of-the-art spectral bin microphysical scheme, which uses 33 different bins to represent particle size distribution of each of the seven hydrometeor species. A forward radiative transfer model calculates TRMM Precipitation Radar (PR) reflectivity and TRMM Microwave Imager (TMI) 85 GHz brightness temperatures from simulated particle size distributions. Comparisons between model outputs and observations reveal that the model overestimates sizes of snow/aggregates in the stratiform region of the squall line. After adjusting temperature-dependent collection coefficients among ice-phase particles, PR comparisons become good while TMI comparisons worsen. Further investigations show that the partitioning between graupel (a high-density form of aggregate), and snow (a low-density form of aggregate) needs to be adjusted in order to have good comparisons in both PR reflectivity and TMI brightness temperature. This study shows that long-term satellite observations, especially those with multiple sensors, can be very useful in constraining model microphysics. It is also the first study in validating and improving a sophisticated spectral bin microphysical scheme according to long-term satellite observations.

Li, Xiaowen↗

NASA NTRS2013

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

spectral mixing analysis↗

DOE OSTI2020

Equation of motion coupled-cluster cumulant approach for intrinsic losses in x-ray spectra

We present an equation of motion coupled cluster approach for calculating and understanding intrinsic inelastic losses in core level x-ray absorption spectra (XAS). The method is based on a factorization of the transition amplitude in the time-domain, which leads to a convolution of an effective one-body spectrum and the core-hole spectral function. The spectral function characterizes these losses in terms of shake-up excitations and satellites, and is calculated using a cumulant representation of the core-hole Green’s function that includes non-linear corrections. The one-body spectrum also includes orthogonality corrections that enhance the XAS at the edge.

Rehr, John J.↗

NASA NTRS1977

Hard X-ray spectra of cosmic gamma-ray bursts

Hard X-ray measurements of six gamma-ray bursts observed during the period from October 1969 to April 1971 are presented. The measurements were made with detectors on the OGO-5 and OSO-6 satellites. Spectra for five of the six bursts have been determined using measurements from both satellites in order to reduce ambiguities due to uncertain source locations. A significant fraction, about 20-60%, of the energy of the bursts falls in the hard X-ray range (20-130 keV). The time-integrated spectra have been fitted by power-law, exponential, and thermal-bremsstrahlung functions. They are consistent with power laws which steepen at energies of at least 150 keV, as reported earlier for two other bursts. Evidence for spectral variability from event to event in the hard X-ray region is presented. For a power-law representation, the power-law index has values ranging from approximately unity to 2.5. The hard X-ray spectra of the gamma-ray bursts differ significantly from those of the recently discovered 1-15-keV X-ray bursts.

Kane, S. R.↗

NASA NTRS1992

Ultraviolet observations of the gas phase abundances in the diffuse clouds toward Zeta Ophiuchi at 3.5 kilometers per second resolution

Goddard High Resolution Spectrograph echelle mode measurements at 3.5 km/s resolution are presented for interstellar absorption produced by C II, O I, Mg I, Mg II, Al III, P II, Cr II, Mn II, Fe II, Ni II, Cu II, Zn II, Ga II, Ge II, and Kr I. The absorption line measurements are converted into representations of apparent column density per unit velocity in order to study the multicomponent nature of the absorption. The high spectral resolution of the measurements allows a comparative study of gas phase abundances for many species in the absorbing clouds near -27 and -15 km/s with a typical precision of about 0.05 dex. The matter absorbing near -27 km/s is situated in the local interstellar medium and has log N(H I) of about 19.74. This absorption provides information about the modest 'base' depletion associated with the lower density interstellar medium. The depletion results suggest that accretion processes are operating interstellar clouds that exhibit similar depletion efficiencies for some elements but much higher depletion efficiencies for others.

Savage, Blair D.↗

NASA NTRS2006

Sensing Super-position: Visual Instrument Sensor Replacement

Maluf, David A.↗