MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSEs) retrievals of Ozone and Carbon Monoxide during 2019 FIREX-AQ
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Malina, Edward↗
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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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MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records
Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.
Fu, Dejian↗
An Oveview of TROPESS Data Products and Services at the NASA GES DISC
The TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) project generates Earth System Data Records (ESDRs) of ozone, and other atmospheric constituents (CH4,CO, H2O, HDO, NH3, PAN and temperature) by processing data from multiple satellites through a common retrieval algorithm and ground data system. Satellite Level-1B input data used in generating the TROPESS L2 data products include CrIS NOAA-20 (JPSS-1), CrIS SNPP, AIRS Aqua, OMI Aura, and TROPOMI S5P. The common retrieval framework is known as the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) science data processing system (MUSES-SDPS). Several of the TROPESS data products are now available from the NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) for users to download. In this presentation we provide an overview of the various TROPESS data products. These data products can be divided into the following Forward Stream types: Standard Products, Summary Products, and Full-Archival Products. Standard Products are for users that are doing full analysis with avenging kernel and covariance corresponding to retrieved vertical profiles. Summary products have a smaller file size and are more convenient for first-look and rapid analysis, include total and partial columns, as well as column averaging kernels. The Full-Archival Products will contain all information used in creating the data. TROPESS also creates Special Products, provided on an as-needed and as-available basis to support NASA field missions and individual-investigator requests over specific regions. Eventually, TROPESS will also produce and deliver a set of Reanalysis Stream products. Data at the GES DISC are being transitioned into the "Cloud". This will allow users with "Cloud” access to perform data analysis directly on the data without downloading the data to their system. Services, such as subsetting and data visualization, will also be provided for TROPESS data products at the GES DISC.
James Johnson↗
Differentiating multi-MeV, multi-ion spectra with CR-39 solid-state nuclear track detectors
The development of high intensity petawatt lasers has created new possibilities for ion acceleration and nuclear fusion using solid targets. In such laser-matter interaction, multiple ion species are accelerated with broad spectra up to hundreds of MeV. To measure ion yields and for species identification, CR-39 solid-state nuclear track detectors are frequently used. However, these detectors are limited in their applicability for multi-ion spectra differentiation as standard image recognition algorithms can lead to a misinterpretation of data, there is no unique relation between track diameter and particle energy, and there are overlapping pit diameter relationships for multiple particle species. In this report, we address these issues by first developing an algorithm to overcome user bias during image processing. Second, we use calibration of the detector response for protons, carbon and helium ions (alpha particles) from 0.1 to above 10 MeV and measurements of statistical energy loss fluctuations in a forward-fitting procedure utilizing multiple, differently filtered CR-39, altogether enabling high-sensitivity, multi-species particle spectroscopy. To validate this capability, we show that inferred CR-39 spectra match Thomson parabola ion spectrometer data from the same experiment. Filtered CR-39 spectrometers were used to detect, within a background of ~ 2 × 10 11 sr -1 J -1 protons and carbons, (1.3 ± 0.7) × 10 8 sr -1 J -1 alpha particles from laser-driven proton-boron fusion reactions.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Resolving the High‐Latitude Ionospheric Irregularity Spectra Using Multi‐Point Incoherent Scatter Radar Measurements
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L. V. Goodwin↗
Detection of multi-modal Doppler spectra – Part 1: Establishing characteristic signals in radar moment data
Vertically pointing millimeter-wavelength radars provide a wealth of information about cloud and precipitation particle properties. Doppler spectral data can inform on how particles of varying vertical velocities contribute to the total backscattered power observed. It is more computationally cost effective to process moment data instead of spectra data, but doing so leaves valuable information on the cutting room floor. To confidently identify a multi-modal spectra event, in which two or more modes are present within a layer, Doppler spectral data are essential. This means long-term identification of layers featuring multi-modal spectra can be cost prohibitive. To address this, we explore three multi-modal spectra cases from winter precipitation events to determine characteristic signatures of these layers in the moment data averaged over short time periods (∼ 145 s) and explore how these layers differ from the rest of the vertical profiles. We find that the mean spectrum width and the standard deviation of mean Doppler velocity can be used to determine whether or not a layer is multi-modal. In particular, multi-modal layers in mixed-phase and ice clouds feature larger mean spectrum width (exceeding 0.17 m s −1 ) and smaller standard deviation of the mean Doppler velocity (below 0.1 m s −1 ). In Part 1 of this study, the identification criteria and methods are described. In Part 2 (Wugofski and Kumjian, 2025), we perform a verification of the method for three years of vertically pointing radar data, and explore the meteorological conditions associated with identified multi-modal spectral events.
Wugofski, Sarah [Pennsylvania State Univ., Univers↗
Learning physics at future $e^–e^+$ colliders with machine
Information deformation and loss in jet clustering are one of the major limitations for precisely measuring hadronic events at future $e^–e^+$ colliders. Because of their dominance in data, the measurements of such events are crucial for advancing the precision frontier of Higgs and electroweak physics in the next decades. We show that this difficulty can be well-addressed by synergizing the event-level information into the data analysis, with the techniques of deep neutral network. In relation to this, we introduce a CMB-like observable scheme, where the event-level kinematics is encoded as Fox-Wolfram (FW) moments at leading order and multi-spectra of spherical harmonics at higher orders. Then we develop a series of jet-level (w/ and w/o the FW moments) and event-level classifiers, and analyze their sensitivity performance comparatively with two-jet and four-jet events. As an application, we analyze measuring Higgs decay width at $e^–e^+$ colliders with the data of 5ab –1 @240GeV. The precision obtained is significantly better than the baseline ones presented in documents. We expect this strategy to be applied to many other hadronic- event measurements at future $e^–e^+$ colliders, and to open a new angle for evaluating their physics capability.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Second Linear Response Theory and the Analytic Calculation of Excited-State Properties
We present a method based on second linear response time-dependent density func- tional theory (TDDFT) to calculate permanent and transition multipoles of excited states, which are required to compute excited-state absorption/emission spectra, multi- photon optical processes, among others. In previous work, we examined computations based on second linear response theory in which linear response TDDFT was employed twice. In contrast, the present methodology only requires information from a single linear response calculation to compute the excited-state properties. These are eval- uated analytically through various algebraic operations involving electron repulsion integrals and excitation vectors. The present derivation focuses on full many-body wave functions instead of single orbitals, as in our previous approach. Here, we test the proposed method by applying it to several diatomic and triatomic molecules. This shows that the computed excited-state dipoles are consistent with respect to reference equation-of-motion coupled cluster calculations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Probabilistic Deep Learning Approach to Automate the Interpretation of Multi-phase Diffraction Spectra
Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase mixtures. At the core of this algorithm lies an ensemble convolutional neural network trained on simulated diffraction spectra, which are systematically augmented with physics-informed perturbations to account for artifacts that can arise during experimental sample preparation and synthesis. In this work, larger perturbations associated with off-stoichiometry are also captured by supplementing the training set with hypothetical solid solutions. Spectra containing mixtures of materials are analyzed with a newly developed branching algorithm that utilizes the probabilistic nature of the neural network to explore suspected mixtures and identify the set of phases that maximize confidence in the prediction. Our model is benchmarked on simulated and experimentally measured diffraction spectra, showing exceptional performance with accuracies exceeding those given by previously reported methods based on profile matching and deep learning. We envision that the algorithm presented here may be integrated in experimental workflows to facilitate the high-throughput and autonomous discovery of inorganic materials.
36 MATERIALS SCIENCE↗
Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems
Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Typical Neutron Emission Spectra for Multi-Mission Radioisotope Thermoelectric Generator Fuel
The Dragonfly rotorcraft currently being designed by the Johns Hopkins Applied Physics Laboratory (APL) is a mission destined to explore, via autonomous flight, the Saturnian moon of Titan and currently scheduled to launch in 2027. This largest moon of Saturn contains a thick, dense atmosphere, that when coupled with the remote distance to the Sun, requires the use of a radioisotope power system (RPS). The multi-mission radioisotope thermoelectric generator (MMRTG) fueled at Idaho National Laboratory is currently the only flight-certified RPS still in production within the Department of Energy complex, thus, an MMRTG was chosen for the Dragonfly mission.
07 ISOTOPE AND RADIATION SOURCES↗
Power spectra of multi-h phase codes
A procedure is presented for calculating the power spectrum of the class of digital continuous-phase signals known as multi-h phase codes. These signals have been shown to have attractive power advantages over other uncoded digital schemes such as QPSK, and represent a bandwidth-efficient alternative to other coding techniques. The method is general, handling M-ary signaling, various frequency pulse shapes, and arbitrary sets of modulation indices. Numerical results are shown for several specific codes. In addition, the issue of spectral lines is resolved, and simple spectral approximations are developed.
Wilson, S. G.↗
Multi-scale roughness spectra of Mount St. Helens debris flows
A roughness spectrum allows surface structure to be interpreted as a sum of sinusoidal components with differing wavelengths. Knowledge of the roughness spectrum gives insight into the mechanisms responsible for electromagnetic scattering at a given wavelength. Measured spectra from 10-year-old primary debris flow surfaces at Mount St. Helens conform to a power-law spectral model, suggesting that these surfaces are scaling over the measured range of spatial frequencies. Measured spectra from water-deposited surfaces deviate from this model.
Austin, Richard T.↗
Multi-Epoch Multiwavelength Spectra and Models for Blazar 3C 279
Of the blazars detected by EGRET in GeV gamma-rays, 3C 279 is not only the best-observed by EGRET, but also one of the best-monitored at lower frequencies. We have assembled eleven spectra, from GHz radio through GeV gamma-rays, from the time intervals of EGRET observations. Although some of the data have appeared in previous publications, most are new, including data taken during the high states in early 1999 and early 2000. All of the spectra show substantial gamma-ray contribution to the total luminosity of the object; in a high state, the gamma-ray luminosity dominates over that at all other frequencies by a factor of more than 10. There is no clear pattern of time correlation; different bands do not always rise and fall together, even in the optical, X-ray, and gamma-ray bands. The spectra are modeled using a leptonic jet, with combined synchrotron self-Compton + external Compton gamma-ray production. Spectral variability of 3C 279 is consistent with variations of the bulk Lorentz factor of the jet, accompanied by changes in the spectral shape of the electron distribution. Our modeling results are consistent with the UV spectrum of 3C 279 being dominated by accretion disk radiation during times of low gamma-ray intensity.
Hartman, R. C.↗
Spectral variability of a sample of extreme variability quasars and implications for the MgII broad-line region
We present new Gemini/GMOS optical spectroscopy of 16 extreme variability quasars (EVQs) that dimmed bymore than 1.5mag in the g band between the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey epochs (separated by a few years in the quasar rest frame). These EVQs are selected from quasars in the SDSS Stripe 82 region, covering a redshift range of 0.5 < z < 2.1. Nearly half of these EVQs brightened significantly (by more than 0.5 mag in the g band) in a few years after reaching their previous faintest state, and some EVQs showed rapid (non-blazar) variations of greater than 1-2 mag on time-scales of only months. To increase sample statistics, we use a supplemental sample of 33 EVQs with multi-epoch spectra from SDSS that cover the broad Mg II lambda 2798 line. Leveraging on the large dynamic range in continuum variability between the multi-epoch spectra, we explore the associated variations in the broad MgII line, whose variability properties have not been well studied before. The broad MgII flux varies in the same direction as the continuum flux, albeit with a smaller amplitude, which indicates at least some portion of Mg II is reverberating to continuum changes. However, the full width at half-maximum (FWHM) of Mg II does not vary accordingly as continuum changes for most objects in the sample, in contrast to the case of the broad Balmer lines. Using the width of broad MgII to estimate the black hole mass with single epoch spectra therefore introduces a luminosity-dependent bias.
79 ASTRONOMY AND ASTROPHYSICS↗
Selective control of conductance modes in multi-terminal Josephson junctions
The Andreev bound state spectra of multi-terminal Josephson junctions form an artificial band structure, which is predicted to host tunable topological phases under certain conditions. However, the number of conductance modes between the terminals of a multi-terminal Josephson junction must be few in order for this spectrum to be experimentally accessible. In this work, we employ a quantum point contact geometry in three-terminal Josephson devices to demonstrate independent control of conductance modes between each pair of terminals and access to the single-mode regime coexistent with the presence of superconducting coupling. These results establish a full platform on which to realize tunable Andreev bound state spectra in multi-terminal Josephson junctions.
36 MATERIALS SCIENCE↗
Preliminary comparison of material charging properties using single-energy and multienergy electron beams
Results of tests designed to compare the charging properties of spacecraft material under a monoenergetic beam and under a continuously distributed beam are summarized. In the test setup the electron source was mounted in the top of a cylindrical vacuum chamber. A sheet of 5-mil-thick Kapton was placed on an insulated metal substrate at the bottom of the vacuum chamber. The dc current arriving on the substrate was measured and a field meter measured the potential of the test sample. A retarding potential analyzer measured the energy spectrum of the incident electron beam. With the monoenergetic beam, the sample charged to 12 kV and electrical discharges occurred. With the multi-energy spectra the samples charged to only 6 kV and 4 kV, and no discharger were observed. In these experiments, no effort was made to duplicate the spectra occurring in space. The tests were intended to simply to compare spacecraft material charging properties using monoenergetic and continuous multi-energy beams.
Adamo, R. C.↗
The Atacama Cosmology Telescope: Likelihood for Small-Scale CMB Data
The Atacama Cosmology Telescope has measured the angular power spectra of microwave fluctuations to arcminute scales at frequencies of 148 and 218 GHz, from three seasons of data. At small scales the fluctuations in the primordial Cosmic Microwave Background (CMB) become increasingly obscured by extragalactic foregounds and secondary CMB signals. We present results from a nine-parameter model describing these secondary effects, including the thermal and kinematic Sunyaev-Zel'dovich (tSZ and kSZ) power; the clustered and Poisson-like power from Cosmic Infrared Background (CIB) sources, and their frequency scaling; the tSZ-CIB correlation coefficient; the extragalactic radio source power; and thermal dust emission from Galactic cirrus in two different regions of the sky. In order to extract cosmological parameters, we describe a likelihood function for the ACT data, fitting this model to the multi-frequency spectra in the multipole range 500 < l < 10000. We extend the likelihood to include spectra from the South Pole Telescope at frequencies of 95, 150, and 220 GHz. Accounting for different radio source levels and Galactic cirrus emission, the same model provides an excellent fit to both datasets simultaneously, with χ2/dof= 675/697 for ACT, and 96/107 for SPT. We then use the multi-frequency likelihood to estimate the CMB power spectrum from ACT in bandpowers, marginalizing over the secondary parameters. This provides a simplified 'CMB-only' likelihood in the range 500 < l < 3500 for use in cosmological parameter estimation
Cosmology↗