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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modification of conventional peak shapes to accurately represent spectral asymmetry: High-Resolution X-ray photoelectron spectra of [C 4 C 1 Pyrr][NTf 2 ] and [C 8 C 1 Im][NTf 2 ] ionic liquids

X-ray photoelectron spectroscopy (XPS) is one of the most widely used techniques for surface characterization. Analysis of XPS data is challenging and requires the analyst to fit the data with synthetic line shapes to reach physically meaningful interpretations. Experimental spectral envelopes, however, are complex and display asymmetric features that are often ignored or attributed to additional chemical components. The high-resolution XPS spectra of [C 4 C 1 Pyrr][NTf 2 ] and [C 8 C 1 Im][NTf 2 ] all exhibit a degree of asymmetry which is systematically observed at the higher binding energy side of photoemission envelopes. Here, we present the development of a refined fitting procedure for XPS spectra of these ionic liquid-based systems which include (a) Shirley background offset necessary to account for the insulator-like region and (b) spectral asymmetry in C 1s and N 1s regions. Further, Shirley and trapezoid components are applied to compensate for inelastic scattering taking place during electron transitions as high as 7.8 eV above the start of the fitting region in C 1s high-resolution spectrum. To demonstrate the fitness of this model, we present an analysis of a 2:1 mixture of [C 4 C 1 Pyrr][NTf 2 ]: [C 8 C 1 Im][NTf 2 ].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

ZTF SN Ia DR2: Improved SN Ia colors through expanded dimensionality with SALT3+

Context. Type Ia supernovae (SNe Ia) are a key probe in modern cosmology, as they can be used to measure luminosity distances at gigaparsec scales. Models of their light curves are used to project heterogeneous observed data onto a common basis for analysis. Aims. The SALT model currently used for SN Ia cosmology describes SNe as having two sources of variability, accounted for by a color parameter c , and a “stretch” parameter x 1 . We extend the model to include an additional parameter we label x 2 , to investigate the cosmological impact of currently unaddressed light-curve variability. Methods. We constructed a new SALT model, that we dub “SALT3+”. This model was trained by an improved version of the SALTshaker code, using training data combining a selection of the second data release of cosmological SNe Ia from the Zwicky Transient Facility and the existing SALT3 training compilation. Results. We find additional, coherent variability in supernova light curves beyond SALT3. Most of this variation can be described as phase-dependent variation in g − r and r − i color curves, correlated with a boost in the height of the secondary maximum in i -band. These behaviors correlate with spectral differences, particularly in line velocity. We find that fits with the existing SALT3 model tend to address this excess variation with the color parameter, leading to less informative measurements of supernova color. We find that neglecting the new parameter in light-curve fits leads to a trend in Hubble residuals with x 2 of 0.039 ± 0.005 mag, representing a potential systematic uncertainty. However, we find no evidence of a bias in current cosmological measurements. Conclusions. We conclude that extended SN Ia light-curve models promise mild improvement in the accuracy of color measurements, and corresponding cosmological precision. However, models with more parameters are unlikely to substantially affect current cosmological results.

Kenworthy, W. D. (ORCID:0000000251535983)↗
DOE OSTI2025

Insights into Slip-Rate Time Functions, Rupture Parameter Correlations, and Ground Motions from Validated Multicycle Earthquake Ruptures

Earthquake strong-motion predictions using kinematic source modeling require knowledge of the slip-rate functions (SRFs) along the rupture and their distinct characteristics in asperities, background (off-asperity) areas and near the surface. Here, in this study we analyzed SRFs from well-validated, self-consistent, and fully dynamic rupture models from earthquake cycles obeying a rate-and-state friction law, from our companion study (Galvez et al., 2021). The shapes of SRFs in asperities are well described by the regularized Yoffe function (RYF), which has only two parameters: rise time T r and smoothing time T s , which control the generation of long- and short-period ground motions, respectively. In background areas, we demonstrate that, in addition to the primary rupture, multiple secondary ruptures may also nucleate from rupture heterogeneities related to asperities, resulting in SRFs with multiple peaks. Because it is impossible to fit a multiple-peak SRF by the single-peak RYF, we describe SRFs in background areas in an effective way by fitting their amplitude spectra with the RYF spectra. Such spectrally effective RYFs capture salient aspects of seismic-wave generation and can be used in rupture generators for strong motion prediction. We found that small T s values correlate with small characteristic weakening distances, large peak slip rates (PSRs), and large rupture velocities. T r values are larger in background areas and smaller in asperities. Within the shallow aseismic zone, T s values approximately quadruple whereas T r values approximately double. Because of this dominant T s increase, PSR values decrease in the near-surface zone. These features indicate that the generation of strong motions by the near-surface portions of the rupture is negligible in the studied scenarios.

Geosciences↗
DOE OSTI2026

Passive Confirmation of the Presence Of High-Explosive Material Via Neutron Transmission Spectroscopy

The goal of this project was to explore a novel approach for identifying presence and potential types of high explosives (HE) in treaty-controlled items with passive neutron sources by using passive neutron transmission spectroscopy. We predominantly look to measure relative elemental abundance of Carbon, Hydrogen, Oxygen, and Nitrogen (CHON) since most relevant materials are certain mix of these elements, as shown in Table 1. Previously, most studies exploring potential identification of CHON elemental content of targets in the vicinity of passive neutron source were focused solely on gamma spectroscopy using high resolution gamma detectors. Using neutron transmission spectroscopy with pulse-shape discrimination (PSD) capable organic scintillators is not only a novel idea in of itself, but arguably necessary for accurate identification of the CHON elemental content of an interrogated target. While high resolution gamma spectroscopy in principle can determine a presence of hydrogen and nitrogen, it is effectively blind to a quantitatively measuring areal densities of C, O. The initially proposed approach, described in detail in the project proposal, was to leverage previous Monte Carlo study on neutron transmission spectroscopy using slab shaped target interrogated with well-collimated (“pencil”) neutron beam. In this study, a simulated test CO 2 target was interrogated by a pencil neutron beam and transmitted neutron spectra were measured using PSD capable organic scintillator using MLEM based unfolding technique. To establish relative elemental content of carbon and oxygen, the unfolded neutron spectrum was fit with a parametrized combination of their respective elemental spectral templates. The individual spectral template was calculated by convoluting ENDF neutron crosssection with the known resolution of the PSD detector used in the study. This approach in the studied configuration successfully quantitatively established relative elemental composition of carbon and oxygen.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Incremental Fermi Large Area Telescope Fourth Source Catalog

We present an incremental version (4FGL-DR3, for Data Release 3) of the fourth Fermi Large Area Telescope (LAT) catalog of γ-ray sources. Based on the first 12 years of science data in the energy range from 50 MeV to 1 TeV, it contains 6658 sources. The analysis improves on that used for the 4FGL catalog over eight years of data: more sources are fit with curved spectra, we introduce a more robust spectral parameterization for pulsars, and we extend the spectral points to 1 TeV. The spectral parameters, spectral energy distributions, and associations are updated for all sources. Light curves are rebuilt for all sources with 1 yr intervals (not 2 month intervals). Among the 5064 original 4FGL sources, 16 were deleted, 112 are formally below the detection threshold over 12 yr (but are kept in the list), while 74 are newly associated, 10 have an improved association, and seven associations were withdrawn. Pulsars are split explicitly between young and millisecond pulsars. Pulsars and binaries newly detected in LAT sources, as well as more than 100 newly classified blazars, are reported. We add three extended sources and 1607 new point sources, mostly just above the detection threshold, among which eight are considered identified, and 699 have a plausible counterpart at other wavelengths. We discuss the degree-scale residuals to the global sky model and clusters of soft unassociated point sources close to the Galactic plane, which are possibly related to limitations of the interstellar emission model and missing extended sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quasar Properties from the Sloan Digital Sky Survey. III. The Quasars Obtained by the SDSS-IV

This paper provides the compilations of properties of the quasars newly obtained by the Sloan Digital Sky Survey (SDSS) during the fourth stage (SDSS-IV). The catalog is available on the journal's website. We have measured the main properties of emission lines around C $\tiny{IV}$ Mg $\tiny{II}$, Hβ, and Hα spectral regions. We estimate the quasar redshifts from our fits of narrow [O $\tiny{III}$], broad Mg $\tiny{II}$, and broad C $\tiny{IV}$ emission lines and find that the best redshifts included in DR16Q are robust with respect to our measurements. Based on the broad C $\tiny{IV}$, Mg $\tiny{II}$, Hβ, and/or Hα emission lines, we calculate the virial black hole mass with empirical relationships provided by previous works. Systematic biases are found among the different line-based mass estimators.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Determination of the argon spectral function from ( e , e ' p ) data

The E12-14-012 experiment, performed in Jefferson Lab Hall A, has measured the $(e, e'p)$ cross section in parallel kinematics using a natural argon target. Here, we report the full results of the analysis of the data set corresponding to beam energy 2.222 GeV, and spanning the missing momentum and missing energy range $15 \lesssim p_m \lesssim 300$ MeV/c and $12 \lesssim E_m \lesssim 80$ MeV. The reduced cross section, determined as a function of $p_m$ and $E_m$ with $\approx$4\% accuracy, has been fitted using the results of Monte Carlo simulations involving a model spectral function and including the effects of final state interactions. The overall agreement between data and simulations turns out to be quite satisfactory ($\chi^2$/n.d.o.f.=1.9). Furthermore, the resulting spectral function will provide valuable new information, needed for the interpretation of neutrino interactions in liquid argon detectors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Diffuse X-ray scattering from polished silicon: application of the distorted wave Born approximation

Measured diffuse X-ray scattering data for a `smooth' as well as for a `rough' silicon sample were fit to theoretical expressions within the distorted wave Born approximation (DWBA). Data for the power spectral density (PSD) for both samples were also obtained by means of atomic force microscopy and optical interferometry. The Fourier transforms of trial correlation functions were fit to the PSD data and then applied to the DWBA formalism. The net correlation functions needed to fit the PSD data for each sample comprised the sum of two terms with different cutoff lengths and different self-affine fractal exponents. At zero distance these correlation functions added up to yield net values of σ 2 = (2) 2 and (71) 2 Å 2 for the smooth and rough samples, respectively. X-ray scattering data were obtained at beamline 1-BM of the Advanced Photon Source. Data and fits at values of q z = 0.05 and 0.10 Å −1 for the smooth sample are reported. Good fits for the smooth sample were obtained at both q z values simultaneously, that is, identical fitting parameters were applied at both values of q z . The smooth sample also exhibited weak Yoneda wings and a clear distinction between the strong specular scattering and the weak diffuse scattering. Data for the rough sample were qualitatively different and exhibited very weak scattering at the specular condition in contrast to extremely large Yoneda wings. Fits for the rough sample are reported for q z = 0.04, 0.05, and 0.06 Å −1 . Although the large Yoneda wings could be fit quite well in both position and amplitude, scattering near the specular condition could not be equally well fit by applying the same fitting parameters at all values of q z . Albeit imperfect, best-fitting results at the specular condition were obtained by invoking only diffuse scattering, that is, without including a separate theoretical expression for specular scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Real-time infrared spectroscopy coupled with blind source separation for nuclear waste process monitoring

On-line infrared absorbance spectroscopy enables rapid measurement of solution-phase molecular species. Many spectra-to-concentration models exist for spectral data, with some models able to handle overlapping spectral bands and nonlinearities. However, model accuracy is limited by the quality of training data used in model fitting. The process spectra of nuclear waste simulants at the Savannah River Site display incongruity between training and process spectra; the glycolate spectral signature in the training data does not match the glycolate signature in Savannah River National Laboratory process data. A novel blind source separation algorithm is proposed that preprocesses spectral data so that process spectra more closely resemble training spectra, thereby improving model quantification accuracy when unexpected sources of variation appear in process spectra. The novel blind source separation preprocessing algorithm is shown to improve nitrate quantification from an R 2 of 0.934 to 0.988 and from 0.267 to 0.978 in two instances analyzing nuclear waste simulants from the Slurry Receipt Adjustment Tank and Slurry Mix Evaporator cycle at the Savannah River Site.

Crouse, Steven H.↗
DOE OSTI2022

Improved galactic foreground removal for B-mode detection with clustering methods

ABSTRACT Characterizing the sub-mm Galactic emission has become increasingly critical especially in identifying and removing its polarized contribution from the one emitted by the cosmic microwave background (CMB). In this work, we present a parametric foreground removal performed on to sub-patches identified in the celestial sphere by means of spectral clustering. Our approach takes into account efficiently both the geometrical affinity and the similarity induced by the measurements and the accompanying errors. The optimal partition is then used to parametrically separate the Galactic emission encoding thermal dust and synchrotron from the CMB one applied on two nominal observations of forthcoming experiments from the ground and from the space. Moreover, the clustering is performed on tracers that are different from the data used for component separation, e.g. the spectral index maps of dust and synchrotron. Performing the parametric fit singularly on each of the clustering derived regions results in an overall improvement: both controlling the bias and the uncertainties in the CMB B-mode recovered maps. We finally apply this technique using the map of the number of clouds along the line of sight, $\mathcal {N}_c$, as estimated from H i emission data and perform parametric fitting on to patches derived by clustering on this map. We show that adopting the $\mathcal {N}_c$ map as a tracer for the patches related to the thermal dust emission, results in reducing the B-mode residuals post-component separation. The code is made publicly available https://github.com/giuspugl/fgcluster.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Global X-Ray Properties of the Vela and Puppis A Supernova Remnants

The Vela and Puppis A supernova remnants (SNRs) comprise a large emission region of ∼8° diameter in the soft X-ray sky. The HaloSat CubeSat mission provides the first soft X-ray (0.4–7 keV) observation of the entire Vela SNR and Puppis A SNR region with a single pointing and moderate spectral resolution. HaloSat observations of the Vela SNR are best fit with a two-temperature thermal plasma model consisting of a cooler component with kT{sub 1}=0.19{sub −0.01}{sup +0.01} keV in collisional ionization equilibrium and a hotter component with kT{sub 2}=1.06{sub −0.27}{sup +0.45} keV in nonequilibrium ionization. Observations of the Puppis A SNR are best fit with a single-component plane-parallel shocked plasma model with kT=0.86{sub −0.05}{sup +0.06} keV in nonequilibrium ionization. For the first time, we find the total X-ray luminosities of both components of the Vela SNR spectrum in the 0.5–7 keV energy band to be L{sub X}=4.4{sub −1.4}{sup +1.4}×10{sup 34} erg s{sup −1} for the cooler component and L{sub X}=4.1{sub −1.5}{sup +1.8}×10{sup 34} erg s{sup −1} for the hotter component. We find the total X-ray luminosities of the Vela and Puppis A SNRs to be L{sub X}=8.4×10{sup 34} erg s{sup −1} and L{sub X}=6.7{sub −0.9}{sup +1.1}×10{sup 36} erg s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Total X-Ray Emission from the LMC Observed with HaloSat

We constrain the global parameters of the Large Magellanic Cloud (LMC) by modeling the first soft X-ray (0.4–6.8 keV) observations of the entire LMC produced in a single pointing with moderate spectral resolution by the HaloSat CubeSat. These data are best fit with the sum of two thermal plasma components in collisional ionization equilibrium and a power law. We find cool (0.210 ± 0.014 keV) and hot (0.89 ± 0.14 keV) components. The total X-ray luminosity of the LMC is (1.08 ± 0.14) × 10{sup 39} erg s{sup −1}. X-ray binaries make up a large fraction of the emission with a luminosity of (6.0 ± 0.8) × 10{sup 38} erg s{sup −1}, followed by cool gas from superbubbles, supernovae, and diffuse emission with a luminosity of (3.0 ± 0.3) × 10{sup 38} erg s{sup −1}. The hot gas from star formation contributes the smallest fraction, with a luminosity of (1.9 ± 0.5) × 10{sup 38} erg s{sup −1}. We estimate the total volume of the cool gas to be between (0.2–1.2) × 10{sup 10} pc{sup 3} and the hot gas to be between (1.0–5) × 10{sup 7} pc{sup 3} for filling factors of f = 1 and 0.2. These volumes result in a total thermal energy for the cool gas between (1.4–3) × 10{sup 54} erg for electron densities of 0.017–0.04 cm{sup −3}, and a thermal energy for the hot gas between (1.7–4) × 10{sup 53} erg for electron densities of 0.12–0.3 cm{sup −3}. This yields cooling timescales for the cool and hot gas of (1.5–3) × 10{sup 8} yr and (1.8–6) × 10{sup 7} yr, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sequential spectral line analysis for accurate density and temperature diagnosis of laboratory opacity measurements

The accuracy of iron opacity calculated in stellar interiors has been questioned since the discovery of the “solar problem” and the discrepancies between the measured and modeled iron opacity reported in 2015. Experimental opacity benchmarks require accurate temperature and density measurements, which were inferred by analyzing tracer magnesium spectra in those experiments. Could the observed discrepancy be explained by insufficient accuracy in the inferred temperature, density, and their uncertainties? Previous analyses may have yielded biased results due to three limitations: (1) simultaneous multi-line fitting, (2) approximations in line-shape models, and (3) exclusion of certain spectral lines due to insufficient background characterization. Notably, the first issue is a common concern for many inversion methods, including Bayesian inferences. We present a refined analysis method that overcomes these limitations, applied to three categories of iron opacity experiments (Anchor 1, 2, and 3). In particular, the sequential fitting method yields unbiased results with more realistic uncertainties by accounting for line inconsistencies in the parameter uncertainties. The average electron temperature and density values are 162 ± 6 eV and (7.0 ± 1.9) × 10 21 cm −3 for six Anchor 1 experiments, 189 ± 7 eV and (3.4 ± 0.3) × 10 22 cm −3 for 21 Anchor 2 experiments, and 201 ± 6 eV and (4.8 ± 1.1) × 10 22 cm −3 for nine Anchor 3 experiments. These results show ∼4% temperature and ∼20% density reproducibility over a decade, which also aligns with the inferred parameter uncertainties. In conclusion, the resulting temperature and density uncertainties lead to a quasi-continuum iron opacity variation of ±4%–7% for wavelengths below 9.5 Å, which is insufficient to explain the significant model-data discrepancies reported in 2015.

Absorption spectroscopy↗
DOE OSTI2023

On Magnitudes and Inferred Yields of the 39 Underground Nuclear Test Explosions at the Novaya Zemlya Test Site

ABSTRACT We review the previously compiled seismic magnitudes for underground nuclear explosions at the Union of the Soviet Socialist Republics Novaya Zemlya Test Site, and analyze these data in the context of published details about individual tests and official Russian reports of annual cumulative explosive energy release at the test site. We derive relationships between teleseismic body wave magnitude mb and explosive yield Y by predicting the yield of each test using mb and minimizing the difference between predicted and reported annual cumulative yield. A linear relationship between mb and logY with a slope of 0.82 provides a good fit to the annual total yield, with a root mean square (rms) misfit of 0.095 logY units. A spectral magnitude relationship based on the explosion source model of Mueller and Murphy (1971) with a single-free-parameter provides a slightly better fit. For the 10 tests for which individual yields can be directly deduced from the official reports, the rms misfit of reported yields is less than 0.1 logY units or about 25%. More complex relationships that differentiate between the northern and southern test areas, or take account of variations in the scaled depth of burial, do not provide substantially better fits to the reported yields.

Geochemistry & Geophysics↗
DOE OSTI2020

Local electric field measurement in GaN diodes by exciton Franz–Keldysh photocurrent spectroscopy

The eXciton Franz–Keldysh (XFK) effect is observed in GaN p–n junction diodes via the spectral variation of photocurrent responsivity data that redshift and broaden with increasing reverse bias. Photocurrent spectra are quantitatively fit over a broad photon energy range to an XFK model using only a single fit parameter that determines the line shape and the local bias (V l ), uniquely determining the local electric field maximum and depletion widths. As expected, the spectrally determined values of V l vary linearly with the applied bias (V) and reveal a large reduction in the local electric field due to electrostatic non-uniformity. The built-in bias (V bi ) is estimated by extrapolating V l at V=0, which, when compared with independent C-V measurements, indicates an overall ±0.31 V accuracy of V l . This demonstrates sub-bandgap photocurrent spectroscopy as a local probe of electric field in wide bandgap diodes that can be used to map out regions of device breakdown (hot spots) for improving electrostatic design of high-voltage devices.

42 ENGINEERING↗
DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗