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DOE OSTI2019

Sparse Bayesian mass mapping with uncertainties: local credible intervals

ABSTRACT Until recently, mass-mapping techniques for weak gravitational lensing convergence reconstruction have lacked a principled statistical framework upon which to quantify reconstruction uncertainties, without making strong assumptions of Gaussianity. In previous work, we presented a sparse hierarchical Bayesian formalism for convergence reconstruction that addresses this shortcoming. Here, we draw on the concept of local credible intervals (cf. Bayesian error bars) as an extension of the uncertainty quantification techniques previously detailed. These uncertainty quantification techniques are benchmarked against those recovered via Px-MALA – a state-of-the-art proximal Markov chain Monte Carlo (MCMC) algorithm. We find that, typically, our recovered uncertainties are everywhere conservative (never underestimate the uncertainty, yet the approximation error is bounded above), of similar magnitude and highly correlated with those recovered via Px-MALA. Moreover, we demonstrate an increase in computational efficiency of $\mathcal {O}(10^6)$ when using our sparse Bayesian approach over MCMC techniques. This computational saving is critical for the application of Bayesian uncertainty quantification to large-scale stage IV surveys such as LSST and Euclid.

Price, M. A.↗

DOE OSTI2022

Variable wildfire impacts on the seasonal water temperatures of western US streams: A retrospective study

Recent increases in the burn area and severity of wildfires in the western US have raised concerns about the impact on stream water temperature–a key determinant of cold-water fish habitats. However, the effect on seasonal water temperatures of concern, including winter and summer, are not fully understood. In this study, we assessed the impact of wildfire burns at Boulder Creek (Oregon), Elk Creek (Oregon), and Gibbon River (Wyoming) watersheds on the downstream winter and summer water temperatures for the first three post-fire years. To obtain results independent of the choice of the analytical method, we evaluated the consequence of each burn using three different statistical approaches that utilize local water temperature data. Our results from the three approaches indicated that the response of water temperatures to wildfire burns varied across seasons and sites. Wildfire burns were associated with a median increase of up to 0.56°C (Standard Error; S.E. < 0.23°C) in the summer mean water temperatures (MWT) and 62 degree-day Celsius (DDC; S.E. < 20.7 DDC) in the summer accumulated degree days (ADD) for the three subsequent years across studied stream sites. Interestingly, these burns also corresponded to a median decrease of up to 0.49°C (S.E. < 0.45°C) in the winter MWT and 39 DDC (S.E. < 40.5 DDC) in the winter ADD for the same period across sites. Wildfire effects on the downstream water temperatures diminished with increasing site distance from the burn perimeter. Our analyses demonstrated that analytical methods that utilize local watershed data could be applied to evaluate fire effects on downstream water temperatures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

2D materials↗

DOE OSTI2026

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗

DOE OSTI2017

New Spectral Evidence of an Unaccounted Component of the Near-infrared Extragalactic Background Light from the CIBER

The extragalactic background light (EBL) captures the total integrated emission from stars and galaxies throughout the cosmic history. The amplitude of the near-infrared EBL from space absolute photometry observations has been controversial and depends strongly on the modeling and subtraction of the zodiacal light (ZL) foreground. We report the first measurement of the diffuse background spectrum at 0.8–1.7 μm from the CIBER experiment. The observations were obtained with an absolute spectrometer over two flights in multiple sky fields to enable the subtraction of ZL, stars, terrestrial emission, and diffuse Galactic light. After subtracting foregrounds and accounting for systematic errors, we find the nominal EBL brightness, assuming the Kelsall ZL model, is 42.7{sub −10.6}{sup +11.9} nW m{sup −2} sr{sup −1} at 1.4 μm. We also analyzed the data using the Wright ZL model, which results in a worse statistical fit to the data and an unphysical EBL, falling below the known background light from galaxies at λ < 1.3 μm. Using a model-independent analysis based on the minimum EBL brightness, we find an EBL brightness of 28.7{sub −3.3}{sup +5.1} nWm{sup −2} sr{sup −1} at 1.4 μm. While the derived EBL amplitude strongly depends on the ZL model, we find that we cannot fit the spectral data to ZL, Galactic emission, and EBL from solely integrated galactic light from galaxy counts. The results require a new diffuse component, such as an additional foreground or an excess EBL with a redder spectrum than that of ZL.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Improving seasonal precipitation forecasts in the Western United States through statistical downscaling

Abstract Seasonal precipitation forecasts in the western United States are critical resources for water resource management, especially during winter. While current seasonal forecasting systems provide monthly precipitation forecasts operationally, their coarse resolution limits their effectiveness in capturing the localized precipitation patterns and snowpack conditions essential for water resource managers in the mountainous regions. Here, analog statistical downscaling is demonstrated as an effective approach to enhance the spatial resolution of operational seasonal forecasts provided by the North American Multi-Model Ensemble. Downscaling was performed by building an analog ‘library’, in which corresponding model forecasts and observed values during the training period were stored. In the testing period, unseen model forecasts referenced the closest historical forecast from the analog library and applied the corresponding observational value for each point. This analysis indicates that downscaled products can capture localized features more accurately than the original coarse resolution forecasts, reducing forecast error across the western United States. Moreover, downscaling individual ensemble members—rather than downscaling the ensemble mean—further reduces forecasting error for their multi-model ensemble mean products. The greatest error reductions in the downscaled product, measured by root mean squared error (RMSE), were observed at low to mid-elevations (500–2000 meters), with 50%–70% improvement relative to the original forecasts. In the higher elevations (2000 meters and above), changes in RMSE relative to the original forecast were limited to 10%–30% improvements. The improvement is more substantial for forecast systems with 10 ensemble members compared to that with 4 members, but this relationship does not hold for the system with 24 ensemble members. These findings show that analog statistical downscaling can effectively address the spatial limitations of seasonal precipitation forecasts with minimal computational cost, providing a valuable framework for enhancing coarse resolution forecasting products while providing insights into the timing of ensemble mean calculations during the downscaling process.

Vernon, B. (ORCID:0009000891670689)↗

DOE OSTI2022

Lifetime measurements of states of S 35 , S 36 , S 37 , and S 38 using the AGATA γ -ray tracking spectrometer

Lifetimes or lifetime limits of a small number of excited states of the sulfur isotopes with mass numbers A = 35 , 36, 37, and 38 have been measured using the differential recoil-distance method. The isotopes of sulfur were populated in binary grazing reactions initiated by a beam of 36 S ions of energy 225 MeV incident on a thin 208 Pb target which was mounted in the Cologne plunger apparatus. The combination of the PRISMA magnetic spectrometer and an early implementation of the AGATA γ-ray tracking array was used to detect γ rays in coincidence with projectile-like nuclear species. Lifetime measurements of populated states were measured within the range from about 1 to 100 ps. The number of states for which lifetime measurements or lifetime limits were possible was limited by statistics. For 35 S, the lifetime was determined for the first 1/2 + state at 1572 keV; the result is compared with a previous published lifetime value. The lifetime of the 3 - state of 36 S at 4193 keV was determined and compared with earlier measurements. No previous lifetime information exists for the (6 + ) state at 6690 keV; a lifetime measurement with large associated error was made in the present work. For 37 S, the states for which lifetime limits were established were those at 646 keV with J π = 3/2 - and at 2776 keV with J π = 11/2 - ; there are no previously published lifetime values for excited states of 37 S. Finally, a lifetime limit was established for the J π =(6 + ) state of 38 S at 3675 keV; no lifetime information exists for this state in the literature. Measured lifetime values were compared with the results of state-of-the-art shell-model calculations based on the PSDPF, SDPF-U, and FSU effective interactions. In addition, nuclear magnetic-dipole and electric-quadrupole moments, branching ratios, mixing ratios, and electromagnetic transition rates, where available, have been compared with shell-model values. The current work suffers from poor statistics; nevertheless, lifetime values and limits have been possible, allowing a useful discussion of the ability of state-of-the-art shell-model calculations to reproduce the experimental results.

electromagnetic transitions↗

DOE OSTI2015

STATISTICS OF MEASURING NEUTRON STAR RADII: ASSESSING A FREQUENTIST AND A BAYESIAN APPROACH

Measuring neutron star radii with spectroscopic and timing techniques relies on the combination of multiple observables to break the degeneracies between the mass and radius introduced by general relativistic effects. Here, we explore a previously used frequentist and a newly proposed Bayesian framework to obtain the most likely value and the uncertainty in such a measurement. We find that for the expected range of masses and radii and for realistic measurement errors, the frequentist approach suffers from biases that are larger than the accuracy in the radius measurement required to distinguish between the different equations of state. In contrast, in the Bayesian framework, the inferred uncertainties are larger, but the most likely values do not suffer from such biases. We also investigate ways of quantifying the degree of consistency between different spectroscopic measurements from a single source. We show that a careful assessment of the systematic uncertainties in the measurements eliminates the need for introducing ad hoc biases, which lead to artificially large inferred radii.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Histogram-free multicanonical Monte Carlo sampling to calculate the density of states

Here, we report a new multicanonical Monte Carlo algorithm to obtain the density of states for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain a closed-form expression for the density of states expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical sampling and Wang–Landau sampling. This is enabled by storing the visited states directly and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches

Since scattered radiation in cone-beam volume CT implies severe degradation of CT images by quantification errors, artifacts, and noise increase, scatter suppression is one of the main issues related to image quality in CBCT imaging. The aim of this review is to structurize the variety of scatter suppression methods, to analyze the common structure, and to develop a general framework for scatter correction procedures. In general, scatter suppression combines hardware techniques of scatter rejection and software methods of scatter correction. The authors emphasize that scatter correction procedures consist of the main components scatter estimation (by measurement or mathematical modeling) and scatter compensation (deterministic or statistical methods). The framework comprises most scatter correction approaches and its validity also goes beyond transmission CT. Before the advent of cone-beam CT, a lot of papers on scatter correction approaches in x-ray radiography, mammography, emission tomography, and in Megavolt CT had been published. The opportunity to avail from research in those other fields of medical imaging has not yet been sufficiently exploited. Therefore additional references are included when ever it seems pertinent. Scatter estimation and scatter compensation are typically intertwined in iterative procedures. It makes sense to recognize iterative approaches in the light of the concept of self-consistency. The importance of incorporating scatter compensation approaches into a statistical framework for noise minimization has to be underscored. Signal and noise propagation analysis is presented. A main result is the preservation of differential-signal-to-noise-ratio (dSNR) in CT projection data by ideal scatter correction. The objective of scatter compensation methods is the restoration of quantitative accuracy and a balance between low-contrast restoration and noise reduction. In a synopsis section, the different deterministic and statistical methods are discussed with respect to their properties and applications. The current paper is focused on scatter compensation algorithms. The multitude of scatter estimation models will be dealt with in a separate paper.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Measuring the impact of additional instrumentation on the skill of numerical weather prediction models at forecasting wind ramp events during the first Wind Forecast Improvement Project (WFIP)

Not provided.

Energy & Fuels↗

DOE OSTI2019

Multidimensional sum-up rounding for integer programming in optimal experimental design

Here we present a numerical method for approximating the solution of convex integer programs stemming from optimal experimental design. The statistical setup consists of a Bayesian framework for linear inverse problems for which the direct relationship is described by a discretized integral equation. Specifically, we aim to find the optimal sensor placement from a set of candidate locations where data are collected with measurement error. The convex objective function is a measure of the uncertainty, described here by the trace or log-determinant of the posterior covariance matrix, for the discretized linear inverse problem solution. The resulting convex integer program is relaxed, producing a lower bound. An upper bound is obtained by extending the sum-up rounding approach to multiple dimensions. For this extension, we analyze its accuracy as a function of the discretization mesh size for a rectangular domain. We show asymptotic optimality of the integer solution defining the upper bound for different experimental design criteria (A- and D-optimal), by proving the convergence to zero of the gap between the upper and lower bounds as the mesh size goes to zero. The technique is illustrated on a two-dimensional gravity surveying problem for both A-optimal and D-optimal sensor placement where our designs yield better results compared with a thresholding rounding approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Corrigendum to ‘Evidence for shock heating and constraints on Martian surface temperatures revealed by 40 Ar/ 39 Ar thermochronometry of Martian meteorites’ [Geochim. Cosmochim. Acta (2010) 6900–6920]

Here, the authors regret they have discovered errors in Eq. (3) and in a spreadsheet used to calculate cosmogenic exposure ages shown in Table 1. Eq. (3) is missing a term. The spreadsheet errors concerned an incorrect cell reference and application of Eq. (3). Correction of these errors results in ~15–20% changes to the exposure ages of all samples, minor (generally <0.2%) changes to the radioisotopic ages of some samples (those that entailed a correction for chlorine-derived 38Ar calculated based on the exposure age; see Section 3.3), and statistically insignificant changes to the inferred trapped components identified through isochron analyses. These modifications have no impact on the modeling, discussions, or conclusions in the paper, nor do the changes to radioisotopic ages exceed the 1 sigma uncertainties.

58 GEOSCIENCES↗

DOE OSTI2018

Radiation defect dynamics in 3 C -, 4 H -, and 6 H -SiC studied by pulsed ion beams

Radiation damage behavior of SiC depends on its lattice structure. Here, we use a pulsed-ion-beam method to study defect interaction dynamics in 6H-SiC and damage buildup in 4H- and 6H-SiC irradiated at 100 °C with 500 keV Ar ions. These results are compared with previously reported data for Ar-ion-irradiated 3C- and 4H-SiC. We find that, for these irradiation conditions, damage buildup in 3C- and 6H-SiC is statistically indistinguishable and is significantly more efficient than in 4H-SiC. Within a stimulated amorphization model, 4H-SiC is described by a reduced amorphization cross-section constant, while the point defect cluster production cross-section is the same (within experimental errors) for the three polytypes studied. Moreover, 4H-SiC exhibits slower defect relaxation dynamics than 3C- and 6H-SiC. These results clearly demonstrate the importance of the lattice structure in damage buildup and defect interaction dynamics in SiC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Producing two-dimensional dust clouds and clusters using a movable electrode for complex plasma and fundamental physics experiments

We report a Bidirectional Electrode Control Arm Assembly (BECAA) for precisely manipulating dust clouds levitated above the powered electrode in RF plasmas. The reported techniques allow the creation of perfectly 2D dust layers by eliminating off-plane particles by moving the electrode from outside the plasma chamber without altering the plasma conditions. Here, the tilting and moving of electrodes using BECAA also allows the precise and repeatable elimination of dust particles one by one to achieve any desired number of grains N without trial and error. Simultaneously acquired top and side view images of dust clusters show that they are perfectly planar or 2D. A demonstration of clusters with N = 1–28 without changing the plasma conditions is presented to show the utility of BECAA for complex plasma and statistical physics experimental design. Demonstration videos and 3D printable part files are available for easy reproduction and adaptation of this new method to repeatably produce 2D clusters in existing RF plasma chambers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2012

AUTOMATICALLY DETECTING AND TRACKING CORONAL MASS EJECTIONS. I. SEPARATION OF DYNAMIC AND QUIESCENT COMPONENTS IN CORONAGRAPH IMAGES

Automated techniques for detecting and tracking coronal mass ejections (CMEs) in coronagraph data are of ever increasing importance for space weather monitoring and forecasting. They serve to remove the biases and tedium of human interpretation, and provide the robust analysis necessary for statistical studies across large numbers of observations. An important requirement in their operation is that they satisfactorily distinguish the CME structure from the background quiescent coronal structure (streamers, coronal holes). Many studies resort to some form of time differencing to achieve this, despite the errors inherent in such an approach-notably spatiotemporal crosstalk. This article describes a new deconvolution technique that separates coronagraph images into quiescent and dynamic components. A set of synthetic observations made from a sophisticated model corona and CME demonstrates the validity and effectiveness of the technique in isolating the CME signal. Applied to observations by the LASCO C2 and C3 coronagraphs, the structure of a faint CME is revealed in detail despite the presence of background streamers that are several times brighter than the CME. The technique is also demonstrated to work on SECCHI/COR2 data, and new possibilities for estimating the three-dimensional structure of CMEs using the multiple viewing angles are discussed. Although quiescent coronal structures and CMEs are intrinsically linked, and although their interaction is an unavoidable source of error in any separation process, we show in a companion paper that the deconvolution approach outlined here is a robust and accurate method for rigorous CME analysis. Such an approach is a prerequisite to the higher-level detection and classification of CME structure and kinematics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

THE 37 MONTH MAXI/GSC SOURCE CATALOG OF THE HIGH GALACTIC-LATITUDE SKY

We present a catalog of high Galactic-latitude (|b| > 10 Degree-Sign ) X-ray sources detected in the first 37 months of data of the Monitor of All-sky X-ray Image/Gas Slit Camera (MAXI/GSC). To achieve the best sensitivity, we develop a background model of the GSC that well reproduces the data based on the detailed on-board calibration. Source detection is performed through image fits with a Poisson likelihood algorithm. The catalog contains 500 objects detected with significances of s{sub D,4-10keV} {>=} 7 in the 4-10 keV band. The limiting sensitivity is Almost-Equal-To 7.5 Multiplication-Sign 10{sup -12} erg cm{sup -2} s{sup -1} ( Almost-Equal-To 0.6 mCrab) in the 4-10 keV band for 50% of the survey area, which is the highest ever achieved in an all-sky survey mission covering this energy band. We summarize the statistical properties of the catalog and results from cross matching with the Swift/BAT 70 month catalog, the meta-catalog of X-ray detected clusters of galaxies, and the MAXI/GSC 7 month catalog. Our catalog lists the source name (2MAXI), position and its error, detection significances and fluxes in the 4-10 keV and 3-4 keV bands, the hardness ratio, and the basic information of the likely counterpart available for 296 sources.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Bayesian inference of nuclear symmetry energy from measured and imagined neutron skin thickness in Sn 116 , 118 , 120 , 122 , 124 , 130 , 132 , Pb 208 , and Ca 48

The neutron skin thickness Δr np in heavy nuclei has been known as one of the most sensitive terrestrial probes of the nuclear symmetry energy E sym (ρ) around $\frac{2}{3}$ of the saturation density ρ 0 of nuclear matter. Existing neutron skin data mostly from hadronic observables suffer from large uncertainties and their extraction from experiments are often strongly model dependent. While waiting eagerly for the promised model-independent and high-precision neutron skin data for 208 Pb and 48 Ca from the parity-violating electron scattering experiments (PREX-II and CREX at JLab as well as MREX at MESA), within the Bayesian statistical framework using the Skyrme-Hartree-Fock model we infer the posterior probability distribution functions (PDFs) of the slope parameter L of the nuclear symmetry energy at ρ 0 from imagined Δr np ( 208 Pb)=0.15, 0.20, and 0.30 fm with a 1σ error bar of 0.02, 0.04, and 0.06 fm, respectively, as well as Δr np ( 48 Ca)=0.12, 0.15, and 0.25 fm, with different 1σ error bar of 0.01 and 0.02 fm, respectively. The results are compared with the PDFs of L inferred using the same approach from the available Δr np data for 116, 118, 120, 122, 124, 130, 132 Sn from hadronic probes. They are also compared with results from a recent Bayesian analysis of the radius and tidal deformability data of canonical neutron stars from GW170817 and NICER. The neutron skin data for Sn isotopes gives L = 45.5 $^{+ 26.5}_{-21.6}$ MeV surrounding its mean value or L = 53 . 4 $^{+ 18.6}_{ -29.5}$ MeV surrounding its maximum a posteriori value, respectively, with the latter smaller than but consistent with the L = 66 $^{+ 12}_{-20}$ MeV from the neutron star data within their 68% confidence intervals. We found that Δr np = 0.17 –0.18 fm in 208 Pb with an error bar of about 0.02 fm leads to a PDF of L compatible with that from analyzing the Sn data. To provide additionally useful information on L extracted from the Δr np of Sn isotopes, the experimental error bar of Δr np in 208 Pb should be at least smaller than 0.06 fm aimed by some current experiments. In addition, the Δr np ( 48 Ca) needs to be larger than 0.15 fm but smaller than 0.25 fm to be compatible with the Sn and/or neutron star results. To further improve our current knowledge about L and distinguish its PDFs in the examples considered, even higher precisions leading to significantly less than ±20 MeV error bars for L at 68% confidence level are necessary.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗