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At least 1,117 records · Page 62

Nuclear Forensics Analysis with Missing and Uncertain Data

We have applied a new imputation-based method for analyzing incomplete data, called Monte Carlo Bayesian Database Generation (MCBDG), to the Spent Fuel Isotopic Composition (SFCOMPO) database. About 60% of the entries are absent for SFCOMPO. The method estimates missing values of a property from a probability distribution created from the existing data for the property, and then generates multiple instances of the completed database for training a machine learning algorithm. Uncertainty in the data is represented by an empirical or an assumed error distribution. The method makes few assumptions about the underlying data, and compares favorably against results obtained by replacing missing information with constant values.

97 MATHEMATICS AND COMPUTING↗

Surface characterization of nanomaterials and nanoparticles: Important needs and challenging opportunities

This review examines characterization challenges inherently associated with understanding nanomaterials and the roles surface and interface characterization methods can play in meeting some of the challenges. In parts of the research community, there is growing recognition that studies and published reports on the properties and behaviors of nanomaterials often have reported inadequate or incomplete characterization. As a consequence, the true value of the data in these reports is, at best, uncertain. With the increasing importance of nanomaterials in fundamental research and technological applications, it is desirable that researchers from the wide variety of disciplines involved recognize the nature of these often unexpected challenges associated with reproducible synthesis and characterization of nanomaterials, including the difficulties of maintaining desired materials properties during handling and processing due to their dynamic nature. It is equally valuable for researchers to understand how characterization approaches (surface and otherwise) can help to minimize synthesis surprises and to determine how (and how quickly) materials and properties change in different environments. Appropriate application of traditional surface sensitive analysis methods (including x-ray photoelectron and Auger electron spectroscopies, scanning probe microscopy, and secondary ion mass spectroscopy) can provide information that helps address several of the analysis needs. In many circumstances, extensions of traditional data analysis can provide considerably more information than normally obtained from the data collected. Less common or evolving methods with surface selectivity (e.g., some variations of nuclear magnetic resonance, sum frequency generation, and low and medium energy ion scattering) can provide information about surfaces or interfaces in working environments (operando or in situ) or information not provided by more traditional methods. Although these methods may require instrumentation or expertise not generally available, they can be particularly useful in addressing specific questions, and examples of their use in nanomaterial research are presented.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Energy Dependence Analysis of Neutrino-Nucleus Interactions in Scintillator for MINERvA

This thesis is on the intrinsic energy dependence in neutrino-nucleus interaction models, especially quasielastic scattering and 2p2h process, and the implications for understanding data from MINERvA, NOvA, and DUNE. Neutrino-nucleus interactions are modeled using fve structure functions, W1, W2, W3, W4 and W5, and each structure function contributes diferently to the energy dependence once it enters the cross-section calculations. The energy independent term in the calculations contains only W2 and the next lower order term (of the order 1/E) contains W3 also. In this thesis, we show that W2 is good enough to describe MINERvA data and energy dependence coming from the cross-section directly is small. However, W3 will be signifcant for lower energy experiments such as NOvA and DUNE (especially at and below the oscillation maximum). We have also developed a method to extract structure functions directly from MINERvA data though we find that systematic uncertainties present in the data are too big to successfully determine 1/E Term. In addition to this, we have applied muon angle cuts on MINERvA data and MC, which have their own energy dependent effects. An apparent energy dependent discrepancy comes from known shortcomings especially in the pion production model. Finally, because the energy dependence analysis has similarities to the low-$\nu$ method, we have evaluated discrepancies between the data and MC in light of diferent fux constraint techniques. The results suggest including MINERvA s low-$\nu$ method constraint is an improvement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

An R Shiny graphical user interface for analyzing, visualizing, and interpreting high precision mass spectrometric data

There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2 , IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

Labone, Elizabeth↗

An R shiny graphical user interface for highprecision mass spectrometric data analysis

• There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2, IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

LABONE, ELIZABETH↗

Unraveling spectral shapes of adventitious carbon on gold using a time-resolved high-resolution X-ray photoelectron spectroscopy and principal component analysis

To extract chemical information reliably, we propose a new data processing method based both on the creation of information vectors and on a vector base change. The originality of this method is the combination of the different core XPS peaks, Auger and/or valence bands in a single vector. We show that the measurement of a sample upon its progressive chemical change, such as accumulation of the adventitious carbon, allows us to create a new vector basis using linear algebra and Principal Component Analysis. In this work, we demonstrate the application of this method using adventitious carbon films on Au foil utilizing Au 4f, C 1s and O 1s spectral envelopes. This method expands the possibilities of XPS measured chemical environment analysis and is an operator-unbiased solution for materials for which the reference XPS spectra are not available. In this demonstration, the emphasis is placed on identifying changes in a C 1s peak assumed to be adventitious carbon and highlight uncertainties associated with calibrating the binding energy scale using a simple peak model to identify a component C 1s assumed to be saturated hydrocarbon in origin.

36 MATERIALS SCIENCE↗

Healing X-ray scattering images

X-ray scattering images contain numerous gaps and defects arising from detector limitations and experimental configuration. Here, we present a method to heal X-ray scattering images, filling gaps in the data and removing defects in a physically meaningful manner. Unlike generic inpainting methods, this method is closely tuned to the expected structure of reciprocal-space data. In particular, we exploit statistical tests and symmetry analysis to identify the structure of an image; we then copy, average and interpolate measured data into gaps in a way that respects the identified structure and symmetry. Importantly, the underlying analysis methods provide useful characterization of structures present in the image, including the identification of diffuse versus sharp features, anisotropy and symmetry. The presented method leverages known characteristics of reciprocal space, enabling physically reasonable reconstruction even with large image gaps. The method will correspondingly fail for images that violate these underlying assumptions. The method assumes point symmetry and is thus applicable to small-angle X-ray scattering (SAXS) data, but only to a subset of wide-angle data. Our method succeeds in filling gaps and healing defects in experimental images, including extending data beyond the original detector borders.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Ramp-release experiments for strength measurements: Strain-rate dependence

This paper presents an enhanced analysis method for investigating material properties at high strain rates, extending the capability of established experimental techniques to gain more information. The ramp-release method has been applied to many experiments reported at high (≈10 5 − 10 6 s −1 ) strain-rates. More recent data gathered at the National Ignition Facility (NIF) has enabled higher (≈10 8 s −1 ) strain-rates to be studied. Here, we present an initial application of ramp-release analysis to NIF ramp-compression data, illustrating both the opportunities and the practical challenges of extending these methods to laser-driven platforms. The higher strain-rates accessed at the NIF mean that there is more strain-rate enhancement to strength, and the experimental configuration means that this enhancement is more readily seen in the data. This is enabled by the capability of avoiding peak-compression attenuation through the sample thickness with a designed hold period made possible by the pulse-shaping capability of NIF. We propose that this combination of experimental conditions and an enhanced analysis method enables the strain-rate enhancement to strength to be studied, and potentially for this to inform physics models at smaller scales than the continuum.

36 MATERIALS SCIENCE↗

The DESI N -body simulation project – I. Testing the robustness of simulations for the DESI dark time survey

ABSTRACT Analysis of large galaxy surveys requires confidence in the robustness of numerical simulation methods. The simulations are used to construct mock galaxy catalogues to validate data analysis pipelines and identify potential systematics. We compare three N-body simulation codes, abacus, gadget-2, and swift, to investigate the regimes in which their results agree. We run N-body simulations at three different mass resolutions, 6.25 × 108, 2.11 × 109, and 5.00 × 109 h−1 M⊙, matching phases to reduce the noise within the comparisons. We find systematic errors in the halo clustering between different codes are smaller than the Dark Energy Spectroscopic Instrument (DESI) statistical error for $s\ \gt\ 20\ h^{-1}$ Mpc in the correlation function in redshift space. Through the resolution comparison we find that simulations run with a mass resolution of 2.1 × 109 h−1 M⊙ are sufficiently converged for systematic effects in the halo clustering to be smaller than the DESI statistical error at scales larger than $20\ h^{-1}$ Mpc. These findings show that the simulations are robust for extracting cosmological information from large scales which is the key goal of the DESI survey. Comparing matter power spectra, we find the codes agree to within 1 per cent for k ≤ 10 h Mpc−1. We also run a comparison of three initial condition generation codes and find good agreement. In addition, we include a quasi-N-body code, FastPM, since we plan use it for certain DESI analyses. The impact of the halo definition and galaxy–halo relation will be presented in a follow-up study.

79 ASTRONOMY AND ASTROPHYSICS↗

XXL-HSC: An updated catalogue of high-redshift ( z ≥ 3.5) X-ray AGN in the XMM-XXL northern field

X-rays offer a reliable method to identify active galactic nuclei (AGNs). However, in the high-redshift Universe, X-ray AGNs are poorly sampled due to their relatively low space density and the small areas covered by X-ray surveys. In addition to wide-area X-ray surveys, it is important to have deep optical data in order to locate the optical counterparts and determine their redshifts. Here, in this work, we built a high-redshift (z ≥ 3.5) X-ray-selected AGN sample in the XMM-XXL northern field using the most updated [0.5–2 keV] catalogue along with a plethora of new spectroscopic and multi-wavelength catalogues, including the deep optical Subaru Hyper Suprime-Cam (HSC) data, reaching magnitude limits i ~ 26 mag. We selected all the spectroscopically confirmed AGN and complement this sample with high-redshift candidates that are HSC g- and r-band dropouts. To confirm the dropouts, we derived their photometric redshifts using spectral energy distribution techniques. We obtained a sample of 54 high-z sources (28 with spec-z), the largest in this field so far (almost three times larger than in previous studies), and we estimated the possible contamination and completeness. We calculated the number counts (log N-log S) in different redshift bins and compared our results with previous studies and models. We provide the strongest high-redshift AGN constraints yet at bright fluxes (f 0.5 – 2 keV > 10 –15 erg s –1 cm –2 ). The samples of z ≥ 3.5, z ≥ 4, and z ≥ 5 are in agreement with an exponential decline model similar to that witnessed at optical wavelengths. Our work emphasises the importance of using wide-area X-ray surveys with deep optical data to uncover high-redshift AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗

Applications of Integral Benchmark Data

The International Reactor Physics Experiment Evaluation Project (IRPhEP) and the International Criticality Safety Benchmark Evaluation Project (ICSBEP) provide evaluated integral benchmark data that may be used for validation of reactor physics / nuclear criticality safety analytical methods and data, nuclear data testing, advanced modeling and simulation, and safety analysis licensing activities. The handbooks produced by these programs are used in over 30 countries. Five example applications are presented in this paper: (1) Use of IRPhEP Data in Uncertainty Analyses and Cross Section Adjustment, (2) Uncertainty Evaluation Methods for Reactor Core Design at JAEA Using Reactor Physics Experimental Data, (3) Application of Benchmarking Data to a Broad Range of Criticality Safety Problems, (4) Cross Section Data Testing with ICSBEP Benchmarks, and (5) Use of the International Handbook of Evaluated Reactor Physics Benchmark Experiments to Support the Power Industry.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Energy resolved electrochemical impedance spectroscopy for electronic structure mapping in organic semiconductors

We introduce an energy resolved electrochemical impedance spectroscopy method to map the electronic density of states (DOS) in organic semiconductor materials. The method consists in measurement of the charge transfer resistance of a semiconductor/electrolyte interface at a frequency where the redox reactions determine the real component of the impedance. The charge transfer resistance value provides direct information about the electronic DOS at the energy given by the electrochemical potential of the electrolyte, which can be adjusted using an external voltage. A simple theory for experimental data evaluation is proposed, along with an explanation of the corresponding experimental conditions. The method allows mapping over unprecedentedly wide energy and DOS ranges. Also, important DOS parameters can be determined directly from the raw experimental data without the lengthy analysis required in other techniques. The potential of the proposed method is illustrated by tracing weak bond defect states induced by ultraviolet treatment above the highest occupied molecular orbital in a prototypical σ-conjugated polymer, poly[methyl(phenyl)silylene]. The results agree well with those of our previous DOS reconstruction by post-transient space-charge-limited-current spectroscopy, which was, however, limited to a narrow energy range. In addition, good agreement of the DOS values measured on two common π-conjugated organic polymer semiconductors, polyphenylene vinylene and poly(3-hexylthiophene), with the rather rare previously published data demonstrate the accuracy of the proposed method.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Evaluation of Methods for Comparison of Spatiotemporal and Time Series Datasets

Data used by the National Renewable Energy Laboratory (NREL) in energy analysis are often produced by industry and licensed or purchased for analysis. While this practice provides needed flexibility in selecting data for analysis it presents challenges in understanding the differences among multiple, ostensibly similar, datasets. As options for source data become more varied, it is important to be able to articulate why certain datasets were chosen and to ensure those include the data that best meet the boundaries and/or limitations of a particular analysis. This report represents the first of three phases of research intended to develop methods to quantitatively assess and compare both input datasets and the results of analyses performed at NREL. This capability is critical to identifying tipping points in the costs or benefits of achieving high spatial and temporal resolution of input data.

97 MATHEMATICS AND COMPUTING↗

Inferring the shape of data: a probabilistic framework for analysing experiments in the natural sciences

A critical step in data analysis for many different types of experiments is the identification of features with theoretically defined shapes in N -dimensional datasets; examples of this process include finding peaks in multi-dimensional molecular spectra or emitters in fluorescence microscopy images. Identifying such features involves determining if the overall shape of the data is consistent with an expected shape; however, it is generally unclear how to quantitatively make this determination. In practice, many analysis methods employ subjective, heuristic approaches, which complicates the validation of any ensuing results—especially as the amount and dimensionality of the data increase. Here, we present a probabilistic solution to this problem by using Bayes’ rule to calculate the probability that the data have any one of several potential shapes. This probabilistic approach may be used to objectively compare how well different theories describe a dataset, identify changes between datasets and detect features within data using a corollary method called Bayesian Inference-based Template Search; several proof-of-principle examples are provided. Altogether, this mathematical framework serves as an automated ‘engine’ capable of computationally executing analysis decisions currently made by visual inspection across the sciences.

Science & Technology - Other Topics↗

Data processing pipeline for Tianlai experiment

The Tianlai project is a 21cm intensity mapping experiment for detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily aected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline called tlpipe to process the drift scan survey data from the Tianlai experiment. It performs oine data processing tasks such as radio frequency interference (RFI) agging, array calibration, binning, and map-making, etc. It also includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhnov regularization for m-mode analysis. In this paper we describe the design and implementation of the pipeline and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

LABQ3: Bayesian method for quantification of mineral compositions and nano-scale elemental mapping of 3D synchrotron XCT data

Quantitative analysis of mineral compositions is essential in understanding geochemical, mineralogical and environmental processes. Fine-resolution 3D imaging is widely done using synchrotron X-ray computed tomography (XCT), but existing analyses are limited to visualization and segmentation. This paper presents a new method, Linear Attenuation Bayesian Quantitative 3D-mapper (LABQ3), based on the linearity of X-ray attenuation with respect to elemental concentrations. To address the random variability in attenuation measurements, LABQ3 employs Bayesian decision theory to minimize classification error, using reference attenuation distributions from scans of pure mineral standards. To demonstrate LABQ3 and test its performance, we studied precipitated carbonate samples. XCT scans were done at multiple energies using the transmission X-ray microscope (TXM) at beamline 32-ID-C of the Advanced Photon Source at Argonne National Laboratory. The reconstructed 3D images have a voxel size of 20 nm. Analyses revealed rich nano-scale compositional heterogeneity within individual particles. A mixture of calcium and cadmium produced an overall stoichiometric composition of (Ca 0.78 ,Cd 0.22 )CO 3 , with some voxels containing nearly pure CdCO 3 . The addition of zinc led to an overall stoichiometric composition of 33% Ca, 28% Cd, 39% Zn, with a nearly pure CaCO 3 core and compositional zonation through the rim. These compositional gradients are related to temporal sequences of carbonate mineral formation where Cd precipitated at the beginning in (Ca,Cd)CO 3 , while Cd and Zn precipitated at the end in (Ca, Cd,Zn)CO 3 . Results differ from bulk analyses using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), showing that LABQ3 provides particle-specific insights. LABQ3 distinguishes itself by quantifying chemical compositions along a continuum, making it different from XCT analyses based on segmentation. LABQ3 allows simultaneous acquisition of morphology and chemical composition in 3D, facilitating the interpretation of chemical gradients of trace elements, quantification of solid solution compositions, inferences about temporal sequences of mineral precipitation, and addressing other concerns about solid-phase chemistry.

58 GEOSCIENCES↗

REANALYSIS OF THE GRAVITATIONAL MICROLENSING EVENT MACHO-97-BLG-41 BASED ON COMBINED DATA

MACHO-97-BLG-41 is a gravitational microlensing event produced by a lens composed of multiple masses detected by the first-generation lensing experiment. For the event, there exist two different interpretations of the lens from independent analyses based on two different data sets: one interpreted the event as produced by a circumbinary planetary system while the other explained the light curve with only a binary system by introducing orbital motion of the lens. According to the former interpretation, the lens would not only be the first planet detected via microlensing but also the first circumbinary planet ever detected. To resolve the issue using state-of-the-art analysis methods, we reanalyze the event based on the combined data used separately by the previous analyses. By considering various higher-order effects, we find that the orbiting binary-lens model provides a better fit than the circumbinary planet model with {Delta}{chi}{sup 2} {approx} 166. The result signifies the importance of even and dense coverage of lensing light curves in the interpretation of events.

79 ASTRONOMY AND ASTROPHYSICS↗

Fault Detection via Occupation Kernel Principal Component Analysis

Reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamics. While traditional model-based methods have been widely used for fault detection, data-driven approaches have garnered increasing attention due to their ease of deployment and minimal need for expert knowledge. In this letter, we present a novel principal component analysis (PCA) method that uses occupation kernels. Occupation kernels result in feature maps that are tailored to the measured data, have inherent noise-robustness due to the use of integration, and can utilize irregularly sampled system trajectories of variable lengths for PCA. The occupation kernel PCA method is used to develop a reconstruction error approach to fault detection and its efficacy is validated using numerical simulations.

42 ENGINEERING↗