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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Resilience of the Aurivillius structure upon La and Cr doping in a Bi 5 Ti 3 FeO 15 multiferroic

Here, combining the experimental techniques of high-resolution X-ray diffraction, magnetometry, specific heat measurement, and X-ray photoelectron, Raman and dielectric spectroscopy techniques, we have studied the influence of La and Cr doping on the crystal structure and magnetism of the room temperature Aurivillius multiferroic Bi 5 Ti 3 FeO 15 by investigating the physical properties of (Bi 4 La)Ti 3 FeO 15 and Bi 5 Ti 3 (Fe 0.5 Cr 0.5 )O 15 . The parent (Bi 5 Ti 3 FeO 15 ) and the doped ((Bi 4 La)Ti 3 FeO 15 and Bi 5 Ti 3 (Fe 0.5 Cr 0.5 )O 15 ) compounds crystallize in the A2 1 am space group, which is confirmed through our analysis of high-resolution synchrotron X-ray diffraction data obtained on phase-pure polycrystalline powders. We determined the oxidation states of the metal atoms in the studied compounds as Fe 3+ , Ti 4+ , Cr 3+ , and La 3+ through the analysis of X-ray photoelectron spectroscopy data. The magnetic susceptibilities of the three compounds are marked by the absence of a long-range ordered ground state, but dominated by superparamagnetic clusters with dominant antiferromagnetic interactions. This signature of short-range magnetism is also seen in specific heat as a low temperature enhancement which is suppressed upon the application of external magnetic fields up to 8 T. Our dielectric spectroscopy experiments showed that the three studied compounds display similar features in the dielectric constant measured as a function of frequency. However, upon doping La at the Bi site, the width of the ferroelectric hysteresis loop increases for (Bi 4 La)Ti 3 FeO 15 compared to that of the parent compound Bi 5 Ti 3 FeO 15 , and with Cr doping, Bi 5 Ti 3 (Fe 0.5 Cr 0.5 )O 15 becomes a leaky dielectric. The resilience of the Aurivillius crystal structure towards doping of La at the Bi site and Cr at the Fe site is clearly seen in the bulk properties of magnetic susceptibility, specific heat and the average crystal structure. The relevance of changes in the local structure is evident from our Raman spectroscopy and X-ray pair distribution function studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Evaluation of a pair-based, joint-likelihood association approach for regional infrasound event identification

SUMMARY A Bayesian framework for the association of infrasonic detections is presented and evaluated for analysis at regional propagation scales. A pair-based, joint-likelihood association approach is developed that identifies events by computing the probability that individual detection pairs are attributable to a hypothetical common source and applying hierarchical clustering to identify events from the pair-based analysis. The framework is based on a Bayesian formulation introduced for infrasonic source localization and utilizes the propagation models developed for that application with modifications to improve the numerical efficiency of the analysis. Clustering analysis is completed using hierarchical analysis via weighted linkage for a non-Euclidean distance matrix defined by the negative log-joint-likelihood values. The method is evaluated using regional synthetic data with propagation distances of hundreds of kilometres in order to study the sensitivity of the method to uncertainties and errors in backazimuth and time of arrival. The method is found to be robust and stable for typical uncertainties, able to effectively distinguish noise detections within the data set from those in events, and can be made numerically efficient due to its ease of parallelization.

58 GEOSCIENCES↗
DOE OSTI2021

SMC 2021 : Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU. RUR: This dataset is the job scheduler traces collected from the Titan supercomputerfrom 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected usingResource Utilization Report (RUR), a Cray-developed resource-usage data collectionand reporting system. It contains the usage information of its critical resources (CPU,Memory, GPU, and I/O) of each running job on Titan during that period [2]. ProjectAreas: Every job is associated with a project ID. TheProjectAreas.csvdatasetprovides a mapping of the project ID to its domain science. GPU: There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has the following fields: 1. SN : Serial number of a GPU 2. location : The location where it is installed 3. insert : The time when it was inserted into that location 4. remove : The time when it was removed from that location 5. duration : Amount of time the GPU spent in this location 6. out : If the device was taken out entirely w/o a re-installment into a new location. 7. event : If the GPU was taken out entirely, the reason for its removal. To learn more about this dataset, please refer to the git repositoryhttps://github.com/olcf/TitanGPULifeand the related publication [1]. References [1] George Ostrouchov, Don Maxwell, Rizwan A Ashraf, Christian Engelmann, MallikarjunShankar, and James H Rogers. Gpu lifetimes on titan supercomputer: Survival analysisand reliability. InSC20: International Conference for High Performance Computing,Networking, Storage and Analysis, pages 1-14. IEEE, 2020. [2] Feiyi Wang, Sarp Oral, Satyabrata Sen, and Neena Imam. Learning from five-yearresource-utilization data of titan system. In2019 IEEE International Conference onCluster Computing (CLUSTER), pages 1-6. IEEE, 2019.

42 ENGINEERING↗
DOE OSTI2022

Does a Free Electron Laser Exhibit Non-Standard Statistics? [Slides and Report]

The originally proposed work under this award sought to develop a theoretical basis for previous experimental observations in free-electron laser (FEL) physics involving certain non-classical effects in the light produced by these devices. A sound and valid theoretical interpretation of these experiments would represent a transformational understanding of free-electron lasers, and of electron-photon interactions in general. The specific objective of the completed work, as described in the attached progress report by Jeongwan Park, was to perform a detailed analysis of an experiment by Chen and Madey (Physical Review Letters; volume 86 number 26, 2001) concerning the purported sub-Poissonian photon statistics in an FEL. Since that published work contradicted FEL theory as presently understood, the purpose of the work under the present subcontract was to obtain a better understanding of the quantum nature of the FEL, to investigate the possibility of theoretical and experimental evidence for the non-standard photon statistics of the FEL, and to critically examine the experimental evidence through a re-evaluation of the data analysis of Chen and Madey. The results of this study showed that there were numerous experimental conditions under which the observed photon statistics could be explained by combining both the photon clustering property and the dead-time effect, and consequently, that the observed photon statistics in the Chen-Madey experiment did not require sub-Poissonian photon statistics for their explanation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1982

Comparing digital data processing techniques for surface mine and reclamation monitoring

The results of three techniques used for processing Landsat digital data are compared for their utility in delineating areas of surface mining and subsequent reclamation. An unsupervised clustering algorithm (ISOCLS), a maximum-likelihood classifier (CLASFY), and a hybrid approach utilizing canonical analysis (ISOCLS/KLTRANS/ISOCLS) were compared by means of a detailed accuracy assessment with aerial photography at NASA's Goddard Space Flight Center. Results show that the hybrid approach was superior to the traditional techniques in distinguishing strip mined and reclaimed areas.

Witt, R. G.↗
NASA NTRS1984

Antarctic sea ice microwave signatures and their correlation with in situ ice observations

The general characteristics and microwave radiative properties of sea ice in the Weddell Sea region during the onset of spring are studied by using the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) and other satellite sensors, in conjunction with in situ observations from the Mikhail Somov. The position of the ice edge, the gradient of ice concentration, and the width of the Marginal Ice Zone are inferred from the microwave data, and are found to be consistent with ship observations, especially at 18 GHz. The sensitivities of the various SMMR frequencies to surface and other effects are investigated by using multispectral cluster analysis. The results show considerable variability in emissivity, especially at 37 GHz, likely associated with varying degrees of surface wetness. Ice concentrations are derived by using two methods: one that assumes fixed emissivities for consolidated ice and an iterative procedure that accounts for the variable emissivities observed. Using the procedure that allows the emissivities to be variable gives ice concentrations that are more consistent with qualitative field observations.

Comiso, J. C.↗
DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗
NASA NTRS2012

Graphics Processing Unit Assisted Thermographic Compositing

Objective: To develop a software application utilizing general purpose graphics processing units (GPUs) for the analysis of large sets of thermographic data. Background: Over the past few years, an increasing effort among scientists and engineers to utilize the GPU in a more general purpose fashion is allowing for supercomputer level results at individual workstations. As data sets grow, the methods to work them grow at an equal, and often great, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU to allow for throughput that was previously reserved for compute clusters. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Signal (image) processing is one area were GPUs are being used to greatly increase the performance of certain algorithms and analysis techniques. Technical Methodology/Approach: Apply massively parallel algorithms and data structures to the specific analysis requirements presented when working with thermographic data sets.

Ragasa, Scott↗
NASA NTRS2013

Graphics Processing Unit Assisted Thermographic Compositing

Objective: To develop a software application utilizing general purpose graphics processing units (GPUs) for the analysis of large sets of thermographic data. Background: Over the past few years, an increasing effort among scientists and engineers to utilize the GPU in a more general purpose fashion is allowing for supercomputer level results at individual workstations. As data sets grow, the methods to work them grow at an equal, and often greater, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU to allow for throughput that was previously reserved for compute clusters. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Signal (image) processing is one area were GPUs are being used to greatly increase the performance of certain algorithms and analysis techniques.

Ragasa, Scott↗
DOE OSTI2021

Experimental Investigation and Monte Carlo Simulation of Quasielastic Electron Scattering From Helium-3 Clusters in Helium-4

Experiment E04-018 was conducted in Hall A of the Jefferson National Laboratory (JLab) from November 2006 through July 2007. The experiment used the two superconducting, high-resolution magnetic spectrometers of Hall A to detect scattered electrons and recoil nuclei. One goal of this experiment was to provide accurate data on the elastic charge form factor of 4He to high momentum transfers (up to Q2 = 77 fm?2). The purpose of this thesis is to analyze and simulate a very unique and unexpected class of data from this experiment. The work performed involved the analysis of electron scattering data with the 4He target of the JLab E04-018 experiment and Monte Carlo simulation studies of elastic and quasielastic electron scattering from the 4He and 3He few-body nuclear systems. The results of this experiment and the simulations provide insights into the existence of A = 3 clustering in 4He, and possibly in heavier nuclei.

Alahmade, Walaa↗
DOE OSTI2026

Validation of the DESI DR2 Ly$α$ forest full-shape analysis

We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$α$ (Ly$α$) forest full-shape analysis. This analysis combines three-dimensional Ly$α$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$α$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$$h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $fσ_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$α$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$α$ forest studies.

Herbold, M. [Chicago U., KICP; Ohio State U.] (ORC↗
NASA NTRS2000

Dimension Reduction of Hyperspectral Data on Beowulf Clusters

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operation. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold a great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, which is used widely in remote sensing, is the Principal Components Analysis (PCA). In light of the growing number of spectral channels of modern instruments, the paper reports on the development of a parallel PCA and its implementation on two Beowulf cluster configurations, on with fast Ethernet switch and the other is with a Myrinet interconnection.

El-Ghazawi, Tarek↗
DOE OSTI2022

Evaluation of macadamia felted coccid (Hemiptera: Eriococcidae) damage and cultivar susceptibility using imagery from a small unmanned aerial vehicle ( sUAV ), combined with ground truthing

Abstract BACKGROUND Macadamia felted coccid, Acanthococcus ioronsidei (Williams) (Hemiptera: Eriococcidae), is a significant pest of macadamia nut, Macadamia integrifolia Maiden & Betche (Protaceae), in Hawaii, and heavy infestations can kill branches, resulting in characteristic dead, copper‐colored leaves. Small Unmanned Aerial Vehicles (sUAV) or ‘drones,’ combined with spatial data analysis, can provide growers with accurate and high‐resolution detection of plant stress due to pest infestations. We investigated the feasibility of using RGB (red‐green‐blue) color images from sUAV to detect dieback caused by macadamia felted coccid infestation and compared sUAV estimates with ground‐based damage estimates (ground truthing). RESULTS Spatial analysis showed clustering of foliar damage that reflected cultivar susceptibility to macadamia felted coccid infestation, with cultivars 344 and 856 being susceptible, and cultivars 800 and 333 being tolerant. sUAV and ground‐based estimates of foliar damage were similar for the cultivar 344, but ground‐based assessments were higher than sUAV for cultivar 856, possibly due to the differences in canopy architecture and significant early dieback in the lower canopy. At foliar damage levels <10%, sUAV and ground truthing data were significantly positively correlated, suggesting sUAV may be useful in detecting early stages of macadamia felted coccid infestation. CONCLUSIONS Cultivars showed varying susceptibility to macadamia felted coccid infestation and the foliage damage appeared in clusters. sUAV was able to detect the foliage damage under high and low infestation scenarios suggesting that it can be effectively used for the early detection of infestations. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The cosmology dependence of galaxy clustering and lensing from a hybrid N -body–perturbation theory model

ABSTRACT We implement a model for the two-point statistics of biased tracers that combines dark matter dynamics from N-body simulations with an analytic Lagrangian bias expansion. Using Aemulus, a suite of N-body simulations built for emulation of cosmological observables, we emulate the cosmology dependence of these non-linear spectra from redshifts z = 0 to z = 2. We quantify the accuracy of our emulation procedure, which is sub-per cent at $k=1\, h \,{\rm Mpc}^{-1}$ for the redshifts probed by upcoming surveys and improves at higher redshifts. We demonstrate its ability to describe the statistics of complex tracer samples, including those with assembly bias and baryonic effects, reliably fitting the clustering and lensing statistics of such samples at redshift z ≃ 0.4 to scales of $k_{\rm max} \approx 0.6\, h\,\mathrm{Mpc}^{-1}$. We show that the emulator can be used for unbiased cosmological parameter inference in simulated joint clustering and galaxy–galaxy lensing analyses with data drawn from an independent N-body simulation. These results indicate that our emulator is a promising tool that can be readily applied to the analysis of current and upcoming data sets from galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs

Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen Aspergillus fumigatus. After liquid chromatography–mass spectrometry quantification of significantly produced analytes, we used network centrality measures to rank the treatments’ ability to elucidate these analytes and confirmed their identity through fragmentation patterns or in silico spiking with commercially available standards. Later, we examined the transcriptional regulation of these metabolites through real-time quantitative polymerase chain reaction. Our data-driven techniques can complement existing metabolomic network analysis by providing an approach to track the influence of any exogenous stimuli on metabolite production. Our experimental-based algorithm can overcome the bottlenecks in elucidating novel fungal compounds used in drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

The z ∼ 1.03 Merging Cluster SPT-CL J0356–5337: New Strong Lensing Analysis with HST and MUSE

We present a strong lensing analysis and reconstruct the mass distribution of SPT-CL J0356−5337, a galaxy cluster at redshift z = 1.034. Our model supersedes previous models by making use of new multiband Hubble Space Telescope data and Multi-Unit Spectroscopic Explorer (MUSE) spectroscopy. We identify two additional lensed galaxies to inform a more well-constrained model using 12 sets of multiple images in five separate lensed sources. The three previously known sources were spectroscopically confirmed by G. Mahler et al. at redshifts of z = 2.363, z = 2.364, and z = 3.048. We measured the spectroscopic redshifts of two of the newly discovered arcs using MUSE data, at z = 3.0205 and z = 5.3288. We increase the number of cluster member galaxies by a factor of 3 compared to previous work. We also report the detection of extended Lyα emission from several background galaxies. We measure the total projected mass density of the two major subcluster components, one dominated by the brightest cluster galaxy and the other by a compact group of luminous red galaxies. We find ${M}_{{\rm{B}}{\rm{C}}{\rm{G}}}(\lt 80\,\rm{kpc})=3.9{3}_{-0.14}^{+0.21}\times 1{0}^{13}$ M⊙ and ${M}_{{\rm{LRG}}}(\lt 80\,\rm{kpc})=2.9{2}_{-0.23}^{+0.16}\times 1{0}^{13}$ M⊙, yielding a mass ratio of $1.3{5}_{-0.08}^{+0.16}$ . The strong lensing constraints offer a robust estimate of the projected mass density regardless of modeling assumptions; allowing more substructure in this line of sight does not change the results or conclusions. Our results corroborate the conclusion that SPT-CL J0356−5337 is dominated by two mass components and is likely undergoing a major merger on the plane of the sky.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Analysis and design of the Multimission Modular Spacecraft hydrazine propulsion module

The translational velocity increment, stabilization and control requirements, vehicle weight, and geometric considerations of the Multimission Modular Spacecraft (MMS) provided the basic data on which to initiate the analysis and design of the hydrazine propulsion modules. The Landsat D was used as the mission model. Tradeoff studies were conducted on thrust level, thruster location, and clustering arrangement together with tankage volume and location. The impact of the use of single and dual seat thruster valves on plumbing configuration, reliability, and overall system cost was studied in detail. Conceptual designs of a recommended propulsion module configuration for both the Delta 3910 and Shuttle were prepared.

Etheridge, F. G.↗