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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Baryonic Effects in Cosmic Shear Tomography: PCA Parameterization and the Importance of Extreme Baryonic Models

Baryonic effects are amongst the most severe systematics to the tomographic analysis of weak lensing data which is the principal probe in many future generations of cosmological surveys like LSST, Euclid etc.. Modeling or parameterizing these effects is essential in order to extract valuable constraints on cosmological parameters. In a recent paper, Eifler et al. (2015) suggested a reduction technique for baryonic effects by conducting a principal component analysis (PCA) and removing the largest baryonic eigenmodes from the data. In this article, we conducted the investigation further and addressed two critical aspects. Firstly, we performed the analysis by separating the simulations into training and test sets, computing a minimal set of principle components from the training set and examining the fits on the test set. We found that using only four parameters, corresponding to the four largest eigenmodes of the training set, the test sets can be fitted thoroughly with an RMS $\sim 0.0011$. Secondly, we explored the significance of outliers, the most exotic/extreme baryonic scenarios, in this method. We found that excluding the outliers from the training set results in a relatively bad fit and degraded the RMS by nearly a factor of 3. Therefore, for a direct employment of this method to the tomographic analysis of the weak lensing data, the principle components should be derived from a training set that comprises adequately exotic but reasonable models such that the reality is included inside the parameter domain sampled by the training set. The baryonic effects can be parameterized as the coefficients of these principle components and should be marginalized over the cosmological parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Breaking the curse of dimensionality to identify causal variants in Breeding 4

In the past, plant breeding has undergone three major transformations and is currently transitioning to a new technological phase, Breeding 4. This phase is characterized by the development of methods for biological design of plant varieties, including transformation and gene editing techniques directed toward causal loci. The application of such technologies will require to reliably estimate the effect of loci in plant genomes by avoiding the situation where the number of loci assayed ($p$) surpasses the number of plant genotypes (n). Here, we discuss approaches to avoid this curse of dimensionality ($n\ll p$), which will involve analyzing intermediate phenotypes such as molecular traits and component traits related to plant morphology or physiology. Because these approaches will rely on novel data types such as DNA sequences and high-throughput phenotyping images, Breeding 4 will call for analyses that are complementary to traditional quantitative genetic studies, being based on machine learning techniques which make efficient use of sequence and image data. In this article, we will present some of these techniques and their application for prioritizing causal loci and developing improved varieties in Breeding 4.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants

In this article, sound speed data measured using a dual-path pulse-echo instrument are reported for binary mixtures of difluoromethane (R-32) with 2,3,3,3-tetrafluoropropene (R-1234yf) or trans-1,3,3,3-tetrafluoropropene (R-1234ze(E)). The sound speed is reported at two compositions for each binary mixture of approximately (0.33/67) and (0.67/0.33) mole fraction at temperatures between 230 K and 345 K. Data are reported from pressures slightly above the bubble point to 12 MPa for R-32/1234yf mixtures to avoid potential polymerization reactions and to 53 MPa for the R-32/1234ze(E) mixtures. The mean uncertainty of the sound speed data are less than 0.1% of the measured value where uncertainties at individual state points range from 0.04% to 0.5% of the measured value as the conditions approach the mixture critical region. The reported data are compared to available Helmholtz-energy-explicit EOS included in REFPROP and all systems studied have average absolute deviations greater than 2%. The comparisons show that further adjustments to the mixture models are needed to provide a reasonable representation of the data within its experimental uncertainty.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation

Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerging from various domain sciences. They provide a low-dimensional emulation framework for systems that may be intrinsically high-dimensional. This is accomplished by utilizing a construction algorithm that is purely data-driven. It is no surprise, therefore, that the algorithmic advances of machine learning have led to non-intrusive ROMs with greater accuracy and computational gains. However, in bypassing the utilization of an equation-based evolution, it is often seen that the interpretability of the ROM framework suffers. This becomes more problematic when black-box deep learning methods are used which are notorious for lacking robustness outside the physical regime of the observed data. In this article, we propose the use of a novel latent-space interpolation algorithm based on Gaussian process regression. Notably, this reduced-order evolution of the system is parameterized by control parameters to allow for interpolation in space. The use of this procedure also allows for a continuous interpretation of time which allows for temporal interpolation. The latter aspect provides information, with quantified uncertainty, about full-state evolution at a finer resolution than that utilized for training the ROMs. This research assesses the viability of this algorithm for an advection-dominated system given by the inviscid shallow water equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The Meson Spectroscopy Program Using the Forward Tagger with CLAS12 at Jefferson Lab

The 12 GeV upgrade to the Continuous Electron Beam Accelerator Facility (CEBAF) will enable a new generation of experiments in hadronic nuclear physics at Jefferson Lab, seeking to address fundamental questions in QCD. For example, confirming the existence of exotic states, suggested by both quark models and lattice calculations, would allow gluonic degrees of freedom to be explored, and may help explain the role played by gluons in the QCD interaction. In Experimental Hall B, meson spectroscopy (the MesonEx experiment) will be performed using low Q2 electron scattering to produce quasi-real photons. The scattered electron is detected at small angles by the Forward Tagger device, determining the properties of the photon on an event-by-event basis. This technique has notable advantages over real photon beams, and over hadronic beam experiments, where most experimental data exists. This article will focus on the development of the Forward Tagger by the INFN Genova group, and the proposed MesonEx experiment.

Fegan, Stuart↗
DOE OSTI2011

Laser mass-spectrometry for online diagnosis of reactive plasmas with many species

The purpose of this study is to design a diagnostic system for reactive plasma environment by combining molecular-beam time-of-flight (TOF) mass spectroscopy with laser spectroscopy technique. The combination of TOF mass spectrometers and pulsed lasers is favorable in the diagnosis of intermediate species distribution since they allow the simultaneous but separate recording of the spectra of different species. In the plasma system, the intermediate species in electronic ground state or low lying excited state is pumped to higher energy level with resonant laser excitation, and then, the ionization with a second laser system is possible which can readily be detected by the TOF analyzer. The ionization itself is only used as a detection mechanism for the observation of the excitation of these states. In this manner, the population distribution of intermediate species can be determined with state-selective and mass-selective feature. Also, in this article, a flexible data acquisition and automatic control system based on LABVIEW was designed to integrate all the stand-alone measurement instruments including a TOF spectrometer, a laser system, a high performance oscilloscope, and a digital delay generator into a single personal computer-based control unit. Moreover, a virtual Boxcar integrator with hundreds of channels has been developed to enhance the signal while filtering out the random noises. Finally, the many potentials of this technique in the application of plasma diagnosis will be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Waveform retrieval for ultrafast applications based on convolutional neural networks

Electric field waveforms of light carry rich information about dynamical events on a broad range of timescales. The insight that can be reached from their analysis, however, depends on the accuracy of retrieval from noisy data. In this article, we present a novel approach for waveform retrieval based on supervised deep learning. We demonstrate the performance of our model by comparison with conventional denoising approaches, including wavelet transform and Wiener filtering. The model leverages the enhanced precision obtained from the nonlinearity of deep learning. The results open a path toward an improved understanding of physical and chemical phenomena in field-resolved spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

New detections of radio minihalos in cool cores of galaxy clusters

Cool cores of some galaxy clusters exhibit faint radio 'minihalos'. Their origin is unclear, and their study has been limited by their small number. We undertook a systematic search for minihalos in a large sample of X-ray luminous clusters with high-quality radio data. In this article, we report four new minihalos (A 478, ZwCl 3146, RXJ 1532.9+3021, and A 2204) and five candidates found in the reanalyzed archival Very Large Array observations. The radio luminosities of our minihalos and candidates are in the range of 10{sup 23-25} W Hz{sup –1} at 1.4 GHz, which is consistent with these types of radio sources. Their sizes (40-160 kpc in radius) are somewhat smaller than those of previously known minihalos. We combine our new detections with previously known minihalos, obtaining a total sample of 21 objects, and briefly compare the cluster radio properties to the average X-ray temperature and the total masses estimated from Planck. We find that nearly all clusters hosting minihalos are hot and massive. Beyond that, there is no clear correlation between the minihalo radio power and cluster temperature or mass (in contrast with the giant radio halos found in cluster mergers, whose radio luminosity correlates with the cluster mass). Chandra X-ray images indicate gas sloshing in the cool cores of most of our clusters, with minihalos contained within the sloshing regions in many of them. This supports the hypothesis that radio-emitting electrons are reaccelerated by sloshing. Advection of relativistic electrons by the sloshing gas may also play a role in the formation of the less extended minihalos.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Quantitative x-ray scattering of free molecules

Advances in x-ray free electron lasers have made ultrafast scattering a powerful method for investigating molecular reaction kinetics and dynamics. Accurate measurement of the ground-state, static scattering signals of the reacting molecules is pivotal for these pump-probe x-ray scattering experiments as they are the cornerstone for interpreting the observed structural dynamics. Here, this article presents a data calibration procedure, designed for gas-phase x-ray scattering experiments conducted at the Linac Coherent Light Source x-ray Free-Electron Laser at SLAC National Accelerator Laboratory, that makes it possible to derive a quantitative dependence of the scattering signal on the scattering vector. A self-calibration algorithm that optimizes the detector position without reference to a computed pattern is introduced. Angle-of-scattering corrections that account for several small experimental non-idealities are reported. Their implementation leads to near quantitative agreement with theoretical scattering patterns calculated with ab-initio methods as illustrated for two x-ray photon energies and several molecular test systems.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Bayesian differential programming for robust systems identification under uncertainty

This paper presents a machine learning framework for Bayesian systems identification from noisy, sparse and irregular observations of nonlinear dynamical systems. The proposed method takes advantage of recent developments in differentiable programming to propagate gradient information through ordinary differential equation solvers and perform Bayesian inference with respect to unknown model parameters using Hamiltonian Monte Carlo sampling. This allows an efficient inference of the posterior distributions over plausible models with quantified uncertainty, while the use of sparsity-promoting priors enables the discovery of interpretable and parsimonious representations for the underlying latent dynamics. A series of numerical studies is presented to demonstrate the effectiveness of the proposed methods, including nonlinear oscillators, predator–prey systems and examples from systems biology. Taken together, our findings put forth a flexible and robust workflow for data-driven model discovery under uncertainty. All codes and data accompanying this article are available at https://bit.ly/34FOJMj .

Science & Technology - Other Topics↗
DOE OSTI2020

An Integrated Indexing and Search Service for Distributed File Systems

Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Virtual strain gage size study

DIC is a non-linear low-pass spatial filtering operation; whether we consider the effect of the subset and shape function, the strain window used in the strain calculation, of other post-processing of the results, each decision will impact the spatial resolution, of the measurement. More fundamentally, the speckle size limits, the spatial resolution by dictating the smallest possible subset. After this decision the processing settings are controlled by the allowable noise level balanced by possible bias errors created by the data filtering. This article describes a process to determine optimum DIC software settings to determine if the peak displacements or strains are being found.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Material report in support to RCC-MRX code 2010 stainless steel parts and products

This paper presents the Material Report dedicated to stainless steels parts and products issued by AFCEN (Association Francaise pour les regles de Conception et de Construction des Materiels des Chaudieres Electro-Nucleaires) in support to RCC-MRx 2010 Code. The RCC-MRx Code is the result of the merger of the RCC-MX 2008, developed in the context of the research reactor Jules Horowitz Reactor project, in the RCC-MR 2007, which set up rules applicable to the design of components operating at high temperature and to the Vacuum Vessel of ITER (a presentation of RCC-MRx 2010 Code is the subject of another paper proposed in this Congress; it explains in particular the status of this Code). This Material Report is part of a set of Criteria of RCC-MRx (this set of Criteria is under construction). The Criteria aim at explaining the design and construction rules of the Code. They cover analyses rules as well as part procurement, welding, methods of tests and examination and fabrication rules. The Material Report particularly provides justifications and explanations on requirements and features dealing with parts and products proposed in the Code. The Material Report contains the following information: Introduction of the grade(s): codes and standards and Reference Procurement Specifications covering parts and products, applications and experience gained, - Physical properties, - Mechanical properties used for design calculations (base metal and welds): basic mechanical properties, creep mechanical properties, irradiated mechanical properties, - Fabrication: experience gained, metallurgy, - Welding: weldability, experience gained during welding and repair procedure qualifications, - Non-destructive examination, - In-service behaviour. In the article, examples of data supplied in the Material Report dedicated to stainless steels will be exposed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Finely Dispersed Micro- and Nano-Gold Recovery Using Thermomorphic Polymer with Diphenylphosphine

The article reports test data on adsorption and flotation characteristics of thermomorphic polymer joined with diphenylphosphine—TMPD. The test materials are natural pyrite and arsenopyrite, and models of gold-bearing sulfide minerals. Electron microscopy and X-ray structure analysis prove that reductive adsorption of gold at the surface of sulfide minerals from HAuCl{sub 4} solution allows modeling natural aggregates of sulfides and finely dispersed gold. UV spectrophotometry proves selective adsorption of TMPD at gold. Laser scanning microscopy shows connection of TMPD with micro- and nano-size gold on polished sections of pyrite and arsenopyrite. During monomineral flotation, joint use of TMPD and butyl xanthate at a ratio of 1:1 doubles the yield of gold-bearing sulfides and enables maximum recovery of gold minerals at the total consumption of reagents reduced by 30–50%. It is found that TMPD is selective relative to gold-bearing minerals and its combination with xanthate ensures a considerable increment in gold-bearing mineral recovery by flotation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Blind Ptychographic Phase Retrieval via Convergent Alternating Direction Method of Multipliers

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A ptychographic reconstruction is normally formulated as a blind phase retrieval problem, where both the image (sample) and the probe (illumination) have to be recovered from phaseless measured data. In this article we address a nonlinear least squares model for the blind ptychography problem with constraints on the image and the probe by maximum likelihood estimation of the Poisson noise model. We formulate a variant model that incorporates the information of phaseless measurements of the probe to eliminate possible artifacts. Next, we propose a generalized alternating direction method of multipliers designed for the proposed nonconvex models with convergence guarantee under mild conditions, where their subproblems can be solved by fast el-ementwise operations. Numerically, the proposed algorithm outperforms state-of-the-art algorithms in both speed and image quality.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Trust in Artificial Intelligence: Meta-Analytic Findings

Objective The present meta-analysis sought to determine significant factors that predict trust in artificial intelligence (AI). Such factors were divided into those relating to (a) the human trustor, (b) the AI trustee, and (c) the shared context of their interaction. Background There are many factors influencing trust in robots, automation, and technology in general, and there have been several meta-analytic attempts to understand the antecedents of trust in these areas. However, no targeted meta-analysis has been performed examining the antecedents of trust in AI. Method Data from 65 articles examined the three predicted categories, as well as the subcategories of human characteristics and abilities, AI performance and attributes, and contextual tasking. Lastly, four common uses for AI (i.e., chatbots, robots, automated vehicles, and nonembodied, plain algorithms) were examined as further potential moderating factors. Results Results showed that all of the examined categories were significant predictors of trust in AI as well as many individual antecedents such as AI reliability and anthropomorphism, among many others. Conclusion Overall, the results of this meta-analysis determined several factors that influence trust, including some that have no bearing on AI performance. Additionally, we highlight the areas where there is currently no empirical research. Application Findings from this analysis will allow designers to build systems that elicit higher or lower levels of trust, as they require.

Behavioral Sciences↗
DOE OSTI2024

Existing evidence on the effects of climate variability and climate change on ungulates in North America: a systematic map

Abstract Background Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors. Climate conditions can directly impact ungulates via changes in the costs of thermoregulation and locomotion, or indirectly, via changes in habitat and forage availability, predation, and species interactions. Many studies have documented the effects of climate variability and climate change on North America’s ungulates, recording impacts to population demographics, physiology, foraging behavior, migratory patterns, and more. However, ungulate responses are not uniform and vary by species and geography. Here, we present a systematic map describing the abundance and distribution of evidence on the effects of climate variability and climate change on native ungulates in North America. Methods We searched for all evidence documenting or projecting how climate variability and climate change affect the 15 ungulate species native to the U.S., Canada, Mexico, and Greenland. We searched Web of Science, Scopus, and the websites of 62 wildlife management agencies to identify relevant academic and grey literature. We screened English-language documents for inclusion at both the title and abstract and full-text levels. Data from all articles that passed full-text review were extracted and coded in a database. We identified knowledge clusters and gaps related to the species, locations, climate variables, and outcome variables measured in the literature. Review findings We identified a total of 674 relevant articles published from 1947 until September 2020. Caribou ( Rangifer tarandus ), elk ( Cervus canadensis ), and white-tailed deer ( Odocoileus virginianus ) were the most frequently studied species. Geographically, more research has been conducted in the western U.S. and western Canada, though a notable concentration of research is also located in the Great Lakes region. Nearly 75% more articles examined the effects of precipitation on ungulates compared to temperature, with variables related to snow being the most commonly measured climate variables. Most studies examined the effects of climate on ungulate population demographics, habitat and forage, and physiology and condition, with far fewer examining the effects on disturbances, migratory behavior, and seasonal range and corridor habitat. Conclusions The effects of climate change, and its interactions with stressors such as land-use change, predation, and disease, is of increasing concern to wildlife managers. With its broad scope, this systematic map can help ungulate managers identify relevant climate impacts and prepare for future changes to the populations they manage. Decisions regarding population control measures, supplemental feeding, translocation, and the application of habitat treatments are just some of the management decisions that can be informed by an improved understanding of climate impacts. This systematic map also identified several gaps in the literature that would benefit from additional research, including climate effects on ungulate migratory patterns, on species that are relatively understudied yet known to be sensitive to changes in climate, such as pronghorn ( Antilocapra americana ) and mountain goats ( Oreamnos americanus ), and on ungulates in the eastern U.S. and Mexico.

Malpeli, Katherine C. (ORCID:000000030780918X)↗