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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Implications of z ~ 6 Quasar Proximity Zones for the Epoch of Reionization and Quasar Lifetimes

In this paper, we study quasar proximity zones in the redshift range $5.77\leqslant z\leqslant 6.54$ by homogeneously analyzing 34 medium-resolution spectra, encompassing both archival and newly obtained data, and exploiting recently updated systemic redshift and magnitude measurements. Whereas previous studies found strong evolution of proximity zone sizes with redshift and argued that this provides evidence for a rapidly evolving intergalactic medium (IGM) neutral fraction during reionization, we measure a much shallower trend $\propto {(1+z)}^{-1.44}$. We compare our measured proximity zone sizes to predictions from hydrodynamical simulations post-processed with one-dimensional radiative transfer and find good agreement between observations and theory, irrespective of the ionization state of the ambient IGM. This insensitivity to IGM ionization state has been previously noted, and results from the fact that the definition of proximity zone size as the first drop of the smoothed quasar spectrum below the 10% flux transmission level probes locations where the ionizing radiation from the quasar is an order of magnitude larger than the expected ultraviolet ionizing background that sets the neutral fraction of the IGM. Our analysis also uncovered three objects with exceptionally small proximity zones (two have ${R}_{p}\lt 1$ proper Mpc), which constitute outliers from the observed distribution and are challenging to explain with our radiative transfer simulations. Finally, we consider various explanations for their origin, such as strong absorption line systems associated with the quasar or patchy reionization, but find that the most compelling scenario is that these quasars have been shining for ≲10 5 years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Impact of point spread function higher moments error on weak gravitational lensing – II. A comprehensive study

ABSTRACT Weak lensing is one of the most powerful probes for dark matter and dark energy science, although it faces increasing challenges in controlling systematic uncertainties as the statistical errors become smaller. The point spread function (PSF) needs to be precisely modeled to avoid systematic error on the weak lensing measurements. The weak lensing biases induced by errors in the PSF model second moments, i.e. its size and shape, are well-studied. However, Zhang et al. showed that errors in the higher moments of the PSF may also be a significant source of systematics for upcoming weak lensing surveys. Therefore, this work comprehensively investigate the modelling quality of PSF moments from the 3rd to 6th order, and propagate the PSFEx higher moments modelling error in the HSC survey data set to the weak lensing shear–shear correlation functions and their cosmological analyses. The overall multiplicative shear bias associated with errors in PSF higher moments can cause an ∼0.1σ shift on the cosmological parameters for LSST Y10, while the associated additive biases can induce 1σ uncertainties in cosmology parameter inference for LSST Y10, if not accounted. We compare the PSFEx model with PSF in Full FOV, and find similar performance in modelling the PSF higher moments. We conclude that PSF higher moment errors of the future PSF models should be reduced from those in current methods, otherwise needed to be explicitly modeled in the weak lensing analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Photometric redshift estimation with convolutional neural networks and galaxy images: Case study of resolving biases in data-driven methods

Deep-learning models have been increasingly exploited in astrophysical studies, but these data-driven algorithms are prone to producing biased outputs that are detrimental for subsequent analyses. In this work, we investigate two main forms of biases: class-dependent residuals, and mode collapse. We do this in a case study, in which we estimate photometric redshift as a classification problem using convolutional neural networks (CNNs) trained with galaxy images and associated spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multichannel outputs, balancing the training data, and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshift or photometric redshift, and the biases with respect to these two definitions are incompatible and should be treated individually. We suggest that a prerequisite for resolving biases in photometric space is resolving biases in spectroscopic space. Experiments show that our methods can better control biases than benchmark methods, and they are robust in various implementing and training conditions with high-quality data. Our methods hold promises for future cosmological surveys that require a good constraint of biases, and they may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance tradeoff and the requirement of sufficient statistics suggest that we need better methods and optimized data usage strategies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1980

The GLAS physical inversion method for analysis of TIROS N data

The Goddard Laboratory for Atmospheric Sciences approach to temperature sounding from satellite observations is fundamentally different from that of NESS in that heavy reliance is placed on the ability to model accurately the instrumental response to atmospheric and surface conditions, while no use is made of statistical relationships between satellite observations and atmospheric temperature profiles. The method involves starting with a guess set of atmospheric and surface conditions from which expected brightness temperatures for the satellite observations are computed. Then, iterative relaxation of atmospheric and surface conditions is performed according to the difference between observed and computed brightness temperatures until sufficient agreement is reached. In the absence of sufficient agreement, no retrieval is produced for that location.

Susskind, J.↗
DOE OSTI2022

Efficient analysis routines for single and double peaked Type 2 AGN spectra

Driven by the imminent need to rapidly process and classify millions of AGN spectra drawn from next generation astronomical facilities, we present a spectral fitting routine for Type 2 AGN spectra optimized for high volume processing, using the quasar spectral fitting library (qsfit). We analyse an optically selected sample of 813 luminous Type 2 AGN spectra at z < 0.83 from the Sloan Digital Sky Survey (SDSS) to qualify its performance. We report a median narrow line H α/H β Balmer decrement of 4.5 ± 0.8, alluding to the presence of dust in the narrow line region (NLR). We publish a specialized QSFIT fitting routine for high signal-to-noise ratio spectra and general fitting routine for double peaked Type 2 AGN spectra applied on a subsample of 45 spectra from our parent sample. We report a median red and blue peak velocity separation of 390 ± 60 kms −1 . No trend is found for red or blue peaks to exhibit systematically different luminosity or ionization properties. Emission line diagnostics show that the double peaks in all sources are illuminated by an AGN-powered ionizing continuum. Finally, we examine the morphology of host galaxies of our double peaked sample. We find double peaked Type 2 AGN reside in merging systems at a comparable frequency to single peaked AGN. This suggests that the double peaked AGN phenomenon is likely to have a bi-conical outflow origin in the majority of cases. We publicly release the code used for spectral analysis and produced catalogues used in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

MALDI Orbitrap Mass Spectrometry Profiling of Dysregulated Sulfoglycosphingolipids in Renal Cell Carcinoma Tissues

Matrix-assisted laser desorption/ionization coupled with Orbitrap mass spectrometry (MALDI-Orbitrap-MS) is used for the clinical study of patients with renal cell carcinoma (RCC), as the most common type of kidney cancer. Significant changes in sulfoglycosphingolipid abundances between tumor and autologous normal kidney tissues are observed. First, sulfoglycosphingolipid species in studied RCC samples are identified using high mass accuracy full scan and tandem mass spectra. Subsequently, optimization, method validation, and statistical evaluation of MALDI-MS data for 158 tissues of 80 patients are discussed. More than 120 sulfoglycosphingolipids containing one to five hexosyl units are identified in human RCC samples based on the systematic study of their fragmentation behavior. Many of them are recorded here for the first time. Multivariate data analysis (MDA) methods, i.e., unsupervised principal component analysis (PCA) and supervised orthogonal partial least square discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples to reveal the most up- and downregulated lipids in tumor tissues. Obtained results are closely correlated with MALDI mass spectrometry imaging (MSI) and histologic staining. Important steps of the present MALDI-Orbitrap-MS approach are also discussed, such as the selection of best matrix, correct normalization, validation for semiquantitative study, and problems with possible isobaric interferences on closed masses in full scan mass spectra. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Passive microrheology of normal and cancer cells after ML7 treatment by atomic force microscopy

Mechanical properties of living cancer and normal thyroidal cells were investigated by atomic force microscopy (AFM). Cell mechanics was compared before and after treatment with ML7, which is known to reduce myosin activity and induce softening of cell structures. We recorded force curves with extended dwell time of 6 seconds in contact at maximum forces from 500 pN to 1 nN. Data were analyzed within different frameworks: Hertz fit was applied in order to evaluate differences in Young’s moduli among cell types and conditions, while the fluctuations of the cantilever in contact with cells were analyzed with both conventional algorithms (probability density function and power spectral density) and multifractal detrended fluctuation analysis (MF-DFA). We found that cancer cells were softer than normal cells and ML7 had a substantial softening effect on normal cells, but only a marginal one on cancer cells. Moreover, we observed that all recorded signals for normal and cancer cells were monofractal with small differences between their scaling parameters. Finally, the applicability of wavelet-based methods of data analysis for the discrimination of different cell types is discussed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

In a carbon-constrained world, future uses of nuclear power technologies can contribute to climate change mitigation as the installed electricity generating capacity and range of applications could be much greater and more diverse than with the current plants. To preserve the nuclear industry competitiveness in the global energy market, prognostics and health management (PHM) of plant assets is expected to be important for supporting and sustaining improvements in the economics associated with operating nuclear power plants (NPPs) while maintaining their high availability. Of interest are long-term operation of the legacy fleet to 80 years through subsequent license renewals and economic operation of new builds of either light water reactors or advanced reactor designs. Recent advances in data-driven analysis methods—largely represented by those in artificial intelligence and machine learning—have enhanced applications ranging from robust anomaly detection to automated control and autonomous operation of complex systems. The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management. This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015. The main approaches and the state of practice are described, including those for the tasks of data acquisition, condition monitoring, diagnostics, prognostics, and planning and decision-making. Research advances in non-nuclear power applications are also included to assess findings that may be applicable to the nuclear industry, along with the opportunities and challenges when adapting these developments to NPPs. Finally, this paper identifies key research needs in regard to data availability and quality, verification and validation, and uncertainty quantification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1976

Results of the asteroid-meteoroid particle experiment on Pioneer 11

The Asteroid-Meteoroid Detector, an electro-optical instrument that detects and measures particles in space by sensing the sunlight reflected from them, is part of the payload of both the Pioneer 10 and 11 spacecraft. The Pioneer 11 instrument is essentially identical to that on Pioneer 10, with some minor modifications. Reduction of the Pioneer 11 data was complicated by the failure of one of the four sensor channels at about 1.1 AU from the sun. Detailed analysis yielded 51 events between 1.0 and 3.5 AU, which were used to determine the particle concentration distribution in that region of space. Weighted curve-fitting of the results shows agreement with the concentrations derived from Pioneer 10 to within about a factor of two. As with the Pioneer 10 results, the exponent of the size dependency varies from about -1.7 for 100-micron radius particles to about -3.2 for 10-cm bodies. The instrument, its operation, and the method of data analysis are reviewed.

Soberman, R. K.↗
DOE OSTI2018

Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era

The Large Synoptic Survey Telescope (LSST) will produce an unprecedented amount of light curves using six optical bands. Robust and efficient methods that can aggregate data from multidimensional sparsely sampled time-series are needed. Here, we present a new method for light curve period estimation based on quadratic mutual information (QMI). The presented method does not assume a particular model for the light curve nor its underlying probability density and it is robust to non-Gaussian noise and outliers. By combining the QMI from several bands the true period can be estimated even when no single-band QMI yields the period. Period recovery performance as a function of average magnitude and sample size is measured using 30,000 synthetic multiband light curves of RR Lyrae and Cepheid variables generated by the LSST Operations and Catalog simulators. The results show that aggregating information from several bands is highly beneficial in LSST sparsely sampled time-series, obtaining an absolute increase in period recovery rate up to 50%. We also show that the QMI is more robust to noise and light curve length (sample size) than the multiband generalizations of the Lomb–Scargle and AoV periodograms, recovering the true period in 10%–30% more cases than its competitors. A python package with efficient Cython implementations of the QMI and other methods is provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Weak lensing magnification in the Dark Energy Survey Science Verification data

In this paper the effect of weak lensing magnification on galaxy number counts is studied by cross-correlating the positions of two galaxy samples, separated by redshift, using data from the Dark Energy Survey Science Verification dataset. The analysis is carried out for two photometrically-selected galaxy samples, with mean photometric redshifts in the $0.2 < z < 0.4$ and $0.7 < z < 1.0$ ranges, in the riz bands. A signal is detected with a $3.5\sigma$ significance level in each of the bands tested, and is compatible with the magnification predicted by the $\Lambda$CDM model. After an extensive analysis, it cannot be attributed to any known systematic effect. The detection of the magnification signal is robust to estimated uncertainties in the outlier rate of the pho- tometric redshifts, but this will be an important issue for use of photometric redshifts in magnification mesurements from larger samples. In addition to the detection of the magnification signal, a method to select the sample with the maximum signal-to-noise is proposed and validated with data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

Structure in the 3D Galaxy Distribution: III. Fourier Transforming the Universe: Phase and Power Spectra

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited sample of the Sloan Digital Sky Survey redshift survey. The direct unbinned transform yields a complex 3D data cube quite similar to that from the Fast Fourier Transform (FFT) of finely binned galaxy positions. In both cases deconvolution of the sampling window function yields estimates of the true transform. Simple power spectrum estimates from these transforms are roughly consistent with those using more elaborate methods. The complex Fourier transform characterizes spatial distributional properties beyond the power spectrum in a manner different from (and we argue is more easily interpreted than) the conventional multi-point hierarchy. We identify some threads of modern large scale inference methodology that will presumably yield detections in new wider and deeper surveys.

Galactic clusters↗
NASA NTRS2017

Structure in the 3D Galaxy Distribution. III. Fourier Transforming the Universe: Phase and Power Spectra

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited sample of the Sloan Digital Sky Survey redshift survey. The direct unbinned transform yields a complex 3D data cube quite similar to that from the Fast Fourier Transform of finely binned galaxy positions. In both cases, deconvolution of the sampling window function yields estimates of the true transform. Simple power spectrum estimates from these transforms are roughly consistent with those using more elaborate methods. The complex Fourier transform characterizes spatial distributional properties beyond the power spectrum in a manner different from (and we argue is more easily interpreted than) the conventional multipoint hierarchy. We identify some threads of modern large-scale inference methodology that will presumably yield detections in new wider and deeper surveys.

Galaxies↗
DOE OSTI2023

A multifrequency characterization of the extragalactic hard X-ray sky

Context: Nowadays, we know that the origin of the cosmic X-ray background (CXB) is mainly due to the integrated emission of active galactic nuclei. Therefore, in order to obtain a precise estimate of the contribution of different source classes to the CXB, it is crucial to achieve full characterization of the hard-X ray sky. Aims: We present a multifrequency analysis of all sources listed in the third release of the Palermo Swift-BAT hard X-ray catalog (3PBC) with the goal of (i) identifying and classifying the largest number of sources adopting multifrequency criteria, with particular emphasis on extragalactic populations and (ii) extracting sources belonging to the class of Seyfert galaxies to present here the release of the second version of the Turin-SyCAT. Methods: We outline a classification scheme based on radio, infrared (IR), and optical criteria that allows us to distinguish between unidentified and unclassified hard X-ray sources, as well as to classify those sources belonging to the Galactic and the extragalactic populations. Results: Our revised version of the 3PBC lists 1176 classified, 820 extragalactic, and 356 Galactic sources, as well as 199 unclassified and 218 unidentified sources. According to our analysis, the hard X-ray sky is mainly populated by Seyfert galaxies and blazars. For the blazar population, we report trends between the hard X-ray and the gamma-ray emissions based on the fact that a large fraction of them also have a counterpart detected by the Fermi satellite. These trends are all in agreement with the expectations of inverse Compton models which are widely adopted to explain the blazar broadband emission. For the Seyfert galaxies, we present the second version of the Turin-SyCAT, including a total of 633 Seyfert galaxies, with 282 new sources corresponding to an increase of ~80% with respect to the previous release. Comparing the hard X-ray and the infrared emissions of Seyfert galaxies, we confirm that there is no clear difference between the flux distribution of the infrared-to-hard X-ray flux ratio of Seyfert galaxies Type 1 and Type 2. However, there is a significant trend between the mid-IR flux and hard X-ray flux, confirming previous statistical results in the literature. Conclusions: We provide two catalog tables. The first is the revised version of the 3PBC catalog based on our multifrequency analyses. The second catalog table is a release of the second version of the Turin-SyCAT catalog. Finally, we highlight that extensive soft X-ray data are already available in the form of the Swift archive which can be used to search for potential counterparts of unidentified hard X-ray sources. All these datasets will be reduced and analyzed in a forthcoming analysis to determine the precise position of low-energy counterparts in the 0.5–10 keV energy range for 3PBC sources that can be targets of future optical spectroscopic campaigns; this is necessary to obtain their precise classification.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

High pressure thermoelasticity and sound velocities of Fe-Ni-Si alloys

The Earth's iron-dominant core is known to contain nickel from cosmochemical analysis and some amount of light elements from geophysical constraints on density and seismic wave velocities. Although there have been several studies to constrain thermoelastic properties of iron-alloys, there has been no systematic study on the effects of nickel and light elements on properties of iron using the same experimental methods and data analysis approach. We conducted nuclear resonant inelastic X-ray scattering and X-ray diffraction experiments on body-centered cubic and hexagonal close-packed (hcp) Fe 0.91 Ni 0.09 and Fe 0.8 Ni 0.1 Si 0.1 up to 104 GPa and 86 GPa, respectively, and compare to similar measurements conducted on hcp-Fe up to 171 GPa. Specifically, we determine the Debye sound velocity from the low-energy transfer region of the (partial) phonon density of states (DOS) using the equation of state determined for each material and a new approach which utilizes information criteria and probability distributions. Nickel decreases the shear velocity of iron, while 10 at% Si has little to no effect on the shear velocity of Fe 0.91 Ni 0.09 . We observe that the shape of the phonon DOS of these alloys remains similar with increasing pressure. In the measured compression range, we therefore apply a generalized scaling law to describe the volume dependence of the phonon DOS and find that the vibrational Grüneisen parameters of hcp-Fe 0.91 Ni 0.09 are nearly indistinguishable from those hcp-Fe and those for Fe 0.8 Ni 0.1 Si 0.1 trend lower. From the vibrational free energy, we constrain the harmonic vibrational component of thermal pressure, which shows a significant positive deviation from theoretical calculations of hcp-Fe at pressures and temperatures of Earth's core. Collectively, our results demonstrate that the effects of nickel should be considered when modeling iron-rich planetary cores.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Extracting enzyme processivity from kinetic assays

A steady-state analysis for the catalytic turnover of molecules containing two substrate sites is presented. A broad class of Markovian dynamic models, motivated by the action of DNA modifying enzymes and the rich variety of translocation mechanisms associated with these systems (e.g., sliding, hopping, intersegmental transfer, etc.), is considered. The modeling suggests an elementary and general method of data analysis, which enables the extraction of the enzyme’s processivity directly and unambiguously from experimental data. This analysis is not limited to the initial velocity regime. The predictions are validated both against detailed numerical models and by revisiting published experimental data for EcoRI endonuclease acting on DNA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Alcock–Paczynski effect from Lyman- α forest correlations: analysis validation with synthetic data

The three-dimensional distribution of the Ly α forest has been extensively used to constrain cosmology through measurements of the baryon acoustic oscillations (BAO) scale. However, more cosmological information could be extracted from the full shapes of the Ly α forest correlations through the Alcock–Paczynski (AP) effect. In this work, we prepare for a cosmological analysis of the full shape of the Ly α forest correlations by studying synthetic data of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We use a set of 100 eBOSS synthetic data sets in order to validate such an analysis. These mocks undergo the same analysis process as the real data. We perform a full-shape analysis on the mean of the correlation functions measured from the 100 eBOSS realizations, and find that our model of the Ly α correlations performs well on current data sets. We show that we are able to obtain an unbiased full-shape measurement of D M /D H (z eff ), where D M is the transverse comoving distance, D H is the Hubble distance, and z eff is the effective redshift of the measurement. We test the fit over a range of scales, and decide to use a minimum separation of r min = 25 h –1 Mpc. Here, we also study and discuss the impact of the main contaminants affecting Ly α forest correlations, and give recommendations on how to perform such analysis with real data. While the final eBOSS Ly α BAO analysis measured D M /D H (z eff = 2.33) with 4 per cent statistical precision, a full-shape fit of the same correlations could provide an $\sim 2~{{\ \rm per\ cent}}$ measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Landscaper v1

Understanding the inner workings of machine learning models through their loss landscapes offers crucial insights into model properties, optimization dynamics, and generalizability. However, accessing these insights has traditionally required specialized mathematical expertise, limiting broader adoption. Landscaper is an open-source Python package designed to bridge this gap. Landscaper seamlessly integrates a suite of multi-dimensional loss landscape analyses with cutting-edge topological data analysis (TDA) methods. This powerful combination makes both fundamental loss landscape analysis and advanced TDA techniques accessible to the broader scientific ML community, without requiring deep pre-existing mathematical knowledge. Landscaper offers three key functionalities: * Construction: Builds detailed loss landscape representations through versatile low and high-dimensional sampling techniques. * Quantification: Applies advanced metrics, including a novel topological data analysis (TDA) based smoothness metric, enabling new perspectives on model behavior. * Visualization: Offers intuitive tools to visualize and interpret loss landscapes, providing actionable insights beyond traditional performance metrics.

Weber, Gunther [Lawrence Berkeley National Laborat↗