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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Carbonated apatite lattice parameter variation across incremental growth lines in teeth

Here, results of microbeam mapping (x-ray excited x-ray fluorescence and transmission x-ray diffraction) of Beluga whale cementum and of beaver dentin reveal growth bands are defined by variation in mineral content (carbonated hydroxyapatite, cAp), by variation in Zn content and by variation in cAp lattice parameter a. For both tissues, diffraction and fluorescence data show that Zn signal and a are anti-correlated, that is high Zn signal is co-located with low a, and vice versa. In cementum and bone, treatment with acid removes Ca, Zn and cAp. The data are strong evidence that Zn is incorporated into the cAp lattice in these tissues and that the amount of Zn incorporated varies across two very different types of growth bands, annual bands in Beluga cementum and daily incremental bands in beaver dentin. To the best of the authors’ knowledge, this is the first observation of spatial variation of lattice parameter within growth bands.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Parameter space for magnetization effects in high-energy-density plasmas

Magnetic fields are well known to affect the evolution of fluids via the J × B force, where J is the current density and B is the magnetic field. This force leads to the influence of magnetic fields on hydrodynamics (magnetohydrodynamics). Magnetic fields are often neglected in modeling of high-energy-density plasmas, since J × B is very small compared with the plasma pressure gradients. However, many experiments lie in a separate part of parameter space where the plasma is indirectly affected via magnetization of the heat flux and charged particle transport. This is true even for initially unmagnetized plasmas, since misaligned density and temperature gradients can self-generate magnetic fields. By comparing terms in the induction equation, we go on to estimate the regions of parameter space where these self-generated fields are strong enough to affect the hydrodynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Particle-in-cell modeling of plasma jet merging in the large-Hall-parameter regime

The merging process of magnetized plasma jets with parameters relevant to the plasma-jet-driven magneto-inertial fusion (PJMIF) design and the plasma liner experiment (PLX) is modeled by fully kinetic particle-in-cell (PIC) simulations in one and two spatial dimensions. Here, the modified two-stream instability is identified to be the main mechanism responsible for stopping the plasma jets and preventing species interpenetration. The electron and ion Hall parameters of the merged plasma are greater than unity, and the plasma β is close to unity, which is the desired characteristic of planned experiments at PLX. Our 2D PIC simulations validate the results of the radiation magneto-hydrodynamics code FLASH, which will be the primary tool for modeling various stages of future PJMIF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatially and temporally resolved plasma parameter estimations of laser heated MagLIF relevant gas pipes at NIF

The ability to control laser pre-heat is an integral part of the inertial confinement fusion concept known as Magnetized Liner Inertial Fusion. This process is studied at the National Ignition Facility (NIF) where 4 of the 192 laser beams are propagated through a 1-cm long gas cell where they deposit >20 kJ of energy into the gaseous fuel via inverse bremsstrahlung absorption. This process ionizes the gas, producing a plasma that follows behind the laser front and expands over the radius of the cell. Emission from this plasma, as viewed by a gated x-ray detector, can be used to build spatially and temporally resolved estimations of the pre-heat plasma's density and temperature profiles. This can then be used to estimate the plasma pressure, internal energy, and radiation losses. Estimations show the evolution of the plasma in magnetized and unmagnetized gas cells filled with ambient temperature neopentane (C5H12) +1% Ar, as well as unmagnetized cryogenically cooled (32 K) deuterium +1% Ne filled targets. This analysis shows the effects of initial gas-fill density, composition, and axial magnetization on the time-dependent plasma parameters. Previously, these parameters at the NIF had not been experimentally characterized, and these estimations provided a potential new means of testing radiation magneto-hydrodynamic predictive capability models. Results in unmagnetized targets have strong agreement with simulations. However, in targets with a 19 T applied axial magnetic field, this method yields electron temperatures up to 100% hotter than those predicted by HYDRA codes.

Bremsstrahlung↗
DOE OSTI2023

Dramatic relativistic effects on the ns dipole angular distribution asymmetry parameter, β ns , of heavy and superheavy elements

A theoretical study of the dipole photoelectron angular distribution asymmetry parameter, β, of the 6s, 5s and 4s subshells has been conducted for a range of closed-shell heavy, Hg (Z = 80), Rn (Z = 86), Ra (Z = 88) and superheavy, No (Z = 102), Cn (Z = 112), Og (Z = 118), Ubn (Z = 120) elements to understand the deviation of β from the nonrelativistic value of 2 owing to relativistic effects. It was found that the deviation, strongest in Cooper minimum regions, persists over all energy for all ns subshells, and the deviations increase with Z. Furthermore, three levels of relativistic calculations were performed in order to pinpoint the particular interactions responsible for the details of the behavior of the ns β's as functions of energy, n, and Z and, in addition to the effects of the (relativistic) spin–orbit interaction, interchannel coupling was found to be of crucial importance in the determination of the β parameter in most of the situations studied.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

The Atacama Cosmology Telescope: DR4 maps and cosmological parameters

In this paper, we present new arcminute-resolution maps of the Cosmic Microwave Background temperature and polarization anisotropy from the Atacama Cosmology Telescope, using data taken from 2013–2016 at 98 and 150 GHz. The maps cover more than 17,000 deg 2 , the deepest 600 deg 2 with noise levels below 10µK-arcmin. We use the power spectrum derived from almost 6,000 deg 2 of these maps to constrain cosmology. The ACT data enable a measurement of the angular scale of features in both the divergence-like polarization and the temperature anisotropy, tracing both the velocity and density at last-scattering. From these one can derive the distance to the last-scattering surface and thus infer the local expansion rate, H 0 . By combining ACT data with large-scale information from WMAP we measure H 0 = 67.6±1.1 km/s/Mpc, at 68% confidence, in excellent agreement with the independently-measured Planck satellite estimate (from ACT alone we find H 0 = 67.9 ± 1.5 km/s/Mpc). The ΛCDM model provides a good fit to the ACT data, and we find no evidence for deviations: both the spatial curvature, and the departure from the standard lensing signal in the spectrum, are zero to within 1σ; the number of relativistic species, the primordial Helium fraction, and the running of the spectral index are consistent with ΛCDM predictions to within 1.5–2.2σ. We compare ACT, WMAP, and Planck at the parameter level and find good consistency; we investigate how the constraints on the correlated spectral index and baryon density parameters readjust when adding CMB large-scale information that ACT does not measure. The DR4 products presented here will be publicly released on the NASA Legacy Archive for Microwave Background Data Analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Statistically-informed deep learning for gravitational wave parameter estimation

We introduce deep learning models to estimate the masses of the binary components of black hole mergers, $(m_1,m_2)$, and three astrophysical properties of the post-merger compact remnant, namely, the final spin, $a_\mathrm f$, and the frequency and damping time of the ringdown oscillations of the fundamental $\ell = m = 2$ bar mode, $(\omega_\mathrm R, \omega_\mathrm I)$. Our neural networks combine a modified WaveNet architecture with contrastive learning and normalizing flow. We validate these models against a Gaussian conjugate prior family whose posterior distribution is described by a closed analytical expression. Upon confirming that our models produce statistically consistent results, we used them to estimate the astrophysical parameters $(m_1,m_2, a_\mathrm f, \omega_\mathrm R, \omega_\mathrm I)$ of five binary black holes: GW150914, GW170104, GW170814, GW190521 and GW190630. We use PyCBC Inference to directly compare traditional Bayesian methodologies for parameter estimation with our deep learning based posterior distributions. Our results show that our neural network models predict posterior distributions that encode physical correlations, and that our data-driven median results and 90% confidence intervals are similar to those produced with gravitational wave Bayesian analyses. This methodology requires a single V100 NVIDIA GPU to produce median values and posterior distributions within two milliseconds for each event. Furthermore, this neural network, and a tutorial for its use, are available at the Data and Learning Hub for Science.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bayesian experimental design and parameter estimation for ultrafast spin dynamics

Abstract Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and materials physics, which often suffer from the scarcity of large-scale facility resources, such as x-ray or neutron scattering centers. To address these limitations, we introduce a methodology that leverages the Bayesian optimal experimental design paradigm to efficiently uncover key quantum spin fluctuation parameters from x-ray photon fluctuation spectroscopy (XPFS) data. Our method is compatible with existing theoretical simulation pipelines and can also be used in combination with fast machine learning surrogate models in the event that real-time simulations are unfeasible. Our numerical benchmarks demonstrate the superior performance in predicting model parameters and in delivering more informative measurements within limited experimental time. Our method can be adapted to many different types of experiments beyond XPFS and spin fluctuation studies, facilitating more efficient data collection and accelerating scientific discoveries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Standardizing Dainotti-correlated gamma-ray bursts, and using them with standardized Amati-correlated gamma-ray bursts to constrain cosmological model parameters

ABSTRACT We show that each of the three Dainotti-correlated gamma-ray burst (GRB) data sets recently compiled by Wang et al. and Hu et al., that together probe the redshift range 0.35 ≤ z ≤ 5.91, obey cosmological-model-independent Dainotti correlations and so are standardizable. We use these GRB data in conjunction with the best currently available Amati-correlated GRB data, that probe 0.3399 ≤ z ≤ 8.2, to constrain cosmological model parameters. The resulting cosmological constraints are weak, providing lower limits on the non-relativistic matter density parameter, mildly favouring non-zero spatial curvature, and largely consistent with currently accelerated cosmological expansion as well as with constraints determined from better-established data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Using Pantheon and DES supernova, baryon acoustic oscillation, and Hubble parameter data to constrain the Hubble constant, dark energy dynamics, and spatial curvature

ABSTRACT We use Pantheon Type Ia supernova (SN Ia) apparent magnitude, DES-3 yr binned SN Ia apparent magnitude, Hubble parameter, and baryon acoustic oscillation measurements to constrain six spatially flat and non-flat cosmological models. These sets of data provide mutually consistent cosmological constraints in the six cosmological models we study. A joint analysis of these data sets provides model-independent estimates of the Hubble constant, $H_0=68.8\pm 1.8\ \rm {km \, s^{-1} \ Mpc^{-1}}$, and the non-relativistic matter density parameter, $\Omega _{\rm m_0}=0.294\pm 0.020$. Although the joint constraints prefer mild dark energy dynamics and a little spatial curvature, they do not rule out dark energy being a cosmological constant and flat spatial hypersurfaces. We also add quasar angular size and H ii starburst galaxy measurements to the combined data set and find more restrictive constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the impact of the galaxy window function on cosmological parameter estimation

One important source of systematics in galaxy redshift surveys comes from the estimation of the galaxy window function. Up until now, the impact of the uncertainty in estimating the galaxy window function on parameter inference has not been properly studied. In this paper, we show that the uncertainty and the bias in estimating the galaxy window function will be salient for ongoing and next-generation galaxy surveys using a simulation-based approach. With a specific case study of cross-correlating emission-line galaxies from the DESI Legacy Imaging Surveys and the Planck cosmic microwave background lensing map, we show that neural network-based regression approaches to modelling the window function are superior in comparison to linear regression-based models. Here, we additionally show that the definition of the galaxy overdensity estimator can impact the overall signal-to-noise of observed power spectra. Finally, we show that the additive biases coming from the window functions can significantly bias the modes of the inferred parameters and also degrade their precision. Thus, a careful understanding of the window functions will be essential to conduct cosmological experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Non-Gaussian estimates of tensions in cosmological parameters

We discuss how to efficiently and reliably estimate the level of agreement and disagreement on parameter determinations from different experiments, fully taking into account non-Gaussianities in the parameter posteriors. We develop two families of scalable algorithms that allow us to perform this type of calculations in increasing number of dimensions and for different levels of tensions. One family of algorithms rely on kernel density estimates of posterior distributions while the other relies on machine learning modeling of the posterior distribution with normalizing flows. We showcase their effectiveness and accuracy with a set of benchmark examples and find both methods agree with each other and the true tension within 0.5σ in difficult cases and generally to 0.2σ or better. This allows us to study the level of internal agreement between different measurements of the clustering of cosmological structures from the Dark Energy Survey and their agreement with measurements of the Cosmic Microwave Background from the Planck satellite.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Constraints on f ( R ) and normal-branch Dvali-Gabadadze-Porrati modified gravity model parameters with cluster abundances and galaxy clustering

In this report we present forecasted cosmological constraints from combined measurements of galaxy cluster abundances from the Simons Observatory and galaxy clustering from a DESI-like experiment on two well-studied modified gravity models, the chameleon-screened Hu-Sawicki f(R) model and the nDGP braneworld Vainshtein model. A Fisher analysis is conducted using σ 8 constraints derived from thermal Sunyaev-Zel’dovich (tSZ) selected galaxy clusters as well as linear and quasilinear redshift-space 2-point galaxy correlation functions. We find that the cluster abundances drive the constraints on the nDGP model while f(R) constraints are led by galaxy clustering. The two tracers of the cosmological gravitational field are found to be complementary, and their combination significantly improves constraints on the f(R) in particular in comparison to each individual tracer alone. For a model of f(R) with a general relativity (GR) fiducial case (f R0 = 0), we find a 2-σ upper limit of f R0 ≤ 5.68 x10 -7 . For the well-studied log-based fiducial parameter value in f(R), log 10 (f R0 ) = -5, paired with the parameter value n = 1, we find combined 1-σ constraints of σ(log 10 (f R0 )) = 0.12 and σ(n) = 0.36. For the nDGP model with fiducial n nDGP = 1 we find σ( n nDGP ) = 0.087. Our results present the exciting potential to utilize upcoming galaxy and CMB survey data available in the near future to discern and/or constrain cosmic deviations from GR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Anisotropic field-induced changes in the superconducting order parameter of UTe 2

UTe 2 is a newly discovered unconventional superconductor, where electron Cooper pairs combine into a spin-triplet ground state. We study the specific heat C( H,T ) of a high-quality UTe 2 single crystal, with a single anomaly at a high superconducting transition temperature T c = 2.1 K and a low residual Sommerfeld coefficient γ 0 . Applying magnetic fields up to 12 T along the crystallographic axes a, b , and c , we observe highly anisotropic behavior in γ 0 ( H ). Below 4 T, γ 0 ( H ) ≈ γ 0 + λi √H (i = a, b, c) , which is expected for an unconventional superconductor with nodes on the Fermi surface away from the direction of the magnetic field. At 4 T ( a and b axes) and 5.5 T ( c axis), distinctive changes in the behavior of γ 0 (H) suggest that a stable low-field ground state begins to evolve above 4 T. The data analysis indicates that the nodes are located near the a–b plane, with possible order parameters d B2u + iεd B1u or d B2u + iεd Au . Our findings support B 2u as the primary superconducting order parameter in UTe 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Enhanced Multi-Dimensional Inversion Through Target-Specific Inversion Parameter Bounds With an Application to Crosswell Electromagnetic for Sequestration Monitoring

In geophysical inversions, lower and upper model parameter bounds are a means of solution stabilization. Further, constraints that intend to let only geologically plausible inverse solutions pass are amenable to lower and upper bounds. Reliable prior information is paramount to construct such bound constraints. It is common practice to narrow and widen bound intervals for regions of, respectively, more and less certain prior information. Contrary to this practice, we experiment with widened bound intervals in zones that are poorly resolved by a given survey configuration but where prior information would suggest structural anomalies of interest. The purpose of enlarged parameter bounds that correlate spatially with predefined targets is to let the inversion explore a larger solution space, thus increasing the potential to resolve otherwise hidden anomalies. Application of the method is based on a carbon-sequestration baseline (pre-injection) crosswell electromagnetic (EM) field survey at the Containment and Monitoring Institute Field Research Station (Alberta, Canada), where impeded measurements led to generally reduced sensitivities for the interwell region. Synthetic-data proofs of concept use augmented bounds designed to boost the resolution of artificial plume targets, indicating an enhanced illumination compared to constant bounds. Comparative field data inversions with spatially variable bounds constructed from prior resistivity and velocity information highlight non-horizontal baseline structures.

3-D electrical resistivity imaging↗
DOE OSTI2021

Optimal Cosmic Microwave Background Lensing Reconstruction and Parameter Estimation with SPTpol Data

Here, we perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg 2 of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 μK arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly suboptimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be ${A}_{\phi }=0.949\,\pm \,0.122$ using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist "bias hardening" or linear bias correction, and reducing the systematic uncertainty on A Φ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain A Φ along with A L , the amplitude of lensing-like effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easily infer parameters both from an optimal lensing reconstruction and from the delensed CMB, while exactly accounting for the correlation between the two. These results demonstrate the feasibility of the Bayesian approach on real data, and pave the way for future analysis of deep CMB polarization measurements with SPT-3G, Simons Observatory, and CMB-S4, where improvements relative to the QE can reach 1.5 times tighter constraints on A Φ and seven times lower effective lensing reconstruction noise.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

On the relationshop between polarimetric parameters and soil moisture

In this paper, we examine the relationship between polarimetric parameters and soil moisture. For example, the co-polarization ratio is independent of surface roughness to the first order of the small perturbation approximation. As surface roughness increases, it can be shown that the co-polarization ratio depends on the surface slope under the tilted Bragg approximation. The coupling of the surface roughness to the co-polarization ratio is theoretically investigated. An algorithm to compensate the surface slope effect will be discussed. We will also study other polarimetric parameters such as the average alpha angle and eigenvalues to understand their relationship with soil moisture.

polarimetric parameters soil moisture↗