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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Bulge growth and quenching since z = 2.5 in CANDELS/3D-HST

Exploiting the deep high-resolution imaging of all five CANDELS fields, and accurate redshift information provided by 3D-HST, we investigate the relation between structure and stellar populations for a mass-selected sample of 6764 galaxies above 10{sup 10} M {sub ☉}, spanning the redshift range 0.5 < z < 2.5. For the first time, we fit two-dimensional models comprising a single Sérsic fit and two-component (i.e., bulge + disk) decompositions not only to the H-band light distributions, but also to the stellar mass maps reconstructed from resolved stellar population modeling. We confirm that the increased bulge prominence among quiescent galaxies, as reported previously based on rest-optical observations, remains in place when considering the distributions of stellar mass. Moreover, we observe an increase of the typical Sérsic index and bulge-to-total ratio (with median B/T reaching 40%-50%) among star-forming galaxies above 10{sup 11} M {sub ☉}. Given that quenching for these most massive systems is likely to be imminent, our findings suggest that significant bulge growth precedes a departure from the star-forming main sequence. We demonstrate that the bulge mass (and ideally knowledge of the bulge and total mass) is a more reliable predictor of the star-forming versus quiescent state of a galaxy than the total stellar mass. The same trends are predicted by the state-of-the-art, semi-analytic model by Somerville et al. In this model, bulges and black holes grow hand in hand through merging and/or disk instabilities, and feedback from active galactic nuclei shuts off star formation. Further observations will be required to pin down star formation quenching mechanisms, but our results imply that they must be internal to the galaxies and closely associated with bulge growth.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Expansion-history preferences of DESI DR2 and external data

We explore the origin of the preference of Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) baryon acoustic oscillation measurements and external data from cosmic microwave background (CMB) and type Ia supernovae (SNIa) that dark energy behavior departs from that expected in the standard cosmological model with vacuum energy (Λ ⁢CDM). In our analysis, we allow a flexible scaling of the expansion rate with redshift that nevertheless allows reasonably tight constraints on the quantities of interest, and adopt and validate a simple yet accurate compression of the CMB data that allows us to constrain our phenomenological model of the expansion history. We find that data consistently show a preference for a 3%–4% increase in the expansion rate at 𝑧 ≃ 0.7 relative to that predicted by the standard Λ⁢ CDM model, in excellent agreement with results from the less flexible (𝑤 0 ,𝑤 𝑎 ) parametrization which was used in previous analyses. Even though our model allows a departure from the best-fit Λ⁢ CDM model at zero redshift, we find no evidence for such a signal. We also find no evidence (at greater than 1⁢𝜎 significance) for a departure of the expansion rate from the Λ ⁢CDM predictions at higher redshifts for any of the data combinations that we consider. Altogether, our results strengthen the robustness of the findings using the combination of DESI, CMB, and SNIa data to dark-energy modeling assumptions.

Cosmological parameters↗
DOE OSTI2017

The effect of self-consistent potentials on EXAFS analysis

A theory program intended for use with extended X-ray-absorption fine structure (EXAFS) spectroscopy and based on the popular FEFF8 is presented. It provides an application programming interface designed to make it easy to integrate high-quality theory into EXAFS analysis software. This new code is then used to examine the impact of self-consistent scattering potentials on EXAFS data analysis by methodical testing of theoretical fitting standards against a curated suite of measured EXAFS data. For each data set, the results of a fit are compared using a well characterized structural model and theoretical fitting standards computed both with and without self-consistent potentials. It is demonstrated that the use of self-consistent potentials has scant impact on the results of the EXAFS analysis.

Instruments & Instrumentation↗
DOE OSTI2022

Comparison of AGR-3/4 Fission Product Transport Model to Measurements and Extraction of Diffusivities via Analytical Fits

A one-dimensional finite-element model based on the MOOSE framework has been constructed, and overall transport estimates are predicted based on available diffusivities and sorption isotherms in the extant literature. The predicted transport profiles are compared to experimental results, where such results are available, including total inventory analysis of gamma emitters, liquid scintillation results for Sr-90 concentrations, radial deconsolidation leach-burn-leach within compacts, tomographic reconstructions based on detailed gamma scanning and destructive physical sampling of several rings. The magnitude of expected transport to the sink ring is generally predicted by the model for silver and cesium, however, modeled detailed concentration profiles are not consistent with experimental results. Strontium and europium transport is not well characterized by model results.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Deep energy-pressure regression for a thermodynamically consistent EOS model

Abstract In this paper, we aim to explore novel machine learning (ML) techniques to facilitate and accelerate the construction of universal equation-Of-State (EOS) models with a high accuracy while ensuring important thermodynamic consistency. When applying ML to fit a universal EOS model, there are two key requirements: (1) a high prediction accuracy to ensure precise estimation of relevant physics properties and (2) physical interpretability to support important physics-related downstream applications. We first identify a set of fundamental challenges from the accuracy perspective, including an extremely wide range of input/output space and highly sparse training data. We demonstrate that while a neural network (NN) model may fit the EOS data well, the black-box nature makes it difficult to provide physically interpretable results, leading to weak accountability of prediction results outside the training range and lack of guarantee to meet important thermodynamic consistency constraints. To this end, we propose a principled deep regression model that can be trained following a meta-learning style to predict the desired quantities with a high accuracy using scarce training data. We further introduce a uniquely designed kernel-based regularizer for accurate uncertainty quantification. An ensemble technique is leveraged to battle model overfitting with improved prediction stability. Auto-differentiation is conducted to verify that necessary thermodynamic consistency conditions are maintained. Our evaluation results show an excellent fit of the EOS table and the predicted values are ready to use for important physics-related tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Dark Energy Survey Year 3 and eBOSS: constraining galaxy intrinsic alignments across luminosity and colour space

ABSTRACT We present direct constraints on galaxy intrinsic alignments (IAs) using the Dark Energy Survey Year 3 (DES Y3), the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and its precursor, the Baryon Oscillation Spectroscopic Survey (BOSS). Our measurements incorporate photometric red sequence (redMaGiC) galaxies from DES with median redshift z ∼ 0.2–1.0, luminous red galaxies from eBOSS at z ∼ 0.8, and also an SDSS-III BOSS CMASS sample at z ∼ 0.5. We measure two-point IA correlations, which we fit using a model that includes lensing, magnification, and photometric redshift error. Fitting on scales 6 Mpc h−1 < rp < 70 Mpc h−1, we make a detection of IAs in each sample, at 5σ–22σ (assuming a simple one-parameter model for IAs). Using these red samples, we measure the IA–luminosity relation. Our results are statistically consistent with previous results, but offer a significant improvement in constraining power, particularly at low luminosity. With this improved precision, we see detectable dependence on colour between broadly defined red samples. It is likely that a more sophisticated approach than a binary red/blue split, which jointly considers colour and luminosity dependence in the IA signal, will be needed in future. We also compare the various signal components at the best-fitting point in parameter space for each sample, and find that magnification and lensing contribute $\sim 2\!-\!18~{{\ \rm per\ cent}}$ of the total signal. As precision continues to improve, it will certainly be necessary to account for these effects in future direct IA measurements. Finally, we make equivalent measurements on a sample of emission-line galaxies from eBOSS at z ∼ 0.8. We constrain the non-linear alignment amplitude to be $A_1=0.07^{+0.32}_{-0.42}$ (|A1| < 0.78 at 95 per cent CL).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole

We present measurements of the properties of the central radio source in M87 using Event Horizon Telescope data obtained during the 2017 campaign. We develop and fit geometric crescent models (asymmetric rings with interior brightness depressions) using two independent sampling algorithms that consider distinct representations of the visibility data. We show that the crescent family of models is statistically preferred over other comparably complex geometric models that we explore. We calibrate the geometric model parameters using general relativistic magnetohydrodynamic (GRMHD) models of the emission region and estimate physical properties of the source. We further fit images generated from GRMHD models directly to the data. We compare the derived emission region and black hole parameters from these analyses with those recovered from reconstructed images. There is a remarkable consistency among all methods and data sets. We find that >50% of the total flux at arcsecond scales comes from near the horizon, and that the emission is dramatically suppressed interior to this region by a factor >10, providing direct evidence of the predicted shadow of a black hole. Across all methods, we measure a crescent diameter of 42 ± 3 μas and constrain its fractional width to be <0.5. Associating the crescent feature with the emission surrounding the black hole shadow, we infer an angular gravitational radius of GM/Dc2 = 3.8 ± 0.4 μas. Folding in a distance measurement of ${16.8}_{-0.7}^{+0.8}\,\mathrm{Mpc}$ gives a black hole mass of $M=6.5\pm 0.2{| }_{\mathrm{stat}}\pm 0.7{| }_{\mathrm{sys}}\times {10}^{9}\hspace{2pt}{M}_{\odot }$. This measurement from lensed emission near the event horizon is consistent with the presence of a central Kerr black hole, as predicted by the general theory of relativity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

LASSO for CALPHAD Model Selection Enables Data-Efficient Thermodynamic Modeling: An Application in Thermochemical Hydrogen Production Materials

Phenomenological CALPHAD (CALculation of PHAse Diagrams) models, widely used for multicomponent materials, often contain a considerable number of parameters and require fitting using data from a relatively small number of experimental measurements or theoretical calculations. Sometimes these parameters are introduced for the purpose of improving model fits but without clear physical justification, which leads to overparametrized models with poor generalization performance. Automated approaches for optimal model selection based on the available data therefore become critical. Here, in this work, a least absolute shrinkage and selection operator (LASSO)-based approach is developed for model selection by leveraging the linearity of the CALPHAD model with respect to its parameters to convert the model selection and fitting to a LASSO minimization problem. We demonstrate its utility for thermodynamic modeling of thermochemical hydrogen (TCH) production materials using lanthanum strontium manganite (LSM) as an example. Various TCH-relevant properties, including oxygen stoichiometry as a function of oxygen partial pressure, enthalpy of reduction, and entropy of reduction, are successfully predicted with reasonable accuracy using a minimal set of model parameters. Importantly, the model selection and fitting involve minimal human decision; it can therefore be applied to high-throughput DFT defect calculations and yield efficient workflows for TCH material modeling and optimization.

CALPHAD↗
DOE OSTI2023

Polarimetric Geometric Modeling for mm-VLBI Observations of Black Holes

The Event Horizon Telescope (EHT) is a millimeter very long baseline interferometry (VLBI) array that has imaged the apparent shadows of the supermassive black holes M87* and Sagittarius A*. Polarimetric data from these observations contain a wealth of information on the black hole and accretion flow properties. In this work, we develop polarimetric geometric modeling methods for mm-VLBI data, focusing on approaches that fit data products with differing degrees of invariance to broad classes of calibration errors. We establish a fitting procedure using a polarimetric “m-ring” model to approximate the image structure near a black hole. By fitting this model to synthetic EHT data from general relativistic magnetohydrodynamic models, we show that the linear and circular polarization structure can be successfully approximated with relatively few model parameters. We then fit this model to EHT observations of M87* taken in 2017. In total intensity and linear polarization, the m-ring fits are consistent with previous results from imaging methods. In circular polarization, the m-ring fits indicate the presence of event-horizon-scale circular polarization structure, with a persistent dipolar asymmetry and orientation across several days. The same structure was recovered independently of observing band, used data products, and model assumptions. Despite this broad agreement, imaging methods do not produce similarly consistent results. Our circular polarization results, which imposed additional assumptions on the source structure, should thus be interpreted with some caution. Polarimetric geometric modeling provides a useful and powerful method to constrain the properties of horizon-scale polarized emission, particularly for sparse arrays like the EHT.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

THE MASS DISTRIBUTION OF STELLAR-MASS BLACK HOLES

We perform a Bayesian analysis of the mass distribution of stellar-mass black holes using the observed masses of 15 low-mass X-ray binary systems undergoing Roche lobe overflow and 5 high-mass, wind-fed X-ray binary systems. Using Markov Chain Monte Carlo calculations, we model the mass distribution both parametrically-as a power law, exponential, Gaussian, combination of two Gaussians, or log-normal distribution-and non-parametrically-as histograms with varying numbers of bins. We provide confidence bounds on the shape of the mass distribution in the context of each model and compare the models with each other by calculating their relative Bayesian evidence as supported by the measurements, taking into account the number of degrees of freedom of each model. The mass distribution of the low-mass systems is best fit by a power law, while the distribution of the combined sample is best fit by the exponential model. This difference indicates that the low-mass subsample is not consistent with being drawn from the distribution of the combined population. We examine the existence of a 'gap' between the most massive neutron stars and the least massive black holes by considering the value, M{sub 1%}, of the 1% quantile from each black hole mass distribution as the lower bound of black hole masses. Our analysis generates posterior distributions for M{sub 1%}; the best model (the power law) fitted to the low-mass systems has a distribution of lower bounds with M{sub 1%}>4.3 M{sub sun} with 90% confidence, while the best model (the exponential) fitted to all 20 systems has M{sub 1%}>4.5 M{sub sun} with 90% confidence. We conclude that our sample of black hole masses provides strong evidence of a gap between the maximum neutron star mass and the lower bound on black hole masses. Our results on the low-mass sample are in qualitative agreement with those of Ozel et al., although our broad model selection analysis more reliably reveals the best-fit quantitative description of the underlying mass distribution. The results on the combined sample of low- and high-mass systems are in qualitative agreement with Fryer and Kalogera, although the presence of a mass gap remains theoretically unexplained.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The electronic structure of thorium monoxide: Ligand field assignment of states in the range 0–5 eV

Configuration interaction ligand field theory (CI LFT) calculations of the electronic energy levels of ThO were performed by treating the molecular electronic states as Th 2+ free-ion levels perturbed by the ligand field of O 2- . Twenty nine experimentally characterized ThO v = 0 energy levels, together with the energy difference between the v = 0 levels of the Y and W states were fitted using a CI LFT model that included Th 2+ 7s 2 , 6d7s, 6d 2 , 7s7p, 6d7p, 5f7s, and 7p 2 configurations. Predictions from these calculations were used to provide tentative assignments for 171 out of 250 ThO band heads listed by Gatterer et al. [“Molecular Spectra of Metallic Oxides”, Specola Vaticana (1957)]. Term energies for 30 electronic states have been determined based on these assignments. Subsequently, the CI LFT model was refined by fitting to a set of 59 electronic term energies. The inclusion of CI effects together with integer valence, atomic-in-molecule, ionic bonding ideas reveals atomic energy level patterns that are multiply replicated in the molecular energy level patterns of six Th 2+ O 2- atomic ion configurations (6d7s, 6d 2 , 7s7p, 6d7p, 5f7s, and 7p 2 ) revealing the underlying atomic ion structure that gives rise to the complex and seemingly erratic unassigned bands reported in the Vatican Atlas.

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

Dark photon and dark Z mediated B meson decays

We study flavor changing neutral current decays of B and K mesons in the dark U(1) D model, with the dark photon/dark Z mass between 10 MeV and 2 GeV. Although the model provides an improved fit (compared to the standard model) to the differential decay distributions of B → K ($\ast$) ℓ + ℓ – , with ℓ = μ, e, and B s → $\phi$μ + μ – , the allowed parameter space is ruled out by measurements of atomic parity violation, K + → μ + + invisible decay, and ${B}_s-{\overline{B}}_s$ mixing, among others. To evade constraints from low energy data, we extend the model to allow for (1) additional invisible Z D decay, (2) a direct vector coupling of Z D to muons, and (3) a direct coupling of Z D to both muons and electrons, with the electron coupling fine-tuned to cancel the Z D coupling to electrons via mixing. We find that only the latter case survives all constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Modeling of Work Hardening During Hot Rolling of Vanadium and Niobium Microalloyed Steels in the Low Temperature Austenite Region

This work extends the application of the well-established Estrin and Mecking (EM) work-hardening model in unstable low temperature austenite region. The interaction between work hardening, recovery and softening attributed to recrystallization and transformation to ferrite under dynamic conditions is considered. Experimental parameters were varied to study the effects of strain, strain rate and temperature during hot rolling in the low temperature austenite region. Hot compression tests were performed two microalloyed steels—one containing V and the other Nb—at strain rates between 0.1 and 10 s{sup −1} over a temperature range of 750-1000 °C. A model is presented that describes the influence of dynamic recovery on flow behavior in the unstable austenite region. The modified work-hardening model incorporates an additional fitting parameter to the EM model and is dependent on the recovery and softening rates. The new model improved prediction in the unstable austenite region, while the original EM model gave better correlation at relatively higher temperatures when dynamic recrystallization is dominant or at relatively lower temperatures when only dynamic recrystallization to ferrite was the softening mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Slitless spectrophotometry with forward modelling: Principles and application to measuring atmospheric transmission

Context.In the next decade, many optical surveys will aim to answer the question of the nature of dark energy by measuring its equation-of-state parameter at the per mill level. This requires trusting the photometric calibration of the survey with a precision never reached so far on many sources of systematic uncertainties. The measurement of the on-site atmospheric transmission for each exposure, or for each season or for the full survey on average, can help reach the per mill precision for the magnitudes. Aims.This work aims at proving the ability to use slitless spectroscopy for standard-star spectrophotometry and its use to monitor on-site atmospheric transmission as needed, for example, by theVera C. RubinObservatory Legacy Survey of Space and Time supernova cosmology program. We fully deal with the case of a disperser in the filter wheel, which is the configuration chosen in theRubinAuxiliary Telescope. Methods.The theoretical basis of slitless spectrophotometry is at the heart of our forward-model approach to extract spectroscopic information from slitless data. We developed a publicly available software calledSpectractor, which implements each ingredient of the model and finally performs a fit of a spectrogram model directly on image data to obtain the spectrum. Results.We show through simulations that our model allows us to understand the structure of spectrophotometric exposures. We also demonstrate its use on real data by solving specific issues and illustrating that our procedure allows the improvement of the model describing the data. Finally, we discuss how this approach can be used to directly extract atmospheric transmission parameters from the data and thus provide the base for on-site atmosphere monitoring. We show the efficiency of the procedure in simulations and test it on the limited available data set.

Astronomy & Astrophysics↗
DOE OSTI2014

Stochastic growth logistic model with aftereffect for batch fermentation process

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

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

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

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

NuSTAR SPECTROSCOPY OF GRS 1915+105: DISK REFLECTION, SPIN, AND CONNECTIONS TO JETS

We report on the results of spectral fits made to a NuSTAR observation of the black hole GRS 1915+105 in a 'plateau' state. This state is of special interest because it is similar to the 'low/hard' state seen in other black holes, especially in that compact, steady jets are launched in this phase. The 3-79 keV bandpass of NuSTAR, and its ability to obtain moderate-resolution spectra free from distortions such as photon pile-up, are extremely well suited to studies of disk reflection in X-ray binaries. In only 15 ks of net exposure, an extraordinarily sensitive spectrum of GRS 1915+105 was measured across the full bandpass. Ionized reflection from a disk around a rapidly spinning black hole is clearly required to fit the spectra; even hybrid Comptonization models including ionized reflection from a disk around a Schwarzschild black hole proved inadequate. A spin parameter of a = 0.98 ± 0.01 (1σ statistical error) is measured via the best-fit model; low spins are ruled out at a high level of confidence. This result suggests that jets can be launched from a disk extending to the innermost stable circular orbit. A very steep inner disk emissivity profile is also measured, consistent with models of compact coronae above Kerr black holes. These results support an emerging association between the hard X-ray corona and the base of the relativistic jet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗