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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Bayesian inferences of electrical current delivered to shocked transmission lines

Small radius Bdot measurements of electrical current delivered by pulsed power devices are routinely compromised by electrode/convolute plasmas endemic to multiterawatt transmission lines. Inferences of delivered current unaffected by these issues have recently been obtained by numerically optimizing consistency between model predictions and local experimental velocimetry data, but these are only unique for shockless velocity profiles. In the paper we describe a more general Bayesian method capable of inferring current despite the presence of shocks. Additionally, we describe uncertainty estimates and use of the technique on experimental data. This technique is the first to provide uncertainty estimates on the full current trace delivered to an inertial confinement fusion target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Semantic Property Graph for Scalable Knowledge Graph Analytics

Graphs are a natural and fundamental representation to describe entities, relationships, activities, and evolution of complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data models to encode information in a graph. Both models are similar in terms of using basic graph elements such as nodes and edges but differ in terms of the modeling approach, expressibility, serialization, and target applications. RDF is a flexible data exchange model for expressing information about entities but it tends to a have high memory footprint and inefficient storage, which does not make it a natural choice to perform scalable graph analytics. In contrast, LPG has gained traction as a reliable model to perform scalable graph analytic tasks such as sub-graph matching, network alignment, and real-time knowledge graph query. It provides efficient storage, fast traversal, and flexibility to model various real-world domains. At the same time, the LPG lacks the support of a formal knowledge representation such as an ontology to provide automated knowledge inference. We propose Semantic Property Graph (SPG) as a logical projection of reified RDF into the LPG model. SPG continues to use RDF ontology to define the type hierarchy of the projected graph and validate it against a given ontology. We present a framework to convert reified RDF graphs into SPG using two different computing environments. We also present cloud-based graph migration capabilities using Amazon Web Services.

Purohit, Sumit↗
DOE OSTI2020

Detection of Cyclopropenylidene on Titan with ALMA

We report the first detection on Titan of the small cyclic molecule cyclopropenylidene (c-C{sub 3}H{sub 2}) from high-sensitivity spectroscopic observations made with the Atacama Large Millimeter/submillimeter Array. Multiple lines of cyclopropenylidene were detected in two separate data sets: ∼251 GHz in 2016 (Band 6) and ∼352 GHz in 2017 (Band 7). Modeling of these emissions indicates abundances of 0.50 ± 0.14 ppb (2016) and 0.28 ± 0.08 (2017) for a 350 km step model, which may either signify a decrease in abundance, or a mean value of 0.33 ± 0.07 ppb. Inferred column abundances are (3–5) × 10{sup 12} cm{sup −2} in 2016 and (1–2) × 10{sup 12} cm{sup −2} in 2017, similar to photochemical model predictions. Previously the C{sub 3}H{sub 3}{sup +} ion has been measured in Titan’s ionosphere by Cassini’s Ion and Neutral Mass Spectrometer (INMS), but the neutral (unprotonated) species has not been detected until now, and aromatic versus aliphatic structure could not be determined by the INMS. Our work therefore represents the first unambiguous detection of cyclopropenylidene, the second known cyclic molecule in Titan’s atmosphere along with benzene (C{sub 6}H{sub 6}) and the first time this molecule has been detected in a planetary atmosphere. We also searched for the N-heterocycle molecules pyridine and pyrimidine finding nondetections in both cases, and determining 2σ upper limits of 1.15 ppb (c-C{sub 5}H{sub 5}N) and 0.85 ppb (c-C{sub 4}H{sub 4}N{sub 2}) for uniform abundances above 300 km. These new results on cyclic molecules provide fresh constraints on photochemical pathways in Titan’s atmosphere, and will require new modeling and experimental work to fully understand the implications for complex molecule formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Map-based cosmology inference with lognormal cosmic shear maps

ABSTRACT Most cosmic shear analyses to date have relied on summary statistics (e.g. ξ+ and ξ−). These types of analyses are necessarily suboptimal, as the use of summary statistics is lossy. In this paper, we forward-model the convergence field of the Universe as a lognormal random field conditioned on the observed shear data. This new map-based inference framework enables us to recover the joint posterior of the cosmological parameters and the convergence field of the Universe. Our analysis properly accounts for the covariance in the mass maps across tomographic bins, which significantly improves the fidelity of the maps relative to single-bin reconstructions. We verify that applying our inference pipeline to Gaussian random fields recovers posteriors that are in excellent agreement with their analytical counterparts. At the resolution of our maps – and to the extent that the convergence field can be described by the lognormal model – our map posteriors allow us to reconstruct all summary statistics (including non-Gaussian statistics). We forecast that a map-based inference analysis of LSST-Y10 data can improve cosmological constraints in the σ8–Ωm plane by $\approx\!{30}{{\ \rm per\ cent}}$ relative to the currently standard cosmic shear analysis. This improvement happens almost entirely along the $S_8=\sigma _8\Omega _{\rm m}^{1/2}$ directions, meaning map-based inference fails to significantly improve constraints on S8.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Study of clathrate hydrates via equilibrium molecular-dynamics simulation employing polarisable and non-polarisable, rigid and flexible water models

Equilibrium molecular-dynamics (MD) simulations have been performed on metastable sI and sII polymorphs of empty hydrate lattices, in addition to liquid water and ice Ih. The non-polarisable TIP4P-2005, simple point charge model (SPC), and polarisable Thole-type models (TTM): TTM2, TTM3, and TTM4 water models were used in order to survey the differences between models and to see what differences can be expected when polarisability is incorporated. Rigid and flexible variants were used of each model to gauge the effects of flexibility. Power spectra are calculated and compared to density-of-states spectra inferred from inelastic neutron scattering (INS) measurements. Thermodynamic properties were also calculated, as well as molecular-dipole distributions. It was concluded that TTM models offer optimal fidelity vis-à-vis INS spectra, together with thermodynamic properties, with the flexible TTM2 model offering optimal placement of vibrational modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The Atacama Cosmology Telescope: Mitigating the Impact of Extragalactic Foregrounds for the DR6 Cosmic Microwave Background Lensing Analysis

We investigate the impact and mitigation of extragalactic foregrounds for the cosmic microwave background (CMB) lensing power spectrum analysis of Atacama Cosmology Telescope (ACT) data release 6 (DR6) data. Two independent microwave sky simulations are used to test a range of mitigation strategies. We demonstrate that finding and then subtracting point sources, finding and then subtracting models of clusters, and using a profile bias-hardened lensing estimator together reduce the fractional biases to well below statistical uncertainties, with the inferred lensing amplitude, A lens , biased by less than 0.2σ. We also show that another method where a model for the cosmic infrared background (CIB) contribution is deprojected and high-frequency data from Planck is included has similar performance. Other frequency-cleaned options do not perform as well, either incurring a large noise cost or resulting in biased recovery of the lensing spectrum. In addition to these simulation-based tests, we also present null tests on the ACT DR6 data for sensitivity of our lensing spectrum estimation to differences in foreground levels between the two ACT frequencies used, while nulling the CMB lensing signal. These tests pass whether the nulling is performed at the map or bandpower level. The CIB-deprojected measurement performed on the DR6 data is consistent with our baseline measurement, implying that contamination from the CIB is unlikely to significantly bias the DR6 lensing spectrum. This collection of tests gives confidence that the ACT DR6 lensing measurements and cosmological constraints presented in companion papers to this work are robust to extragalactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The NuSTAR extragalactic surveys: the number counts of active galactic nuclei and the resolved fraction of the cosmic X-ray background

We present the 3–8 keV and 8–24 keV number counts of active galactic nuclei (AGNs) identified in the Nuclear Spectroscopic Telescope Array (NuSTAR) extragalactic surveys. NuSTAR has now resolved 33%–39% of the X-ray background in the 8–24 keV band, directly identifying AGNs with obscuring columns up to ∼10{sup 25} cm{sup −2}. In the softer 3–8 keV band the number counts are in general agreement with those measured by XMM-Newton and Chandra over the flux range 5×10{sup −15} ≲ S(3–8 keV)/erg s{sup −1} cm{sup −2} ≲ 10{sup −12} probed by NuSTAR. In the hard 8–24 keV band NuSTAR probes fluxes over the range 2×10{sup −14} ≲ S(8–24 keV)/erg s{sup −1} cm{sup −2} ≲ 10{sup −12}, a factor ∼100 fainter than previous measurements. The 8–24 keV number counts match predictions from AGN population synthesis models, directly confirming the existence of a population of obscured and/or hard X-ray sources inferred from the shape of the integrated cosmic X-ray background. The measured NuSTAR counts lie significantly above simple extrapolation with a Euclidian slope to low flux of the Swift/BAT 15–55 keV number counts measured at higher fluxes (S(15–55 keV) ≳ 10{sup −11} erg s{sup −1} cm{sup −2}), reflecting the evolution of the AGN population between the Swift/BAT local (z<0.1) sample and NuSTAR’s z∼1 sample. CXB synthesis models, which account for AGN evolution, lie above the Swift/BAT measurements, suggesting that they do not fully capture the evolution of obscured AGNs at low redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Classification and computation of extreme events in turbulent combustion

In the design of practical combustion systems, ensuring safety and reliability is an important requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is critical for ensuring safe operation. Currently, the science of predicting such events is based on prior experience, limited modeling or diagnostic tools and purely statistical approaches. Even though computational and experimental tools for studying combustion devices have vastly advanced in the last three decades, the analysis of such failure events has not been pursued widely. While the use of data for model development and calibration is being widely accepted, the extension to failure events introduces numerous challenges. In particular, the focus here is on so-called data-poor problems, where the cost of generating data is extremely high and is not easily amenable to existing computational and experimental approaches. Data-poor problems are particularly relevant when related to extreme events (also called anomalous events) that can lead to catastrophic failure of the system. It is argued that transient events that describe such failure can have different causal mechanisms. To develop the scientific inference process, a classification of such problems is used to determine specific modeling paths as well as computational tools needed. Research opportunities in the emerging field of extreme event prediction are highlighted in order to identify critical and immediate needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Models for HEU objects in the NDSE IV and III series

A Neutron-Diagnosed Subcritical Experiment (NDSE) proof-of-principle setup exists at area-11 in Nevada. An exquisite set of gamma-ray flux die-away data has been obtained at this facility for a number of highly-enriched uranium (HEU) objects, including objects referred to as IV, IV', IV'' (the object IV series), IIIa, and IIIb (the object III series). These objects are constructed via a set of hemi-spherical concentric HEU shells (known as the Rocky Flats shells), surrounded by a sphere of aluminum (Al), encased in an outer sphere of high-density polyethylene (HDP). The “as built” detailed MCNP-calculated k eff values obtained by Goorley, for the object IV and III series, are listed in Table II. These model calculations contain detailed information about the inner and outer radii and masses of each hemi-shell used to make each of the objects. Objects IV', and IV'' were obtained by replacing inner HEU shells with Al. The low k eff of object IIIa was obtained by substituting a single HEU shell, with an inner radius of ~5 cm, with an Al shell. For object IIIb the substitution was a little further out but only in one hemi-shell. Except for the inner most shell (ball), all HEU shells have a thickness close to 0.333 cm. Previously the k eff of objects IV', IV'', IIIa, and IIIb, were determined from measured gamma ray die-away data via an analysis using a simple modification of the density of the HEU in our simple three layered model (HEU, Al, and HDP) of object IV including the outer safety can. This was done to see the quality of the inference and investigate any limitations associated with not using detailed information about the known perturbations used to make these objects. In this work, we built models (priors) of objects IV', IV'', IIIa, and IIIb that make use of our knowledge about the nature of the perturbations. With these models, instead of adjusting the density of the HEU in our object IV model to match the data from objects IV', IV'', IIIa, and IIIb, as done previously, we will be able to (in future studies) adjust r AL , and r i to infer the k eff of the corresponding objects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

The overarching framework of core-collapse supernova explosions as revealed by 3D fornax simulations

We have conducted 19 state-of-the-art 3D core-collapse supernova simulations spanning a broad range of progenitor masses. This is the largest collection of sophisticated 3D supernova simulations ever performed. We have found that while the majority of these models explode, not all do, and that even models in the middle of the available progenitor mass range may be less explodable. This does not mean that those models for which we did not witness explosion would not explode in Nature, but that they are less prone to explosion than others. One consequence is that the ‘compactness’ measure is not a metric for explodability. We find that lower-mass massive star progenitors likely experience lower-energy explosions, while the higher-mass massive stars likely experience higher-energy explosions. Moreover, most 3D explosions have a dominant dipole morphology, have a pinched, wasp-waist structure, and experience simultaneous accretion and explosion. We reproduce the general range of residual neutron-star masses inferred for the galactic neutron-star population. The most massive progenitor models, however, in particular vis à vis explosion energy, need to be continued for longer physical times to asymptote to their final states. We find that while the majority of the inner ejecta have Ye = 0.5, there is a substantial proton-rich tail. This result has important implications for the nucleosynthetic yields as a function of progenitor. Finally, we find that the non-exploding models eventually evolve into compact inner configurations that experience a quasi-periodic spiral SASI mode. We otherwise see little evidence of the SASI in the exploding models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

(U) An Analytic Examination of Piezoelectric Ejecta Mass Measurements

Ongoing efforts to validate a Richtmyer-Meshkov instability (RMI) based ejecta source model [1, 2, 3] in LANL ASC codes use ejecta areal masses derived from piezoelectric sensor data [4, 5, 6]. However, the standard technique for inferring masses from sensor voltages implicitly assumes instantaneous ejecta creation [7], which is not a feature of the RMI source model. To investigate the impact of this discrepancy, we define separate “areal mass functions” (AMFs) at the source and sensor in terms of typically unknown distribution functions for the ejecta particles, and derive an analytic relationship between them. Then, for the case of single-shock ejection into vacuum, we use the AMFs to compare the analytic (or “true”) accumulated mass at the sensor with the value that would be inferred from piezoelectric voltage measurements. We confirm the inferred mass is correct when creation is instantaneous, and furthermore prove that when creation is not instantaneous, the inferred values will always overestimate the true mass. Finally, we derive an upper bound for the error imposed on a perfect system by the assumption of instantaneous ejecta creation. When applied to shots in the published literature, this bound is frequently less than several percent. Errors exceeding 15% may require velocities or timescales at odds with experimental observations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Impact of Varying Dark Energy on Future Large-Scale Structure Studies

The cosmos withholds multiple mysteries such as dark forms of matter and energy that are yet beyond human comprehension. In the standard cosmological model, $\Lambda$CDM, the cosmological constant $\Lambda$ is thought to be responsible for the late accelerated expansion of the Universe. However, recent results from the Dark Energy Spectroscopic Instrument (DESI) suggest the possibility of evolving dark energy, which warrants further exploration. Future surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST) will map the large-scale structure (LSS) with unprecedented precision, giving us valuable statistical information about the cosmos. The goal of this research is to investigate the potential impact of an evolving dark energy scenario on cosmological parameters constrained by LSS probes, as will be mapped by the LSST. For this, we examine the power spectra of lens galaxies, source galaxies, and cross-power spectra between lens galaxies and source galaxies. The combination of these statistics is commonly referred to as '3 $\times$ 2 points'. For this investigation, we created a set of simulations resembling LSST data and used them to perform cosmological parameter inference in two scenarios: one in which the simulated data is based on the fiducial model and another on evolving dark energy. We then examined the degeneracy between the cosmological parameters and checked for potential shifts in the parametric space when the data contains dynamical dark energy but the modeling assumes $\Lambda$CDM. Our findings indicate that mismodeling the dark energy equation of state can significantly impact parameter inference, particularly affecting the total matter density, $\Omega_m$, and the growth of structures, as represented by the $S_8$ parameter. These results highlight the importance of further exploring extensions of the $\Lambda$CDM model in future LSS studies.

Yaman Acharya, A.↗
DOE OSTI2024

Accurate field-level weak lensing inference for precision cosmology

We present miko, a catalog-to-cosmology pipeline for general flat-sky field-level inference, which provides access to cosmological information beyond the two-point statistics. In the context of weak lensing, we identify several new field-level analysis systematics (such as aliasing, Fourier mode-coupling, and density-induced shape noise), quantify their impact on cosmological constraints, and correct the biases to a percent level. Next, we find that model misspecification can lead to both absolute bias and incorrect uncertainty quantification for the inferred cosmological parameters in realistic simulations. The Gaussian map prior infers unbiased cosmological parameters, regardless of the true data distribution, but it yields overconfident uncertainties. The log-normal map prior quantifies the uncertainties accurately, although it requires careful calibration of the shift parameters for unbiased cosmological parameters. Here, we demonstrate systematics control down to the 2% level for both models, making them suitable for ongoing weak lensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Simultaneous inference of equation of state parameters and unknown data errors with uncertainty quantification via hierarchical Bayesian posterior maximization

Equations of state (EOSs) are a key component in running hydrodynamic simulations as they relate the thermodynamic states for the material. The Davis reactants EOS is commonly used for modeling high explosives (HEs), and the EOS model parameters are calibrated using material specific data. The calibrations are often performed with uncertainty quantification via Bayesian inference to account for uncertainty in the data and generate ensembles of likely parameters. However, there are relatively few HE data sets to use for calibration and many are historical and lack error information. In this work, we simultaneously calibrate the Davis reactants EOS model parameters and unknown data error terms for the high explosive PBX 9501. To quantify the uncertainty in the models and the data, we use a Bayesian framework for the calibration and compute the hierarchical Bayesian posterior distribution with both a posteriori maximization approach and Markov Chain Monte Carlo. In general, we find that, given our assumptions, the two approaches result in similar calibrated parameters, posterior covariance matrices, and insights about the parameters but that the posterior maximization requires far less computational resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Structural Control on Downdip Locking Extent of the Himalayan Megathrust

Here, geologic reconstructions of the Main Himalayan Thrust in Nepal show a laterally extensive midcrustal ramp, hypothesized to form the downdip boundary of interseismic locking. Using a recent compilation of interseismic GPS velocities and a simplified model of fault coupling, we estimate the width of coupling across Nepal using a series of two-dimensional transects. We find that the downdip width of fault coupling increases smoothly from 70 to 90 km in eastern Nepal to 100–110 km in central Nepal, then narrows again in western Nepal. The inferred coupling transition is closely aligned with geologic reconstructions of the base of the midcrustal ramp in central and eastern Nepal, but in western Nepal, the data suggest that the location is intermediate between two proposed ramp locations. The result for western Nepal implies either an anomalous coupling transition that occurs along a shallowly dipping portion of the fault or that both ramps may be partially coupled and that a proposed crustal-scale duplexing process may be active during the interseismic period. We also find that the models require a convergence rate of 15.5 ± 2 mm/year throughout Nepal, reducing the geodetic moment accumulation rate by up to 30% compared with earlier models, partially resolving an inferred discrepancy between geodetic and paleoseismic estimates of moment release across the Himalaya.

58 GEOSCIENCES↗
DOE OSTI2025

Comprehensive Neural Posterior Estimation for Galaxy-Galaxy Strong Lensing

We present a deep learning model based on neural posterior estimation (NPE) for comprehensive extraction of astrophysical parameters from galaxy-scale strong gravitational lenses. The unprecedentedly large amount of galaxy-scale strong lenses expected in future cosmological surveys (${\cal O}(10^5)$) promises to enable valuable statistical constraints in various studies ranging from galaxy formation to the nature of dark matter, but it also poses a significant challenge for traditional modelling pipelines. To this end, our automated model includes several new, state-of-the-art features and approaches leveraging the framework of simulation-based inference (SBI). We infer a total of 20 parameters describing the mass and light profiles of both lens and source galaxies, using simulated raw multi-band data modelled under noise and observing conditions expected by the Legacy Survey of Space and Time (LSST), with its summary statistics generated by a residual network. We examine the efficacy of multi-band data in extracting nearly 20 model parameters simultaneous from strong lensing images including lens light. Finally, We perform a comprehensive set of diagnostics for SBI models, evaluating the model's prediction accuracy, stability, and uncertainty quantification.

Zhao, Roy J. [Chicago U., KICP]↗
DOE OSTI2016

The effects of the small-scale DM power on the cosmological neutral hydrogen (HI) distribution at high redshifts

The particle nature of dark matter remains a mystery. In this paper, we consider two dark matter models—Late Forming Dark Matter (LFDM) and Ultra-Light Axion (ULA) models—where the matter power spectra show novel effects on small scales. The high redshift universe offers a powerful probe of their parameters. In particular, we study two cosmological observables: the neutral hydrogen (HI) redshifted 21-cm signal from the epoch of reionization, and the evolution of the collapsed fraction of HI in the redshift range 2 < z < 5. We model the theoretical predictions of the models using CDM-like N-body simulations with modified initial conditions, and generate reionization fields using an excursion set model. The N-body approximation is valid on the length and halo mass scales studied. We show that LFDM and ULA models predict an increase in the HI power spectrum from the epoch of reionization by a factor between 2–10 for a range of scales 0.1 < k < 4 Mpc{sup −1}. Assuming a fiducial model where a neutral hydrogen fraction x-bar {sub HI} = 0.5 must be achieved by z = 8, the reionization process allows us to put approximate bounds on the redshift of dark matter formation z{sub f} > 4 × 10{sup 5} (for LFDM) and the axion mass m{sub a} > 2.6 × 10{sup −23} eV (for ULA). The comparison of the collapsed mass fraction inferred from damped Lyman-α observations to the theoretical predictions of our models lead to the weaker bounds: z{sub f} > 2 × 10{sup 5} and m{sub a} > 10{sup −23} eV. These bounds are consistent with other constraints in the literature using different observables; we briefly discuss how these bounds compare with possible constraints from the observation of luminosity function of galaxies at high redshifts. In the case of ULAs, these constraints are also consistent with a solution to the cusp-core problem of CDM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗