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NASA NTRS2012

Thermal Phase Variations of WASP-12b: Defying Predictions

We report Warm Spitzer full-orbit phase observations of WASP-12b at 3.6 and 4.5 micrometers. This extremely inflated hot Jupiter is thought to be overflowing its Roche lobe, undergoing mass loss and accretion onto its host star, and has been claimed to have a C/O ratio in excess of unity. We are able to measure the transit depths, eclipse depths, thermal and ellipsoidal phase variations at both wavelengths. The large-amplitude phase variations, combined with the planet's previously measured dayside spectral energy distribution, are indicative of non-zero Bond albedo and very poor day-night heat redistribution. The transit depths in the mid-infrared-(R(sub p)/R(sub ∗))(sup 2) = 0.0123(3) and 0.0111(3) at 3.6 and 4.5 micrometers, respectively-indicate that the atmospheric opacity is greater at 3.6 than at 4.5 micrometers, in disagreement with model predictions, irrespective of C/O ratio. The secondary eclipse depths are consistent with previous studies: F(sub day)/F(sub ∗) = 0.0038(4) and 0.0039(3) at 3.6 and 4.5 micrometers, respectively. We do not detect ellipsoidal variations at 3.6 micrometers, but our parameter uncertainties-estimated via prayer-bead Monte Carlo-keep this non-detection consistent with model predictions. At 4.5 micrometers, on the other hand, we detect ellipsoidal variations that are much stronger than predicted. If interpreted as a geometric effect due to the planet's elongated shape, these variations imply a 3:2 ratio for the planet's longest:shortest axes and a relatively bright day-night terminator. If we instead presume that the 4.5 micrometer ellipsoidal variations are due to uncorrected systematic noise and we fix the amplitude of the variations to zero, the best-fit 4.5 micrometer transit depth becomes commensurate with the 3.6 micrometer depth, within the uncertainties. The relative transit depths are then consistent with a solar composition and short scale height at the terminator. Assuming zero ellipsoidal variations also yields a much deeper 4.5 micrometer eclipse depth, consistent with a solar composition and modest temperature inversion. We suggest future observations that could distinguish between these two scenarios.

planetary↗

DOE OSTI2021

A Comprehensive Open-Source R Software For Statistical Metrology Calculations: From Uncertainty Evaluation To Risk Analysis

Whether calibrating equipment or inspecting products on the factory floor, metrology requires many complicated statistical calculations to achieve a full understanding and evaluation of measurement uncertainty and quality. In order to assist its workforce in performing these calculations in a consistent and rigorous way, the Primary Standards Lab at Sandia National Laboratories (SNL) has developed a free and open-source software package for computing various metrology calculations from uncertainty propagation to risk analysis. In addition to propagating uncertainty through a measurement model using the well-known Guide to Expression of Uncertainty in Measurement or Monte Carlo approaches, evaluating the individual Type A and Type B uncertainty components that go into the measurement model often requires other statistical methods such as analysis of variance or determining uncertainty in a fitted curve. Once the uncertainty in a measurement has been calculated, it is usually evaluated from a risk perspective to ensure the measurement is suitable for making a particular conformance decision. Finally, SNL’s software can perform all these calculations in a single application via an easy-to-use graphical interface, where the different functions are integrated so the results of one calculation can be used as inputs to another calculation.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2017

A Fast Hybrid (3-D/1-D) Model for Thermal Radiative Transfer in Cirrus via Successive Orders of Scattering

We investigate the impact of cirrus cloud heterogeneity on the direct emission by cloud or surface and on the scattering by ice particles in the thermal infrared (TIR). Realistic 3-D cirri are modeled with the 3DCLOUD code, and top-of-atmosphere radiances are simulated by the 3-D Monte Carlo radiative transfer (RT) algorithm 3DMCPOL for two (8.65 micrometers and 12.05 micrometers) channels of the Imaging Infrared Radiometer on CALIPSO. At nadir, comparisons of 1-D and 3-D RT show that 3-D radiances are larger than their 1-D counterparts for direct emission but smaller for scattered radiation. For our cirrus cases, 99% of the 3-D total radiance is computed by the third scattering order, which corresponds to 90% of the total computational effort, but larger optical thicknesses need more scattering orders. To radically accelerate the 3-D RT computations (using only few percent of 3-D RT time with a Monte Carlo code), even in the presence of large optical depths, we develop a hybrid model based on exact 3-D direct emission, the first scattering order from 1-D in each homogenized column, and an empirical adjustment linearly dependent on the optical thickness to account for higher scattering orders. Good agreement is found between the hybrid model and the exact 3-D radiances for two very different cirrus models without changing the empirical parameters. We anticipate that a future deterministic implementation of the hybrid model will be fast enough to process multiangle thermal imagery in a practical tomographic reconstruction of 3-D cirrus fields.

radiative transfer↗

DOE OSTI2022

Spacetime symmetric qubit regularization of the asymptotically free two-dimensional O ( 4 ) model

Not Available

1-dimensional spin chains↗

DOE OSTI2021

Bayesian Monte-Carlo Evaluation Framework for Imperfect Data [Slides]

BMC evaluation is a tool to address imperfect data & models, non-linear models, and non-normal PDFs. New posterior PDFs may need new storage formats to allow storage of non-normal PDFs. Storing posterior sets allows for: variance, covariance, skewness, etc.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Tensor train continuous time solver for quantum impurity models

The simulation of strongly correlated quantum impurity models is a significant challenge in modern condensed matter physics that has multiple important applications. Thus far, the most successful methods for approaching this challenge involve Monte Carlo techniques that accurately and reliably sample perturbative expansions to any order. However, the cost of obtaining high precision through these methods is high. Recently, tensor train decomposition techniques have been developed as an alternative to Monte Carlo integration. In this study, we apply these techniques to the single-impurity Anderson model at equilibrium by calculating the systematic expansion in power of the hybridization of the impurity with the bath. Furthermore, we demonstrate the performance of the method in a paradigmatic application, examining the first-order phase transition on the infinite-dimensional Bethe lattice, which can be mapped to an impurity model through dynamical mean field theory. Our results indicate that using tensor train decomposition schemes allows the calculation of finite-temperature Green's functions and thermodynamic observables with unprecedented accuracy. The methodology holds promise for future applications to frustrated multiorbital systems, using a combination of partially summed series with other techniques pioneered in diagrammatic and continuous time quantum Monte Carlo.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Capabilities of multivariate Bayesian inference toward seismic hazard assessment

Multivariate Bayesian analysis can bring significant benefits to seismic hazard analysis: Its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure; and Its updating feature enables a seamless integration of new ground motion data into the hazard results. Here, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault-type, magnitude, and distance dependencies, and also the linear and the rock intensity dependent site response. We use a hybrid Markov Chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis-Hastings step. We then perform several checks on the model and note that its performance is satisfactory. Finally, we illustrate the merits of this multivariate Bayesian analysis, which include: ground motion model updating with ground motion data recorded in the last four years not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties.

58 GEOSCIENCES↗

DOE OSTI2020

Variations of the physical parameters of the blazar Mrk 421 based on analysis of the spectral energy distributions

Abstract We report on the variations of the physical parameters of the jet observed in the blazar Mrk 421, and discuss the origin of X-ray flares in the jet, based on analysis of several spectral energy distributions (SEDs). The SEDs are modeled using the one-zone synchrotron self-Compton model, its parameters determined using a Markov chain Monte Carlo method. The lack of data at TeV energies means many of the parameters cannot be uniquely determined and are correlated. These are studied in detail. We find that the optimal solution can be uniquely determined only when we apply a constraint to one of four parameters: the magnetic field (B), the Doppler factor, the size of the emitting region, and the normalization factor of the electron energy distribution. We used 31 sets of SEDs from 2009 to 2014 with optical–UV data observed with UVOT/Swift and the Kanata telescope, X-ray data with XRT/Swift, and γ-ray data with the Fermi Large Area Telescope. The result of our SED analysis suggests that, in the X-ray faint state, the emission occurs in a relatively small area (∼1016 cm) with a relatively strong magnetic field (B ∼ 10−1 G). The X-ray bright state shows a tendency opposite to that of the faint state, that is, a large emitting area (∼1018 cm), probably downstream of the jet, and a weak magnetic field (B ∼ 10−3 G). The high X-ray flux was due to an increase in the maximum energy of electrons. On the other hand, the presence of two kinds of emitting areas implies that the one-zone model is unsuitable for reproducing at least part of the observed SEDs.

Yamada, Yurika↗

DOE OSTI2023

Making digital objects FAIR in high energy physics: An implementation for Universal FeynRules Output (UFO) models

Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

Neubauer, Mark S.↗

DOE OSTI2023

Codebase release 2.0 for UFOManager

Neubauer, Mark S.↗

DOE OSTI2025

Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code TRIFORCE

The ability to accurately model burn propagation in inertial confinement fusion plasmas is crucial for advancing fusion energy research. This work presents enhancements to the triforce hybrid fluid-kinetic multiphysics code, focusing on its kinetic half, which employs the particle-in-cell (PIC) method with Monte Carlo collisions (MCC). We use a moment-preserving collision model that mitigates numerical noise, particularly in spherical geometries where particle weights vary significantly. Additionally, we refine the treatment of inverse bremsstrahlung to account for electron–ion collision frequency reductions in degenerate plasmas and incorporate a blackbody radiation source to enable realistic photon injection. These improvements enable the simulation of 1-dimensional (1D) spherical fusion burn propagation in deuterium–tritium plasmas. Benchmark comparisons with the hydra radiation-hydrodynamics code confirm that triforce accurately captures the dynamics of hot-spot expansion and burn propagation, demonstrating sensitivity to ignition thresholds consistent with theoretical models. Findings show the ignition cliff to be less steep in our work compared to radiation-hydrodynamic modeling. These results highlight the role of kinetic effects in fusion ignition physics and underscore the necessity of hybrid fluid-kinetic models for advancing predictive capabilities in high-energy-density plasma systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Models of dislocation glide and strengthening mechanisms in bcc complex concentrated alloys

Abstract The mechanical response of complex concentrated alloys (CCAs) deviates from that of their pure and dilute counterparts due to the introduction of a combinatorially sized chemical concentration dimension. Compositional fluctuations constantly alter the energy landscape over which dislocations move, leading to line roughness and the appearance of defects such as kinks and jogs under stress and temperature conditions where they would ordinarily not exist in pure metals and dilute alloys. The presence of such chemical defects gives rise to atomic-level mechanisms that fundamentally change how CCAs deform plastically at meso- and macroscales. In this article, we provide a review of recent advances in modeling dislocation glide processes in CCAs, including atomistic simulations of dislocation glide using molecular dynamics, kinetic Monte Carlo simulations of edge and screw dislocation motion in refractory CCAs, and phase-field models of dislocation evolution over complex energy landscapes. We also discuss pathways to develop comprehensive simulation methodologies that connect an atomic-level description of the compositional complexity of CCAs with their mesoscopic dislocation-mediated plastic response with an eye toward improved design of CCA with superior mechanical response. Graphical abstract

36 MATERIALS SCIENCE↗

DOE OSTI2026

Studies of Localization Effects on Transverse Kinematic Imbalance in the GENIE Generator

The forthcoming Deep Underground Neutrino Experiment (DUNE) requires precise modeling of neutrino--nucleus interactions to achieve its neutrino-oscillation measurement goals. GENIE, the Monte Carlo event generator used by DUNE and other Fermilab-based experiments as a central value model for neutrino-nucleus cross sections, exhibits known discrepancies in comparison to MicroBooNE cross section data, especially when considering neutrino scattering events' transverse kinematic imbalance (TKI). For quasielastic-like measurements, the data show a larger transverse missing momentum tail while maintaining a peak similar to that predicted by the baseline GENIE model. Previous attempts at a solution include variations of final-state interaction (FSI) strengths, incorrectly decreasing both the peak and tail, thus leaving the discrepancy unresolved. This work investigates whether inconsistencies between local and global treatments of intranuclear physics contribute to the observed mismodeling. In this work, GENIE FSI routines have been modified to directly utilize intranuclear particle positions, thereby introducing a newly localized momentum treatment in correlation with the nominal density in both the hA and hN intranuclear cascade models for their 2018 and 2025 variants. Meson-exchange-current (MEC) localization was also tested for the hN 2018 model. Comparisons of the intranuclear nucleons' ("scattering center") momentum and its radial dependence validate the localization implementation. However, while such consistent localization produces modest changes in the proton momentum spectrum at low-to-medium momenta, only small changes are observed in the TKI distributions. These changes are insufficient to account for the discrepancy with MicroBooNE data. Although a localized treatment improves the internal consistency of the GENIE model, the origin of the TKI discrepancy remains unresolved by such a solution.

Bulla, Braden [Ctr. Coll., Danville; Fermilab]↗

NASA NTRS1991

Composite load spectra for select space propulsion structural components

The work performed to develop composite load spectra (CLS) for the Space Shuttle Main Engine (SSME) using probabilistic methods. The three methods were implemented to be the engine system influence model. RASCAL was chosen to be the principal method as most component load models were implemented with the method. Validation of RASCAL was performed. High accuracy comparable to the Monte Carlo method can be obtained if a large enough bin size is used. Generic probabilistic models were developed and implemented for load calculations using the probabilistic methods discussed above. Each engine mission, either a real fighter or a test, has three mission phases: the engine start transient phase, the steady state phase, and the engine cut off transient phase. Power level and engine operating inlet conditions change during a mission. The load calculation module provides the steady-state and quasi-steady state calculation procedures with duty-cycle-data option. The quasi-steady state procedure is for engine transient phase calculations. In addition, a few generic probabilistic load models were also developed for specific conditions. These include the fixed transient spike model, the poison arrival transient spike model, and the rare event model. These generic probabilistic load models provide sufficient latitude for simulating loads with specific conditions. For SSME components, turbine blades, transfer ducts, LOX post, and the high pressure oxidizer turbopump (HPOTP) discharge duct were selected for application of the CLS program. They include static pressure loads and dynamic pressure loads for all four components, centrifugal force for the turbine blade, temperatures of thermal loads for all four components, and structural vibration loads for the ducts and LOX posts.

Newell, J. F.↗

DOE OSTI2021

Microemulsions in the driven Widom-Rowlinson lattice gas

An investigation of the two-dimensional Widom-Rowlinson lattice gas under an applied drive uncovered a remarkable nonequilibrium steady state in which uniform stripes (reminiscent of an equilibrium lamellar phase) form perpendicular to the drive direction [R. Dickman and R. K. P. Zia, Phys. Rev. E 97, 062126 (2018)]. Here we study this model at low particle densities in two and three dimensions, where we find a disordered phase with a characteristic length scale (a “microemulsion”) along the drive direction. Further we develop a continuum theory of this disordered phase to derive a coarse-grained field-theoretic action for the nonequilibrium dynamics. The action has the form of two coupled driven diffusive systems with different characteristic velocities, generated by an interplay between the particle repulsion and the drive. We then show how fluctuation corrections in the field theory may generate the characteristic features of the microemulsion phase, including a peak in the static structure factor corresponding to the characteristic length scale. This work lays the foundation for understanding the stripe phenomenon more generally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Double differential distributions of e-emission in ionization of N 2 by 3,4 and 5 keV electron impact

In this paper, we report the measurement of the absolute double differential cross sections (DDCS) of secondary electrons emitted due to the ionization of N2 molecule in collisions with fast electrons having energies between 3 and 5 keV. The emitted electrons with energies from 1-500 eV have been measured for different forward and backward emission angles. The measured DDCS have been compared with the state-of-the-art first Born approximation with correct boundary condition (CB1) model calculations as well as with the classical trajectory Monte Carlo (CTMC) method. From the measured DDCS, the single differential cross sections (SDCS) as a function of the emission energies have been computed and eventually the total ionization cross sections (TCS) have been derived. The TCS values are also compared with a semi-empirical calculation, namely, the CSP-ic (complex scattering potential-ionization contribution) model.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Differentiable stochastic halo occupation distribution

ABSTRACT In this work, we demonstrate how differentiable stochastic sampling techniques developed in the context of deep reinforcement learning can be used to perform efficient parameter inference over stochastic, simulation-based, forward models. As a particular example, we focus on the problem of estimating parameters of halo occupation distribution (HOD) models that are used to connect galaxies with their dark matter haloes. Using a combination of continuous relaxation and gradient re-parametrization techniques, we can obtain well-defined gradients with respect to HOD parameters through discrete galaxy catalogue realizations. Having access to these gradients allows us to leverage efficient sampling schemes, such as Hamiltonian Monte Carlo, and greatly speed up parameter inference. We demonstrate our technique on a mock galaxy catalogue generated from the Bolshoi simulation using a standard HOD model and find near-identical posteriors as standard Markov chain Monte Carlo techniques with an increase of ∼8× in convergence efficiency. Our differentiable HOD model also has broad applications in full forward model approaches to cosmic structure and cosmological analysis.

79 ASTRONOMY AND ASTROPHYSICS↗