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DOE OSTI2025

Continuous-variable quantum Boltzmann machine

Here, we propose a continuous-variable quantum Boltzmann machine (CVQBM) using a powerful energy-based neural network. It can be realized experimentally on a continuous-variable (CV) photonic quantum computer. We used a CV quantum imaginary time evolution (QITE) algorithm to prepare the essential thermal state and then designed the CVQBM to proficiently generate continuous probability distributions. We applied our method to both classical and quantum data. Using real-world classical data, such as synthetic-aperture radar (SAR) images, we generated probability distributions. For quantum data, we used the output of CV quantum circuits. We obtained high fidelity and low Kullback–Leibler (KL) divergence showing that our CVQBM learns distributions from given data well and generates data sampling from that distribution efficiently. We also discussed the experimental feasibility of our proposed CVQBM. Our method can be applied to a wide range of real-world problems by choosing an appropriate target distribution (corresponding to, e.g., SAR images, medical images, and risk management in finance). Moreover, our CVQBM is versatile and could be programmed to perform tasks beyond generation, such as anomaly detection.

SAR images↗

DOE OSTI2023

Energy-Resolved Femtosecond Hot Electron Dynamics in Single Plasmonic Nanoparticles

Efficient excitation and harvesting of hot carriers from nanoscale metals is central to many emerging photochemical, photovoltaic, and ultrafast optoelectronic applications. Nevertheless, direct experimental evidence of the energy-dependent femtosecond dynamics in ubiquitous tens-of-nanometer gold structures remains elusive, despite the potentially rich interplay between interfacial and internal plasmonic fields, excitation distributions, and scattering processes. To explore the effects of nanoscale structure on these dynamics, we employ simultaneous time-, angle-, and energy-resolved photoemission spectroscopy of single plasmonic nanoparticles. Photoelectron velocity and electric field distributions reveal bulk-like ballistic hot electron transport in different geometries, lacking any signatures of surface effects. Energy-resolved dynamics are measured in the 1–2 eV range and extrapolated to lower energies via Boltzmann theory, providing a detailed view of hot electron lifetimes within nanoscale gold. Here, we find that particles with relevant dimensions as small as 10 nm serve as exemplary platforms for studying intrinsic metal dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Intensity modulated Ir-192 brachytherapy using high-Z 3D printed applicators

Gynecologic cancers are often asymmetric, yet current Ir-192 brachytherapy techniques provide only limited radial modulation of the dose. The shielded solutions investigated here solve this by providing the ability to modulate between highly asymmetric and radially symmetric dose distributions at a given location. To find applicator designs that can modulate between full dose and less than 50% dose, at the dimensions of the urethra, a 2D calculation algorithm was developed to narrow down the search space. Two shielding design types were then further investigated using Monte Carlo and Boltzmann-solver dose calculation algorithms. 3D printing techniques using ISO 10993 certified biocompatible plastics and 3D printable tungsten-loaded plastics were tested. It was also found that shadowing effects set by the shape of the shielding cannot be easily modulated out, hence careful design is required. The shielded applicator designs investigated here, allow for reduction of the dose by over 50% at 5 mm from the applicator surface in desired regions, while also allowing radially symmetric dose with isodose line deviations less than 0.5 mm from circular. The shielding designs were also chosen with treatment delivery time in mind. Treatment times for these shielded designs were found to be less than 1.4 times longer than a 6-channel unshielded cylinder for the equivalent fully symmetric dose distribution. The 2D calculation methods developed here provide a simple way to rapidly evaluate shielding designs, while the 3D printing techniques also allow for devices with novel shapes to be rapidly prototyped. Both TOPAS Monte Carlo and Acuros BV calculations show that significant dose shaping and organ at risk sparing can be achieved without significantly compromising the plan in regions that require the full dose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Conditioned quantum-assisted deep generative surrogate for particle-calorimeter interactions

Particle collisions at accelerators like the Large Hadron Collider (LHC), recorded by experiments such as ATLAS and CMS, enable precise standard model measurements and searches for new phenomena. Simulating these collisions significantly influences experiment design and analysis but incurs immense computational costs, projected at millions of CPU-years annually during the high luminosity LHC (HL-LHC) phase. Currently, simulating a single event with Geant4 consumes around 1000 CPU seconds, with calorimeter simulations especially demanding. To address this, we propose a conditioned quantum-assisted generative model, integrating a conditioned variational autoencoder (VAE) and a conditioned restricted Boltzmann machine (RBM). Our RBM architecture is tailored for D-Wave’s Pegasus-structured advantage quantum annealer for sampling, leveraging the flux bias for conditioning. This approach combines classical RBMs as universal approximators for discrete distributions with quantum annealing’s speed and scalability. We also introduce an adaptive method for efficiently estimating effective inverse temperature, and validate our framework on Dataset 2 of CaloChallenge.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

Study of Atmospheric Nitric Oxide

We investigated the contribution of energetic nitrogen atoms to the production of nitric oxide in the thermosphere and their influence on the infrared emission spectrum. The nitric oxide molecules are important contributors to the cooling of the atmosphere. We first pointed out that in determining the energy distribution of the nitrogen atoms, it is important to take into account the thermal motion of the atmospheric gases. It had been ignored in all earlier studies. The source spectra are broadened considerably by the center of mass motion of the reactants. We worked out the consequences for the production of nitric oxide at night, using as sources of energetic N atoms, NO(+) + e yield N + O, N(D-2) + O yield N + O. The high energy tail is enhanced by orders of magnitude. We had earlier suggested (Sharma et al. 1993) that the reaction of energetic nitrogen atoms with O2 was responsible for the rotationally enhanced NO identified in the infrared spectrum. Our calculations provided quantitative confirmation of the suggestion. We proceeded to explore the validity of another approximation used in earlier analyses, the hard sphere approximation for the energy loss in elastic collisions. We carried out precise quantum mechanical calculations of the elastic 2 differential scattering of nitrogen atoms in collisions with oxygen atoms and showed that although the hard sphere approximation was nowhere of high precision, reasonable results could be obtained with an effective cross section of 6 x 10(exp 15)sq cm. We also initiated a program to include inelastic energy loss processes in the determination of the energy distribution function. We began a calculation of the rotation and vibrational excitation cross sections of molecular nitrogen and nitrogen atoms and developed a method for including inelastic energy loss as a function of scattering angle in the Boltzmann equation. A procedure for obtaining the solution of the Boltzman equation was worked out.

Dalgarno, A.↗

NASA NTRS1992

Recovery of the Navier-Stokes equations using a lattice-gas Boltzmann method

A lattice Boltzmann model is presented which gives the complete Navier-Stokes equation and may provide an efficient parallel numerical method for solving various fluid problems. The model uses the single-time relaxation approximation and a particular Maxwell-type distribution. The model eliminates exactly (1) the non-Galilean invariance caused by a density-dependent coefficient in the convection term and (2) a velocity-dependent equation of state.

Chen, Hudong↗

DOE OSTI2025

High-order limiting methods using maximum principle bounds derived from the Boltzmann equation I: Euler equations

The use of limiting methods for high-order numerical approximations of hyperbolic conservation laws generally requires defining an admissible region/bounds for the solution. In this work, we present a novel approach for computing solution bounds and limiting for the Euler equations through the kinetic representation provided by the Boltzmann equation, which allows for extending limiters designed for linear advection directly to the Euler equations. Given an arbitrary set of solution values to compute bounds over (e.g., numerical stencil) and a desired linear advection limiter, the proposed approach yields an analytic expression for the admissible region of particle distribution function values, which may be numerically integrated to yield a set of bounds for the density, momentum, and total energy. Further, these solution bounds are shown to preserve positivity of density/pressure/internal energy and, when paired with a limiting technique, can robustly resolve strong discontinuities while recovering high-order accuracy in smooth regions without any ad hoc corrections (e.g., relaxing the bounds). This approach is demonstrated in the context of an explicit unstructured high-order discontinuous Galerkin/flux reconstruction scheme for a variety of difficult problems in gas dynamics, including cases with extreme shocks and shock-vortex interactions. Furthermore, this work presents a foundation for limiting techniques for more complex macroscopic governing equations that can be derived from an underlying kinetic representation for which admissible solution bounds are not well-understood.

42 ENGINEERING↗

DOE OSTI2021

Insight on electrolyte infiltration of lithium ion battery electrodes by means of a new three-dimensional-resolved lattice Boltzmann model

Electrolyte filling takes place between sealing and formation in Lithium Ion Battery (LIB) manufacturing process. This step is crucial as it is directly linked to LIB quality and affects the subsequent time consuming electrolyte wetting process. Although having fast, homogeneous and complete wetting is of paramount importance, this process has not been sufficiently examined and fully understood. For instance, experimentally available data is insufficient to fully capture the complex interplay upon filling between electrolyte and air inside the porous electrode. We report here for the first time a 3D-resolved Lattice Boltzmann Method (LBM) model able to simulate electrolyte filling upon applied pressure of LIB porous electrodes obtained both from experiments (micro X-ray tomography) and computations (stochastic generation, simulation of the manufacturing process using Coarse Grained Molecular Dynamics and Discrete Element Method). The model allows obtaining advanced insights about the impact of the electrode mesostructures on the speed of electrolyte impregnation and wetting, highlighting the importance of porosity, pore size distribution and pores interconnectivity on the filling dynamics. Furthermore, we identify scenarios where volumes with trapped air (dead zones) appear and evaluate the impact of those on the electrochemical behavior of the electrodes.

25 ENERGY STORAGE↗

NASA NTRS1976

Deviation from a Maxwellian velocity distribution in regions of interstellar molecular hydrogen

The deviation from a Maxwellian velocity distribution caused by excitation of the J = 2 rotational level of parahydrogen (followed by radiative decay) in a molecular hydrogen gas is investigated. It is noted that inelastic collisions deplete the high-velocity tail of the distribution, while elastic collisions tend to refill it; the resulting steady-state distribution has a small depletion in the tail which slightly reduces the cooling rate of the gas. The elastic-collision transport is approximated by a continuous process, a simplified expression is obtained for the inelastic-collision operator, and the Boltzmann equation is then solved analytically. A correction to the inelastic-collision rate is evaluated, and it is found that the relative magnitude of the effect of tail depletion on the inelastic-collision rate is strongly temperature-dependent. The critical molecular density above which the J = 2 level deexcites by superelastic collisions is shown to be a weak function of temperature.

Gould, R. J.↗

DOE OSTI2024

Scalable Implicit Solvers with Dynamic Mesh Adaptation for a Relativistic Drift-Kinetic Fokker–Planck–Boltzmann Model

In this work we consider a relativistic drift-kinetic model for runaway electrons along with a Fokker–Planck operator for small-angle Coulomb collisions, a radiation damping operator, and a secondary knock-on (Boltzmann) collision source. Here, we develop a new scalable fully implicit solver utilizing finite volume and conservative finite difference schemes and dynamic mesh adaptivity. A new data management framework in the PETSc library based on the p4est library is developed to enable simulations with dynamic adaptive mesh refinement (AMR), distributed memory parallelization, and dynamic load balancing of computational work. This framework and the runaway electron solver building on the framework are able to dynamically capture both bulk Maxwellian at the low-energy region and a runaway tail at the high-energy region. To effectively capture features via the AMR algorithm, a new AMR indicator prediction strategy is proposed that is performed alongside the implicit time evolution of the solution. This strategy is complemented by the introduction of computationally cheap feature-based AMR indicators that are analyzed theoretically. Numerical results quantify the advantages of the prediction strategy in better capturing features compared with nonpredictive strategies; and we demonstrate trade-offs regarding computational costs. The robustness with respect to model parameters, algorithmic scalability, and parallel scalability are demonstrated through several benchmark problems including manufactured solutions and solutions of different physics models. We focus on demonstrating the advantages of using implicit time stepping and AMR for runaway electron simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2020

A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealing

A class of quantum-classical hybrid machine-learning algorithms can be obtained by integrating classical deep generative models with quantum probability distributions as 'priors' over their latent variables. We introduce a hybrid implementation of variational autoencoders (QVAE) and also present a technique to hybridize flow-based invertible generative models. We demonstrate the use of D-Wave quantum annealers as physical simulators of quantum Boltzmann machines (QBM) to perform quantum-assisted training of QVAE. Latent-space QBM develop slowly mixing modes, opening a path to obtain quantum advantage in generative modeling with available quantum devices.

Vinci, Walter↗

DOE OSTI2021

Nanopore networks in colloidal silica assemblies characterized by XCT for confined fluid flow modeling

Fluid flow through nanopore structures has exhibited different behavior than that described by Darcy's law, derived from pore networks of micrometer scale. Here, pressure assemblies of colloidal silica spheres of specified diameters from 94 to 620 nanometers were prepared as model nano-porous media. The smaller silica spheres tended to form random packing, but some substantial ordering was found in the packing of the larger silica spheres. X-ray computed tomography (XCT), with a voxel resolution of 16 nm, was used to characterize the nanopore networks. The porosity of the Nano-XCT pore network (34%) was less than the total porosity of the assemblies as determined by X-ray attenuation (52%), possibly due to the limits of voxel resolution during segmentation. Fluid flow in the nanopore networks was simulated using the single-phase Lattice Boltzmann Method, and the simulated permeability was compared with the empirical and experimental values. Based on our characterization, although a well-ordered packing of silica spheres was not achieved, it was found that the nanopore networks in the colloidal silica assemblies had pore size distributions corresponding to the particle sizes. The simulated permeability was less than the experimental measurement for water flow, but the complex packing of silica spheres and surface chemistry issues need to be considered in future research.

02 PETROLEUM↗

DOE OSTI2024

The Information Length Concept Applied to Plasma Turbulence

A methodology to study statistical properties of anomalous transport in fusion plasma is investigated. Three time traces generated by the full-f gyrokinetic code GKNET are analyzed for this purpose. The time traces consist of heat flux as a function of the radial position, which is studied in a novel manner using statistical methods. The simulation data exhibit transport processes with both medium and long correlation length along the radius. A typical example of a phenomenon with long correlation length is avalanches. In order to investigate the evolution of the turbulent state, two basic configurations are studied, one flux-driven and one gradient-driven with decaying turbulence. The information length concept in tandem with Boltzmann–Gibbs and Tsallis entropy is used in the investigation. It is found that the dynamical states in both flux-driven and gradient-driven cases are surprisingly similar, but the Tsallis entropy reveals differences between them. This indicates that the types of probability distribution function are nevertheless quite different since the higher moments are significantly different.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1975

Theory of photoelectron thermalization and transport in the ionosphere

A new theoretical approach for calculating the equilibrium photoelectron flux energy and pitch angle distribution in the ionosphere is presented. Photoelectron transport, secondary electron production, and energy degradation by the excitation of the discrete energy states of the neutral atmospheric constituents and by continuous energy transfer to the ambient thermal electron gas are included in a manner consistent with the Boltzmann equation which constitutes the foundation of the theory. A difference equation, suitable for numerical solution, is given, and a numerical method for the solution of this equation is discussed in detail.

Mantas, G. P.↗

NASA NTRS1991

Transport of photons produced by lightning in clouds

The optical effects of the light produced by lightning are of interest to atmospheric scientists for a number of reasons. Two techniques are mentioned which are used to explain the nature of these effects: Monte Carlo simulation; and an equivalent medium approach. In the Monte Carlo approach, paths of individual photons are simulated; a photon is said to be scattered if it escapes the cloud, otherwise it is absorbed. In the equivalent medium approach, the cloud is replaced by a single obstacle whose properties are specified by bulk parameters obtained by methods due to Twersky. Herein, Boltzmann transport theory is used to obtain photon intensities. The photons are treated like a Lorentz gas. Only elastic scattering is considered and gravitational effects are neglected. Water droplets comprising a cuboidal cloud are assumed to be spherical and homogeneous. Furthermore, it is assumed that the distribution of droplets in the cloud is uniform and that scattering by air molecules is neglible. The time dependence and five dimensional nature of this problem make it particularly difficult; neither analytic nor numerical solutions are known.

Solakiewicz, Richard↗

DOE OSTI2021

Reduced-model scrape-off layer turbulence (nSOLT) simulations comparing three fueling scenarios

The 2D scrape-off-layer turbulence code (nSOLT) includes 1D Boltzmann neutral–plasma interactions, a model of divertor recycling (introduced here), and a fixed source of plasma concentrated at the core-side boundary. Three fueling methods are considered herein: (1) neutral injection in the far-SOL is accomplished by specifying the density of Franck–Condon distributed neutrals streaming in from the boundary. (2) Divertor recycling is modeled by injecting a fraction of the particle parallel flux in the scrape-off layer (SOL) back into the edge region as a source of plasma. (3) A constant source fuels the edge plasma from the core-side boundary to model pellet injection. For machine parameters (B, R m , and L // ) illustrative of the MAST-U device, and for a deuterium plasma, turbulent equilibria are obtained that share the same plasma fueling rate for each of the three fueling methods, with only one of the sources on in each case. In the presence of self-consistent turbulence, quasi-steady plasma and neutral (deuterium) profiles, fueling efficiencies, SOL transparencies, and heat flux widths are compared. Characteristics of the turbulent fluctuations, including skewness, cross-phases, and power spectra, are described. The calculated fueling efficiencies, SOL transparencies to neutral penetration, and many of the turbulent properties are remarkably similar for all three fueling methods despite significant differences in the plasma profiles. The nonlinear states of the three cases are dominated by separatrix-spanning vortex cells that control particle and heat losses into the SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Entanglement features of random neural network quantum states

Restricted Boltzmann machines (RBMs) are a class of neural networks that have been successfully employed as a variational ansatz for quantum many-body wave functions. Here, we develop an analytic method to study quantum many-body spin states encoded by random RBMs with independent and identically distributed complex Gaussian weights. By mapping the computation of ensemble-averaged quantities to statistical mechanics models, we are able to investigate the parameter space of the RBM ensemble in the thermodynamic limit. We discover qualitatively distinct wave functions by varying RBM parameters, which correspond to distinct phases in the equivalent statistical mechanics model. Notably, there is a regime in which the typical RBM states have near-maximal entanglement entropy in the thermodynamic limit, similar to that of Haar-random states. However, these states generically exhibit nonergodic behavior in the Ising basis, and do not form quantum state designs, making them distinguishable from Haar-random states.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Electromagnetic scattering in clouds

Techniques used to explain the nature of the optical effects of clouds on the light produced by lightning include a Monte Carlo simulation, an equivalent medium approach, and methods based on Boltzmann transport theory. A cuboidal cloud has been considered using transform methods and a diffusion approximation. Many simplifying assumptions have been used by authors to make this problem tractable. In this report, the cloud will have a spherical shape and its interior will consist of a uniform distribution of identical spherical water droplets. The source will be modeled as a Hertz dipole, electric or magnetic, inside or outside the cloud. An impulsive source is used. Superposition may be employed to obtain a sinusoid within an envelope which describes a lightning event. The problem is investigated by transforming to the frequency domain, obtaining Green's functions, and then using the Cagniard-DeHoop method to symbolically recover the time domain solution.

Solakiewicz, Richard↗