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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding how chemical structure affects ignition-delay-time $\phi$-sensitivity

$\phi$-sensitivity is the change in ignition delay time (IDT) with respect to the fuel-to-air equivalence ratio ($\phi$). High $\phi$-sensitivity is a desirable fuel property for applications in advanced compression ignition and multi-mode engine designs. Understanding how $\phi$-sensitivity depends on chemical structure is essential for selecting promising biofuels from the ever-growing list of proposed candidates. Here, we investigate the effect of chemical structure on $\phi$-sensitivity with experiment, simulation, and theory. Experimental Advanced Fuel Ignition Delay Analyzer (AFIDA) measurements for 2,4-dimethylpentane and diisopropyl ether provide evidence that branching and functional groups strongly impact $\phi$-sensitivity. Further insights into this dependence are obtained with 0-D kinetic simulations with existing mechanisms for n-pentane, diethyl ether, 3-pentanone, n-heptane, 2-methylhexane, 2,4-dimethylpentane, and 2,2,3-trimethylbutane. Quantum mechanical (QM) G4 calculations of low-temperature reactions help explain the observed experimental and simulation trends. Specifically, these QM calculations provide theoretical estimates of the ketohydroperoxide (KHP) dissociation rates, the HO 2 formation rates from peroxy radical (ROO), and the “cross-over” temperatures, i.e., the temperature at which ROO dissociation is favored compared to hydroperoxyl radical (QOOH) formation. Each of these reaction rates is compared to the n-alkane reference point to determine the impact of branching and different functional groups. Although kinetic mechanisms typically assume that KHP dissociation rates are invariant of chemical environment, our QM results suggest that this rate can span a range of roughly two orders of magnitude. We also discuss the importance of including the peroxy-hydroperoxy (OO-OOH) hydrogen transfer reaction for branched ethers. Finally, the insights gained assist in proposing a highly $\phi$-sensitive compound, namely, isopropyl propyl ether.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

HPC4Mfg with Samsung: Making semiconductor devices cool through HPC ab initio simulations

For decades, the semiconductor technology has followed the Moore’s law, making newer devices more powerful and energy efficient. Recently, however, it has reached a point where the performance and the energy efficiency of the device do not improve with the shrinking device size. One of the fundamental reasons of this deviation from the past trend is the interconnect resistance, which becomes larger with the shrinking size. The devices size is so small that the quantum mechanical effects can no longer be ignored and the traditional continuum simulation tools such as TCAD become inadequate. In this project, Samsung Semiconductor Inc. and Lawrence Berkeley National Laboratory has collaborated to perform first of kind device-scale ab initio simulations to optimize materials and interconnect morphology to minimize interconnect resistance. We have tested the use of LS3DF method and the PEtot_trans approach on top of the folded spectrum method (FSM) Escan code to calculate the scattering state, and to study various effects influence the interconnect conductivity. We found that, the LS3DF can be used to calculate such metallic system. On the other hand, the use of Escan code to solve the linear equation is not practical due to the slow convergence. We have implemented a Chebyshev filter technique to calculate a few hundred eigen states near the scattering state energy E, then use these eigen states as preconditioner to solve the linear equation. We have used this approach to study the different factors which affect the interconnect conductivity, including the shape, the point defect, the temperature, and the grain boundary.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Loschmidt-echo approach to error estimation in Krylov-subspace approximation

The Krylov subspace method is a traditional approach to approximate quantum evolution, allowing us to treat systems with large Hilbert spaces. Despite its popularity, current bounds typically overestimate the error, which translates into more expensive simulation routines. Here, in this paper, we tackle this problem by realizing that the error can be understood as a Loschmidt echo in a one-dimensional (1D) noninteracting tight-binding Hamiltonian. We show that the different time regimes of the approximation can be understood using simple physical ideas. More importantly, we obtain computationally cheap error bounds that describe with high precision the actual error in the approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Correlator convolutional neural networks as an interpretable architecture for image-like quantum matter data

Image-like data from quantum systems promises to offer greater insight into the physics of correlated quantum matter. However, the traditional framework of condensed matter physics lacks principled approaches for analyzing such data. Machine learning models are a powerful theoretical tool for analyzing image-like data including many-body snapshots from quantum simulators. Recently, they have successfully distinguished between simulated snapshots that are indistinguishable from one and two point correlation functions. Thus far, the complexity of these models has inhibited new physical insights from such approaches. Here, we develop a set of nonlinearities for use in a neural network architecture that discovers features in the data which are directly interpretable in terms of physical observables. Applied to simulated snapshots produced by two candidate theories approximating the doped Fermi-Hubbard model, we uncover that the key distinguishing features are fourth-order spin-charge correlators. Our approach lends itself well to the construction of simple, versatile, end-to-end interpretable architectures, thus paving the way for new physical insights from machine learning studies of experimental and numerical data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Modeling Turbulence in Galactic Centers

Turbulence is a prevalent phenomenon in the interstellar medium, and in particular, the environment at the centers of galaxies. For example, detailed observations of the Milky Way’s Central Molecular Zone (CMZ) revealed that it has a complex and turbulent structure. Turbulence on galactic scales is often modeled using star formation and feedback. However, these effects do not appear to be sufficient for explaining the high-velocity dispersion observed in the CMZ, indicating that additional gas-stirring processes are likely to be operating. Here we introduce a proof-of-concept method to drive turbulence in gas that orbits under the influence of a galactic potential. Instead of relying on a particular physical mechanism, we have adopted a Fourier forcing module and have applied it using a smoothed particle hydrodynamics code. To test our method, we performed simulations of a simplistic model of the CMZ. Our turbulence injection method is capable of balancing the self-gravity of the gas, which allows us to run the simulations for long timescales and thereby follow the evolution of the CMZ. Our results show that turbulence induces a flocculent spiral pattern in our model, analogous to that found in galactic-scale simulations. Furthermore, we find that our turbulence injection method induces inward migration of gas, a result consistent with previous numerical simulations. We submit that this injection method is a promising new tool to simulate turbulence in galactic centers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Koopman wavefunctions and Clebsch variables in Vlasov–Maxwell kinetic theory

Motivated by recent discussions on the possible role of quantum computation in plasma simulations, here, we present different approaches to Koopman's Hilbert-space formulation of classical mechanics in the context of Vlasov–Maxwell kinetic theory. The celebrated Koopman–von Neumann construction is provided with two different Hamiltonian structures: one is canonical and recovers the usual Clebsch representation of the Vlasov density, the other is non-canonical and appears to overcome certain issues emerging in the canonical formalism. Furthermore, the canonical structure is restored for a variant of the Koopman–von Neumann construction that carries a different phase dynamics. Going back to van Hove's prequantum theory, the corresponding Koopman–van Hove equation provides an alternative Clebsch representation which is then coupled to the electromagnetic fields. Finally, the role of gauge transformations in the new context is discussed in detail.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Verification of local electrostatic gyrokinetic simulation of driftwave instability in field-reversed configuration

Local linear simulations of ion temperature gradient (ITG) instabilities using a gyrokinetic particle code GKD1D have been verified by comparing with the analytic dispersion relation in the slab geometry and by benchmarking with a global gyrokinetic code GTC-X in a realistic field-reversed configuration (FRC). Results of ITG simulations using either adiabatic or kinetic electrons exhibit excellent agreements between the two codes for linear frequencies, growth rates, and mode structures. The ITG modes in the FRC scrape-off layer region are mostly dominated by the poloidal m = 1 harmonic. Kinetic electrons enhance the subdominant m = 2 harmonic and the even parity dominates the ITG mode structure. Kinetic electrons increase the growth rates for the low-n modes, but decrease the growth rates for the high-n modes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Fast-forwarding quantum simulation with real-time quantum Krylov subspace algorithms

Quantum subspace diagonalization (QSD) algorithms have emerged as a competitive family of algorithms that avoid many of the optimization pitfalls associated with parameterized quantum circuit algorithms. While the vast majority of the QSD algorithms have focused on solving the eigenpair problem for ground, excited-state, and thermal observable estimation, there has been a lot less work in considering QSD algorithms for the problem of quantum dynamical simulation. In this work, we propose several quantum Krylov fast-forwarding (QKFF) algorithms capable of predicting long-time dynamics well beyond the coherence time of current quantum hardware. Our algorithms use real-time evolved Krylov basis states prepared on the quantum computer and a multi-reference subspace method to ensure convergence towards high-fidelity, long-time dynamics. In particular, we show that the proposed multi-reference methodology provides a systematic way of trading off circuit depth with classical post-processing complexity. Further, we also demonstrate the efficacy of our approach through numerical implementations for several quantum chemistry problems including the calculation of the auto-correlation and dipole moment correlation functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description of electrons, phase space sampling of liquid electrolytes, and equilibration of electrolytes over nanosecond time scales. All models of electrochemistry make different trade-offs in the approximation of electrons and atomic configurations, from the extremes of classical molecular dynamics of a complete interface with point-charge atoms to correlated electronic structure methods of a single electrode configuration with no dynamics or electrolyte. Here, we review the spectrum of simulation techniques suitable for electrochemistry, focusing on the key approximations and accuracy considerations for each technique. Additionally, we discuss promising approaches, such as enhanced sampling techniques for atomic configurations and computationally efficient beyond density functional theory (DFT) electronic methods, that will push electrochemical simulations beyond the present frontier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Representation Learning via Quantum Neural Tangent Kernels

Variational quantum circuits are used in quantum machine learning and variational quantum simulation tasks. Designing good variational circuits or predicting how well they perform for given learning or optimization tasks is still unclear. Here we discuss these problems, analyzing variational quantum circuits using the theory of neural tangent kernels. We define quantum neural tangent kernels, and derive dynamical equations for their associated loss function in optimization and learning tasks. We analytically solve the dynamics in the frozen limit, or lazy training regime, where variational angles change slowly and a linear perturbation is good enough. We extend the analysis to a dynamical setting, including quadratic corrections in the variational angles. We then consider a hybrid quantum classical architecture and define a large-width limit for hybrid kernels, showing that a hybrid quantum classical neural network can be approximately Gaussian. The results presented here show limits for which analytical understandings of the training dynamics for variational quantum circuits, used for quantum machine learning and optimization problems, are possible. These analytical results are supported by numerical simulations of quantum machine-learning experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Using Complex Probability Amplitudes to Simulate Solute Transport in Composite Porous Media

Probability amplitudes are fundamental to quantum mechanics and offer robust descriptions of complicated systems, which have allowed physicists to explain behaviors inaccessible to classical physics. This article ponders how some of the same conceptual underpinnings of the mathematics used for modeling quantum systems might be applied to subsurface water resources problems and speculates how these tools could facilitate applications on quantum computers. A probability amplitude-based model for describing advective-dispersive transport in porous media using linear operators is investigated. The proposed complex valued model decomposes spreading into two “sub-continuum partial dispersion” coefficients, and this recovers classical spreading when the sum of these coefficients is the Fickian dispersion coefficient. However, the probability amplitudes have a manyto-one relationship to a probability distribution, so it embeds a level of heterogeneity into seemingly equivalent functions. Two propagators with different sub-continuum coefficients may have the same macroscopic behavior when either is considered in isolation, but when they act on the other the system’s behavior changes. Additionally, differences in the amplitudes cause a reduction in spreading as velocity correlations are disrupted, despite both propagators having identical dispersion coefficients, and this cannot be achieved using classical methods without changing the dispersion coefficient. The main point is that these amplitude-based models offer a way to embed information about the system into the propagators, instead of just “averaging it out” when making an upscaled model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Monitoring of mechanical changes in a pipe assembly with complex geometry using multi-mode acoustic signals

Guided wave ultrasonic testing has been widely used for nondestructive and long-range evaluation of diverse mechanical structures, such as pipes and plates. In general, a large number of guided wave modes exist even in the simplest geometries, and they exhibit highly dispersive characteristics. Thus, sophisticated excitation methods and elaborate modal analyses need to be implemented to excite, acquire, and process well-defined pure modes as part of such a measurement method. If the interrogated structure has complex geometry, for example, with cross-sectional variations or multiple joints, the utilization of pure modes becomes significantly more difficult. To overcome this difficulty, this paper proposes the use of multi-mode, multi-frequency guided waves for long-range inspection of structures with arbitrarily complex geometries. Furthermore, using broadband chirp signals and multi-mode time–frequency analysis in a prototypical complex pipe assembly that includes multiple pipe diameters, elbows, and flange connections, we experimentally show sensitive detection of mechanical changes (both material addition and loss). In addition, we demonstrate that the complexity of the structure can be modeled in the digital domain with sufficient detail to allow accurate numerical simulation of the acoustic response using this method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Primary Velocity and Orbital Phase Effects on Planetary Detectability from Small Epoch Number Data Sets

Cross-correlation analyses of high-resolution spectroscopic data have recently shown great success in directly detecting planetary signals and enabling the characterization of their atmospheres. One such technique aims to observe a system at multiple epochs and combine the measured planetary radial velocities from each epoch into a measurement of the planetary Keplerian orbital velocity K {sub p}, constituting a direct detection of the planetary signal. Recent work has shown that in few-epoch (∼5) data sets, unintended structure can arise at a high level, obscuring the planetary detection. In this work, we look to simulations to examine whether there are ways to reduce this structured noise in few-epoch data sets by careful planning of observations. The choice of observation date allows observers to select the primary (stellar) velocity through a set systemic velocity and chosen barycentric velocity and the planetary orbital phase so we focus on the effects of these two parameters. We find that epochs taken when the primary velocity is near zero and the stellar lines remain relatively fixed to the telluric rest-frame greatly reduce the level of structured noise and allow for much stronger planetary detections, on average more than twice the significance of detections made with epochs using randomly selected primary velocities. Following these results, we recommend that observers looking to build up high-resolution multi-epoch data sets target nights when their system has a near-zero primary velocity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Measurement accuracy and spatial resolution of a distributed temperature sensor based on a two-pulse differential coherent reflectometer

We present a model and numerical simulation of a distributed temperature sensor based on a two-pulse differential coherent optical time-domain reflectometer (COTDR). The differential phase measured using a phase-sensitive Rayleigh reflectometer is shown to have a regular component, which is a linear function of temperature, and a random component, which is related to a random distribution of scattering centres in the fibre and restricts the accuracy of measurements of variations in temperature. Measurement accuracy can be improved by reducing the relative contribution of the random component via a decrease in pulse duration and/or an increase in the time delay between pulses. The spatial resolution of a differential two-pulse phase-sensitive reflectometer is shown to be determined by the time delay between pulses and to vary little with pulse duration. At a typical pulse duration (200 ns) and delay time (300 ns), the accuracy in measurements of variations in temperature in the 0.1-K range is 2 % and the spatial resolution is about 30 m. (fibre-optic sensors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Fixed Depth Hamiltonian Simulation via Cartan Decomposition

Simulating quantum dynamics on classical computers is challenging for large systems due to the significant memory requirements. Simulation on quantum computers is a promising alternative, but fully optimizing quantum circuits to minimize limited quantum resources remains an open problem. In this study, we tackle this problem by presenting a constructive algorithm, based on Cartan decomposition of the Lie algebra generated by the Hamiltonian, which generates quantum circuits with time-independent depth. We highlight our algorithm for special classes of models, including Anderson localization in one-dimensional transverse field $\mathrm{XY}$ model, where $\mathscr{O}$(n 2 )-gate circuits naturally emerge. Compared to product formulas with significantly larger gate counts, our algorithm drastically improves simulation precision. In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Theoretical methods to design and test quantum simulators for the compact Abelian Higgs model

The lattice compact Abelian Higgs model is a nonperturbative regularized formulation of low-energy scalar quantum electrodynamics. In 1+1 dimensions, this model can be quantum simulated using a ladder-shaped optical lattice with Rydberg-dressed atoms. In this setup, one spatial dimension is used to carry the angular momentum of the quantum rotors. One can use truncations corresponding to spin-2 and spin-1 to build local Hilbert spaces associated with the links of the lattice. We argue that ladder-shaped configurable arrays of Rydberg atoms can be used for the same purpose. We make concrete proposals involving two and three Rydberg atoms to build one local spin-1 space (a qutrit). We show that the building blocks of the Hamiltonian calculations are models with one and two spins. We compare target and simulators using perturbative and numerical methods. The two-atom setup provides an easily controllable simulator of the one-spin model while the three-atom setup involves solving nonlinear equations. We discuss approximate methods to couple two spin-1 spaces. The article provides analytical and numerical tools necessary to design and build the proposed simulators with current technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Digital Quantum Simulation of the Schwinger Model and Symmetry Protection with Trapped Ions

Tracking the dynamics of physical systems in real time is a prime application of quantum computers. Using a trapped-ion system with up to six qubits, we simulate the real-time dynamics of a lattice gauge theory in 1+1 dimensions, i.e., the lattice Schwinger model, and demonstrate nonperturbative effects such as pair creation for times much longer than previously accessible. We study the gate requirement of two formulations of the model using the Suzuki-Trotter product formula, as well as the trade-off between errors from the ordering of the Hamiltonian terms, the Trotter step size, and experimental imperfections. To mitigate experimental errors, a recent symmetry-protection protocol for suppressing coherent errors and a symmetry-inspired postselection scheme are applied. This work demonstrates the integrated theoretical, algorithmic, and experimental approach that is essential for efficient simulation of lattice gauge theories and other complex physical systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Effect of diffusion constant on the morphology of dendrite growth in lithium metal batteries

Lithium dendrites can lead to a short circuit and battery failure, and developing strategies for their suppression is of considerable importance. In this work, we study the growth of dendrites in a simple model system where the solvent is a continuum and the lithium ions are hard spheres that can deposit by sticking to existing spheres or the electrode surface. Using stochastic dynamics simulations, we investigate the effect of applied voltage and diffusion constant on the growth of dendrites. We find that the diffusion constant is the most significant factor, and the inhomogeneity of the electric field does not play a significant role. Additionally, the growth is most pronounced when the applied voltage and diffusion constant are both low. We observe a structural change from broccoli to cauliflower shape as the diffusion constant is increased. The simulations suggest that a control of electrolyte parameters that impact lithium diffusion might be an attractive route to controlling dendrite growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗