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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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NASA NTRS2002

Atomistic Modeling of Semiconductors: Si, C, and 3C-SiC

An ongoing task of the Computational Materials Group (CMG) at the NASA Glenn Research Center is to enhance the role of atomistic simulations based on quantum-approximate methods in the study of new materials and their properties. One of the main goals of the activity continues to be breaching limitations that arise from the natural balance between accuracy, range of application, and computational simplicity. Whether that balance can be maintained while breaking new ground depends on the methods available with a minimum of constraints and limitations for the study of the energetics of arbitrary systems. The main tool used in CMG research, the Bozzolo- Ferrante-Smith (BFS) method for alloys, has no inherent constraint in its formulation, a feature that has allowed for successful research on various topics. In this article, we report on the latest development of the CMG program, namely, the extension and application of the BFS method to compound semiconductors, a departure from our previous research based primarily on metallic alloys.

Bozzolo, Guillermo↗
NASA NTRS1971

Photoactivation of the manganese catalyst of O2 evolution. II A two-quantum mechanism.

A kinetic analysis is presented of the data obtained in previously described kinetic experiments relating to the photoactivation of the Mn complex required for photosynthetic O2 evolution. The results obtained from the computer simulation of the derived kinetic model compare favorably with the experimentally derived values. They also suggest that photoactivation can be rationalized in terms of a two-quantum process.

Radmer, R.↗
NASA NTRS2002

Dynamics of Quantum Adiabatic Evolution Algorithm for Number Partitioning

We have developed a general technique to study the dynamics of the quantum adiabatic evolution algorithm applied to random combinatorial optimization problems in the asymptotic limit of large problem size n. We use as an example the NP-complete Number Partitioning problem and map the algorithm dynamics to that of an auxiliary quantum spin glass system with the slowly varying Hamiltonian. We use a Green function method to obtain the adiabatic eigenstates and the minimum exitation gap, gmin = O(n2(sup -n/2)), corresponding to the exponential complexity of the algorithm for Number Partitioning. The key element of the analysis is the conditional energy distribution computed for the set of all spin configurations generated from a given (ancestor) configuration by simultaneous flipping of a fixed number of spins. For the problem in question this distribution is shown to depend on the ancestor spin configuration only via a certain parameter related to the energy of the configuration. As the result, the algorithm dynamics can be described in terms of one-dimensional quantum diffusion in the energy space. This effect provides a general limitation of a quantum adiabatic computation in random optimization problems. Analytical results are in agreement with the numerical simulation of the algorithm.

Smelyanskiy, Vadius↗
NASA NTRS2002

Dynamics of Quantum Adiabatic Evolution Algorithm for Number Partitioning

We have developed a general technique to study the dynamics of the quantum adiabatic evolution algorithm applied to random combinatorial optimization problems in the asymptotic limit of large problem size n. We use as an example the NP-complete Number Partitioning problem and map the algorithm dynamics to that of an auxiliary quantum spin glass system with the slowly varying Hamiltonian. We use a Green function method to obtain the adiabatic eigenstates and the minimum excitation gap. g min, = O(n 2(exp -n/2), corresponding to the exponential complexity of the algorithm for Number Partitioning. The key element of the analysis is the conditional energy distribution computed for the set of all spin configurations generated from a given (ancestor) configuration by simultaneous flipping of a fixed number of spins. For the problem in question this distribution is shown to depend on the ancestor spin configuration only via a certain parameter related to 'the energy of the configuration. As the result, the algorithm dynamics can be described in terms of one-dimensional quantum diffusion in the energy space. This effect provides a general limitation of a quantum adiabatic computation in random optimization problems. Analytical results are in agreement with the numerical simulation of the algorithm.

Smelyanskiy, V. N.↗
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
NASA NTRS1999

Computational Study of Field Initiated Surface Reactions for Synthesis of Diamond and Silicon

This project involves using quantum chemistry to simulate surface chemical reactions in the presence of an electric field for nanofabrication of diamond and silicon. A field delivered by a scanning tunneling microscope (STM) to a nanometer scale region of a surface affects chemical reaction potential energy surfaces (PES) to direct atomic scale surface modification to fabricate sub-nanometer structures. Our original hypothesis is that the applied voltage polarizes the charge distribution of the valence electrons and that these distorted molecular orbitals can be manipulated with the STM so as to change the relative stabilities of the electronic configurations over the reaction coordinates and thus the topology of the PES and reaction kinetics. Our objective is to investigate the effect of applied bias on surface reactions and the extent to which STM delivered fields can be used to direct surface chemical reactions on an atomic scale on diamond and silicon. To analyze the fundamentals of field induced chemistry and to investigate the application of this technique for the fabrication of nanostructures, we have employed methods capable of accurately describing molecular electronic structure. The methods we employ are density functional theory (DFT) quantum chemical (QC) methods. To determine the effect of applied bias on surface reactions we have calculated the QC PESs in various applied external fields for various reaction steps for depositing or etching diamond and silicon. We have chosen reactions which are thought to play a role in etching and the chemical vapor deposition growth of Si and diamond. The PESs of the elementary reaction steps involved are then calculated under the applied fields, which we vary in magnitude and configuration. We pay special attention to the change in the reaction barriers, and transition state locations, and search for low energy reaction channels which were inaccessible without the applied bias.

Musgrave, Charles Bruce↗
NASA NTRS1998

Computational Modeling of Vertical-Cavity Surface-Emitting Lasers

Vertical-Cavity Surface-Emitting Lasers (VCSELs) have become increasingly important for many applications, such as optical interconnects and optical data storages. In many applications, critical requirements are very often high beam quality and/or high output powers. To help the design and optimization of VCSELs for such applications, it is essential to have a simulation model that includes the time evolution of the transverse space dependence of the hewn. Such models allow arbitrary transverse profiles of laser intensity or carrier density to develop in time without any a priori assumption about the number and types of transverse modes. In addition, extensive research in the past has shown that many-body effects are important in influencing the optical gain and the refractive index of semiconductor quantum wells. It is thus important to include the key many-body effects in simulation models for semiconductor lasers. A computational model, called the Maxwell-Effective Bloch Equations (MEBE) was developed recently that simulates the above features and effects. This model combines the space-time resolution with microscopic many-body effects in a way that is both accurate enough and computationally manageable. This model has been used to simulate edge-emitting high power lasers recently. A new finite-difference algorithm has been developed for solving these equations and will be shown in the presentation. That algorithm will be used to calculate the detailed time evolution of the transverse mode profiles of VCSELs. The VCSELs are based on InGaAs/GaAs quantum well structures. Effects of pumping current and refractive index profiles will be investigated in detail. The simulation results will be compared with other results the use the rate-equation model.

Goorjian, Peter M.↗
NASA NTRS1998

Computational Nonlinear of Vertical-Cavity Surface-Emitting Lasers

Vertical-Cavity Surface-Emitting Lasers (VCSELs) have become increasingly important for many applications, such as optical interconnects and optical data storages. In many applications, critical requirements are very often high beam quality and/or high output powers. To help the design and optimization of VCSELs for such applications, it is essential to have a simulation model that includes the time evolution of the transverse space dependence of the beam. Such models allow arbitrary transverse profiles of laser intensity or carrier density to develop in time without any a priori assumption about the number and types of transverse modes. In addition, extensive research in the past has shown that many-body effects are important in influencing the optical gain and the refractive index of semiconductor quantum wells. It is thus important to include the key many-body effects in simulation models for semiconductor lasers. A computational model, called the Maxwell-Effective Bloch Equations (MEBE) was developed recently that simulates the above features and effects. This model combines the space-time resolution with microscopic many-body effects in a way that is both accurate enough and computationally manageable. This model has been used to simulate edge-emitting high power lasers recently. A new finite-difference algorithm has been developed for solving these equations and will be shown in the presentation. That algorithm will be used to calculate the detailed time evolution of the transverse mode profiles of VCSELs. The VCSELs are based on InGaAs/GaAs quantum well structures. Effects of pumping current and refractive index profiles will be investigated in detail. The simulation results will be compared with other results the use the rate-equation model.

Goorjian, Peter M.↗
NASA NTRS1998

Quantum Molecular Dynamics Simulations of Nanotube Tip Assisted Reactions

In this report we detail the development and application of an efficient quantum molecular dynamics computational algorithm and its application to the nanotube-tip assisted reactions on silicon and diamond surfaces. The calculations shed interesting insights into the microscopic picture of tip surface interactions.

Menon, Madhu↗
NASA NTRS2017

QSPIN: A High Level Java API for Quantum Computing Experimentation

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Quantu↗
NASA NTRS1983

Maximizing the quantum efficiency of microchannel plate detectors - The collection of photoelectrons from the interchannel web using an electric field

High quantum efficiency and two-dimensional imaging capabilities make the microchannel plate (MCP) a suitable detector for a sky survey instrument. The Extreme Ultraviolet Explorer satellite, to be launched in 1987, will use MCP detectors. A feature which limits MCP efficiency is related to the walls of individual channels. The walls are of finite thickness and thus form an interchannel web. Under normal circumstances, this web does not contribute to the detector's quantum efficiency. Panitz and Foesch (1976) have found that in the case of a bombardment with ions, electrons were ejected from the electrode material coating the web. By applying a small electric field, the electrons were returned to the MCP surface where they were detected. The present investigation is concerned with the enhancement of quantum efficiencies in the case of extreme UV wavelengths. Attention is given to a model and a computer simulation which quantitatively reproduce the experimental results.

Taylor, R. C.↗
NASA NTRS1998

Modeling and Simulation of Semiconductor Quantum Well Structures and Lasers

In this talk I will cover two aspects of modeling and simulation efforts at NASA Ames Research Center. In the quantum well structure simulation, we typically start from the quantum mechanical calculation of the quantum well structures for the confined/and unconfined eigen states and functions. A bandstructure calculation of the k*p type is then performed for the confined valence states. This information is then used to computer the optical gain and refractive index of the quantum well structures by solving the linearized multiband semiconductor Bloch equations with the many-body interactions included. In our laser simulation, we typically solve the envelope equations for the laser field in space-time domain, coupled with a reduced set of material equations using the microscopic calculation of the first step. Finally I will show some examples of both aspects of simulation and modeling.

Ning, Cun-Zheng↗
NASA NTRSDate not supplied

Exploring Quantum State Preparation Using Tensor Networks and Sparse Wavefunction Simulations

The variational quantum eigenvalue solver is a powerful hybrid quantum-classical approach that has been suggested as a candidate method to run on near-term quantum hardware for computing ground state electronic energies of molecular systems. However, even for small molecules, the number of variational parameters and qubits required to minimize the electronic energy is beyond the reach of current quantum computers except for small basis sets. We explore a new paradigm for state preparation where we test how much of the optimization can be approximately prepared with classical computers to reduce the number of optimization steps performed using a quantum device. By adapting a recent algorithm for the factorized form of the UCC ansatz, we can study molecular electronic structure problems with up to 64 qubits. In addition, we also test a related approach of using tensor networks to optimize quantum circuits in order to benchmark various lattice models. We present results using these approaches and discuss strategies for incorporating these ideas into variational algorithms involving near-term quantum computers. Our results help demonstrate the strength of the UCC ansatz and address pressing questions about optimal initial parameterizations and circuit construction.

quantum computing↗
NASA NTRS2011

Comparison of DSMC and CFD Solutions of Fire II Including Radiative Heating

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. These flows may also contain significant radiative heating. To prepare for these missions, NASA is developing the capability to simulate rarefied, ionized flows and to then calculate the resulting radiative heating to the vehicle's surface. In this study, the DSMC codes DAC and DS2V are used to obtain charge-neutral ionization solutions. NASA s direct simulation Monte Carlo code DAC is currently being updated to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced Quantum-Kinetic chemistry model, and to include electronic energy levels as an additional internal energy mode. The Fire II flight test is used in this study to assess these new capabilities. The 1634 second data point was chosen for comparisons to be made in order to include comparisons to computational fluid dynamics solutions. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid. It is shown that there can be quite a bit of variability in the vibrational temperature inferred from DSMC solutions and that, from how radiative heating is computed, the electronic temperature is much better suited for radiative calculations. To include the radiative portion of heating, the flow-field solutions are post-processed by the non-equilibrium radiation code HARA. Acceptable agreement between CFD and DSMC flow field solutions is demonstrated and the progress of the updates to DAC, along with an appropriate radiative heating solution, are discussed. In addition, future plans to generate more high fidelity radiative heat transfer solutions are discussed.

Liechty, Derek S.↗
NASA NTRS2001

2-D Modeling of Nanoscale MOSFETs: Non-Equilibrium Green's Function Approach

We have developed physical approximations and computer code capable of realistically simulating 2-D nanoscale transistors, using the non-equilibrium Green's function (NEGF) method. This is the most accurate full quantum model yet applied to 2-D device simulation. Open boundary conditions and oxide tunneling are treated on an equal footing. Electrons in the ellipsoids of the conduction band are treated within the anisotropic effective mass approximation. Electron-electron interaction is treated within Hartree approximation by solving NEGF and Poisson equations self-consistently. For the calculations presented here, parallelization is performed by distributing the solution of NEGF equations to various processors, energy wise. We present simulation of the "benchmark" MIT 25nm and 90nm MOSFETs and compare our results to those from the drift-diffusion simulator and the quantum-corrected results available. In the 25nm MOSFET, the channel length is less than ten times the electron wavelength, and the electron scattering time is comparable to its transit time. Our main results are: (1) Simulated drain subthreshold current characteristics are shown, where the potential profiles are calculated self-consistently by the corresponding simulation methods. The current predicted by our quantum simulation has smaller subthreshold slope of the Vg dependence which results in higher threshold voltage. (2) When gate oxide thickness is less than 2 nm, gate oxide leakage is a primary factor which determines off-current of a MOSFET (3) Using our 2-D NEGF simulator, we found several ways to drastically decrease oxide leakage current without compromising drive current. (4) Quantum mechanically calculated electron density is much smaller than the background doping density in the poly silicon gate region near oxide interface. This creates an additional effective gate voltage. Different ways to. include this effect approximately will be discussed.

Svizhenko, Alexei↗
NASA NTRS2003

Study of alloy disorder in quantum dots through multi-million atom simulations

A tight binding model which includes s, p, d, s orbitals is used to examine the electronic structures of an ensemble of dome-shaped In0.6 Ga0.4 As quantum dots. Given ensembles of identically sized quantum dots, variations in composition and configuration yield a linewidth broadening of less than 0.35 meV, much smaller than the total broadening determined from photoluminescence experiments. It is also found that the computed disorder-induced broadening is very sensitive to the applied boundary conditions, so that care must be taken to ensure proper convergence of the numerical results. Examination of local eigenenergies as functions of position shows similar convergence problems and indicates that an inaccurate resolution of the equilibrium atomic positions due to truncation of the simulation domain may be the source of the slow ground state convergence.

disorder↗
NASA NTRS2016

Li-Doped Ionic Liquid Electrolytes: From Bulk Phase to Interfacial Behavior

Ionic liquids have been proposed as candidate electrolytes for high-energy density, rechargeable batteries. We present an extensive computational analysis supported by experimental comparisons of the bulk and interfacial properties of a representative set of these electrolytes as a function of Li-salt doping. We begin by investigating the bulk electrolyte using quantum chemistry and ab initio molecular dynamics to elucidate the solvation structure of Li(+). MD simulations using the polarizable force field of Borodin and coworkers were then performed, from which we obtain an array of thermodynamic and transport properties. Excellent agreement is found with experiments for diffusion, ionic conductivity, and viscosity. Combining MD simulations with electronic structure computations, we computed the electrochemical window of the electrolytes across a range of Li(+)-doping levels and comment on the role of the liquid environment. Finally, we performed a suite of simulations of these Li-doped electrolytes at ideal electrified interfaces to evaluate the differential capacitance and the equilibrium Li(+) distribution in the double layer. The magnitude of differential capacitance is in good agreement with our experiments and exhibits the characteristic camel-shaped profile. In addition, the simulations reveal Li(+) to be highly localized to the second molecular layer of the double layer, which is supported by additional computations that find this layer to be a free energy minimum with respect to Li(+) translation.

molecular dynamics↗