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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design of InGaN-ZnSnGa 2 N 4 quantum wells for high-efficiency amber light emitting diodes

A novel type-II InGaN-ZnSnGa 2 N 4 quantum well (QW) structure is proposed based on recent experimental achievements for the successful epitaxy of ZnSnN 2 -GaN alloys and the determination of their band offsets with GaN. The simulation results indicate that this structure is promising as the active region for high-efficiency InGaN-based amber (λ ~ 590 nm) light-emitting diodes (LEDs). The hole wavefunction in the valence band is better confined with the insertion of a monolayer scale of ZnSnGa 2 N 4 into the InGaN QW while the electron wavefunction in the conduction band is better confined with the incorporation of an AlGaN layer in the GaN quantum barrier. The band structure of the InGaN-ZnSnGa 2 N 4 QW is numerically simulated based on the experimentally measured band offsets between ZnSnGa 2 N 4 and GaN. With the InGaN-ZnSnGa 2 N 4 QW design, a low In content (20%) is required in the InGaN layer to reach a peak emission wavelength of ~590 nm, yet an In composition of 25% is needed to reach the same emission wavelength for a conventional InGaN QW with the same layer thicknesses. Moreover, the electron-hole wavefunction overlap (Гe1-hh1) for the InGaN-ZnSnGa 2 N 4 QW design reaches 18% for an emission wavelength at ~590 nm. This result is much improved over the conventional InGaN QW overlap of 5% emitting at the same wavelength. The increase in electron-hole wavefunction overlap results in an approximately 14 times enhancement in the predicted spontaneous emission radiative recombination rate of the InGaN-ZnSnGa 2 N 4 QW as compared to that of the conventional InGaN QW. This InGaN-ZnSnGa 2 N 4 QW structure design can be promising to pave a new way to achieve high efficiency amber LEDs.

42 ENGINEERING↗
DOE OSTI2022

Triple-junction solar cells with 39.5% terrestrial and 34.2% space efficiency enabled by thick quantum well superlattices

Multijunction solar cell design is guided by both the theoretical optimal bandgap combination as well as the realistic limitations to materials with these bandgaps. For instance, triple-junction III-V multijunction solar cells commonly use GaAs as a middle cell because of its near-perfect material quality, despite its bandgap being higher than optimal for the global spectrum. Here, we modify the middle cell bandgap using thick GaInAs/GaAsP strain-balanced quantum well (QW) solar cells with excellent voltage and absorption. Additionally, these high-performance QWs are incorporated into a triple-junction inverted metamorphic multijunction device consisting of a GaInP top cell, GaInAs/GaAsP QW middle cell, and lattice-mismatched GaInAs bottom cell, each of which has been highly optimized. We demonstrate triple-junction efficiencies of 39.5% and 34.2% under the AM1.5 global and AM0 space spectra, respectively, and the global efficiency is higher than previous record six-junction devices.

14 SOLAR ENERGY↗
DOE OSTI2022

High-efficiency microwave-optical quantum transduction based on a cavity electro-optic superconducting system with long coherence time

Abstract Frequency conversion between microwave and optical photons is a key enabling technology to create links between superconducting quantum processors and to realize distributed quantum networks. We propose a microwave-optical transduction platform based on long-coherence time superconducting radio-frequency (SRF) cavities coupled to electro-optic optical cavities to mitigate the loss mechanisms that limit the attainment of high conversion efficiency. We optimize the microwave-optical field overlap and optical coupling losses in the design while achieving long microwave and optical photon lifetime at milli-Kelvin temperatures. This represents a significant enhancement of the transduction efficiency up to 50% under incoming pump power of 140 μW, which allows the conversion of few-photon quantum signals. Furthermore, this scheme exhibits high resolution for optically reading out the dispersive shift induced by a superconducting transmon qubit coupled to the SRF cavity. We also show that low microwave losses enhance the fidelity of heralded entanglement generation between two remote quantum systems. Finally, high precision in quantum sensing can be reached below the standard quantum limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Efficient sparse state preparation via quantum walks

Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work, we develop an algorithm that converts single-edge and self-loop dynamic CTQWs to the gate model of computation. We use this mapping to introduce an efficient sparse quantum state preparation framework based on dynamic CTQWs. Our approach utilizes combinatorics techniques such as minimal hitting sets, minimum spanning trees, and shortest Hamiltonian paths to reduce the number of controlled gates required to prepare sparse states. We show that our framework encompasses the current state of the art ancilla-free sparse state preparation method by reformulating this method as a CTQW. This CTQW-based framework offers an alternative to the uniformly controlled rotation method used by Qiskit by requiring fewer CX gates when the target state has a polynomial number of non-zero amplitudes.

dynamic continuous time quantum walks↗
DOE OSTI2023

Efficient fully-coherent quantum signal processing algorithms for real-time dynamics simulation

Simulating the unitary dynamics of a quantum system is a fundamental problem of quantum mechanics, in which quantum computers are believed to have significant advantage over their classical counterparts. One prominent such instance is the simulation of electronic dynamics, which plays an essential role in chemical reactions, non-equilibrium dynamics, and material design. These systems are time-dependent, which requires that the corresponding simulation algorithm can be successfully concatenated with itself over different time intervals to reproduce the overall coherent quantum dynamics of the system. In this paper, we quantify such simulation algorithms by the property of being fully-coherent: the algorithm succeeds with arbitrarily high success probability 1 − δ while only requiring a single copy of the initial state. Here we subsequently develop fully-coherent simulation algorithms based on quantum signal processing (QSP), including a novel algorithm that circumvents the use of amplitude amplification while also achieving a query complexity additive in time t, ln(1/δ), and ln(1/ϵ) for error tolerance ϵ: $Θ‖\mathscr{H}‖|t|+ln(1/ϵ)+ln(1/δ)$. Furthermore, we numerically analyze these algorithms by applying them to the simulation of the spin dynamics of the Heisenberg model and the correlated electronic dynamics of an H2 molecule. Since any electronic Hamiltonian can be mapped to a spin Hamiltonian, our algorithm can efficiently simulate time-dependent ab initio electronic dynamics in the circuit model of quantum computation. Accordingly, it is also our hope that the present work serves as a bridge between QSP-based quantum algorithms and chemical dynamics, stimulating a cross-fertilization between these exciting fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Low-efficiency-droop c -plane InGaN/GaN light-emitting diodes through the use of thick single quantum wells and doped barriers

Efficiency droop at high current densities is a problem for InGaN-based light-emitting diodes (LEDs), especially for conventional c-plane devices. The large internal electric fields in c-plane quantum wells (QWs) lead to an increase in the active region carrier density (n), causing the electrical efficiency droop onset to occur at low current densities. Here, we present an approach to reduce the internal electric fields (Eint) in c-plane QWs by placing doped p-type and n-type GaN barriers close to the QW. The reduced Eint also allows a thick QW active region design, which helps to lower n to further reduce the droop. The concept of using doped barriers to control Eint is explained using theory and device simulations. Following that, multiple series of thick single QW (SQW) LEDs were grown and characterized. Key parameters in the epitaxial design such as the doping levels and the relative position of the doped barriers were systematically studied and optimized. In conclusion, by using optimized doped barriers and a thick SQW, c-plane LEDs with a low-efficiency droop of 14% at 300 A/cm2 [with respect to the peak external quantum efficiency (EQE)] and a high peak EQE of 49% were demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Quantum embedding theories to simulate condensed systems on quantum computers.

Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties that are more complex than tractable at present on classical architectures. Here, we discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate-scale quantum computers using embedding theories, and we give examples for a specific class of materials, that is, solid materials hosting spin defects. These are promising systems to build future quantum technologies, such as quantum computers, quantum sensors and quantum communication devices. Although quantum simulations on quantum architectures are in their infancy, promising results for realistic systems appear to be within reach.

Vorwerk, Christian↗
DOE OSTI2024

Rational design of efficient defect-based quantum emitters

Single-photon emitters are an essential component of quantum networks, and defects or impurities in semiconductors are a promising platform to realize such quantum emitters. Here, we present a model that encapsulates the essential physics of coupling to phonons, which governs the behavior of real single-photon emitters, and critically evaluate several approximations that are commonly utilized. Emission in the telecom wavelength range is highly desirable, but our model shows that nonradiative processes are greatly enhanced at these low photon energies, leading to a decrease in efficiency. Our results suggest that reducing the phonon frequency is a fruitful avenue to enhance the efficiency.

Optics↗
DOE OSTI2024

Efficient simulation of open quantum systems coupled to a reservoir through multiple channels

It is challenging to simulate open quantum systems that are connected to a reservoir through multiple channels. For example, vibrations may induce fluctuations in both energy gaps and electronic couplings, which represent two independent channels of system–bath couplings. Systems of this kind are ubiquitous in the processes of excited state radiationless decay. Combined with density matrix renormalization group (DMRG) and matrix product states (MPS) methods, we develop an interaction-picture chain mapping strategy for vibrational reservoirs to simulate the dynamics of these open systems, resulting in time-dependent spatially local system–bath couplings in the chain-mapped Hamiltonian. This transformation causes the entanglement generated by the system–bath interactions to be restricted within a narrow frequency window of vibrational modes, enabling efficient DMRG/MPS dynamical simulations. We demonstrate the utility of this approach by simulating singlet fission dynamics using a generalized spin-boson Hamiltonian with both diagonal and off-diagonal system–bath couplings. This approach generalizes an earlier interaction-picture chain mapping scheme, allowing for efficient and exact simulation of systems with multi-channel system–bath couplings using matrix product states, which may further our understanding of nonlocal exciton–phonon couplings in exciton transport and the non-Condon effect in energy and electron transfer.

Chemistry↗
DOE OSTI2024

Your Best Single-Junction Solar Cell Does Not Always Make an Efficient Tandem Partner

Tandem solar cells, where multiple single-junction cells are combined optically in series, provide a path to making cells with high areal efficiencies, with multiple material systems capable of achieving greater than 30% efficiency under 1-sun conditions. However, there are many different material combinations and configurations used to make a tandem, and it can be challenging to understand how advances in one material system will impact the performance of a tandem device. Here, we have built an open-source calculator based on the spectral efficiency metric proposed by Yu et al. to easily enable calculation of spectral efficiency for single junctions and predicted maximum efficiency of tandem pairs, accounting for different optical and electrical coupling between the top and bottom junctions.

14 SOLAR ENERGY↗
DOE OSTI2024

Learning energy-based representations of quantum many-body states

Efficient representation of quantum many-body states on classical computers is a problem of practical importance. An ideal representation of a quantum state combines a succinct characterization informed by the structure and symmetries of the system along with the ability to predict the physical observables of interest. Several machine-learning approaches have been recently used to construct such classical representations, which enable predictions of observables and account for physical symmetries. However, the structure of a quantum state typically gets lost unless a specialized is employed based on prior knowledge of the system. Moreover, most such approaches give no information about what states are easier to learn in comparison with others. Here, we propose a generative energy-based representation of quantum many-body states derived from Gibbs distributions used for modeling the thermal states of classical spin systems. Based on the prior information on a family of quantum states, the energy function can be specified by a small number of parameters using an explicit low-degree polynomial or a generic parametric family such as neural nets and can naturally include the known symmetries of the system. Our results show that such a representation can be efficiently learned from data using exact algorithms in a form that enables the prediction of expectation values of physical observables. Importantly, the structure of the learned energy function provides a natural explanation for the difficulty of learning an energy-based representation of a given class of quantum states when measured in a certain basis. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Efficient flexible characterization of quantum processors with nested error models

We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short- and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This Perspective discusses select examples of these approaches and provides an outlook on the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.

36 MATERIALS SCIENCE↗