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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantum algorithm for electronic band structures with local tight-binding orbitals

While the main thrust of quantum computing research in materials science is to accurately measure the classically intractable electron correlation effects due to Coulomb repulsion, designing optimal quantum algorithms for simpler problems with well-understood solutions is a useful tactic to advance our quantum “toolbox”. With this in mind, we consider the quantum calculation of a periodic system’s single-electron band structure over a path through reciprocal space. Previous efforts have used the Variational Quantum Eigensolver algorithm to solve the energy of each band, which involves numerically optimizing the parameters of a variational quantum circuit to minimize a cost function, constructed as the expectation value of a Hamiltonian operator. Traditionally, a unique Hamiltonian operator is constructed for each k-point, so that many cost functions, each with their own parameter space, must be optimized to generate a single band. Similarly, calculating higher bands than the first has traditionally involved modifying the cost function with additional overlap terms to ensure higher-energy eigenstates are orthogonal to those of lower bands. In this paper, we adopt a direct space approach, using a novel hybrid first/second-quantized qubit mapping which allows us to construct a single Hamiltonian, and a single cost-function, suitable for solving the entire electronic band structure. In contrast to previous approaches, the k-point and the band index are selected by additional parameters in our quantum circuit, rather than through modifications to the cost function. The result is a technically and conceptually simpler approach to band structure calculations on a quantum computer. Moreover, we expect that the tools developed herein will motivate new strategies for tackling highly-correlated materials beyond the grasp of classical computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Local Bayesian Dirichlet mixing of imperfect models

Abstract To improve the predictability of complex computational models in the experimentally-unknown domains, we propose a Bayesian statistical machine learning framework utilizing the Dirichlet distribution that combines results of several imperfect models. This framework can be viewed as an extension of Bayesian stacking. To illustrate the method, we study the ability of Bayesian model averaging and mixing techniques to mine nuclear masses. We show that the global and local mixtures of models reach excellent performance on both prediction accuracy and uncertainty quantification and are preferable to classical Bayesian model averaging. Additionally, our statistical analysis indicates that improving model predictions through mixing rather than mixing of corrected models leads to more robust extrapolations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

In-plane selective area InSb–Al nanowire quantum networks

Abstract Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2 e -periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Introduction to spectral line shape theory

Spectral line-shape models are an important part of understanding high-energy-density (HED) plasmas. Models are needed for calculating opacity of materials and can serve as diagnostics for astrophysical and laboratory plasmas. However, much of the literature on line shapes is directed toward specialists. This perspective makes it difficult for non-specialists to enter the field. We have two broad goals with this topical review. First, we aim to give information so that others in HED physics may better understand the current field. Additionally, this first goal may help guide future experiments to test different aspects of the theory. Second, we provide an introduction for those who might be interested in line-shape theory, and enough materials to be able to navigate the field and the literature. We give a high-level overview of line broadening process, as well as dive into the formalism, available methods, and approximations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

What sets the splashback radius of dark matter haloes: accretion history or other properties?

The density profiles of dark matter haloes contain rich information about their growth history and physical properties. One particularly interesting region is the splashback radius, R sp , which marks the transition between particles orbiting in the halo and particles undergoing first infall. While the dependence of R sp on the recent accretion rate is well-established and theoretically expected, it is not clear exactly what parts of the accretion history R sp responds to, and what other halo properties might additionally influence its position. Here, we comprehensively investigate these questions by correlating the dynamically measured splashback radii of a large set of simulated haloes with their individual growth histories as well as their structural, dynamical, and environmental properties. We find that R sp is sensitive to the accretion over one crossing time but largely insensitive to the prior history (in contrast to concentration, which probes earlier epochs). All secondary correlations are much weaker, but we discern a relatively higher R sp in less massive, older, more elliptical, and more tidally deformed haloes. Despite these minor influences, we conclude that the splashback radius is a clean indicator of a halo’s growth over the past dynamical time. We predict that the magnitude gap should be a promising observable indicator of a halo’s accretion rate and splashback radius.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Wavelength conversion for single-photon polarization qubits through continuous-variable quantum teleportation

A quantum internet connects remote quantum processors that need to interact and exchange quantum signals over a long distance through photonic channels. However, these quantum nodes operate at the wavelength ranges unsuitable for long-distance transmission. Therefore, quantum wavelength conversion to telecom bands is crucial for long-distance quantum networks based on optical fiber. Here, we propose wavelength conversion devices for single-photon polarization qubits using continuous-variable quantum teleportation that can efficiently convert qubits between near-infrared (780–795 nm suitable for interacting with atomic quantum nodes) and telecom wavelength (1300–1500 nm suitable for long-distance transmission). The teleportation uses entangled photon fields (i.e., nondegenerate two-mode squeezed state) that can be generated by four-wave mixing in a rubidium atomic gas using a diamond configuration of atomic transitions. The entangled fields can be emitted in two orthogonal polarizations with locked relative phase, making them especially suitable for interfacing with single- photon polarization qubits. Furthermore, our work may pave the way for the realization of long-distance quantum networks.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Fully Arbitrary Control of Frequency-Bin Qubits

Accurate control of two-level systems is a longstanding problem in quantum mechanics. One such quantum system is the frequency-bin qubit: a single photon existing in superposition of two discrete frequency modes. In this Letter, we demonstrate fully arbitrary control of frequency-bin qubits in a quantum frequency processor for the first time. Furthermore, we numerically establish optimal settings for multiple configurations of electro-optic phase modulators and pulse shapers, experimentally confirming near-unity mode-transformation fidelity for all fundamental rotations. Performance at the single-photon level is validated through the rotation of a single frequency-bin qubit to 41 points spread over the entire Bloch sphere, as well as tracking of the state path followed by the output of a tunable frequency beam splitter, with Bayesian tomography confirming state fidelities Fρ>0.98 for all cases. Overall, such high-fidelity transformations expand the practical potential of frequency encoding in quantum communications, offering exceptional precision and low noise in general qubit manipulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Reformulation of the No-Free-Lunch Theorem for Entangled Datasets

The No-Free-Lunch (NFL) theorem is a celebrated result in learning theory that limits one’s ability to learn a function with a training data set. With the recent rise of quantum machine learning, it is natural to ask whether there is a quantum analog of the NFL theorem, which would restrict a quantum computer’s ability to learn a unitary process with quantum training data. However, in the quantum setting, the training data can possess entanglement, a strong correlation with no classical analog. In this work, we show that entangled data sets lead to an apparent violation of the (classical) NFL theorem. This motivates a reformulation that accounts for the degree of entanglement in the training set. As our main result, we prove a quantum NFL theorem whereby the fundamental limit on the learnability of a unitary is reduced by entanglement. We employ Rigetti's quantum computer to test both the classical and quantum NFL theorems. In conclusion, our work establishes that entanglement is a commodity in quantum machine learning.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Topological Defect Mediated Helical Phase Reorientation by Uniaxial Stress

Strain engineering enables precise, energy-efficient control of nanoscale magnetism. However, unlike well-studied strain-dislocation interactions in mechanical deformation, the spatial evolution of strain-induced spin rearrangement remains poorly understood. Using Lorentz transmission electron microscopy, we manipulate and observe helical domain reorientation under quantitatively applied uniaxial tensile stress. Our findings reveal striking similarity to plastic deformation in metals, where the critical stress for propagation vector ( Q ) reorientation depends on its angle with the stress direction. Magnetic defects mediate reorientation via “break-and-reconnect” or “dislocation gliding–annihilation” processes. Simulations confirm that strain-induced anisotropic Dzyaloshinskii-Moriya interaction may play a key role. These insights advance strain-driven magnetism and offer a promising route for energy-efficient magnetic nanophase control in next-generation information technology. Published by the American Physical Society 2025

36 MATERIALS SCIENCE↗
DOE OSTI2024

Broadband coplanar-waveguide-based impedance-transformed Josephson parametric amplifier

Quantum-limited Josephson parametric amplifiers play a pivotal role in advancing the field of circuit quantum electrodynamics by enabling the fast and high-fidelity measurement of weak microwave signals. Therefore, it is necessary to develop robust parametric amplifiers with low noise, broad bandwidth, and reduced design complexity for microwave detection. However, current broadband parametric amplifiers either have degraded noise performance or rely on complex designs. Here, we present a device based on the broadband impedance-transformed Josephson parametric amplifier that integrates a hornlike coplanar waveguide transmission line, which significantly decreases the design and fabrication complexity while keeping comparable performance. The device shows an instantaneous bandwidth of 700 (200) MHz for 15 (20) dB gain with an average input saturation power of − 110 dBm and near quantum-limited added noise. The operating frequency can be tuned over 1.4 GHz using an external flux bias. We further demonstrate the negligible backaction from our device on a transmon qubit. The amplification performance and simplicity of our device promise its wide adaptation in quantum metrology, quantum communication, and quantum information processing. Published by the American Physical Society 2024

Qing, Bingcheng (ORCID:0000000345227017)↗
DOE OSTI2025

Quantum-enhanced distributed phase sensing with a truncated SU(1,1) interferometer

In recent years, distributed quantum sensing has gained interest for a range of applications requiring networks of sensors, from global-scale clock synchronization to high energy physics. In particular, a network of entangled sensors can improve not only the sensitivity beyond the shot noise limit, but also enable a Heisenberg scaling with the number of sensors. Here, using bright entangled twin beams, we theoretically and experimentally demonstrate the detection of a linear combination of two distributed phases beyond the shot noise limit with a truncated SU(1,1) interferometer. Specifically, we show a quantum noise reduction of 1.7 ± 0.3 dB below what is possible with the corresponding classical configuration. Additionally, we theoretically extend the use of a truncated SU(1,1) interferometer to a multi-phase-distributed sensing scheme that leverages entanglement as a resource to achieve a quantum improvement in the scaling with the number of sensors in the network. Our results pave the way for developing quantum-enhanced sensor networks that can achieve an entanglement-enhanced sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Smart manufacturing maturity models and their applicability: a review

The purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability. Nineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions. The five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance. Researchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories. Finally, compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.

42 ENGINEERING↗
DOE OSTI2024

Advancing attenuation estimation through integration of the Hessian in multiparameter viscoacoustic full-waveform inversion

Accurate seismic attenuation models of subsurface structures not only enhance subsequent migration processes by improving fidelity, resolution, and facilitating amplitude-compliant angle gather generation but also provide valuable constraints on subsurface physical properties. Leveraging full-wavefield information, multiparameter viscoacoustic full-waveform inversion ( Q-FWI) simultaneously estimates seismic velocity and attenuation ( Q) models. However, a major challenge in Q-FWI is the contamination of crosstalk artifacts, where inaccuracies in the velocity model are mistakenly mapped to the inverted attenuation model. While incorporating the Hessian is expected to mitigate these artifacts, the explicit implementation is prohibitively expensive due to its formidable computational cost. In this study, we formulate and develop a Q-FWI algorithm via the Newton-conjugate gradient (CG) framework, where the search direction at each iteration is determined through an internal CG loop. In particular, the Hessian is integrated into each CG step in a matrix-free fashion using the second-order adjoint-state method. We find through synthetic experiments that our Newton-CG Q-FWI significantly mitigates crosstalk artifacts compared with the limited-memory Broyden-Fletcher-Goldfarb-Shanno method and the CG method, albeit with a notable computational cost. In the discussion of several key implementation details, we also determine the significance of the approximate Gauss-Newton Hessian, the second-order adjoint-state method, and the two-stage inversion strategy.

Geochemistry & Geophysics↗
DOE OSTI2020

A Survey of Constrained Gaussian Process: Approaches and Implementation Challenges

Gaussian process regression is a popular Bayesian framework for surrogate modeling of expensive data sources. As part of a larger effort in scientific machine learning, many recent works have incorporated physical constraints or other a priori information within Gaussian process regression to supplement limited data and regularize the behavior of the model. We provide an overview and survey of several classes of Gaussian process constraints, including positivity or bound constraints, monotonicity and convexity constraints, differential equation constraints provided by linear PDEs, and boundary condition constraints. We compare the strategies behind each approach as well as the differences in implementation, concluding with a discussion of the computational challenges introduced by constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Universality in Quantum Gravity. Final Technical Report

This is the final technical report for the DOE Early Career Award to PI Thomas Hartman at Cornell University, outlining the goals of the research project and summarizing its main technical achievements. These include the discovery of new constraints on quantum field theory, new theoretical methods that allow for a direct derivation of emergent spacetime from conformal field theory in certain settings, and the discovery of fundamental bounds on the dynamics of quantum information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Scaling the Microbial Ecology of Soil Carbon (Final Report)

This work developed new techniques and discoveries in quantitative microbial ecology, focusing on soil carbon. The work advanced a new approach to stable isotope probing (SIP), adding a quantitative way to infer taxon-specific rates of growth, mortality, and associated carbon (C) fluxes in soil microbial communities, a framework that the work demonstrated can scale from individual microbial taxa to the integrated soil system. Among the “-omics” techniques in microbial ecology, those based on stable isotope probing (SIP) hold particular promise for addressing the challenge of scaling from molecules to the major biogeochemical element cycles. Because SIP measures directly the fluxes of elements into nucleic acids, it physically connects element flux to genetic information. The work explored new ways to quantify taxon-specific C-use and growth efficiency and tested hypotheses about responses of the soil microbial community to experimental warming and to latitudinal variation in temperature. This work pushed the frontier of –omics enabled techniques by demonstrating their applicability at the ecosystem scale, and by relating taxon-specific isotope assimilation to dissimilatory processes in the C cycle, thereby enabling the identification of organisms especially responsible for soil C loss, in other words, attributing ecosystem-scale element fluxes to individual microbial taxa.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using the Criticality Accident Alarm System modeling capabilities in SCALE [Slides]

The following is a summary of advice for CAAS modeling in SCALE. Refer to the SCALE Criticality Safety and Radiation Shielding training slides or to the SCALE manual for exact syntax. Use a mesh for the fission source that is the most adequate for the problem to solve (coarse/fine). Don’t spend unnecessary resources; simplify the model if it does not impact the final results of interest. Be careful to deactivate secondary fissions in MAVRIC or the calculation may never end. Check that k eff and $\overline{\upsilon}$ calculated results are logical. Between KENO and MAVRIC, cross section libraries, materials, geometry, and mesh grid can be the same or different. Iterative calculations are usually complex problems that need variance reduction. It will be hard to find the best solving parameters in the first attempt; expert judgement is needed. Check each step separately. Use Fulcrum to visualize fission source, mesh source, and spatial/energy distributions to find potential errors or impactful imprecisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗