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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Nucleon tensor form factors at large N c

We investigate nucleon tensor form factors in the large- N c limit. In this picture, the nucleon emerges as a state of the N c valence quarks, which were bound by pion mean fields that were created by the presence of the valence quarks self-consistently. We find that the tensor charge ( g T u − d = 0.99 ) and the anomalous tensor magnetic moment ( κ T u + d = 7.61 ) are dominated by valence quarks, while the tensor quadrupole moment ( Q T u − d = − 7.02 ) shows significant sea quark effects. We examine how these quantities vary as the average size of the pion mean field is changed, showing interpolation between nonrelativistic quark and Skyrme limits. We also observe that g T u − d and κ T u + d depend weakly on the pion mass. In contrast, Q T u − d exhibits strong enhancement near the chiral limit. The numerical results are in good agreement with available lattice quantum chromodynamics (QCD) data and provide predictions for unmeasured quantities. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1986

EUV astronomical spectroscopy with CCD detectors

The applicability of CCD detectors to astronomical extreme ultraviolet (EUV) spectroscopy (100-1250 A) is discussed. The advantages of CCDs in this spectral region include internal electron yield, the potential for very high quantum efficiency (about 50-90 percent), and broad wavelength response. Visible light suppression is achieved by a combination of low grating scattering, greater than unity electron yield in the EUV, and various filter techniques. For the current generation of CCDs, detection of only a few EUV photons will rapidly overwhelm the read noise; thus, for all practical S/N ratios used in astronomical spectroscopy, read noise will be negligible compared to the poisson statistics of the detected photons. A model based on experimental data for the quantum efficiency and electron yield of CCDs in the EUV is discussed.

Stern, R. A.↗

NASA NTRS1996

Diffusion lengths in irradiated N/P InP-on-Si solar cells

Indium phosphide (InP) solar cells were made on silicon (Si) wafers (InP/Si) by to take advantage of both the radiation-hardness properties of the InP solar cell and the light weight and low cost of Si wafers. The InP/Si cell application is for long duration and/or high radiation orbit space missions. Spire has made N/P InP/Si cells of sizes up to 2 cm by 4 cm with beginning-of-life (BOL) AM0 efficiencies over 13% (one-sun, 28C). These InP/Si cells have higher absolute efficiency and power density after a high radiation dose than gallium arsenide (GaAs) or silicon (Si) solar cells after a fluence of about 2e15 1 MeV electrons/sq. cm. In this work, we investigate the minority carrier (electron) base diffusion lengths in the N/P InP/Si cells. A quantum efficiency model was constructed for a 12% BOL AM0 N/P InP/Si cell which agreed well with the absolutely measured quantum efficiency and the sun-simulator measured AM0 photocurrent (30.1 mA/sq. cm). This model was then used to generate a table of AM0 photocurrents for a range of base diffusion lengths. AM0 photocurrents were then measured for irradiations up to 7.7e16 1 MeV electrons/sq. cm (the 12% BOL cell was 8% after the final irradiation). By comparing the measured photocurrents with the predicted photocurrents, base diffusion lengths were assigned at each fluence level. A damage coefficient K of 4e-8 and a starting (unirradiated) base electron diffusion length of 0.8 microns fits the data well. The quantum efficiency was measured again at the end of the experiment to verify that the photocurrent predicted by the model (25.5 mA/sq. cm) agreed with the simulator-measured photocurrent after irradiation (25.7 mA/sq. cm).

Wojtczuk, Steven↗

DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗

DOE OSTI2025

Systematic uncertainties from higher-twist corrections in DIS at large x

We investigate the systematic uncertainties and potential biases arising from the inclusion of large- x corrections to proton and deuteron deep inelastic scattering (DIS) data in global quantum chromodynamics (QCD) analyses. Using the CTEQ-JLab framework, we examine various approaches to implementing higher-twist corrections in nucleon structure functions and off-shell PDF modifications in deuteron targets. We analyze how these components interact and influence the determination of the d -quark PDF and the neutron structure function at large x . We find that it is very important to consider isospin-dependent higher-twist corrections in order to minimize implementation biases in the extracted quantities. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Spectral Efficiency and Tandem Performance Calculators [SWR-24-92]

The Spectral Efficiency and Tandem Performance Calculators allow users to test material types for use in tandem photovoltaic devices to better understand if a given material could work well. The Spectral Efficiency (SE) calculator takes a set of current vs voltage (I-V) and quantum efficiency (QE) data along with a spectrum input and plots the spectral efficiency of the cells represented by the datasets for the spectrum provided. The Tandem Performance calculator uses the calculated spectral efficiency of top and bottom cells and the transmission data of the top cell to calculate performance metrics for a tandem device in either a two or four terminal architecture. The SE and Tandem Performance calculators are based on the following publication: Yu, Z., Leilaeioun, M. & Holman, Z. Selecting tandem partners for silicon solar cells. Nat Energy 1, 16137 (2016).

Warren, Emily↗

NASA NTRS1972

Excitation of Na D-line radiation in collisions of sodium atoms with internally excited H2, D2, and N2

Excitation of D-line radiation in collisions of Na atoms with vibrationally excited N2, H2 and D2 was studied in two modulated crossed beam experiments. In both experiments, the vibrational excitation of the molecules was provided by heating the molecular beam source to temperatures in the range of 2000 to 3000 K, which was assumed to give populations according to the Boltzmann expression. In the first experiment, a total rate coefficient was measured as a function of molecular beam temperature, with absolute calibration of the photon detector being made using the black body radiation from the heated molecular beam source. Since heating affects both the internal energy and the collisional kinetic energy, the first experiment could not determine the relative contributions of internal energy transfer versus collisional excitation. The second experiment achieved partial separation of internal versus kinetic energy transfer effects by using a velocity-selected molecular beam. Using two simple models for the kinetic energy dependence of the transfer cross section for a given change in vibrational quantum number, the data from both experiments were used to determine parameters in the models.

Krause, H. F.↗

NASA NTRS1979

Shallow-homojunction GaAs solar cells

Single-crystal GaAs shallow-homojunction solar cells on GaAs or Ge substrates, without Ga sub 1-x Al sub x As window layers, that have conversion efficiencies exceeding 20% at AM1 (17% at AMO). Using a simple theoretical model, good fits were obtained between computer calculations and experimental data for external quantum efficiency and conversion efficiency of cells with different values of n+ layer thickness. The calculations not only yield values for material properties of the GaAs layers composing the cells but will also permit the optimization of cell designs for space and terrestrial applications. Preliminary measurements indicate that the shallow-homojunction cells are resistant to electron irradiation. In the best test so far, bombardment with 1 x 10 to the 16th power/sq cm fluence of 1 MeV electrons reduced the short-circuit current by only about 6%.

Fan, J. C. C.↗

NASA NTRS1983

GaInAs-AlInAs heterostructures for optical devices grown by MBE

The band gap of Ga(0.47)In(0.53)As corresponds to an emission wavelength of about 1.65 microns. Lasers have been produced with Al(0.48)In(0.52)As as cladding layers operating at room temperature. The peak emission of Ga(0.47)In(0.53)As can be continuously varied from 1.65 to 1.2 microns by the use of the multiquantum well structures. This range of wavelengths covers the minimum loss and dispersion in optical fibers and will be applicable to integrated optics. Double heterostructure broad area lasers have been fabricated using AlInAs as cladding layers to the GaInAs active layer. Room temperature threshold current densities of 4.3 kA/sq cm have been obtained for lasers with a 4500 A active region. The first data on GaInAs/AlInAs quantum well emitters will be presented. Photoluminescence of 4 K from quantum well layers of 100, 150, and 180 A with 150 A AlInAs barrier layers produced emission at 1.27, 1.35, and 1.41 microns, respectively. Ga(0.47)In(0.52)As quantum well LEDs have also been produced which emit at 1.34 microns.

Welch, D. F.↗

NASA NTRS1988

Temperature dependence of the atmospheric photolysis rate coefficient for NO2

Accurate values for the photolysis rate coefficient of NO2 (j1) are required for studies related to the observed imbalance in the photostationary state of O3, NO, and NO2 in the troposphere. Direct measurements of the temperature dependence of j1 at temperatures from -70 to 30 C were made in sunlight for relatively cloudless summer days in Boulder, Colorado. The ratios of j1 (30 C)/j1 (T C) for T = -10 C and -70 C, respectively, were 1.046 + or - 0.040 and 1.070 + or - 0.031. The j1 ratios were independent of solar zenith angle. Theoretical estimates of the temperature-dependent j1 ratios based upon recently reported cross section (sigma) and quantum yield (phi) data are more consistent with these experimental measurements than those based upon the currently accepted sigma and phi data.

Shetter, Richard E.↗

NASA NTRS2005

High-Efficiency Multi-Junction Space Solar Development Utilizing Lattice Grading

Progress towards achieving a high one-sun air mass 0 (AM0) efficiency in a monolithic dual junction solar cell comprised of a 1.62 eV InGaP top cell and a 1.1 eV InGaAs bottom cell grown on buffered GaAs is reported. The performance of stand-alone 1.62 eV InGaP and 1.1 eV InGaAs cells is compared to that of the dual junction cell. Projected AM0 efficiencies of 15.7% and 16.5% are expected for the 1.62 eV InGaP and 1.1 eV InGaAs cells grown on buffered GaAs. The dual junction cell has a projected one-sun AM0 conversion efficiency of 17%. The projected efficiencies are based upon the application of an optimized anti-reflective coating (ARC) to the as-grown cells. Quantum efficiency (QE) data obtained from the dual junction cell indicate that is is bottom cell current limited with the top cell generating 50% more current than the bottom cell. A comparison of the QE data for the stand-alone 1.1 eV InGaAs cell to that of the 1.1 eV InGaAs bottom cell in the tandem configuration indicates a degradation of the bottom cell conversion efficiency in the tandem configuration. The origin of this performance degradation is at present unknown. If the present limitation can be overcome, then a one-sun AM0 efficiency of 26% is achievable with the 1.62 eV/1.1 eV dual junction cell grown lattice-mismatched to GaAs.

Stan, Mark A.↗

DOE OSTI2026

Thermodynamic Modeling of Intrinsic Defects in MnBi₂Te₄

This repository contains the computational data supporting the manuscript titled “The critical role of intrinsic defects and many-body interactions on the stability of MnBi₂Te₄.” It includes: 1. DFT data generated using VASP, used for training and benchmarking electronic structure models. 2. Quantum Monte Carlo (QMC) data produced with QMCPACK, used to apply many-body corrections and validate the electronic and magnetic properties of MnBi₂Te₄. 3. Relevant scripts used to run, analyze, and process the calculations, enabling reproducibility and transparency of the workflows.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗

DOE OSTI2026

Learning thermodynamic master equations for open quantum systems

The characterization of Hamiltonians and other components of open quantum dynamical systems plays a crucial role in quantum computing and other applications. Scientific machine learning techniques have been applied to this problem in a variety of ways, including by modeling with deep neural networks. However, the majority of mathematical models describing open quantum systems are linear, and the natural nonlinearities in learnable models have not been incorporated using physical principles. We present a data-driven model for open quantum systems that includes learnable, thermodynamically consistent terms. The trained model is interpretable, as it directly estimates the system Hamiltonian and linear components of coupling to the environment. We validate the model on synthetic two and three-level data, as well as experimental two-level data collected from a quantum device at Lawrence Livermore National Laboratory.

Mathematics and Computing↗

NASA NTRS1988

Identification of interstellar methanol lines

The extended internal axis method Hamiltonian of Herbst et al. (1984) was used to study the rotational spectrum of methanol out to high values of the rotational quantum number J. Laboratory data for 783 lines of (C-12)H3OH from the lowest three torsional levels out to a rotational quantum number of J = 22 were fitted to an rms deviation of 4.40 MHz. For (C-13)H3OH, 455 lines out to J = 22 were fitted to an rms of 2.28 MHz.

Sutton, E. C.↗

DOE OSTI2026

Characterizing thermal-induced temporal drift in deployed quantum fiber networks

We study temperature-induced fiber-delay drifts affecting entanglement fidelity in deployed quantum systems. Using field data and simulations, we model timing uncertainties and evaluate their impact on coincidence detection, revealing critical challenges for robust quantum networks.

Alshowkan, Muneer [ORNL] (ORCID:0000000264293450)↗

DOE OSTI2026

Spinon mediation of witness spin dynamics in herbertsmithite

The kagome lattice of spin-1/2 copper atoms in herbertsmithite is conjectured to sustain a quantum spin liquid state with spinon quasiparticles. Ideally, the kagome crystal planes are each separated by a plane of spinless zinc atoms. However, in real crystals, some spin-1/2 copper atoms substitute randomly onto these inter-kagome zinc sites. Here we reconceptualize such ‘impurity’ atoms as quantum witness spins whose dynamics is designed to probe the spin liquid state. We then introduce spin noise spectroscopy to measure the frequency and temperature dependence of witness spin dynamics, demonstrating that their phenomenology is consistent with extensive interactions between witness spins mediated by propagation of spinons through a quantum spin liquid. Ultimately, a sharp transition occurs at around 260 mK, below which the properties of both spin noise and magnetic susceptibility suggest that the witness spins form a spin glass phase. Among the theoretical models considered, we demonstrate that our observations are only consistent with spinon-mediated interactions between witness spins by either a Z 2 or U(1) quantum spin liquid, with the former model more closely matching the data. Our work demonstrates that quantum mechanical witness spins may now conceivably be used as a widely applicable probe of quantum spin liquid physics.

Takahashi, Hiroto [University of Oxford (United Ki↗

DOE OSTI2025

A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

LLVM↗