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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

Lee, Heechan [ORNL]↗
DOE OSTI2025

The influence of V-defects, leakage, and random alloy fluctuations on the carrier transport in red InGaN MQW LEDs

Red InGaN-based light-emitting diodes (LEDs) exhibit lower internal quantum efficiencies than violet, blue, and green InGaN LEDs due to a reduction in radiative recombination rates relative to non-radiative recombination rates as the Indium composition increases. Additionally, the larger polarization and band offset barriers between high indium content InGaN quantum wells and GaN quantum barriers increase the forward voltage. In blue and green LEDs, random alloy fluctuations and V-defects play a key role in reducing the forward voltage. When V-defects are present, either naturally or intentionally introduced, they create an alternative path for carrier injection into the MQWs through the V-defect sidewalls. This injection mechanism explains the turn-on voltages of green LEDs. However, in InGaN red LEDs, these two phenomena do not reduce the forward voltage as effectively as in blue and green LEDs, and consequently, the computed forward voltage remains significantly higher than the measured one. Furthermore, currents are observed at low voltages before the turn-on voltage (V<ℏω/e=2.0 V) of red LEDs. To address this, we introduce dislocation-induced tail states in the modeling, suggesting that leakage current through these states may play a significant role both below and at turn-on voltages. The simulation also indicates that leakage carriers below turn-on accumulate, partially diffuse in the QWs, screen the polarization-induced barrier in the low injection regime, and further reduce the forward voltage. Despite these beneficial effects, a drawback of dislocation-induced tail states is the enhanced nonradiative recombination in the dislocation line region. This study provides a detailed analysis of device injection physics in InGaN QW red LEDs and outlines potential optimization strategies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Chaos as the cause of randomness in tearing mode onset times in DIII-D ITER baseline scenario plasmas

The first evidence of widespread chaotic plasma dynamics relevant to the onset of disruptive tearing modes is found in DIII-D tokamak discharges. This evidence is obtained by calculating positive maximal Lyapunov exponents from Mirnov signals using the Rosenstein algorithm, implying the chaotic growth and/or rotation of magnetohydrodynamic modes in DIII-D [Luxon, Nucl. Fusion 42, 614 (2002)] plasmas. Such chaotic dynamics offer an explanation for the random tearing mode onset times previously observed in ITER baseline scenario discharges. Further, the Lyapunov timescales associated with this chaos could inhibit reliable prediction of tearing mode onset beyond the angular momentum confinement timescale; this constraint should inform the design of plasma control systems on ITER.

Chaotic dynamics↗
DOE OSTI2025

Coherent optical imaging of moving objects hidden in a heavily scattering random medium

Experimental results are presented that provide insight into the physics of statistical imaging in heavily scattering random media based on measured speckle correlations as a function of the change in position of a moving object. In this way, definitive interpretation of a rather complex and earlier theory is achieved, making this work an experimental complement to that theory paper []. Motion could be natural, where the set of positions is estimated or separately obtained, or directed, where a mechanical stage can be used to adjust the object's position. In the experiment, a coherent laser illuminates two scattering diffusers, while an object is translated between them in the resulting speckled field and images are collected in a transmission configuration. Results are shown for various objects of differing size and geometry, allowing the theory to be validated and interpreted with new understanding. This work demonstrates imaging opportunities, and applications include material characterization, environmental imaging and sensing, and deep-tissue imaging. Published by the American Physical Society 2025

Hastings, Ryan L. (ORCID:0009000095977807)↗
DOE OSTI2024

Random-exchange Heisenberg behavior in the electron-doped quasi-one-dimensional spin-1 chain compound AgVP 2 ⁢S 6

Recent theoretical work suggests that a pair-density wave superconducting state can be realized by doping a one-dimensional spin-1 chain. Here, we report the physical properties of single crystals of Mg x Ag 1–x VP 2 S 6 [x = 0, x = 0.017(6), x = 0.067(8), and 0.098(11)] prepared by solid-state synthesis. Single-crystal x-ray-diffraction measurements confirm that Mg 2+ is substituting for Ag + to electron dope the V 3+ zigzag chains. Magnetization measurements reveal that electron doping breaks up the V 3+ chains, resulting in unpaired spins at the chain ends. The Mg x Ag 1–x VP 2 S 6 series is consistent with random-exchange Heisenberg antiferromagnetic chain behavior and can be well described by the exchange-coupled pair model at low temperatures. As a result, transport measurements show Mg x Ag 1–x VP 2 S 6 remains insulating in the range 0 ≤ x ≤ 0.098(11), with the band gap decreasing to ~ 0.2 eV at x = 0.098(11).

1-dimensional spin chains↗
DOE OSTI2024

Random matrix model of the Virasoro minimal string

The model of two dimensional quantum gravity defining the Virasoro minimal string, presented recently by Collier, Eberhardt, Mühlmann, and Rodriguez, was also shown to be perturbatively (in topology) equivalent to a random matrix model. An alternative definition is presented here, in terms of double-scaled orthogonal polynomials, thereby allowing direct access to nonperturbative physics. Already at leading order, the defining string equation’s properties yield valuable information about the nonperturbative fate of the model, confirming that the case ( c = 25 , c ^ = 1 ) (central charges of spacelike and timelike Liouville sectors) is special, by virtue of sharing certain key features of the N = 1 supersymmetric JT gravity string equation. Solutions of the full string equation are constructed using a special limit, and the (Cardy) spectral density is completed to all genus and beyond. The distributions of the underlying discrete spectra are readily accessible too, as is the spectral form factor. Some examples of these are exhibited. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Nonperturbative random matrix model of N = 2 JT supergravity

It is shown how to nonperturbatively define a random matrix model that captures key physics of N = 2 Jackiw-Teitelboim supergravity, going well beyond the perturbative topological expansion defined recently by Turiaci and Witten. A decomposition into an infinite family of certain multicritical models is derived, leading to the definition of a nonlinear ordinary differential equation from which the physics may be computed. Bogomol’nyi-Prasad-Sommerfield (BPS) states are naturally described by the model. The nonperturbative completions of the spectral densities for non-BPS multiplets are readily extracted. Published by the American Physical Society 2024

Johnson, Clifford V. (ORCID:0000000189645830)↗
DOE OSTI2025

Statistical model of the stimulated forward Brillouin scattering driven by a randomized laser beam in plasma

The modeling of a spatially incoherent laser beam remains a central problem of the parametric instabilities in the context of inertial confinement fusion. This letter gives a simplified and comprehensive overview of the recent analytical developments regarding the modeling of these laser beams and a comparison with a dedicated experiment. Our model accounts for the first time for the statistical standard deviation of the gain and accurately captures the entanglement between wave mixing processes and the speckle correlations thus resolving the longstanding contradictions between the random phase approximation and the model of independent speckles. It is successfully compared to a recent laser beam spray experiment and the associated paraxial simulations, demonstrating that backscattering predictions require accounting for the beam spray. Furthermore, our framework thus provides a way to evaluate and guide the analysis of parametric instabilities in high laser energy experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Randomized low-rank decompositions of nuclear three-body interactions

First-principles simulations of many-fermion systems are commonly limited by the computational requirements of processing large data objects. As a remedy, we propose the use of low-rank approximations of three-body interactions, which are the dominant such limitation in nuclear physics. We introduce a randomized decomposition technique to handle the excessively large matrix dimensions and study the sensitivity of low-rank properties to interaction details. The developed low-rank three-nucleon interactions are benchmarked in ab initio simulations of few- and many-body systems. Exploiting low-rank properties provides a promising route to extend the microscopic description of atomic nuclei to large systems where storage requirements exceed the computational capacities of the most advanced high-performance computing facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Computational Power of Random Quantum Circuits in Arbitrary Geometries

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of approximately 50 qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and, therefore, how much infidelity is suffered) in generating highly entangled states. Here, we describe recent hardware upgrades to Quantinuum’s H2 quantum computer, enabling it to operate on up to 56 qubits with arbitrary connectivity and 99.843(5)% two-qubit gate fidelity. We define a class of circuits with random geometries that become hard to classically simulate in very low depth and implement them utilizing the flexible connectivity of H2. A careful analysis demonstrating the fast saturation of classical simulation complexity with depth indicates that H2 can yield data well beyond the reach of state-of-the art classical simulation methods at unprecedented fidelities. We find that the considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the quantum charge-coupled device architecture as continued progress is made toward building larger machines. Published by the American Physical Society 2025

DeCross, M.↗
DOE OSTI2025

Quasiprobabilistic Readout Correction of Midcircuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Quantum measurements are a fundamental component of quantum computing. However, on present-day quantum computers, measurements can be more error prone than quantum gates and are susceptible to nonunital errors as well as nonlocal correlations due to measurement crosstalk. While readout errors can be mitigated in postprocessing, this is inefficient in the number of qubits due to a combinatorially large number of possible states that need to be characterized. In this work, we show that measurement errors can be tailored into a simple stochastic error model using randomized compiling, enabling the efficient mitigation of readout errors via quasiprobability distributions reconstructed from the measurement of a single preparation state in an exponentially large confusion matrix. We demonstrate the scalability and power of this approach by correcting readout errors without matrix inversion on a large number of different preparation states applied to a register of eight superconducting transmon qubits. Moreover, we show that this method can be extended to midcircuit measurements used for active feedback via quasiprobabilistic error cancellation, and we demonstrate the correction of measurement errors on an ancilla qubit used to detect and actively correct bit-flip errors on an entangled memory qubit. Our approach enables the correction of readout errors on large numbers of qubits and offers a strategy for correcting readout errors in adaptive circuits in which the results of midcircuit measurements are used to perform conditional operations on nonlocal qubits in real time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Entanglement Randomness and Gapped Itinerant Carriers in a Frustrated Quantum Magnet

The quantum spin liquid is a state manifesting extraordinary many-body entanglement, and the material NaYbSe 2 is thought to be one of the most promising candidates for its realization. Through low-temperature heat capacity and thermal conductivity measurements, we identify an apparent contradiction familiar to many quantum spin liquid candidates: While entropy is stored by apparently gapless excitations, the itinerant carriers of entropy are gapped. By studying the compositional series NaYb 𝑥⁢ Lu 1−𝑥⁢ Se 2 across a percolation transition of the magnetic lattice, we suggest that this contradiction can be resolved by the presence of entanglement scales of random sizes. Moreover, as we truncate the scale of entanglement by magnetic dilution, we show that the itinerant magnetic entropy carrier in NaYbSe 2 does not arise from a uniform globally entangled spin ground state but rather materializes through the stochastic propagation of boundaries between locally entangled spin objects.

Lyu, Yuanqi 吕源祺 [University of California, Berkele↗
DOE OSTI2026

Comparison of theory with the experimental characterization of the spatial frequency response of interferometers using a binary pseudo-random array sample

Experimental evaluations of the surface height response of an interference microscope using a binary pseudo-random array test sample are compared with a theory based on a Fourier optics model. Measurements of key instrument characteristics, including the illumination, imaging, and obscuring apertures of three different Mirau objectives, support the theoretical calculations. Agreement between experimental and theoretical modeling confirms the predictability of the spatial frequency response for the purpose of specification and optimization of instrument configuration for specific metrology tasks. The results also provide confidence in methods of compensating for the decrease in instrument response with spatial frequency.

Calibration↗
DOE OSTI2024

Randomized control trial of moderate dose vitamin D alters microbiota stability and metabolite networks in healthy adults

ABSTRACT Evidence indicates that both vitamin D and the gut microbiome are involved in the process of colon carcinogenesis. However, it is unclear what effects supplemental vitamin D 3 has on the gut microbiome and its metabolites in healthy adults. We conducted a double-blind, randomized, placebo-controlled trial to identify the acute and long-term microbiota structural and metabolite changes that occur in response to a moderate dose (4,000 IU) of vitamin D 3 for 12 weeks in healthy adults. Our results demonstrated a significant increase in serum 25-hydroxy-vitamin D (25(OH)D) in the treatment group compared to placebo ( P < 0.0001). Vitamin D 3 significantly increased compositional similarity ( P < 0.0001) in the treatment group, and enriched members of the Bifidobacteriaceae family. We also identified a significant inverse relationship between the percent change in serum 25(OH)D and microbial stability in the treatment group ( R = −0.52, P < 0.019). Furthermore, vitamin D 3 supplementation resulted in notable metabolic shifts, in addition to resulting in a drastic rewiring of key gut microbial-metabolic associations. In conclusion, we show that a moderate dose of vitamin D 3 among healthy adults has unique acute and persistent effects on the fecal microbiota, and suggest novel mechanisms by which vitamin D may affect the host-microbiota relationship. IMPORTANCE Preventative measures to reduce the rise in early-onset colorectal cancer are of critical need. Both vitamin D, dietary and serum levels, and the gut microbiome are implicated in the etiology of colorectal cancer. By understanding the intimate relationship between vitamin D, the gut microbiome, and its metabolites, we may be able to identify key mechanisms that can be targeted for intervention, including inflammation and metabolic dysfunction. Furthermore, the similarity of vitamin D to cholesterol, which is metabolized by the gut microbiome, gives precedence to its ability to produce metabolites that can be further studied and leveraged for controlling colorectal cancer incidence and mortality.

Wyatt, Madhur↗
DOE OSTI2025

Bias-Variance Trade-Off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs

Physics-Informed Neural Networks (PINNs) have triggered a paradigm shift in scientific computing, leveraging mesh-free properties and robust approximation capabilities. While proving effective for low-dimensional partial differential equations (PDEs), the computational cost of PINNs remains a hurdle in high-dimensional scenarios. This is particularly pronounced when computing high-order and high-dimensional derivatives in the physics-informed loss. Randomized Smoothing PINN (RS-PINN) introduces Gaussian noise for stochastic smoothing of the original neural net model, enabling the use of Monte Carlo methods for derivative approximation, which eliminates the need for costly automatic differentiation. Despite its computational efficiency, especially in the approximation of high-dimensional derivatives, RS-PINN introduces biases in both loss and gradients, negatively impacting convergence, especially when coupled with stochastic gradient descent (SGD) algorithms. We present a comprehensive analysis of biases in RS-PINN, attributing them to the nonlinearity of the Mean Squared Error (MSE) loss as well as the intrinsic nonlinearity of the PDE itself. We propose tailored bias correction techniques, delineating their application based on the order of PDE nonlinearity. The derivation of an unbiased RS-PINN allows for a detailed examination of its advantages and disadvantages compared to the biased version. Specifically, the biased version has a lower variance and runs faster than the unbiased version, but it is less accurate due to the bias. To optimize the bias-variance trade-off, we combine the two approaches in a hybrid method that balances the rapid convergence of the biased version with the high accuracy of the unbiased version. In addition to methodological contributions, we present an enhanced implementation of RS-PINN. Extensive experiments on diverse high-dimensional PDEs, including Fokker-Planck, Hamilton-Jacobi-Bellman (HJB), viscous Burgers’, Allen-Cahn, and Sine-Gordon equations, illustrate the bias-variance trade-off and highlight the effectiveness of the hybrid RS-PINN. Empirical guidelines are provided for selecting biased, unbiased, or hybrid versions, depending on the dimensionality and nonlinearity of the specific PDE problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Perspective on “Active Brownian particles moving in a random Lorentz gas”

Self-propelled active matter can exhibit vastly different behavior than systems with purely Brownian motion. In Eur. Phys. J. E 40, 23 (2017), Zeitz, Wolf, and Stark compared an active matter particle with a Brownian particle moving in a random obstacle array. They showed that near the obstacle percolation density, both Brownian and active particles exhibit the same subdiffusive behavior, but the active particle reaches a steady state more rapidly. They also found that for high activity, the active particle has a lower effective diffusion than the Brownian particle due to the increased self-trapping effect generated by the activity. This result opens new directions for the study of active matter in disordered media, including bacteria in porous media, active colloids on quenched disorder, and active particles in crowded environments.

36 MATERIALS SCIENCE↗