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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine Learning Eliminates Reanalysis Warm Bias and Reveals Weaker Winter Surface Cooling Over Arctic Sea Ice

The surface energy budget governs Arctic sea-ice growth/melt, yet observations are sparse, and reanalysis data sets suffer from systematic biases. Here, we train a neural network with observational data to bias-correct hourly ERA5 fluxes over Arctic ice-covered regions (≥70°N; sea-ice concentration >80%) for 1994–2024. Training data cover two full seasonal cycles and different sea-ice regimes. The neural network reduces RMSE for net shortwave radiation by ∼40%, downward longwave radiation by ∼16% and the total surface energy budget by ∼55%, eliminating the wintertime warm bias of ∼4 K in ERA5. Wintertime surface cooling is reduced by ∼50%, yielding thermodynamic ice-growth estimates of ∼80–120 cm, consistent with SMOS–CryoSat satellite thickness increases and in contrast to the 150–200 cm growth implied by ERA5. Our bias-corrected data capture the observed clear/cloudy states of the winter boundary layer and can be used to study Arctic climatology, evaluate climate models and drive sea-ice-ocean models.

Hossain, Akil [Alfred Wegener Institute for Polar ↗
DOE OSTI2026

Root Dynamics Mitigate Warm and Dry Biases over the Central United States

The central United States frequently exhibits warm and dry biases in simulations of summertime conditions, a persistent feature that remains unresolved. While previous studies linked these biases to misrepresented surface energy exchanges, the role of belowground processes remains poorly understood. Here, we demonstrate that inadequate representation of root water uptake in land surface models contributes to this bias. Using both offline Noah-MP and coupled WRF-Noah-MP simulations with static and dynamic root water uptake schemes, we show that the inclusion of dynamic root processes reduces 2-m air temperature biases and enhances precipitation, primarily by increasing the rain rate of convective systems. Offline and coupled simulations further reveal that the cooling effects and precipitation increases are amplified through positive land-atmosphere feedback, active only in the coupled model. These findings highlight an important role of root in modulating land-atmosphere interactions and underscore the need to refine root-zone processes to improve regional atmospheric simulations.

Yang, Zhao (ORCID:0000000288027130)↗
DOE OSTI2021

Statistically bias-corrected and downscaled climate models underestimate the adverse effects of extreme heat on U.S. maize yields

Abstract Efforts to understand and quantify how a changing climate can impact agriculture often rely on bias-corrected and downscaled climate information, making it important to quantify potential biases of this approach. Here, we use a multi-model ensemble of statistically bias-corrected and downscaled climate models, as well as the corresponding parent models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), to drive a statistical panel model of U.S. maize yields that incorporates season-wide measures of temperature and precipitation. We analyze uncertainty in annual yield hindcasts, finding that the CMIP5 models considerably overestimate historical yield variability while the bias-corrected and downscaled versions underestimate the largest weather-induced yield declines. We also find large differences in projected yields and other decision-relevant metrics throughout this century, leaving stakeholders with modeling choices that require navigating trade-offs in resolution, historical accuracy, and projection confidence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distinctive exchange bias and unusual memory effects in magnetically compensated Pr 0.75 Gd 0.25 ScGe

Tuning the chemistry of materials often leads to discoveries of interesting phenomena that expand basic science and support practical applications. Here we show how different spin–orbit coupling in light and heavy lanthanides can be exploited to create complex magnetic ground states and thereby unusual spontaneous exchange bias (SEB), conventional exchange bias (CEB), and magnetic memory effects in almost ideally magnetically compensated Pr 0.75 Gd 0.25 ScGe, which is a representative of the PrScGe–GdScGe solid solution. We report the synthesis and detailed characterization of Pr 0.75 Gd 0.25 ScGe by X-ray powder diffraction, scanning electron microscopy, and magnetization measurements in magnetic fields up to 140 kOe. Partial substitution of a light lanthanide, Pr, with a heavy lanthanide, Gd, results in a complex magnetic ground state, which includes large spontaneous and conventional exchange biases reaching magnitudes of ~1.7 kOe and ~3.5 kOe, respectively, at T = 2 K, as well as shape dependent magnetic compensation and bias phenomena occurring in small external fields.

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

Redshifting galaxies from DESI to JWST CEERS: Correction of biases and uncertainties in quantifying morphology

Observations of high-redshift galaxies with unprecedented detail have now been rendered possible with the James Webb Space Telescope (JWST). However, accurately quantifying their morphology remains uncertain due to potential biases and uncertainties. To address this issue, we used a sample of 1816 nearby DESI galaxies, with a stellar mass range of 10 9.75 - 11.25 M ⊙ , to compute artificial images of galaxies of the same mass located at 0.75 ≤ z ≤ 3 and observed at rest-frame optical wavelength in the Cosmic Evolution Early Release Science (CEERS) survey. We analyzed the effects of cosmological redshift on the measurements of Petrosian radius (R p ), half-light radius (R 50 ), asymmetry (A), concentration (C), axis ratio (q), and Sérsic index (n). Our results show that R p and R 50 , calculated using non-parametric methods, are slightly overestimated due to PSF smoothing, while R 50 , q, and n obtained through fitting a Sérsic model does not exhibit significant biases. By incorporating a more accurate noise effect removal procedure, we improve the computation of A over existing methods, which often overestimate, underestimate, or lead to significant scatter of noise contributions. Due to PSF asymmetry, there is a minor overestimation of A for intrinsically symmetric galaxies. However, for intrinsically asymmetric galaxies, PSF smoothing dominates and results in an underestimation of A, an effect that becomes more significant with higher intrinsic A or at lower resolutions. Moreover, PSF smoothing also leads to an underestimation of C, which is notably more pronounced in galaxies with higher intrinsic C or at lower resolutions. We developed functions based on resolution level, defined as R p /FWHM, for correcting these biases and the associated statistical uncertainties. Applying these corrections, we measured the bias-corrected morphology for the simulated CEERS images and we find that the derived quantities are in good agreement with their intrinsic values – except for A, which is robust only for angularly large galaxies where R p /FWHM ≥ 5. Our correction functions can be applied to other surveys, offering valuable tools for future studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Bias-free terahertz generation from a silicon-compatible photoconductive emitter operating at telecommunication wavelengths

Here, we present a telecommunication-compatible bias-free photoconductive terahertz emitter composed of a bilayer InAs structure directly grown on a high-resistivity silicon substrate. The bilayer InAs structure includes p + -doped and undoped InAs layers, inducing a strong built-in electric field that enables terahertz generation without requiring any external bias voltage. A large-area plasmonic nanoantenna array is used to enhance and confine optical generation inside the photoconductive region with the highest built-in electric field, leading to the generation of a strong ultrafast photocurrent and broadband terahertz radiation. Thanks to a higher terahertz transmission through the silicon substrate and a shorter carrier lifetime in the InAs layers grown on silicon, higher signal-to-noise ratios are achieved at high terahertz frequencies compared with previously demonstrated bias-free terahertz emitters realized on GaAs. In addition to compatibility with silicon integrated optoelectronic platforms, the presented bias-free photoconductive emitter provides more than a 6 THz radiation bandwidth with more than 100 dB dynamic range when used in a terahertz time-domain spectroscopy system.

42 ENGINEERING↗
DOE OSTI2020

Possibility of reducing nonlinear distortions of a frequency response of a gas ring laser with a periodic alternating frequency bias

We report a theoretical study of the dependence of the beat frequency of counterpropagating waves on the rotation velocity in a gas ring laser with a periodic alternating frequency bias. Rectangular biases of two types are considered: with constant amplitude and with periodic amplitude modulation. We have found dynamic zones for locking-in the counterpropagating wave frequencies and determined deviations of the frequency response from the ideal one that arise when measuring frequency nonreciprocities, close in magnitude to the amplitude of an alternating frequency bias. It is shown that in the case of a rectangular bias with periodic amplitude modulation, nonlinear distortions of the frequency response can be reduced by an order of magnitude. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Very massive tracers and higher derivative biases

Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite precision. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a consistent framework to make predictions for LSS observables in the mildly non-linear regime. Herein we focus on biased tracers. We argue that in calculations at a given order in the dark matter perturbations, highly biased tracers will underperform because of their larger higher derivative biases. A natural prediction of the EFTofLSS is therefore that by simply adding higher derivative biases, highly massive tracers should perform comparably well. We implement this prediction for the halo-halo and the halo-matter power spectra at one loop, and the halo-halo-halo, halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare with simulations. We find good agreement with the prediction: at $z$ = 0, for all tracers, we are able to match the power spectra up to $k ≃$ 0.28$h$ Mpc -1 , as well as a small set of about 10 2 bispectra triangles up to $k ≃$ 0.17$h$ Mpc -1 . We also discuss the limitations of our study and some avenues to pursue to further establish these findings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Blinding scheme for the scale-dependence bias signature of local primordial non-Gaussianity for DESI 2024

The next generation of spectroscopic surveys is expected to achieve an unprecedented level of accuracy in the measurement of cosmological parameters. To avoid confirmation bias and thereby improve the reliability of these results, blinding procedures become a standard practice in the cosmological analyses of such surveys. Blinding is especially crucial when the impact of observational systematics is important relative to the cosmological signal, and a detection of that signal would have significant implications. This is the case for local primordial non-gaussianity, as probed by the scale-dependent bias of the galaxy power spectrum at large scales that are heavily sensitive to the dependence of the target selection on the imaging quality, known as imaging systematics. We propose a blinding method for the scale-dependent bias signature of local primordial non-gaussianity at the density field level which consists in generating a set of weights for the data that replicate the scale-dependent bias. The applied blinding is predictable, and can be straightforwardly combined with other catalog-level blinding procedures that have been designed for the baryon acoustic oscillation and redshift space distortion signals. The procedure is validated through simulations that replicate data from the first year of observation of the Dark Energy Spectroscopic Instrument, but may find applications to other upcoming spectroscopic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Analyzing line-of-sight selection biases in galaxy-scale strong lensing with external convergence and shear

The upcoming Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will dramatically increase the number of strong gravitational lensing systems, requiring precise modeling of line-of-sight (LOS) effects to mitigate biases in lensing observations and cosmological inferences. We develop a method to construct joint distributions of external convergence (κ ext ) and shear (γ ext ) for strong lensing LOS by aggregating large-scale structure simulations with high-resolution halo renderings and non-linear correction. Our approach captures both smooth background matter and perturbations from halos, enabling accurate modeling of LOS effects. Here, we apply non-linear LOS corrections to κ ext and γ ext that address the non-additive lensing effects caused by objects along the LOS in strong lensing. We find that, with a minimum image separation of 1.0'', non-linear LOS correction due to the presence of a dominant deflector slightly increases the ratio of quadruple to double lenses; this non-linear LOS correction also introduces systematic biases of ∼ 0.1% for galaxy-AGN lens in the inferred Hubble constant (H 0 ) if not accounted for. We also observe a 0.66% bias for galaxy-galaxy lenses on H 0 , and even larger biases 1.02% for galaxy-AGN systems if LOS effects are not accounted for. These results highlight the importance of LOS for precision cosmology. The publicly available code and datasets provide tools for incorporating LOS effects in future analyses.

Hubble constant↗
DOE OSTI2025

Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors

ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.

Zazzera, Stefano (ORCID:0000000158979221)↗
DOE OSTI2022

Mitigating foreground bias to the CMB lensing power spectrum for a CMB-HD survey

A promising way to measure the distribution of matter on small scales (k~10 h Mpc –1 ) is to use gravitational lensing of the cosmic microwave background (CMB). CMB-HD, a proposed high-resolution, low-noise millimeter survey over half the sky, can measure the CMB lensing auto spectrum on such small scales enabling measurements that can distinguish between a cold dark matter (CDM) model and alternative models designed to solve problems with CDM on small scales. However, extragalactic foregrounds can bias the CMB lensing auto spectrum if left untreated. Here, we present a foreground mitigation strategy that provides a path to reduce the bias from two of the most dominant foregrounds, the thermal Sunyaev-Zel’dovich effect and the cosmic infrared background. Given the level of realism included in our analysis, we find that the thermal Sunyaev-Zel’dovich alone and the cosmic infrared background alone bias the lensing auto spectrum by 0.6σ and 1.1σ, respectively, in the lensing multipole range of Lϵ[5000,20000] for a CMB-HD survey; combined these foregrounds yield a bias of only 1.3σ. Including these foregrounds, we also find that a CMB-HD survey can distinguish between a CDM model and a 10 –22 eV fuzzy dark matter model at the 5σ level. These results provide an important step in demonstrating that foreground contamination can be sufficiently reduced to enable a robust measurement of the small-scale matter power spectrum with CMB-HD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Photometric redshifts and intrinsic alignments: Degeneracies and biases in the 3 × 2 pt analysis

We present a systematic study of cosmological parameter bias in weak lensing and large-scale structure analyses for upcoming imaging surveys induced by the interplay of intrinsic alignments (IA) and photometric redshift (photo-z) model misspecification error. We first examine the degeneracies between the parameters of the tidal alignment–tidal torquing (TATT) model for IA and of a photo-z model including a mean shift ( Δ z ¯ ) and variance ( σ z ) for each tomographic bin of lenses and sources, under a variety of underlying true IA behaviors. We identify strong degeneracies between: (1) the redshift scaling of the tidal alignment amplitude and the mean shift and variances of source bins, (2) the redshift scaling of the tidal torquing amplitude and the variance of the lowest- z source bin, and (3) the IA source density weighting and the mean shift and variance of several source bins. We then use this information to guide our exploration of the level of cosmological parameter bias which can be induced given incorrect modeling of IA, photo-z, or both. We find that marginalizing over all the parameters of TATT is generally sufficient to preclude cosmological parameter bias in the scenarios we consider. However, this does not necessarily mean that IA and photo-z parameters are themselves unbiased, nor does it mean that the best-fit model is a good fit to the data. We also find scenarios where the inferred parameters produce χ d . o . f . 2 values indicative of a good fit but cosmological parameter bias is significant, particularly when the IA source density weighting parameter is not marginalized over. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Large Rashba spin splittings in bulk and monolayer of BiAs

There is great interest in developing new materials with Rashba split bands near the Fermi level for spintronics. Here, using first-principles calculations, we predict BiAs as a semiconductor with large Rashba splitting in bulk and monolayer forms. Bulk BiAs has a layered crystal structure with two atoms in a rhombohedral primitive cell, derived from the structure of the parent Bi and As elemental phases. It is a narrow band gap semiconductor, and it shows a combination of Rashba and Dresselhaus spin splitting with a characteristic spin texture around the L point in the Brillouin zone of the hexagonal conventional unit cell. It has sizable Rashba energies and Rashba coupling constants in the valence and conduction bands at the band edges. The 2D monolayer of BiAs has a much larger band gap at Γ, with a circular spin texture characteristic of a pure Rashba effect. The Rashba energy and Rashba coupling constant of monolayer BiAs are large compared to other known 2D materials and rapidly increase under biaxial tensile strain.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nonequilibrium dynamics of two-level systems directly after cryogenic alternating bias

Two-level systems (TLSs) are a dominant decoherence mechanism in superconducting qubits, microwave kinetic inductance detectors, and quantum dots. TLSs are tunneling states commonly found in amorphous materials and interfaces, which interact electromechanically, leading to energy loss. Fluctuations in the frequency of the TLSs are a significant problem for qubit operation and force recalibration every few hours. In this study, we probe the effect of alternating bias at cryogenic temperatures on TLSs in a purpose-built LC oscillator. When an in situ alternating bias is applied, the steady-state spectra of the TLSs disappear. Spectroscopy reveals transient behavior, in which the TLS frequency fluctuates on the order of minutes. Thermal cycling above 10 K reverses these effects, restoring the TLS spectrum to its original state. Importantly, the intrinsic loss tangent of the LC oscillator remains unchanged before and after the application of the alternating bias. We propose that the disappearance of the steady-state spectrum is caused by nonequilibrium energy buildup from strain in the oxide film introduced by the pulsed voltage-bias sequence. Understanding this nonequilibrium energy could shed light on TLS fluctuations and reduce the calibration requirements for qubits.

general physics↗
DOE OSTI2020

Angiotensin and biased analogs induce structurally distinct active conformations within a GPCR

Biased agonists of G protein–coupled receptors (GPCRs) preferentially activate a subset of downstream signaling pathways. In this work, we present crystal structures of angiotensin II type 1 receptor (AT1R) (2.7 to 2.9 angstroms) bound to three ligands with divergent bias profiles: the balanced endogenous agonist angiotensin II (AngII) and two strongly β-arrestin–biased analogs. Compared with other ligands, AngII promotes more-substantial rearrangements not only at the bottom of the ligand-binding pocket but also in a key polar network in the receptor core, which forms a sodium-binding site in most GPCRs. Divergences from the family consensus in this region, which appears to act as a biased signaling switch, may predispose the AT1R and certain other GPCRs (such as chemokine receptors) to adopt conformations that are capable of activating β-arrestin but not heterotrimeric G q protein signaling.

Wingler, Laura M. (ORCID:0000000236885088)↗
DOE OSTI2025

Evaluating Probabilistic Deep Learning Methods for Uncertainty Quantification of Precipitation Bias Correction

Climate models often exhibit biases in their precipitation predictions, particularly underestimating high-intensity events and overestimating low precipitation. Deep learning approaches offer promising solutions, but their epistemic uncertainty associated with a deep learning–based bias correction method has not previously been quantified for reliable downstream climate impact studies. While methods for capturing the epistemic uncertainty in deep learning frameworks exist, there is currently no consensus on the best method. In this work, we compare three uncertainty quantification (UQ) methods—Deep Ensembles (DEns), Monte Carlo Dropout (MCD), and Flipout—by assessing the reliability of their uncertainty estimates using standard measures such as sharpness and calibration. These UQ methods are applied to an existing deep learning precipitation bias correction model known as UFNet: a coupled U-Net and fully connected neural network. The methods utilized to assess the models’ uncertainties are 1) calibration, which ensures that the expected probabilities of the model align with reality and 2) sharpness, which is a measure of the precision of the model’s probabilistic predictions. Of the three UQ methods evaluated, the DEns and MCD methods demonstrated the best-calibrated performance (expected calibration error of 0.36 and 0.35, respectively), compared to Flipout (0.58). In contrast, Flipout had the sharpest predictions and the highest metric performance in bias correcting precipitation—especially for higher-order moments such as kurtosis with a spatial correlation of 72% compared to 32% and 55% spatial correlation for DEns and MCD, respectively. Of the three UQ methods, MCD was found to be the most suitable method for UQ purposes based on its calibration, sharpness, and computational requirements.

Bayesian methods↗
DOE OSTI2024

California Offshore Wind Resource Bias Investigation and Correction [Slides]

This presentation highlights the findings of an investigation into the causes of high wind speed bias in offshore California's 20-year wind resource dataset, CA20, released by the National Renewable Energy Laboratory (NREL) in 2020. Utilizing observations from floating lidars deployed by the Pacific Northwest National Laboratory (PNNL), considerable bias in modeled hub-height winds was identified. The study reveals that the choice of planetary boundary layer (PBL) scheme significantly impacts wind speed accuracy, with the less common Yonsei University (YSU) scheme nearly eliminating bias compared to the widely used Mellor-Yamada-Nakanishi-Niino (MYNN) scheme. Furthermore, it shows that one of the key factors contributing to this modeled bias is the fact that MYNN overestimates the frequency of stable atmospheric conditions in offshore California. As a result, an updated dataset, NOW-23, incorporating YSU as the PBL scheme, has been produced.

17 WIND ENERGY↗