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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

In Situ Investigation of Upper Airway Occlusion in Sleep Disordered Breathing Using Ultrasonic Transducer Arrays

This work presents a novel application of ultrasound for the real-time, non-invasive investigation of occlusion of the upper airway during events of obstructive sleep apnea/hypopnea syndrome. It is hypothesized that ultrasonic pulses applied to the neck during apneic events produce spectral and temporal features that can detect apnea occurrence. Theoretical models of ultrasound propagation and an in vitro test were conducted to test this hypothesis in both transmission and reflection modes. Complete specifications and technical details of the system design and fabrication, which is mounted on each subject’s neck, are presented, including the methodology. Nine patients (seven male and two female, mean age of 42 years, with a range of 25 to 56 years, and body mass index 37.6 ± 6.6 kg/m2) were recruited for a full night study, which included simultaneous nocturnal polysomnography for the validation of the results. Nine temporal features and four spectral features were extracted from the envelope of the received pulse waveform. These were used to compute 26 metrics to quantify the changes in the ultrasonic waveforms between normal breathing and apneic events. The statistical analysis of the collected ultrasonic data showed that at least two or more of the proposed features could detect apneic events in all subjects. The findings establish the feasibility of the proposed method as a cost-effective and non-invasive OSAHS screening tool.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

DIGS: deep inference of galaxy spectra with neural posterior estimation

Abstract With the advent of billion-galaxy surveys with complex data, the need of the hour is to efficiently model galaxy spectral energy distributions (SEDs) with robust uncertainty quantification. The combination of simulation-based inference (SBI) and amortized neural posterior estimation (NPE) has been successfully used to analyse simulated and real galaxy photometry both precisely and efficiently. In this work, we utilise this combination and build on existing literature to analyse simulated noisy galaxy spectra. Here, we demonstrate a proof-of-concept study of spectra that is (a) an efficient analysis of galaxy SEDs and inference of galaxy parameters with physically interpretable uncertainties; and (b) amortized calculations of posterior distributions of said galaxy parameters at the modest cost of a few galaxy fits with Markov chain Monte Carlo (MCMC) methods. We utilise the SED generator and inference framework Prospector to generate simulated spectra, and train a dataset of 2 × 10 6 spectra (corresponding to a five-parameter SED model) with NPE. We show that SBI—with its combination of fast and amortized posterior estimations—is capable of inferring accurate galaxy stellar masses and metallicities. Our uncertainty constraints are comparable to or moderately weaker than traditional inverse-modelling with Bayesian MCMC methods (e.g. 0.17 and 0.26 dex in stellar mass and metallicity for a given galaxy, respectively). We also find that our inference framework conducts rapid SED inference (0.9–1.2 × 10 5 galaxy spectra via SBI/NPE at the cost of 1 MCMC-based fit). With this work, we set the stage for further work that focuses of SED fitting of galaxy spectra with SBI, in the era of JWST galaxy survey programs and the wide-field Roman Space Telescope spectroscopic surveys.

spectroscopy↗
DOE OSTI2025

Designing for cooperative grain boundary segregation in multicomponent alloys

Tailoring the nanoscale distribution of chemical species at grain boundaries is a powerful method to dramatically influence the properties of polycrystalline materials. However, classical approaches to the problem have tacitly assumed that only competition is possible between solute species. In this paper, we show that solute elements can cooperate in the way they segregate to grain boundaries: In properly targeted alloys, the different chemical species cooperate to each fill complementary grain boundary sites disfavored by the other. By developing a theoretical “spectral” approach to this problem based on quantum-accurate grain boundary site distributions, we show how grain boundaries can be cooperatively alloyed, whether by depletion or enrichment. We provide machine-learned cosegregation information for over 700 ternary aluminum-based alloys and experimentally validate the concept in one ternary alloy where cosegregation is not expected by prior models but is expected based on the cooperative model.

grain boundaries↗
DOE OSTI2021

On the shear-current effect: toward understanding why theories and simulations have mutually and separately conflicted

ABSTRACT The shear-current effect (SCE) of mean-field dynamo theory refers to the combination of a shear flow and a turbulent coefficient β21 with a favourable negative sign for exponential mean-field growth, rather than positive for diffusion. There have been long-standing disagreements among theoretical calculations and comparisons of theory with numerical experiments as to the sign of kinetic ($\beta ^u_{21}$) and magnetic ($\beta ^b_{21}$) contributions. To resolve these discrepancies, we combine an analytical approach with simulations, and show that unlike $\beta ^b_{21}$, the kinetic SCE $\beta ^u_{21}$ has a strong dependence on the kinetic energy spectral index and can transit from positive to negative values at $\mathcal {O}(10)$ Reynolds numbers if the spectrum is not too steep. Conversely, $\beta ^b_{21}$ is always negative regardless of the spectral index and Reynolds numbers. For very steep energy spectra, the positive $\beta ^u_{21}$ can dominate even at energy equipartition urms ≃ brms, resulting in a positive total β21 even though $\beta ^b_{21}\lt 0$. Our findings bridge the gap between the seemingly contradictory results from the second-order-correlation approximation versus the spectral-τ closure, for which opposite signs for $\beta ^u_{21}$ have been reported, with the same sign for $\beta ^b_{21}\lt 0$. The results also offer an explanation for the simulations that find $\beta ^u_{21}\gt 0$ and an inconclusive overall sign of β21 for $\mathcal {O}(10)$ Reynolds numbers. The transient behaviour of $\beta ^u_{21}$ is demonstrated using the kinematic test-field method. We compute dynamo growth rates for cases with or without rotation, and discuss opportunities for further work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Evaluation of the Reliability of Passive Infrared (PIR) Occupancy Sensors for Residential Indoor Lighting

Solid-state lighting (SSL) technologies have penetrated the general illumination market in recent years, largely replacing conventional technologies such as incandescent and fluorescent lighting. Most of the initial excitement about light-emitting diode (LED) sources for SSL devices focused on their energy savings potential resulting from vast improvements in source efficiency and luminous efficacy compared with conventional illumination products. More recently, the focus has shifted toward other aspects of lighting application efficiency, namely intensity effectiveness and spectral efficiency, because of the ease of controlling both the light intensity of LEDs with drive voltage and the color properties of the LED-based illuminators. To capitalize on the energy savings of increased intensity effectiveness and spectral efficiency, a lighting control system (LCS) is often used. While the current penetration of LCSs is relatively modest, it is anticipated that lighting controls (i.e., connected lighting, controls and LED and conventional lighting) could have an installed penetration as higher as 46% by the year 2035, saving an additional 1.3 quads of energy. Despite the large energy savings that can be gained from using LCSs, standard test methods for evaluating sensors employed in LCSs and reliability data of the LCSs and their components are generally lacking. The National Electrical Manufacturers Association (NEMA) developed the only standard, NEMA WD 7-2011 (R2016), to test occupancy and motion sensor performance (herein referred to as “the NEMA protocol”). In a previous U.S. Department of Energy (DOE) effort, some concerns of the NEMA protocol were identified (e.g., strict height and weight limits on test subjects, large amounts of manual effort, sometimes inconsistent repeatability). During the current work, a consistent detection length test (DLT) and a Robotic Sensor Evaluation System (RoboSES) were developed to alleviate some of these concerns. RoboSES acts as a human surrogate by using thermal pads on a mannequin and a remote-controlled mobile base to test a sensor’s field of view (FOV). This report builds on the earlier DOE efforts to understand sensor technologies used in LCSs for general illumination. Specifically, this report describes the optimization of RoboSES, characterizes and establishes test methods to assess the reliability of multiple passive infrared (PIR) sensors, and reports the findings of robustness and reliability testing on two commercial PIR sensors intended for residential applications. The information presented in this report is gained from up to 4,000 hours (hrs) of accelerated stress tests (ASTs).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Autonomous Flow Electrochemistry for Accelerated Catalyst Discovery

Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Optical array for high-quality imaging in harsh environments

Methods and apparatus are disclosed for producing high quality images in uncontrolled or impaired environments. In some examples of the disclosed technology, groups of cameras for high dynamic range (HDR), polarization diversity, and optional other diversity modes are arranged to concurrently image a common scene. For example, in a vehicle checkpoint application, HDR provides discernment of dark objects inside a vehicle, while polarization diversity aids in rejecting glare. Spectral diversity, infrared imaging, and active illumination can be applied for better imaging through a windshield. Preprocessed single-camera images are registered and fused. Faces or other features of interest can be detected in the fused image and identified in a library. Impairments can include weather, insufficient or interfering lighting, shadows, reflections, window glass, occlusions, or moving objects.

42 ENGINEERING↗
DOE OSTI2023

Optical array for high-quality imaging in harsh environments

Methods and apparatus are disclosed for producing high quality images in uncontrolled or impaired environments. In some examples of the disclosed technology, groups of cameras for high dynamic range (HDR), polarization diversity, and optional other diversity modes are arranged to concurrently image a common scene. For example, in a vehicle checkpoint application, HDR provides discernment of dark objects inside a vehicle, while polarization diversity aids in rejecting glare. Spectral diversity, infrared imaging, and active illumination can be applied for better imaging through a windshield. Preprocessed single-camera images are registered and fused. Faces or other features of interest can be detected in the fused image and identified in a library. Impairments can include weather, insufficient or interfering lighting, shadows, reflections, window glass, occlusions, or moving objects.

Baba, Justin S.↗
DOE OSTI2022

SDSS-IV MaStar: Stellar parameter determination with continuum-supplemented full-spectrum fitting

We present a stellar parameter catalog built to accompany the MaStar Stellar Library, which is a comprehensive collection of empirical, medium-resolution stellar spectra. We constructed this parameter catalog by using a multicomponent χ 2 fitting approach to match MaStar spectra to models generated by interpolating the ATLAS9-based BOSZ model spectra. The total χ 2 for a given model is defined as the sum of components constructed to characterize narrow-band features of observed spectra (e.g., absorption lines) and the broadband continuum shape separately. Extinction and systematics due to flux calibration were taken into account in the fitting. The χ 2 distribution for a given region of model space was sampled using a Markov chain Monte Carlo (MCMC) algorithm, the data from which were then used to extract atmospheric parameter estimates (T eff , log g, [Fe/H], and [α/Fe]), their corresponding uncertainties, and direct extinction measurements. Two methods were used to extract parameters and uncertainties: one that accepts the MCMC’s prescribed minimum-χ 2 result, and one that uses Bayesian inference to compute a likelihood-weighted mean from the χ 2 distribution sampled by the MCMC. Results were evaluated for internal consistency using repeat observations where available and by comparing them with external data sets (e.g., APOGEE-2 and Gaia DR2). Our spectral-fitting exercise reveals possible deficiencies in current theoretical model spectra, illustrating the potential power of MaStar spectra for helping to improve the models. This paper represents an update to the parameters that were originally presented with SDSS-IV DR17. The MaStar parameter catalog containing our BestFit results is available on the SDSS-IV DR17 website as part of version 2 of the MaStar stellar parameter value-added catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structural behavior

High-frequency (e.g., 10 Hz) eddy covariance measurements are typically used to estimate fluxes at the land–atmosphere interface at timescales of 15–60 min. These multivariate data contain information about the interdependency at high frequency between the interacting variables such as wind, humidity, temperature, and CO 2⁠ . We use data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US, which offers an opportunity to move beyond the traditional spectral analyses to explore causal dependency among variables. In this study, we quantify the structure of inter-dependencies of interacting variables at high frequency represented by a directed acyclic graph (DAG). We compare DAGs to investigate changes in structural differences in causal interactions. We then apply a distance-based classification and -means clustering approach to identify the evolution of the causal structure represented by a DAG. Our method selects an unbiased number of clusters of similar structures and characterizes the similarities and differences between them. We explore a range of dynamic behavior using data from a clear sky day and during a solar eclipse in 2017. Our results show well-defined clusters of similar causal dependencies as the system evolves. Furthermore, our approach provides a methodological framework to understand how causal dependence in turbulence manifests in high-frequency data when represented through a DAG.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Deep learning for NLTE spectral opacities

Computer simulations of high energy density science experiments are computationally challenging, consisting of multiple physics calculations including radiation transport, hydrodynamics, atomic physics, nuclear reactions, laser–plasma interactions, and more. To simulate inertial confinement fusion (ICF) experiments at high fidelity, each of these physics calculations should be as detailed as possible. However, this quickly becomes too computationally expensive even for modern supercomputers, and thus many simplifying assumptions are made to reduce the required computational time. Much of the research has focused on acceleration techniques for the various packages in multiphysics codes. In this work, we explore a novel method for accelerating physics packages via machine learning. The non-local thermodynamic equilibrium (NLTE) package is one of the most expensive calculations in the simulations of indirect drive inertial confinement fusion, taking several tens of percent of the total wall clock time. We explore the use of machine learning to accelerate this package, by essentially replacing the physics calculation with a deep neural network that has been trained to emulate the physics code. Overall, we demonstrate the feasibility of this approach on a simple problem and perform a side-by-side comparison of the physics calculation and the neural network inline in an ICF Hohlraum simulation. We show that the neural network achieves a 10× speed up in NLTE computational time while achieving good agreement with the physics code for several quantities of interest.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

What lies beneath: Vertical temperature heterogeneity in a Mediterranean woodland savanna

As the availability of satellite and airborne thermal infrared remote sensing (TIR-RS) data increases and their spatial, temporal, and spectral resolutions improve, researchers are finding diverse applications for TIR-RS measurements. TIR-RS is now commonly applied in regional- and continental-scale analyses, such as those focused on fire and surface energy balance. However, its application lags in plant physiology and ecology, for which a finer-scale understanding of plant canopy temperatures would be useful to elucidate plant water dynamics, for example. In particular, while methods to disaggregate TIR-RS pixels in horizontal space have advanced, possible vertical stratification of plant canopy temperature and its implications for understanding the correspondence between TIR-RS and finer-scale, field-based thermal measurements (e.g. made with a thermal camera) remain unexplored. Here, we use data from a thermal camera deployed concurrently with the recent ECOSTRESS mission to quantify vertical temperature gradients within tree canopies and temperatures of over- vs. under-story plants in a Mediterranean woodland savanna. We then leverage diverse ancillary data to maximize the geometric comparability of ECOSTRESS and thermal camera measurements, in order to assess the extent to which the two forms of thermal measurements correspond. Specifically, we ask: (1) What are the patterns of intra-canopy and over- vs. under-story vertical temperature in a Mediterranean woodland savanna?, and (2) How can vertically-resolved, but spatially-limited field-based temperature measurements be reconciled with spatially-extensive, but surface-only, temperature measurements of a space-borne remote sensor? Further, we found consistent patterns of vertical thermal heterogeneity both within tree canopies and between ecosystem over- and under-stories. The daytime difference between the top and bottom thirds of blue oak canopies was, on average, 0.48 ° C – and sometimes several times larger. Notably, canopy tops are cooler, likely associated with the under-story grass reaching daytime temperatures often exceeding over-story temperatures by 10° C. Given the consistency of the intra-canopy temperature gradients, we expected the ECOSTRESS sensor would be in better agreement with camera measurements of canopy tops than bulk canopies or canopy bottoms. However, within-canopy gradients were overwhelmed by other sources of disagreement between the measurements, in part associated with upscaling camera measurements across space. Overall, thermal camera and ECOSTRESS measurements were largely in agreement at night (pixel RMSE = 1.1°C), but they were more divergent during times of low (but >0 W/m2) and high incoming solar radiation (daytime pixel RMSE = 3.5°C).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data

Abstract We develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.

Geochemistry & Geophysics↗
DOE OSTI2022

Cosmic rays in molecular clouds probed by H 2 rovibrational lines

Context. Low-energy cosmic rays (<1 TeV) play a fundamental role in the chemical and dynamical evolution of molecular clouds, as they control the ionisation, dissociation, and excitation of H 2 . Their characterisation is therefore important both for the interpretation of observations and for the development of theoretical models. However, the methods used so far for estimating the cosmic-ray ionisation rate in molecular clouds have several limitations due to uncertainties in the adopted chemical networks. Aims. Here, we refine and extend a previously proposed method to estimate the cosmic-ray ionisation rate in molecular clouds by observing rovibrational transitions of H 2 at near-infrared wavelengths, which are mainly excited by secondary cosmic-ray electrons. Methods. Combining models of interstellar cosmic-ray propagation and attenuation in molecular clouds with the rigorous calculation of the expected secondary electron spectrum and updated electron-H 2 excitation cross sections, we derive the intensity of the four H 2 rovibrational transitions observable in cold dense gas: (1—0)O(2), (1—0)Q(2), (1—0)S(0), and (1—0)O(4). Results. The proposed method allows the estimation of the cosmic-ray ionisation rate for a given observed line intensity and H 2 column density. We are also able to deduce the shape of the low-energy cosmic-ray proton spectrum impinging upon the molecular cloud. In addition, we present a look-up plot and a web-based application that can be used to constrain the low-energy spectral slope of the interstellar cosmic-ray proton spectrum. We finally comment on the capability of the James Webb Space Telescope to detect these near-infrared H 2 lines, which will make it possible to derive, for the first time, spatial variation in the cosmic-ray ionisation rate in dense gas. Besides the implications for the interpretation of the chemical-dynamic evolution of a molecular cloud, it will finally be possible to test competing models of cosmic-ray propagation and attenuation in the interstellar medium, as well as compare cosmic-ray spectra in different Galactic regions

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Highly cascaded first-order fiber Bragg gratings in highly multimode optical fibers for distributed temperature sensing under harsh environment conditions

This study presents a pioneering technique for fabricating highly cascaded first-order fiber Bragg gratings (FBGs) using a femtosecond laser-assisted point-by-point inscription method in highly multimode optical fibers, specifically Sapphire crystalline fiber, and pure silica coreless fiber. Notably, it marks the first successful demonstration of a distributed array comprising 10 FBGs within highly multimode fibers. This achievement is facilitated by a high-power laser technique that yields larger reflectors characterized by a Gaussian intensity profile. These first-order FBGs offer various advantages, including enhanced reflectivity, reduced fabrication time, and simplified spectral characteristics, enhancing their accessibility for interpretation when contrasted with higher-order FBGs. In addition to that it encompasses a comprehensive analysis of the robustness and efficacy of these FBGs, with particular emphasis on their ability to endure extreme temperatures. These FBGs demonstrate an advantageous capability for localized multi-point temperature monitoring, reaching temperatures up to 1500°C with sapphire crystalline fiber and 1100°C with pure silica coreless fiber. This resilience makes them suitable for deployment in harsh environmental conditions. This innovative approach substantially broadens the potential applications of highly multimode optical fibers, particularly in the arena of sensing and communication, where challenges related to thermal gradients and harsh environments prevail. Furthermore, these groundbreaking first-order FBGs signify a substantial advancement in the realm of distributed temperature sensing, offering supreme capabilities for temperature monitoring and signal stability. As such, our work holds the promise of a substantial impact on industries and applications that demand unwavering reliability under extreme conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A Method to Extract Spatially Resolved Polycyclic Aromatic Hydrocarbon Emission from Spitzer Spectra: Application to M51

The mid-infrared spectrum contains rich diagnostics to probe the physical properties of galaxies, among which the pervasive emission features from polycyclic aromatic hydrocarbons (PAHs) offer promising means of estimating the star formation rate (SFR) relatively immune from dust extinction. This paper investigates the effectiveness of PAH emission as a SFR indicator on subkiloparsec scales by studying the Spitzer/IRS mapping-mode observations of the nearby grand-design spiral galaxy M51. We present a new approach of analyzing the spatial elements of the spectral data cube that simultaneously maximizes spatial resolution and spatial coverage, while yielding reliable measurements of the total, integrated 5–20 μm PAH emission. We devise a strategy of extracting robust PAH emission using spectra with only partial spectral coverage, complementing missing spectral regions with properly combined mid-infrared photometry. We find that in M51 the PAH emission correlates tightly with the extinction-corrected far-ultraviolet, near-ultraviolet, and Hα emission, from scales of ∼0.4 kpc close to the nucleus to 6 kpc out in the disk of the galaxy, indicating that PAH serves as an excellent tracer of SFR over a wide range of galactic environments. But regional differences exist. Close to the active nucleus of M51 the 6.2 μm feature is weaker, and the overall level of PAH emission is suppressed. The spiral arms and the central star-forming region of the galaxy emit stronger 7.7 and 8.6 μm PAH features than the inter-arm regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quasi-Lindblad pseudomode theory for open quantum systems

Here, we introduce a new framework to study the dynamics of open quantum systems with linearly coupled Gaussian baths. Our approach replaces the continuous bath with an auxiliary discrete set of pseudomodes with dissipative dynamics, but we further relax the complete positivity requirement in the Lindblad master equation and formulate a quasi-Lindblad pseudomode theory. We show that this quasi-Lindblad pseudomode formulation directly leads to a representation of the bath correlation function in terms of a complex weighted sum of complex exponentials, an expansion that is known to be rapidly convergent in practice and thus leads to a compact set of pseudomodes. The pseudomode representation is not unique and can differ by a gauge choice. When the global dynamics can be simulated exactly, the system dynamics is unique and independent of the specific pseudomode representation. However, the gauge choice may affect the stability of the global dynamics, and we provide an analysis of why and when the global dynamics can retain stability despite losing positivity. We showcase the performance of this formulation across various spectral densities in both bosonic and fermionic problems, finding significant improvements over conventional pseudomode formulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗