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NASA NTRS1992

Automated in situ observations of upper ocean biogeochemistry, bio-optics, and physics and their potential use for global studies

The processes controlling the flux of carbon in the upper ocean have dynamic ranges in space and time of at least nine orders of magnitude. These processes depend on a broad suite of inter-related biogeochemical, bio-optical, and physical variables. These variables should be sampled on scales matching the relevant phenomena. Traditional ship-based sampling, while critical for detailed and more comprehensive observations, can span only limited portions of these ranges because of logistical and financial constraints. Further, remote observations from satellite platforms enable broad horizontal coverage which is restricted to the upper few meters of the ocean. For these main reasons, automated subsurface measurement systems are important for the fulfillment of research goals related to the regional and global estimation and modeling of time varying biogeochemical fluxes. Within the past few years, new sensors and systems capable of autonomously measuring several of the critical variables have been developed. The platforms for deploying these systems now include moorings and drifters and it is likely that autonomous underwater vehicles (AUV's) will become available for use in the future. Each of these platforms satisfies particular sampling needs and can be used to complement both shipboard and satellite observations. In the present review, (1) sampling considerations will be summarized, (2) examples of data obtained from some of the existing automated in situ sampling systems will be highlighted, (3) future sensors and systems will be discussed, (4) data management issues for present and future automated systems will be considered, and (5) the status of near real-time data telemetry will be outlined. Finally, we wish to make it clear at the outset that the perspectives presented here are those of the authors and are not intended to represent those of the United States JGOFS program, the International JGOFS program, NOAA's C&GC program, or other global ocean programs.

Dickey, Tommy D.↗

DOE OSTI2024

RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project

Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.

Geology↗

NASA NTRS1996

Propagation and Breaking at High Altitudes of Gravity Waves Excited by Tropospheric Forcing

An anelastic approximation is used with a time-variable coordinate transformation to formulate a two-dimensional numerical model that describes the evolution of gravity waves. The model is solved using a semi-Lagrangian method with monotone (nonoscillatory) interpolation of all advected fields. The time-variable transformation is used to generate disturbances at the lower boundary that approximate the effect of a traveling line of thunderstorms (a squall line) or of flow over a broad topographic obstacle. The vertical propagation and breaking of the gravity wave field (under conditions typical of summer solstice) is illustrated for each of these cases. It is shown that the wave field at high altitudes is dominated by a single horizontal wavelength; which is not always related simply to the horizontal dimension of the source. The morphology of wave breaking depends on the horizontal wavelength; for sufficiently short waves, breaking involves roughly one half of the wavelength. In common with other studies, it is found that the breaking waves undergo "self-acceleration," such that the zonal-mean intrinsic frequency remains approximately constant in spite of large changes in the background wind. It is also shown that many of the features obtained in the calculations can be understood in terms of linear wave theory. In particular, linear theory provides insights into the wavelength of the waves that break at high altitudes, the onset and evolution of breaking. the horizontal extent of the breaking region and its position relative to the forcing, and the minimum and maximum altitudes where breaking occurs. Wave breaking ceases at the altitude where the background dissipation rate (which in our model is a proxy for molecular diffusion) becomes greater than the rate of dissipation due to wave breaking, This altitude, in effect, the model turbopause, is shown to depend on a relatively small number of parameters that characterize the waves and the background state.

Prusa, Joseph M.↗

DOE OSTI2020

The impact of wind, solar, and other factors on the decline in wholesale power prices in the United States

Across multiple organized wholesale power markets in the United States, annual average prices declined by 19–64 dollars per MWh between 2008 and 2017 while retirements of thermal power plants accelerated. Several prominent changes over the last decade are often discussed as contributors to this decline in prices. These include growth in wind and solar, a reduction in the price of natural gas, and weakened load growth. Here we construct a fundamental supply curve model for each of seven organized wholesale market regions and use counterfactual simulations to assess the degree to which wind and solar—among other factors—have influenced wholesale electricity prices. We find that growth in wind and solar since 2008 reduced average annual wholesale electricity prices by less than 3 dollars per MWh. In contrast the decline in natural gas prices reduced wholesale prices by 7–53 dollars per MWh, depending on the region. This suggests that recent thermal-plant retirements in the U.S. are primarily due to low natural gas prices, not growth in wind and solar. Fully isolating the impact of individual factors, however, is limited by non-linear interactions between factors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Detailed study of quark-hadron duality in spin structure functions of the proton and neutron

Background: The response of hadrons, the bound states of the strong force (QCD), to external probes can be described in two different, complementary frameworks: as direct interactions with their fundamental constituents, quarks and gluons, or alternatively as elastic or inelastic coherent scattering that leaves the hadrons in their ground state or in one of their excited (resonance) states. The former picture emerges most clearly in hard processes with high momentum transfer, where the hadron response can be described by the perturbative expansion of QCD, while at lower energy and momentum transfers, the resonant excitations of the hadrons dominate the cross section. The overlap region between these two pictures, where both yield similar predictions, is referred to as quark-hadron duality and has been extensively studied in reactions involving unpolarized hadrons. Some limited information on this phenomenon also exists for polarized protons, deuterons, and 3 He nuclei, but not yet for neutrons. Purpose: In this paper, we present comprehensive and detailed results on the correspondence between the extrapolated deep inelastic structure function g 1 of both the proton and the neutron with the same quantity measured in the nucleon resonance region. Thanks to the fine binning and high precision of our data, and using a well-controlled perturbative QCD (pQCD) fit for the partonic prediction, we can make quantitative statements about the kinematic range of applicability of both local duality and global duality. Method: We use the most updated QCD global analysis results at high x from the Jefferson Lab Angular Momentum Collaboration to extrapolate the spin structure function g 1 into the nucleon resonance region and then integrate over various intervals in the scaling variable x. We compare the results with the large data set collected in the quark-hadron transition region by the CLAS Collaboration, including, for the first time, deconvoluted neutron data, integrated over the same intervals. We present this comparison as a function of the momentum transfer Q 2 . Results: We find that, depending on the integration interval and the minimum momentum transfer chosen, a clear transition to quark-hadron duality can be observed in both nucleon species. Furthermore, we show, for the first time, the approach to scaling behavior for g 1 measured in the resonance region at sufficiently high momentum transfer. Conclusions: Here, our results can be used to quantify the deviations from the applicability of pQCD for data taken at moderate energies and can help with extraction of quark distribution functions from such data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Optimization problems governed by systems of PDEs with uncertainties

This paper reviews current theoretical and numerical approaches to optimization problems governed by partial differential equations (PDEs) that depend on random variables or random fields. Such problems arise in many engineering, science, economics and societal decision-making tasks. This paper focuses on problems in which the governing PDEs are parametrized by the random variables/fields, and the decisions are made at the beginning and are not revised once uncertainty is revealed. Examples of such problems are presented to motivate the topic of this paper, and to illustrate the impact of different ways to model uncertainty in the formulations of the optimization problem and their impact on the solution. A linear–quadratic elliptic optimal control problem is used to provide a detailed discussion of the set-up for the risk-neutral optimization problem formulation, study the existence and characterization of its solution, and survey numerical methods for computing it. Different ways to model uncertainty in the PDE-constrained optimization problem are surveyed in an abstract setting, including risk measures, distributionally robust optimization formulations, probabilistic functions and chance constraints, and stochastic orders. Furthermore, approximation-based optimization approaches and stochastic methods for the solution of the large-scale PDE-constrained optimization problems under uncertainty are described. Some possible future research directions are outlined.

Heinkenschloss, Matthias [Rice Univ., Houston, TX ↗

DOE OSTI2025

The Three Hundred Project: Modeling baryon and hot-gas fraction evolution in simulated clusters

The baryon fraction of galaxy clusters, expressed as the ratio between the mass in baryons (including both stars and cold or hot gas) and the total mass, is a powerful tool to provide information on the cosmological parameters, while the hot-gas fraction provides indications on the physics of the intracluster plasma and its interplay with the processes that drive galaxy formation. Using cosmological hydrodynamical simulations of about 300 simulated massive galaxy clusters with a median mass M 500 ≈ 7 × 10 14 M ⊙ at z = 0, we model the relations between total mass and either baryon fraction or the hot gas fractions at overdensities Δ = 2500, 500, and 200 with respect to the cosmic critical density, and their evolution from z ∼ 0 to z ∼ 1.3. We utilized the simulated galaxy clusters from the Three Hundred project, which include star formation and feedback from both supernovae and active galactic nuclei. We fit the simulation results for such scaling relations against three analytic forms (linear, quadratic, and logarithmic in a logarithmic plane) and three forms for the redshift dependence, and we considered as a variable both the inverse of the cosmic scale factor, (1 + z), and the Hubble expansion rate, E(z). We show that power-law dependencies on cluster mass poorly describe the investigated relations. A power law fails to simultaneously capture the flattening of the total baryon and gas fractions at high masses, their drop at low masses, and the transition between these two regimes. The other two functional forms provide a more accurate description of the curvature in mass scaling. The fractions measured within smaller radii exhibit a stronger evolution than those measured within larger radii. From the analysis of these simulations, we evince that as long as we include systems in the mass range herein investigated, the baryon or gas fraction can be accurately related to the total mass through either a parabola or a logarithm in the logarithmic plane. The trends are common to all modern hydro simulations, although the amplitude of the drop at low masses might differ. Being able to observationally determine the gas fraction in groups will thus provide constraints on the baryonic physics.

galaxy clusters↗

DOE OSTI2025

Trends in spatial correlations, two-phase coexistence, and criticality in a class of type-2 Schloegl models for autocatalysis

A class of type-2 Schloegl models is considered for particles on a square lattice with variable-range cooperativity. These models involve: (i) spontaneous particle annihilation at rate p; (ii) autocatalytic particle creation at unoccupied sites (i, j) with n ⩾ 2 particles within a specified neighborhood, Ω 𝑁 (i, j), of sites at rate $k_n$ = $\frac{^{(^n_2)}}{_{(^N_2)}}$ = $\frac{n{(n-1)}}{_{N(N-1)}}$; and (iii) possible spontaneous particle creation at unoccupied sites at “small” rate ɛ ⩾ 0. In some cases, Ω 𝑁 just includes all symmetry-equivalent sites at a single specific distance 𝑑 (in units of lattice constants) from the unoccupied site, e.g., 𝑑 = 1 (nearest-neighbor sites) where 𝑁 = 4, or 𝑑 = √5 (or √13 or…) where 𝑁 = 8. In other cases, Ω 𝑁 includes sites multiple distances from the unoccupied site, e.g., 𝑑 = {1,√2}, where 𝑁 = 8. Kinetic Monte Carlo (KMC) simulation reveals that these models exhibit a nonequilibrium discontinuous phase transition between high- and low-density states below a critical point, ɛ < ɛ c , with generic two-phase coexistence (2PC) at least for smaller 𝑁. With some exceptions, there is an approach toward mean-field behavior with increasing 𝑁 (so the regime of generic 2PC shrinks, and ɛ c approaches the mean-field value of 1/27). Additional insight into trends is provided by analysis of the exact master equations for the models via hierarchical truncation. These truncations utilize suitably tailored pair approximations which reflect the dominant nonequilibrium spatial correlations. These correlations in turn are shown to reflect the details of the autocatalytic particle creation process. For spatially heterogeneous states, the truncations produce coupled sets of lattice differential equations (LDE) which can describe orientation-dependent propagation of an interface between high- and low-density steady states for ɛ < ɛ c . Pair approximation values of 𝑝 = 𝑝 eq where the interface is stationary, and its orientation-dependence, are in semiquantitative agreement with KMC results. In conclusion, this comparison accounts for propagation failure in the LDE which complicates interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Sylvester-preconditioned adaptive-rank implicit time integrators for advection-diffusion equations with variable coefficients

Here, we consider the adaptive-rank integration of multi-dimensional time-dependent advection-diffusion partial differential equations (PDEs) with variable coefficients. We employ a standard finite-difference method for spatial discretization coupled with high-order diagonally implicit Runge-Kutta temporal schemes. The discrete equation is a generalized Sylvester equation (GSE), which we solve with a projection-based adaptive-rank algorithm structured around two key strategies: (i) constructing dimension-wise subspaces using a novel atypical extended Krylov strategy, and (ii) efficiently solving the basis coefficient matrix with a preconditioned GMRES solver. The low-rank decomposition is performed in 2D using SVD and with high-order SVD (HOSVD) in 3D to represent the tensor in a compressed Tucker format. For d-dimensional problems (here, d = 2 or 3), the computational complexity and memory storage of the approach are found numerically to scale as and $\mathscr{O}(Nr^2) + \mathscr{O} (r^{d+1})$ and $\mathscr{O}(Nr) + \mathscr{O} (r^{d})$, respectively, with the one-dimensional resolution and the maximal rank during the Krylov iteration (which we find to be largely independent of on our numerical examples). We present numerical examples that illustrate the advertised properties of the algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Birefringent Color Filter by Layered Metal‐Organic Chalcogenides: In‐Plane Anisotropy and Odd/Even Effect

Anisotropic 2D materials are gaining interest recently as building blocks for angular‐dependent optical/electrical devices. However, the fundamental understanding of their structure‐property‐relationship is limited, which hinders further modulation of their unique characteristics via structure tailoring. Here the in‐plane structural anisotropy and the tunable optical/electrical properties of a series of radiation‐sensitive (X‐ray, e‐beam) metal‐organic chalcogenide (MOC) single crystals are comprehensively revealed with ligands of variable length/parity. Their monoclinic crystallography is determined at atomic resolution by a simple method that couples X‐ray/electron diffraction with first‐principles calculations. The in‐plane inorganic backbone of the MOCs exhibits a strong lattice anisotropy with odd/even alternations, which originates from that of the out‐of‐plane organic motifs via organic/inorganic accommodation. Such structural anisotropy is implied mechanically by the preferred orientation of crystal cleavage. It triggers a maximum ≈8 × distinction of in‐plane electrical conductivity of the semiconducting MOCs, plus a distinct birefringence (maximum Δn ≈ 0.03) with a dispersive orientation of dielectric axes, which rotate up to 25.7° from UV to visible‐light regime, inspiring an emerging pathway for color filtering via single crystal rotation. Such in‐plane optical characteristics also exhibit odd/even alternation and can be flexibly tuned by the designable out‐of‐plane ligands.

birefringence↗

DOE OSTI2025

Single Crystals of Vanadium Oxides as a Lens for Understanding Structural and Electronic Phase Transformations, Ion Transport, Chemo-Mechanical Coupling, and Electrothermal Neuronal Emulation

Vanadium oxides cystallize in a diverse array of structures and compositions arising from the redox versatility of vanadium, variable covalency of V−O bonds, and myriad coordination geometries. Their open frameworks present abundant interstitial sites that enable insertion of guest-ions. In such compounds, V3d electron and spin localization and disorder couple strongly to structural preferences. The rich structural diversity manifests as a “rugged” free energy landscape with multiple interconvertible polymorphs. Such a landscape sets up structural, electronic, and magnetic transitions that underpin the promise of these materials as ion-insertion battery electrodes; compact primitives for brain-inspired computing, and heterogeneous catalysts. Here, we examine the structural and compositional diversity, electronic instabilities, defect dynamics, structure transformations, mechanical properties, and surface structure of vanadium oxides using single crystals as a distinctive lens. Single crystals enable the measurement of structure−function correlations without the ensemble and orientational averaging inevitable in polycrystalline materials. Their well-defined surfaces further enable examination of facet-dependent reactivity toward molecular adsorbates, ion fluxes, and lattice (mis)matched solids. We provide a comprehensive account of vanadium-oxide single-crystal studies, from delineation of common structural motifs to single-crystal growth techniques, topochemical modification strategies, mechanisms underpinning electronic instabilities, and implementation as electrothermal neurons and battery electrode materials.

Ponis, John [Texas A&M University, College Station↗

NASA NTRS2010

Physical Invariants of Intelligence

A program of research is dedicated to development of a mathematical formalism that could provide, among other things, means by which living systems could be distinguished from non-living ones. A major issue that arises in this research is the following question: What invariants of mathematical models of the physics of systems are (1) characteristic of the behaviors of intelligent living systems and (2) do not depend on specific features of material compositions heretofore considered to be characteristic of life? This research at earlier stages has been reported, albeit from different perspectives, in numerous previous NASA Tech Briefs articles. To recapitulate: One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Mathematical models of motor dynamics are used to simulate the observable physical behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. At the time of reporting the information for this article, the focus of this research was upon the following aspects of the formalism: Intelligence is considered to be a means by which a living system preserves itself and improves its ability to survive and is further considered to manifest itself in feedback from the mental dynamics to the motor dynamics. Because of the feedback from the mental dynamics, the motor dynamics attains quantum-like properties: The trajectory of the physical aspect of the system in the space of dynamical variables splits into a family of different trajectories, and each of those trajectories can be chosen with a probability prescribed by the mental dynamics. From a slightly different perspective, the mechanism of decision-making is feedback from the mental dynamics to the motor dynamics, and this mechanism provides a quantum-like collapse of a random motion into an appropriate deterministic state, such that entropy undergoes a pronounced decrease. The existence of this mechanism is considered to be an invariant of intelligent behavior of living systems, regardless of the origins and material compositions of the systems.

Zak, Michail↗

DOE OSTI2025

Climatic controls on erosional efficiency vary with lithology across the Himalaya

Although climate can strongly influence erosional efficiency (i.e., erosion rate for a given topography), demonstrating its impact in tectonically active areas has been challenging due to other confounding controlling factors, such as lithology. Here, we show that 10 Be-derived erosion rates and efficiencies in the Himalayan orogen exhibit distinct relationships with climatic factors depending on lithology. We compile 173 10 Be-derived, basin-averaged erosion rates across the orogen, including 12 newly measured rates from the Dibang and Lohit valleys in the easternmost Himalaya, regions characterized by high precipitation magnitudes and variability. We group basins based on lithologies separated by orogen-scale thrust faults and quantify erosional efficiency coefficients based on the relationships between erosion rates and topographic metrics. Our results show that erosion rates and erosional efficiency from sedimentary and metasedimentary rocks along the Himalayan range front display a positive, nonlinear correlation with climatic factors, such as the number of extreme rainfall events and mean annual precipitation rates. In contrast, erosion rates from crystalline lithologies in the hanging wall of the Main Central thrust show a strong correlation with fluvial topography, whereas erosional efficiency shows no statistically significant correlation with climatic factors. Rapid erosion rates and high erosional efficiencies in the eastern Himalayan range front are likely driven by extreme precipitation on tectonically active, steep slopes composed of mechanically weak metasedimentary rocks. Our findings highlight the importance of the interplay between controlling factors, which include tectonics, lithology, and climate, that drive surface erosion and influence the topographic evolution of orogenic systems.

Channel steepness↗

DOE OSTI2026

Dynamics and observational signatures of core-collapse supernovae with central engines: hydrodynamics simulations with Monte Carlo post-processing

A long-lived central engine embedded in expanding supernova ejecta can alter the dynamics and observational signatures of the event, producing an unusually luminous, energetic, and/or rapidly evolving transient. We use 2D hydrodynamics simulations to study the effect of a central energy source, varying the amount, rate, and isotropy of the energy deposition. We post-process the results with a time-dependent Monte Carlo radiation transport code to extract observational signatures. The engine excavates a bubble at the centre of the ejecta, which becomes Rayleigh–Taylor unstable. Sufficiently powerful engines are able to break through the edge of the bubble and accelerate, shred, and compositionally mix the entire ejecta. The breakout of the engine-driven wind occurs at distinct rupture points, and the outflowing high-velocity gas may eventually give rise to radio emission. The dynamical impact of the engine leads to faster rising optical light curves, with photon escape facilitated by the faster expansion of the ejecta and the opening of low-density channels. For models with strong engines, the spectra are initially hot and featureless, but later evolve to resemble those of broad-line Ic supernovae. Under certain conditions, line emission from ionized, low-velocity material near the centre of the ejecta may be able to escape and produce narrow emission similar to that seen in interacting supernovae. We discuss how variability in the engine energy reservoir and injection rate could give rise to a heterogeneous set of events spanning multiple observational classes, including the fast blue optical transients, broad-line Ic supernovae, and superluminous supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

From disorganized data to emergent dynamic models: Questionnaires to partial differential equations

Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate the data-driven derivation of parameter dependent, evolutionary partial differential equation (PDE) models capable of generating the data. This tensor type of data is reminiscent of shuffled (multidimensional) puzzle tiles. The independent variables for the evolution equations (their “space” and “time”) as well as their effective parameters are all emergent , i.e. determined in a data-driven way from our disorganized observations of behavior in them. We use a diffusion map based questionnaire approach to build a smooth parametrization of our emergent space/time/parameter space for the data. This approach iteratively processes the data by successively observing them on the “space,” the “time” and the “parameter” axes of a tensor. Once the data become organized, we use machine learning (here, neural networks) to approximate the operators governing the evolution equations in this emergent space. Our illustrative examples are based (i) on a simple advection–diffusion model; (ii) on a previously developed vertex-plus-signaling model of Drosophila embryonic development; and (iii) on two complex dynamic network models (one neuronal and one coupled oscillator model) for which no obvious smooth embedding geometry is known a priori. This allows us to discuss features of the process like symmetry breaking, translational invariance, and autonomousness of the emergent PDE model, as well as its interpretability.

generative models↗

NASA NTRS1993

Measurements of dimethyl sulfide and H2S over the western North Atlantic and the tropical Atlantic

Airborne measurements of DMS and H2S were made off the east coast of the United States and over the tropical Atlantic off Brazil. Samples were collected through a fluorinated ethylene propylene Teflon inlet manifold. Dimethyl sulfide (DMS) was preconcentrated onto gold wool and analyzed by gas chromatography/flame photometric detection. H2S was collected on AgNO3-impregnated filters and determined by fluorescence quenching. Use of a new scrubber material (cotton) to remove negative interference on DMS measurements was investigated. Comparison with a Na2CO3/Anakrom scrubber gave good overall agreement. Only under extreme conditions, e.g., on flight 9 (continental air mass, low humidity, high O3, and low DMS values) did Na2CO3 show noticeable loss of DMS compared to cotton. On most flights, especially in marine air masses with high humidity and relatively low O3, the results from both scrubbers agreed well with each other and with other instruments used during the intercalibration. Off the U.S. East Coast, DMS levels showed strong dependence on air mass origin with high values (up to 83 ppt) in marine tropical air masses and low values (10-20 ppt) in continental and polar air. Over the tropical Atlantic, DMS ranged over 20-100 ppt in the mixed layer. Nighttime values were a factor of 1.6-2.3 higher than daytime levels. DMS decreased with altitude to less than 1 ppt at 4000 m. H2S in the mixed layer off the U.S. East Coast ranged from 10 to 200 ppt. Significant influence from terrestrial and pollution sources was evident. H2S in air masses originating over the eastern seaboard was much higher than in continental polar air or over the remote tropical continents. In contrast, over the tropical Atlantic, concentrations were very low (5-10 ppt), typical of truly marine air. Night/day ratios were about 1.4. No significant geographical variability was seen in H2S levels over the tropical Atlantic. The correlation of atmospheric Rn-222 and H2S was significant, with both being higher off the U.S. East Coast than over the tropical Atlantic.

Andreae, T. W.↗

DOE OSTI2025

Joint Modeling of Quasar Variability and Accretion Disk Reprocessing Using Latent Stochastic Differential Equations

Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing, trained with supervised learning on simulated LSST-like 10 yr quasar light curves. We encode the light curves using a transformer encoder, and the driving variability is reconstructed using latent stochastic differential equations, a physically motivated generative deep learning method that can model continuous-time stochastic dynamics. By embedding the physical processes of the driving signal and reprocessing into our network, we achieve a model that is more robust and interpretable. We demonstrate that our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wave bands, even for out-of-distribution driving signals. Our approach provides a powerful framework that can be adapted to solve other inverse problems in multivariate time series.

Fagin, Joshua [City Univ. of New York (CUNY), NY (↗

DOE OSTI2026

KRAS4a and KRAS4b show distinct lipid-dependent regulation of RAS-RAF membrane dynamics

KRAS4a and KRAS4b are important regulators of signaling, and their interactions with the plasma membrane are dynamic and influenced by lipid composition. KRAS 4a and 4b have nearly identical globular domains but differ in their membrane-associated hyper variable region (HVR). The functional distinctions between these isoforms remain unclear, particularly with regards to their dependence on specific lipids and the membrane environment. Previous work showed that the membrane orientation of KRAS4b affects its ability to bind to RAF kinase RBDCRD and that the KRAS–RBDCRD complex adopts different poses on the membrane as well as influences the size and composition of the lipid environment. To model differences between KRAS 4a and 4b protein–lipid interactions, we extended the Multiscale Machine-Learned Modeling Infrastructure (MuMMI) to incorporate continuum simulations in the grand canonical ensemble, enabling sampling across macroscopic, coarse-grained, and all-atom resolutions. Using this framework, we systematically altered PIP2 concentrations, KRAS 4a versus 4b, and RAF RBDCRD complexation to assess impacts on membrane–protein interactions and dynamics. Our results reveal that reducing PIP2 shifts and broadens the membrane orientational preference of both KRAS 4b and 4a, with stronger effects on 4b HVR localization versus 4a. We demonstrate that with depletion of the strong negatively charged PIP2 lipid, the less charged phosphatidylserine replaces PIP2. Our findings highlight similarities and distinctions in the dynamics and lipid dependency of KRAS isoforms and suggest that ordering of the local lipid composition by HVRs is a shared property and key modulator of RAS-mediated signaling at the plasma membrane.

Biological and medical sciences↗