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DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Assessing shellfish water exposure to fecal bacteria pollution in Salish Sea: three-dimensional modeling and implications for monitoring

Fecal bacteria (FB) contamination poses significant risks to shellfish safety and management in coastal and estuarine waters. Despite extensive pollution identification and correction efforts, FB contamination in shellfish-growing areas persists in the Salish Sea, highlighting the need to identify overlooked sources and better understand FB transport from riverine and shoreline inputs to shellfish beds. To address this, a high-resolution three-dimensional hydrodynamic model coupled with FB kinetics was developed and applied to a case study site in Salish Sea—Portage Bay—to simulate freshwater plume circulation, flushing dynamics, and bacterial transport. Daily FB loading from the major freshwater inflow—Nooksack River was generated by both linear interpolation and integrating a machine learning approach (XGBoost), trained on historical hydrological and meteorological data. The model successfully reproduced both the magnitude and seasonal variation of FB concentrations in Portage Bay for the year of 2021, demonstrating that simplified FB kinetics with first-order decay due to mortality was effective in this dynamic coastal environment with short flushing time. Model results identified the Nooksack River as the dominant far-field FB source, while scenario simulations showed that near-field coastal stormwater outfalls elevated local FB levels following rainfall, particularly under low-flow conditions. The XGBoost prediction provided comparable or superior accuracy to linear interpolation, particularly during periods of missing observational data, by capturing short-term variability and event-driven loading more effectively. Integrating data-driven riverine FB inputs with mechanistic coastal numerical modeling provides a robust framework for operational forecasting of shellfish bed exposure risk and supports adaptive monitoring and management of shellfish growing areas in the Salish Sea and similar coastal systems.

Salish Sea↗

DOE OSTI2024

Geometry of Non-Diffusive Tracer Transport in Gridded Atmospheric Models

A first-order linear and numerically non-diffusive Eulerian transport algorithm, minVAR, was recently developed for preservation of correlations between interrelated tracers during advective transport. The present study extends this work by: (1) providing further investigation of several interesting geometric constructions found in contours of constant minVAR, short for minimum variance, through extension to three coordinate dimensions. These contours capture point-by-point representations of thousands of individual atmospheric aerosol and/or cloud particles as they evolve and are rendered on Eulerian grids at a level of sub-grid resolution limited only by numerical precision; and (2) exploration of geometric similarities between the Arakawa C-grid, used to obtain interpolated values of the wind field at grid scale and minVAR. In particular, we consider interpolation of the u and v horizontal components of wind velocity from grid to sub-grid scales. The last results are motivated by recent applications of the Weather Research and Forecasting (WRF) model applied in the coastal Houston region, where the recent TRacking Aerosol Convection Interactions ExpeRiment (TRACER) field campaign was organized. A unique and fully consistent mapping is obtained between particles moving along meteorological wind trajectories and the non-diffusive, non-dispersive representation of such trajectories on an Eulerian grid.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A Scalable Gaussian Process Approach to Shear Mapping with MuyGPs

Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in turn provides us with information about the nature of dark energy. Conventional methods generate shear maps from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser–Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations—an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly scaling shear map construction alternative using a scalable Gaussian process prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest neighbors and fits hyperparameters using batched leave-one-out cross-validation. This work is the first step toward a full, scalable mass mapping method. We work in a simplified regime where we validate our method by interpolating and analyzing maps given noisy point-estimate data from all three shear fields, taken from a suite of N -body ray-tracing simulations. We also show that we can perform these operations at the scale of billions of galaxies on high-performance computing platforms.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware

We implement a quantum generalization of a neural network on trapped-ion and IBM superconducting quantum computers to classify MNIST images, a common benchmark in computer vision. The network feedforward involves qubit rotations whose angles depend on the results of measurements in the previous layer. The network is trained via simulation, but inference is performed experimentally on quantum hardware. The classical-to-quantum correspondence is controlled by an interpolation parameter, $a$, which is zero in the classical limit. Increasing $a$ introduces quantum uncertainty into the measurements, which is shown to improve network performance at moderate values of the interpolation parameter. We then focus on particular images that fail to be classified by a classical neural network but are detected correctly in the quantum network. For such borderline cases, we observe strong deviations from the simulated behavior. We attribute this to physical noise, which causes the output to fluctuate between nearby minima of the classification energy landscape. Such strong sensitivity to physical noise is absent for clear images. We further benchmark physical noise by inserting additional single-qubit and two-qubit gate pairs into the neural network circuits. Our work provides a springboard toward more complex quantum neural networks on current devices: while the approach is rooted in standard classical machine learning, scaling up such networks may prove classically non-simulable and could offer a route to near-term quantum advantage.

FOS: Physical sciences↗

DOE OSTI2025

The algebraic structure of gravitational scrambling

We introduce a new algebraic framework to describe gravitational scrambling, including the semiclassical limit of any out-of-time-order correlation function that is built out of operator insertions separated by approximately the scrambling time. In two dimensions, the scrambling algebra, which we call a modular-twisted product, is defined in terms of two copies of the Leutheusser-Liu half-sided modular inclusion of von Neumann algebras; these describe early- and late-time operators respectively. In limits where the separation between insertions is taken to be either significantly greater or smaller than the scrambling time, the modular-twisted product reduces, respectively, to free- and tensor-product algebras that were previously studied in [arXiv:2209.10454]. In a sense, the modular-twisted product interpolates between these two products. Including the Hamiltonian in the scrambling algebra leads to a Type II$_\infty$ von Neumann algebra with finite renormalized entropies that interpolate between single-QES and multi-QES phases. We also describe how to generalize the modular-twisted product algebra to higher dimensions, including spatially localized boundary excitations.

FOS: Physical sciences↗

NASA NTRS1967

Relationship Between Magnitude of Applied Spin Recovery Moment and Ensuing Number of Recovery Turns

An analytical study has been made to investigate the relationship between the magnitude of the applied spin recovery moment and the ensuing number of turns made during recovery from a developed spin with a view toward determining how to interpolate or extrapolate spin recovery results with regard to determining the amount of control required for a satisfactory recovery. Five configurations were used which are considered to be representative of modern airplanes: a delta-wing fighter, a stub-wing research vehicle, a boostglide configuration, a supersonic trainer, and a sweptback-wing fighter. The results obtained indicate that there is a direct relationship between the magnitude of the applied spin recovery moments and the ensuing number of recovery turns made and that this relationship can be expressed in either simple multiplicative or exponential form. Either type of relationship was adequate for interpolating or extrapolating to predict turns required for recovery with satisfactory accuracy for configurations having relatively steady recovery motions. Any two recoveries from the same developed spin condition can be used as a basis for the predicted results provided these recoveries are obtained with the same ratio of recovery control deflections. No such predictive method can be expected to give satisfactory results for oscillatory recoveries.

SPIN DYNAMICS↗

NASA NTRS1971

Determination of stratospheric temperature and height gradients from nimbus 3 radiation data

To improve the specification of stratospheric horizontal temperature and geopotential height fields from satellite radiation data, needed for high flying aircraft, a technique was derived to estimate data between satellite tracks using interpolated IRIS 15-micron data from Nimbus III. The interpolation is based on the observed gradients of the MRIR 15-micron radiances between subsatellite tracks. The technique was verified with radiosonde data taken within 6 hours of the satellite data. The sample varied from 1126 pairs at low levels to 383 pairs at 10 mb using northern hemisphere data for June 15 to July 20, 1969. The data were separated into five latitude bands. The Rms temperature differences were generally from 2 to 5 C for all levels above 300 mb. From 500 to 300 mb RMS differences vary from 4 to 9C except at high latitudes which show values near 3C. The RMS differences between radiosonde heights and those calculated hydrostatically from the surface were from 30 to 280 meters increasing from the surface to 10 mb. Integration starting at 100 mb reduced the RMS difference in the stratosphere to 20 to 120 meters from 70 to 10 mb. From a comparison with actual operational maps at 50 and 10 mb, it appears the techniques developed produce analyses in general agreement with those from radiosonde data. In addition, they are able to indicate details over areas of sparse data not shown by conventional techniques.

Nicholas, G. W.↗

NASA NTRS1972

A calibration model for a stellar photometer using a SEC vidicon.

Description of a SEC vidicon response model that was used to calculate intensities of stars in the ultraviolet. The tube was used only as a stellar filter photometer. The model proposed is applicable for point sources. Experiments with both curve- or surface-fitting techniques and with extrapolation-interpolation procedures were conducted. The curve-fitting techniques were not successful, and the target gain was calculated with the aid of interpolation techniques.

Deutschman, W. A.↗

NASA NTRS1971

Isoelectronic wavelength calculations for argon spectra /Research note/.

A recent comprehensive set of isoelectronic calculations based on the data of Kelly (1968) has yielded two argon wavelengths that correspond with two of the unidentified wavelengths reported by Connerade et al. (1971) and a third wavelength which supports an uncertain identification. The observed and the interpolated wavelengths are presented in a table together with their identifications, and information concerning the interpolations.

Williams, M. D.↗

NASA NTRS1972

Applications of remote sensing to stream discharge predictions

A feasibility study has been initiated on the use of remote earth observations for augmenting stream discharge prediction for the design and/or operation of major reservoir systems, pumping systems and irrigation systems. The near-term objectives are the interpolation of sparsely instrumented precipitation surveillance networks and the direct measurement of water loss by evaporation. The first steps of the study covered a survey of existing reservoir systems, stream discharge prediction methods, gage networks and the development of a self-adaptive variation of the Kentucky Watershed model, SNOPSET, that includes snowmelt. As a result of these studies, a special three channel scanner is being built for a small aircraft, which should provide snow, temperature and water vapor maps for the spatial and temporal interpolation of stream gages.

Krause, F. R.↗

NASA NTRS1973

Approximate thermochemical tables for some C-H and C-H-O species

Approximate thermochemical tables are presented for some C-H and C-H-O species and for some ionized species, supplementing the JANAF Thermochemical Tables for application to finite-chemical-kinetics calculations. The approximate tables were prepared by interpolation and extrapolation of limited available data, especially by interpolations over chemical families of species. Original estimations have been smoothed by use of a modification for the CDC-6600 computer of the Lewis Research Center PACl Program which was originally prepared for the IBM-7094 computer Summary graphs for various families show reasonably consistent curvefit values, anchored by properties of existing species in the JANAF tables.

Bahn, G. S.↗

NASA NTRS1972

Advanced study of video signal processing in low signal to noise environments

The frame to frame correlation properties of the video process are utilized to reduce the mean squared error of the demodulated video where zero mean noise is a factor. An interpolative estimator is used for continuous estimation with the output process delayed in time by one frame. Theoretical development shows that for the model herein developed reduction of the mean squared error by 1.0 to 4.0 db possible for parameter ranges of interest. Interpolative estimation using inter-frame correlation properties of a video process is then applied to the Apollo 17 parameters to yield a model for application on that mission.

Carden, F.↗

NASA NTRS1973

An automated procedure for computing flutter eigenvalues.

A new, fast and economical automated procedure for implementing the traditional V-g method of flutter solution is described. The procedure requires as input the generalized aerodynamic forces for a range of reduced frequencies obtained from an aerodynamic program. These aerodynamic forces are interpolated with respect to reduced frequency using a newly developed, partially tabulated cubic spline that is both fast in execution and economical in storage. The flutter solution is then obtained using an eigenvalue routine that has been developed to take advantage of the parametric nature of the V-g type of solution. Furthermore, the routine takes care of the fundamental and troublesome problem of properly sorting the output eigenvalues. By solving the root-sorting problem, the interpolation for flutter crossings and automatic plotting are accomplished efficiently. The computational techniques used in this new program are described and some sample results are given.

Desmarais, R. N.↗

NASA NTRS1972

Calibration of platinum resistance thermometers.

Results of five years experience in calibrating about 1000 commercial platinum resistance thermometers (PRT) are reported. These PRT were relatively small and rugged, with ice-point resistances from 200 to 5000 ohms. Calibrations normalized in terms of resistance-difference ratios (Cragoe Z function) were found to be remarkably uniform for five of six different types of PRT tested, and to agree very closely with normalized calibrations of the primary reference standard type PRT. The Z function normalization cancels residual resistances which are not temperature dependent and simplifies interpolation between calibration points when the quality of a given type of PRT has been established in terms of uniform values of the Z function. Measurements at five or six well spaced base-point temperatures with Z interpolation will suffice to calibrate a PRT accurately from 4 to 900 K.

Sinclair, D. H.↗

NASA NTRS1973

Determination of stratospheric temperature and height gradients from Nimbus 3 radiation data

To improve the specification of stratospheric, horizontal, temperature and geopotential height fields needed for high-flying aircraft, we derived a technique to estimate data between satellite tracks using interpolated infrared interferometer spectrometer 15-micron radiation data from Nimbus 3. The interpolation is based on the observed gradients of the medium resolution infrared 15-micron radiances between subsatellite tracks. The technique was verified with radiosonde data taken within 6 hr of the satellite data. Comparison indicates that the technique developed here produces analyses that are in general agreement with those from radiosonde data. In addition, this technique provides details over areas of sparse data not shown by conventional techniques.

Nicholas, G. W.↗

NASA NTRS1974

Method of Characteristics Calculations and Computer Code for Materials with Arbitrary Equations of State and Using Orthogonal Polynomial Least Square Surface Fits

A numerical scheme using the method of characteristics to calculate the flow properties and pressures behind decaying shock waves for materials under hypervelocity impact is developed. Time-consuming double interpolation subroutines are replaced by a technique based on orthogonal polynomial least square surface fits. Typical calculated results are given and compared with the double interpolation results. The complete computer program is included.

Chang, T. S.↗

NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 3

The following subjects were covered: (1) ASM80 manual, (2) signal preprocessing as an aid to on-line EKG analysis, and (3) high speed evaluation of magnetic tape recordings of electrocardiograms. A description of the ASM80 symbolic assembly program for the INTEL 8080 microprocessor and a user's manual were presented. The capability of three redundancy reduction algorithms to produce adequate representations of electrocardiographic data was examined. A hardware device was constructed which carried out zero order interpolation on a signal. Examination of the zero order interpolators reconstructed signal indicated that this representation was adequate for analysis of rhythm. A system to analyze magnetic tapes of electrocardiograms recorded over 24 hour intervals was designed. The recordings are sampled 200 times per second using a Nova computer and a special interface system. This system was tested on several recordings of clinical data, containing over 75 premature ventricular contractions, each one of which was flagged.

Mark, R. G.↗