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DOE OSTI2015

A MACHINE-LEARNING METHOD TO INFER FUNDAMENTAL STELLAR PARAMETERS FROM PHOTOMETRIC LIGHT CURVES

A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are >10{sup 9} photometrically cataloged sources, yet modern spectroscopic surveys are limited to ∼few× 10{sup 6} targets. As we approach the Large Synoptic Survey Telescope era, new algorithmic solutions are required to cope with the data deluge. Here we report the development of a machine-learning framework capable of inferring fundamental stellar parameters (T {sub eff}, log g, and [Fe/H]) using photometric-brightness variations and color alone. A training set is constructed from a systematic spectroscopic survey of variables with Hectospec/Multi-Mirror Telescope. In sum, the training set includes ∼9000 spectra, for which stellar parameters are measured using the SEGUE Stellar Parameters Pipeline (SSPP). We employed the random forest algorithm to perform a non-parametric regression that predicts T {sub eff}, log g, and [Fe/H] from photometric time-domain observations. Our final optimized model produces a cross-validated rms error (RMSE) of 165 K, 0.39 dex, and 0.33 dex for T {sub eff}, log g, and [Fe/H], respectively. Examining the subset of sources for which the SSPP measurements are most reliable, the RMSE reduces to 125 K, 0.37 dex, and 0.27 dex, respectively, comparable to what is achievable via low-resolution spectroscopy. For variable stars this represents a ≈12%-20% improvement in RMSE relative to models trained with single-epoch photometric colors. As an application of our method, we estimate stellar parameters for ∼54,000 known variables. We argue that this method may convert photometric time-domain surveys into pseudo-spectrographic engines, enabling the construction of extremely detailed maps of the Milky Way, its structure, and history.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2013

The Global Land-Ocean Temperature Index in Relation to Sunspot Number, the Atlantic Multidecadal Oscillation Index, the Mauna Loa Atmospheric Concentration of CO2, and Anthropogenic Carbon Emissions

Global warming/climate change has been a subject of scientific interest since the early 19th century. In particular, increases in the atmospheric concentration of carbon dioxide (CO2) have long been thought to account for Earth's increased warming, although the lack of a dependable set of observational data was apparent as late as the mid 1950s. However, beginning in the late 1950s, being associated with the International Geophysical Year, the opportunity arose to begin accurate continuous monitoring of the Earth's atmospheric concentration of CO2. Consequently, it is now well established that the atmospheric concentration of CO2, while varying seasonally within any particular year, has steadily increased over time. Associated with this rising trend in the atmospheric concentration of CO2 is a rising trend in the surface-air and sea-surface temperatures (SSTs). This Technical Publication (TP) examines the statistical relationships between 10-year moving averages (10-yma) of the Global Land-Ocean Temperature Index (GLOTI), sunspot number (SSN), the Atlantic Multidecadal Oscillation (AMO) index, and the Mauna Loa CO2 (MLCO2) index for the common interval 1964-2006, where the 10-yma values are used to indicate trends in the data. Scatter plots using the 10-yma values between GLOTI and each of the other parameters are determined, both as single-variate and multivariate fits. Scatter plots are also determined for MLCO2 using single-variate and bivariate (BV) fits, based on the GLOTI alone and the GLOTI in combination with the AMO index. On the basis of the inferred preferential fits for MLCO2, estimates for MLCO2 are determined for the interval 1885-1964, thereby yielding an estimate of the preindustrial level of atmospheric concentration of CO2. Lastly, 10-yma values of MLCO2 are compared against 10-yma estimates of the total carbon emissions (TCE) to determine the likelihood that manmade sources of carbon emissions are indeed responsible for the recent warming now being experienced. (Parametric values used in this TP are those available prior to the end of 2012.)

Wilson, Robert M.↗

DOE OSTI2021

Dynamic flow stress of pure polycrystalline aluminum: Pressure-shear plate impact experiments and extension of dislocation-based modeling to large strains

The dynamic thermo-mechanical behavior of pure aluminum has attracted renewed interest lately due to experimental observations of an anomalous increase in Hugoniot Elastic Limit (HEL) at incipient plasticity and elevated temperatures in polycrystalline pure metals. In context of current dislocation-mediated plasticity models for metals, this increase in dynamic strength is indicative of a transition in the rate controlling mechanism for dislocation glide from being thermally assisted to phonon-drag restricted due to increase in phonon viscosity at elevated temperatures. Though these studies have helped to shed light on these important mechanisms operative in FCC metals at incipient plasticity, the extent to which they contribute to flow stress, particularly at larger strains, remains unclear. Here, we address these questions through a combined experimental and modeling effort focused on investigating the evolution of dynamic flow stress in polycrystalline aluminum using experimental data gathered from a series of combined pressure-and-shear plate impact (PSPI) experiments designed to reveal the flow stress of pure aluminum at strain rates ~ 10 5 /s, plastic strains of up to 40% and temperatures ranging from room to 866 K. In all cases, the flow stress of aluminum, as inferred from the measured transverse particle velocity histories at the free surface of an elastic tungsten carbide target plate, reveals saturation with increasing plastic strains at stress levels that decrease with increasing test temperatures. Numerical simulations are performed to correlate the experimentally observed temperature and strain rate dependence of flow stress at small and large plastic strains using the Austin-McDowell dislocation-mediated plasticity model parametrized to normal plate impact experiments conducted in an earlier study by Zaretsky and Kanel (2012). Extensions to the model are made to better represent dynamic behavior of pure aluminum at larger plastic strains as observed in elevated temperature split Hopkinson Pressure bar (SPHB) experiments of Samanta (1971) and Lindholm and Yeakly (1965), and the combined pressure-and-shear plate-impact experiments conducted in the present study. The main theoretical extension to the Austin-McDowell model made in this paper is the introduction of a new rate- and temperature- dependent dynamic recovery function, which can potentially allow for an effective reduction in the rate of accumulation of dislocations at large plastic strains. The numerical predictions of the revised and re-calibrated plasticity model are brought into agreement with the experimental observations, correlating sufficiently well with dynamic yield stress at incipient plasticity and the flow stress levels at larger plastic strains, plastic strain rates in the range 10 3 – 10 6 /s, and elevated temperatures up to near melt. The model, in concert with the experimental measurements, suggests that at incipient plasticity the rate governing mechanism for plastic flow is phonon-drag restricted dislocation glide, whereas, at higher magnitudes of plastic strain, it transitions to stress-assisted thermally activated glide. The transition between these two rate governing mechanisms is controlled by the evolution of dislocations throughout the deformation process.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Fabric-enriched continuum breakage mechanics (F-CBM )

A fabric-enriched continuum breakage mechanics (F-CBM) framework is developed to examine the relation between elastic and inelastic anisotropy in granular materials subjected to high pressure. For this purpose, emphasis is given to the influence of the anisotropic fabric on the plastic cap regime – that is, a macroscopic signature of the inelasticity of granular materials widely dependent on the particle crushability. Anisotropic behaviour prior to yielding is introduced through a symmetric second-order fabric tensor embedded in the expression of the elastic energy potential. It is shown that, thanks to its energy-based formulation, the F-CBM framework provides a platform to predict the rotation and distortion of the yield cap of granular materials as an outcome of anisotropic strain energy storage prior to grain crushing. Parametric analyses indicate that both the degree of anisotropy and the orientation of the fabric have an impact on the energy release resulting from grain crushing and contribute to the resulting stress–strain behaviour. It is shown that, despite the use of very few parameters, the proposed framework can accurately predict the anisotropic yielding and inelastic stress–strain response solely on the basis of the directional properties inferred from measurements of elastic anisotropy.

Engineering↗

DOE OSTI2016

ON THE CONTRIBUTION OF FLUORESCENCE TO LYα HALOS AROUND STAR-FORMING GALAXIES

We quantify the contribution of Lyα fluorescence to observed spatially extended Lyα halos around Lyα emitters at redshift z = 3.1. The key physical quantities that describe the fluorescent signal include (i) the distribution of cold gas in the circumgalactic medium (CGM); we explore simple analytic models and fitting functions to recent hydrodynamical simulations; and (ii) local variations in the ionizing background due to ionizing sources that cluster around the central galaxy. We account for clustering by boosting the observationally inferred volumetric production rate of ionizing photons, ϵ{sub LyC}, by a factor of 1+ξ{sub LyC}(r), in which ξ{sub LyC}(r) quantifies the clustering of ionizing sources around the central galaxy. We compute ξ{sub LyC}(r) by assigning an “effective” bias parameter to the ionizing sources. This novel approach allows us to quantify our ignorance of the population of ionizing sources in a simple parametrized form. We find a maximum enhancement in the local ionizing background in the range 50–200 at r ∼ 10 physical kpc. For spatially uncorrelated ionizing sources and fluorescing clouds we find that fluorescence can contribute up to ∼ 50%–60% of the observed spatially extended Lyα emission. We briefly discuss how future observations can shed light on the nature of Lyα halos around star-forming galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Transit timing variations for planets co-orbiting in the horseshoe regime

Although not yet detected, pairs of exoplanets in 1:1 mean motion resonance probably exist. Low eccentricity, near-planar orbits, which in the comoving frame follow horseshoe trajectories, are one of the possible stable configurations. Here we study transit timing variations (TTVs) produced by mutual gravitational interaction of planets in this orbital architecture, with the goal to develop methods that can be used to recognize this case in observational data. In particular, we use a semi-analytic model to derive parametric constraints that should facilitate data analysis. We show that characteristic traits of the TTVs can directly constrain the (1) ratio of planetary masses and (2) their total mass (divided by that of the central star) as a function of the minimum angular separation as seen from the star. In an ideal case, when transits of both planets are observed and well characterized, the minimum angular separation can also be inferred from the data. As a result, parameters derived from the observed transit timing series alone can directly provide both planetary masses scaled to the central star mass.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2008

Anticipating Cycle 24 Minimum and its Consequences: An Update

This Technical Publication updates estimates for cycle 24 minimum and discusses consequences associated with cycle 23 being a longer than average period cycle and cycle 24 having parametric minimum values smaller (or larger for the case of spotless days) than long term medians. Through December 2007, cycle 23 has persisted 140 mo from its 12-mo moving average (12-mma) minimum monthly mean sunspot number occurrence date (May 1996). Longer than average period cycles of the modern era (since cycle 12) have minimum-to-minimum periods of about 139.0+/-6.3 mo (the 90-percent prediction interval), inferring that cycle 24 s minimum monthly mean sunspot number should be expected before July 2008. The major consequence of this is that, unless cycle 24 is a statistical outlier (like cycle 21), its maximum amplitude (RM) likely will be smaller than previously forecast. If, however, in the course of its rise cycle 24 s 12-mma of the weighted mean latitude (L) of spot groups exceeds 24 deg, then one expects RM >131, and if its 12-mma of highest latitude (H) spot groups exceeds 38 deg, then one expects RM >127. High-latitude new cycle spot groups, while first reported in January 2008, have not, as yet, become the dominant form of spot groups. Minimum values in L and H were observed in mid 2007 and values are now slowly increasing, a precondition for the imminent onset of the new sunspot cycle.

Wilson, Robert M.↗

NASA NTRS1979

On the inference of properties of Saturn's Ring E from energetic charged particle observations

The paper demonstrates that information about Saturn's Ring E particle size is potentially obtainable from observations of Saturnian trapped radiation. It is shown that observations of the radial dependence of the intensities, energy spectra, electron-to-proton intensity ratio, and pitch angle distributions of energetic charged particles trapped outside of Ring A can potentially provide information (1) on the existence of Ring E, (2) on the effective size of the particulate matter therein, and (3) on the magnitude of the radial diffusion coefficient for energetic particles. A parametric study of these possibilities is specialized to the characteristics of the University of Iowa detectors on Pioneer 11 which was scheduled to make a close encounter with Saturn in 1979.

Thomsen, M. F.↗

DOE OSTI2016

SOLAR MODULATION OF THE LOCAL INTERSTELLAR SPECTRUM WITH VOYAGER 1 , AMS-02, PAMELA , AND BESS

In recent years, the increasing precision of direct cosmic rays measurements opened the door to high-sensitivity indirect searches of dark matter and to more accurate predictions for radiation doses received by astronauts and electronics in space. The key ingredients in the study of these phenomena are the knowledge of the local interstellar spectrum (LIS) of galactic cosmic rays and the understanding of how the solar modulation affects the LIS inside the heliosphere. Voyager 1 , AMS-02, PAMELA , and BESS measurements of proton and helium fluxes provide valuable information, allowing us to shed light on the shape of the LIS and the details of the solar modulation during solar cycles 22-24. A new parametrization of the LIS is presented, based on the latest data from Voyager 1 and AMS-02. Using the framework of the force-field approximation, the solar modulation parameter is extracted from the time-dependent fluxes measured by PAMELA and BESS . A modified version of the force-field approximation with a rigidity-dependent modulation parameter is introduced, yielding better fits than the force-field approximation. The results are compared with the modulation parameter inferred by neutron monitors.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

The abundance properties of nearby late-type galaxies. II. The relation between abundance distributions and surface brightness profiles

The relations between oxygen abundance and disk surface brightness (OH–SB relation) in the infrared W1 band are examined for nearby late-type galaxies. The oxygen abundances were presented in Paper I. The photometric characteristics of the disks are inferred here using photometric maps from the literature through bulge-disk decomposition. We find evidence that the OH–SB relation is not unique but depends on the galactocentric distance r (taken as a fraction of the optical radius R{sub 25}) and on the properties of a galaxy: the disk scale length h and the morphological T-type. We suggest a general, four-dimensional OH–SB relation with the values r, h, and T as parameters. The parametric OH–SB relation reproduces the observed data better than a simple, one-parameter relation; the deviations resulting when using our parametric relation are smaller by a factor of ∼1.4 than that of the simple relation. The influence of the parameters on the OH–SB relation varies with galactocentric distance. The influence of the T-type on the OH–SB relation is negligible at the centers of galaxies and increases with galactocentric distance. In contrast, the influence of the disk scale length on the OH–SB relation is at a maximum at the centers of galaxies and decreases with galactocentric distance, disappearing at the optical edges of galaxies. Two-dimensional relations can be used to reproduce the observed data at the optical edges of the disks and at the centers of the disks. The disk scale length should be used as a second parameter in the OH–SB relation at the center of the disk while the morphological T-type should be used as a second parameter in the relation at optical edge of the disk. The relations between oxygen abundance and disk surface brightness in the optical B and infrared K bands at the center of the disk and at optical edge of the disk are also considered. The general properties of the abundance–surface brightness relations are similar for the three considered bands B, K, and W1.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Equivalent Fundamental-Mode Source Simulations for Spherical Uranium and Plutonium Systems [Abstract]

The equivalent fundamental-mode source refers to a “source” which is identically distributed in space, energy, and angle as that of a fundamental-mode fission source distribution. It has previously been shown that the system fixed source multiplication ($M_{fs}$) relates to the effective multiplication factor ($\kappa_{eff}$) as $M_{fs} = \frac{g^*}{1-k_{eff}}$ The term $\mathcal{g}$* therefore relates the system source distribution to the system equivalent fundamental-mode source. As previously shown, the $\mathcal{g}$* term is approximately 1 for deeply subcritical systems and then diverges as the system multiplication increases. For a system with a point source located in the center of an assembly (such a sphere), $\mathcal{g}$* will be greater than 1; this happens because there is a higher probability of induced fission when all of the starter neutrons originate from the center of the sphere. For a uniform source, $\mathcal{g}$* is less than 1, but does not diverge from 1 as dramatically as seen by a point source. One reason that $\mathcal{g}$* is an important parameter is that it is used in measurement methods to infer reactor kinetics parameters ($β_{eff}$ being one example). This work will discuss multiple ways to simulate $\mathcal{g}$* using MCNP®6.2, which include use of traditional methods versus a single input file method that was recently published. A discussion related to methods to simulate $M_{fs}$ will be presented. Spherical systems of Highly Enriched Uranium (HEU) will be compared with previous works. In addition, results of plutonium including multiple reflector materials will be investigated. Simulated systems will include both parametric studies as well as configurations used in recent experiments performed at the National Criticality Experiments Research Center (NCERC). These studies will include subtleties associated with system geometry that have not been previously shown. Last, this work will investigate the relationship between $\mathcal{g}$* and reactor kinetics parameters (such as $β_{eff}$).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Multiprobe constraints on early and late time dark energy

We perform a multiprobe analysis combining cosmic microwave background (CMB) data from Planck and the Atacama Cosmology Telescope (ACT), ACT CMB lensing, and large-scale structure (LSS) measurements from the Dark Energy Spectroscopic Instrument (DESI), including DESI Legacy Imaging Survey (LS) galaxies and baryon acoustic oscillations (BAOs). We present the first 5×2 pt analysis of ACT DR6 lensing, DESI LS, and Planck Integrated Sachs-Wolfe (ISW). Within Λ⁢CDM, this yields 𝑆 8 =𝜎 8 ⁢(Ω 𝑚 /0.3) 0.5 =0.819 ±0.016, in good agreement with primary CMB inferences and provides a sound-horizon-free Hubble constant constraint of 𝐻 0 =70.0±4.4 km s −1 Mpc −1 . Then, combining with CMB primary and BAO, we reconfirm a CMB–BAO discrepancy in the Ω 𝑚 –$\frac{𝐷𝑣}{𝑟𝑑}$ plane, which is heightened when combining BAO with the 5 ×2 pt data vector. We explore two dark-energy extensions that may reconcile this: an early-time modification, early dark energy (EDE), and late-time dynamical dark energy (DDE) parametrized by 𝑤 0 ⁢𝑤 𝑎 . For CMB primary +BAO +5 ×2 pt, we find a 3.3⁢𝜎 preference for DDE over Λ⁢CDM, while EDE is modestly favored at 2.3⁢𝜎. The models address different shortcomings of Λ⁢CDM: DDE relaxes the neutrino mass bound (𝑀 𝜈 <0.17 eV vs <0.050 eV under Λ⁢CDM), making it compatible with neutrino oscillation measurements, while EDE raises the Hubble constant to 𝐻 0 =70.5±1.2 km s −1 Mpc −1 , easing the discrepancy with SH0ES. However, neither model resolves both issues simultaneously. Our analysis indicates that both DDE and EDE remain viable extensions of Λ⁢CDM within current uncertainties and demonstrates the capacity of combined probes to place increasingly stringent constraints on cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Vitality models found useful in modeling tag-failure times in acoustic-tag survival studies

Abstract Acoustic telemetry studies often rely on the assumption that premature tag failure does not affect the validity of inferences. However, in some cases this assumption is possibly or likely invalid and it is necessary to apply a correction to estimation procedures. The question of which approaches and specific models are best suited to modeling acoustic tag failures has received little research attention. In this short communication, we present a meta-analysis of 42 acoustic tag-life studies, originally used to correct survival studies involving outmigrating juvenile salmonids in the Columbia/Snake river basin. We compare the performance of nine alternative parametric models including common failure–time/survival models and the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013). The tag-life studies used acoustic tags from three different tag manufacturers, had expected lifetimes between 12 and 61 days, and had dry weights ranging from 0.22 to 1.65 g. In 57% of the cases, the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013) fit the tag-failure times best. The vitality models were also the second-best choices in 17% of the cases. Together, the vitality models, log-logistic, (19%), and gamma models (14%) accounted for 90% of the models selected. Unlike more traditional failure–time models (e.g., Weibull, Gompertz, gamma, and log-logistic), the vitality models are capable of characterizing both the early onset of tag failure due to manufacturing errors and the anticipated battery life. We provide further guidance on appropriate sample sizes (50–100 tags) and procedures to be considered when applying precise tag-life corrections in release–recapture survival studies.

Skalski, John R. (ORCID:0000000270702505)↗

DOE OSTI2012

Parameterization of the Extinction Coefficient in Ice and Mixed-Phase Arctic Clouds during the ISDAC Field Campaign

This report documents the history of attempts to directly measure cloud extinction, the current measurement device known as the Cloud Extinction Probe (CEP), specific problems with direct measurement of extinction coefficient, and the attempts made here to address these problems. Extinction coefficient is one of the fundamental microphysical parameters characterizing bulk properties of clouds. Knowledge of extinction coefficient is of crucial importance for radiative transfer calculations in weather prediction and climate models given that Earth's radiation budget (ERB) is modulated much by clouds. In order for a large-scale model to properly account for ERB and perturbations to it, it must ultimately be able to simulate cloud extinction coefficient well. In turn this requires adequate and simultaneous simulation of profiles of cloud water content and particle habit and size. Similarly, remote inference of cloud properties requires assumptions to be made about cloud phase and associated single-scattering properties, of which extinction coefficient is crucial. Hence, extinction coefficient plays an important role in both application and validation of methods for remote inference of cloud properties from data obtained from both satellite and surface sensors (e.g., Barker et al. 2008). While estimation of extinction coefficient within large-scale models is relatively straightforward for pure water droplets, thanks to Mie theory, mixed-phase and ice clouds still present problems. This is because of the myriad forms and sizes that crystals can achieve, each having their own unique extinction properties. For the foreseeable future, large-scale models will have to be content with diagnostic parametrization of crystal size and type. However, before they are able to provide satisfactory values needed for calculation of radiative transfer, they require the intermediate step of assigning single-scattering properties to particles. The most basic of these is extinction coefficient, yet it is rarely measured directly, and therefore verification of parametrizations is difficult. The obvious solution is to be able to measure microphysical properties and extinction at the same time and for the same volume. This is best done by in situ sampling by instruments mounted on either balloon or aircraft. The latter is the usual route and the one employed here. Yet the problem of actually measuring extinction coefficient directly for arbitrarily complicated particles still remains unsolved.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

Identifying Suitable Degradation Parameters for Individual-Based Prognostics

The ultimate goal of most prognostic systems is accurate prediction of the remaining useful life of individual systems or components based on their use and performance. Traditionally, individual-based prognostic methods use a measure of degradation to make lifetime estimates. Degradation measures may include sensed measurements, such as temperature or vibration level, or inferred measurements, such as model residuals or physics-based model predictions. Often, it is beneficial to combine several measures of degradation into a single parameter. Parameter features such as trendability, monotonicity, and prognosability can be used to compare candidate prognostic parameters to determine which is most useful for individual-based prognosis. By quantifying these features for a given parameter, the metrics can be used with any traditional optimization technique to identify an appropriate parameter. This parameter may be used with a parametric extrapolation model to make prognostic estimates for an individual unit. The proposed methods are illustrated with an application to simulated turbofan engine data.

Diagnostics↗

DOE OSTI2025

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗

DOE OSTI2026

Gaussian processes for inferring parton distributions

The extraction of parton distribution functions (PDFs) from experimental or lattice QCD data is an ill-posed inverse problem, where regularization strongly impacts both systematic uncertainties and the reliability of the results. We study a framework based on Gaussian Process Regression (GPR) to reconstruct PDFs from lattice QCD matrix elements. Within a Bayesian framework, Gaussian processes serve as flexible priors that encode uncertainties, correlations, and constraints without imposing rigid functional forms. We investigate a wide range of kernel choices, mean functions, and hyperparameter treatments. We quantify information gained from the data using the Kullback-Leibler divergence. Synthetic data tests demonstrate the consistency and robustness of the method. Our study establishes GPR as a systematic and non-parametric approach to PDF reconstruction, offering controlled uncertainty estimates and reduced model bias in lattice QCD analyses.

hadronic spectroscopy↗