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NASA NTRS1984

On the maximum-entropy/autoregressive modeling of time series

The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relation which relates a complex conjugate pair of poles of the AR process in the z-plane (or the z domain) on the one hand, to the complex frequency of one complex harmonic function in the time domain on the other. Thus the AR model of a time series is one that models the time series as a linear combination of complex harmonic functions, which include pure sinusoids and real exponentials as special cases. An AR model is completely determined by its z-domain pole configuration. The maximum-entropy/autogressive (ME/AR) spectrum, defined on the unit circle of the z-plane (or the frequency domain), is nothing but a convenient, but ambiguous visual representation. It is asserted that the position and shape of a spectral peak is determined by the corresponding complex frequency, and the height of the spectral peak contains little information about the complex amplitude of the complex harmonic functions.

Chao, B. F.↗
DOE OSTI2022

Revisiting stellar properties of star-forming galaxies with stellar and nebular spectral modelling

Spectral synthesis is a powerful tool for interpreting the physical properties of galaxies by decomposing their spectral energy distributions (SEDs) into the main luminosity contributors (e.g. stellar populations of distinct age and metallicity or ionised gas). However, the impact nebular emission has on the inferred properties of star-forming (SF) galaxies has been largely overlooked over the years, with unknown ramifications to the current understanding of galaxy evolution. The objective of this work is to estimate the relations between stellar properties (e.g. total mass, mean age, and mean metallicity) of SF galaxies by simultaneously fitting the stellar and nebular continua and comparing them to the results derived through the more common purely stellar spectral synthesis approach. The main galaxy sample from SDSS DR7 was analysed with two distinct population synthesis codes: FADO, which estimates self-consistently both the stellar and nebular contributions to the SED, and the original version of STARLIGHT, as representative of purely stellar population synthesis codes. Differences between codes regarding average mass, mean age and mean metallicity values can go as high as ~0.06 dex for the overall population of galaxies and ~0.12 dex for SF galaxies (galaxies with EW(Hα) > 3 Å), with the most prominent difference between both codes in the two populations being in the light-weighted mean stellar age. FADO presents a broader range of mean stellar ages and metallicities for SF galaxies than STARLIGHT, with the latter code preferring metallicity solutions around the solar value (Z ⊙ = 0.02). A closer look into the average light- and mass-weighted star formation histories of intensively SF galaxies (EW(Hα) > 75 Å) reveals that the light contributions of simple stellar populations (SSPs) younger than ≤10 7 (10 9 ) years in STARLIGHT are higher by ~5.41% (9.11%) compared to FADO. Moreover, FADO presents higher light contributions from SSPs with metallicity ≤ Z ⊙ /200 (Z ⊙ /50) of around 8.05% (13.51%) when compared with STARLIGHT. This suggests that STARLIGHT is underestimating the average light-weighted age of intensively SF galaxies by up to ~0.17 dex and overestimating the light-weighted metallicity by up to ~0.13 dex compared to FADO (or vice versa). The comparison between the average stellar properties of passive, SF and intensively SF galaxy samples also reveals that differences between codes increase with increasing EW(Hα) and decreasing total stellar mass. Moreover, comparing SF results from FADO in a purely stellar mode with the previous results qualitatively suggests that differences between codes are primarily due to mathematical and statistical differences and secondarily due to the impact of the nebular continuum modelling approach (or lack thereof). However, it is challenging to adequately quantify the relative role of each factor since they are likely interconnected. This work finds indirect evidence that a purely stellar population synthesis approach negatively impacts the inferred stellar properties (e.g. mean age and mean metallicity) of galaxies with relatively high star formation rates (e.g. dwarf spirals, ‘green peas’, and starburst galaxies). In turn, this can bias interpretations of fundamental relations such as the mass-age or mass-metallicity, which are factors worth bearing in mind in light of future high-resolution spectroscopic surveys at higher redshifts (e.g. MOONS and 4MOST-4HS).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Search for a high-mass dimuon resonance produced in association with b quark jets at $ \sqrt{s} $ = 13 TeV

A search for high-mass dimuon resonance production in association with one or more b quark jets is presented. The study uses proton-proton collision data collected with the CMS detector at the LHC corresponding to an integrated luminosity of 138 fb$^{−1}$ at a center-of-mass energy of 13 TeV. Model-independent limits are derived on the number of signal events with exactly one or more than one b quark jet. Results are also interpreted in a lepton-flavor-universal model with Z′ boson couplings to a bb quark pair (g$_{b}$), an sb quark pair (g$_{b}$δ$_{bs}$), and any same-flavor charged lepton (g$_{ℓ}$) or neutrino pair (g$_{ν}$), with |g$_{ν}$| = |g$_{ℓ}$|. For a Z′ boson with a mass $ {m}_{{\textrm{Z}}^{\prime }} $ = 350 GeV (2 TeV) and |δ$_{bs}$| < 0.25, the majority of the parameter space with 0.0057 < |g$_{ℓ}$| < 0.35 (0.25 < |g$_{ℓ}$| < 0.43) and 0.0079 < |g$_{b}$| < 0.46 (0.34 < |g$_{b}$| < 0.57) is excluded at 95% confidence level. Finally, constraints are set on a Z′ model with parameters consistent with low-energy b → sℓℓ measurements. In this scenario, most of the allowed parameter space is excluded for a Z′ boson with 350 < $ {m}_{{\textrm{Z}}^{\prime }} $ < 500 GeV, while the constraints are less stringent for higher $ {m}_{{\textrm{Z}}^{\prime }} $ hypotheses. This is the first dedicated search at the LHC for a high-mass dimuon resonance produced in association with multiple b quark jets, and the constraints obtained on models with this signature are the most stringent to date.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗
NASA NTRS1990

Interpretation of the microlensing event in QSO 2237 + 0305

A model of microlensing for image A of the gravitationally lensed QSO 2237 + 0305 for which Irwin et al. reported in 1989 an increase of the apparent luminosity by about 0.5 mag on a time scale of a few months is presented. The model, with the Salpeter mass function over the mass range of 0.1-1.0 solar mass and the transverse velocity of the lens (or observer) of 600 km/s, can reproduce the reported luminosity variation if the source of the optical continuum has a radius smaller than about 2 x 10 to the 15th cm. This size is compatible with the accretion disk interpretation of the big ultraviolet bump in quasar spectra. The model demonstrates a very large diversity of light curves while the source crosses individual microcaustics or clusters of microcaustics. It will take more than 100 yr before the full variety of light curves will be sampled by the observations.

Wambsganss, J.↗
DOE OSTI2022

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Precise interpretations of traditional fine-tuning measures

We uncover two precise interpretations of traditional electroweak fine-tuning (FT) measures that were historically missed. (i) a statistical interpretation : the traditional FT measure shows the change in plausibility of a model in which a parameter was exchanged for the 𝑍 boson mass relative to an untuned model in light of the 𝑍 boson mass measurement. (ii) an information-theoretic interpretation : the traditional FT measure shows the exponential of the extra information, measured in nats, relative to an untuned model that you must supply about a parameter in order to fit the 𝑍 mass. We derive the mathematical results underlying these interpretations, and explain them using examples from weak scale supersymmetry. These new interpretations allow us to rigorously define FT in particle physics and beyond, shed fresh light on the status of extensions to the Standard Model and, lastly, allow us to precisely reinterpret historical and recent studies using traditional FT measures.

electroweak symmetry breaking↗
NASA NTRS1977

Model predictions of wind and turbulence profiles associated with an ensemble of aircraft accidents

The feasibility of predicting conditions under which wind/turbulence environments hazardous to aviation operations exist is studied by examining a number of different accidents in detail. A model of turbulent flow in the atmospheric boundary layer is used to reconstruct wind and turbulence profiles which may have existed at low altitudes at the time of the accidents. The predictions are consistent with available flight recorder data, but neither the input boundary conditions nor the flight recorder observations are sufficiently precise for these studies to be interpreted as verification tests of the model predictions.

Williamson, G. G.↗
DOE OSTI2023

Search for leptoquarks decaying into the bτ final state in pp collisions at $\sqrt{\textrm{s}}$ = 13 TeV with the ATLAS detector

A search for leptoquarks decaying into the $bτ$ final state is performed using Run 2 proton-proton collision data from the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb —1 at $\sqrt{\textrm{s}}$ = 13 TeV recorded by the ATLAS detector. The benchmark models considered in this search are vector leptoquarks with electric charge of 2/3e and scalar leptoquarks with an electric charge of 4/3e. No significant excess above the Standard Model prediction is observed, and 95% confidence level upper limits are set on the cross-section times branching fraction of leptoquarks decaying into bτ. For the vector leptoquark production two models are considered: the Yang-Mills and Minimal coupling models. In the Yang-Mills (Minimal coupling) scenario, vector leptoquarks with a mass below 1.58 (1.35) TeV are excluded for a gauge coupling of 1.0 and below 2.05 (1.99) TeV for a gauge coupling of 2.5. In the case of scalar leptoquarks, masses below 1.28 (1.53) TeV are excluded for a Yukawa coupling of 1.0 (2.5). Finally, an interpretation of the results with minimal model dependence is performed for each of the signal region categories, and limits on the visible cross-section for beyond the Standard Model processes are provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2020

The Impact of Planetary Rotation Rate on the Reflectance and Thermal Emission Spectrum of Terrestrial Exoplanets around Sunlike Stars

Robust atmospheric and radiative transfer modeling will be required to properly interpret reflected-light and thermal emission spectra of terrestrial exoplanets. This will help break observational degeneracies between the numerous atmospheric, planetary, and stellar factors that drive planetary climate. Here, we simulate the climates of earthlike worlds around the Sun with increasingly slow rotation periods, from earthlike to fully Sun-synchronous, using the ROCKE-3D general circulation model. We then provide these results as input to the Spectral Planet Model, which employs the Spectral Mapping Atmospheric Radiative Transfer model to simulate the spectra of a planet as it would be observed from a future space-based telescope. We find that the primary observable effects of slowing planetary rotation rate are the altered cloud distributions, altitudes, and opacities that subsequently drive many changes to the spectra by altering the absorption band depths of biologically relevant gas species(e.g.,HO2,O2, andO3). We also identify a potentially diagnostic feature of synchronously rotating worlds in mid-infraredHO2absorption/emission lines.

Exoplanet atmospheres↗
NASA NTRS1993

Differential scaling: Implications for central structures in large lunar craters

The change in morphology of central structures with crater size on the terrestrial planets has been studied by many investigators. While the progression of morphological change essentially follows the same basic pattern, the appearance of central peaks, and the transitions from single to multiple peaks and peaks to peak rings occur at crater diameters that appear to be dependent on parameters associated with the target planet. Statistical data, morphological information, and model results exist for central structures in large craters, but the amount of 'ground truth' is comparatively meager. What, for instance, is the amount of stratigraphic uplift in craters? Answers to questions such as this will provide useful constraints on models of origin for central structures and would help in interpretation of remote-sensing data. This contribution uses terrestrial information and model calculations to estimate the amount of stratigraphic uplift for central-peak craters on the Moon--the only planet other than Earth for which sufficient topographic data are available.

Cintala, M. J.↗
NASA NTRS2004

An XMM-Newton Study of the Bright Ultrasoft Narrow-Line Quasar NAB 0205+024

The broad-band X-ray continuum of NAB 0205424 is well constrained due to the excellent photon statistics obtained (about 97,700 counts), and its impressive soft X-ray excess is clearly apparent. The hard X-ray power law has become notably steeper than when NAB 0205424 was observed with ASCA, attesting to the presence of significant X-ray spectral variability. A strong and broad emission feature is detected from about 5 to 6.4 keV, and we have modeled this as a relativistic line emitted close to the black hole from a narrow annulus of the accretion disk. Furthermore, a strong X-ray flare is detected with a hard X-ray spectrum; this flare may be responsible for illuminating the inner line-emitting part of the accretion disk. The combined observational results can be broadly interpreted in terms of the "thundercloud model proposed by Merloni & Fabian (2001).

Brandt, Niel↗
DOE OSTI2026

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗
NASA NTRS1976

Vibroacoustic test plan evaluation: Parameter variation study

Statistical decision models are shown to provide a viable method of evaluating the cost effectiveness of alternate vibroacoustic test plans and the associated test levels. The methodology developed provides a major step toward the development of a realistic tool to quantitatively tailor test programs to specific payloads. Testing is considered at the no test, component, subassembly, or system level of assembly. Component redundancy and partial loss of flight data are considered. Most and probabilistic costs are considered, and incipient failures resulting from ground tests are treated. Optimums defining both component and assembly test levels are indicated for the modified test plans considered. modeling simplifications must be considered in interpreting the results relative to a particular payload. New parameters introduced were a no test option, flight by flight failure probabilities, and a cost to design components for higher vibration requirements. Parameters varied were the shuttle payload bay internal acoustic environment, the STS launch cost, the component retest/repair cost, and the amount of redundancy in the housekeeping section of the payload reliability model.

Stahle, C. V.↗
NASA NTRS2020

The Impact of Planetary Rotation Rate on the Reflectance and Thermal Emission Spectrum of Terrestrial Exoplanets Around Sun-L ike Stars

Robust atmospheric and radiative transfer modeling will be required to properly interpret reflected light and thermal emission spectra of terrestrial exoplanets. This will help break observational degeneracies between the numerous atmospheric, planetary, and stellar factors that drive planetary climate. Here we simulate the climates of Earth-like worlds around the Sun with increasingly slow rotation periods, from Earth-like to fully Sun-synchronous, using the ROCKE-3D general circulation model. We then provide these results as input to the Spectral Planet Model (SPM), which employs the SMART radiative transfer model to simulate the spectra of a planet as it would be observed from a future space-based telescope. We find that the primary observable effects of slowing planetary rotation rate are the altered cloud distributions, altitudes, and opacities which subsequently drive many changes to the spectra by altering the absorption band depths of biologically-relevant gas species (e.g., H2O, O2, and O3). We also identify a potentially diagnostic feature of synchronously rotating worlds in mid-infrared H2O absorption/emission lines.

Scott D Guzewich↗