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At least 1,099 records · Page 61

Simulated Polarimetric Fields of Ice Vapor Growth Using the Adaptive Habit Model. Part II: A Case Study from the FROST Experiment

Abstract A new adaptive habit model (AHM) grows ice crystals through vapor deposition while evolving ice particle properties, including shape and effective density. The AHM provides an opportunity to investigate observed microphysical processes through the computation of polarimetric variables and corroboration with microphysical model output. This study is unique because the polarimetric scattering calculations are computed using predicted microphysical parameters rather than a priori assumptions that are imposed within the scattering calculations in the forward simulator, allowing for a more effective comparison to radar observations. Through the simulation of a case in the Front Range of the Rocky Mountains in Colorado using the Advanced Research version of the Weather Research and Forecasting Model, it is found that the AHM approximates ice mass, shape, cloud vertical structure, and temporal evolution as reflected through polarimetric quantities compared to observations. AHM reflectivity magnitudes are similar to those observed with radar and are an improvement over spherical ice crystal assumptions. Further analyses are completed to examine the effect of microphysical processes on the evolution of the differential reflectivity and specific differential phase, both of which are simulated using the AHM. Simulations reveal a polarimetric response to ice crystal mass, number, size, density, and aspect ratio. While results reveal the need for model improvements (e.g., parameterizations for aggregation rate), testing forward-simulated radar fields against observations is a first step in the validation of model microphysical and precipitation processes.

54 ENVIRONMENTAL SCIENCES↗

A Co-Registered In-Situ and Ex-Situ Tensile Properties Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-11)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from five Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L builds containing 6,299 SS-J3 individually tracked tensile coupons. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, room-temperature static tensile test results, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein

Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BP SS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BP SS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BP SS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BP SS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R 0 ) and fluorophore orientation factor (κ 2 ) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.

59 BASIC BIOLOGICAL SCIENCES↗

Journal paper

Laser technology is being widely studied for controlled energy deposition for a range of applications, including flow control, ignition, combustion, and diagnostics. The absorption and scattering of laser radiation by liquid droplets in aerosols affects propagation of the laser beam in the atmosphere, while the ignition and combustion characteristics in combustion chambers are influenced by the evaporation rate of the sprayed fuel. In this work, we present a mathematical model built on OpenFOAM for laser heating and evaporation of a single droplet in the diffusion-dominated regime taking into account absorption of the laser radiation, evaporation process, and vapor flow dynamics. The developed solver is validated against available experimental and numerical data for heating and evaporation of ethanol and water droplets. The two main regimes—continuous and pulsed laser heating—are explored. For continuous laser heating, the peak temperature is higher for larger droplets. For pulsed laser heating, when the peak irradiance is close to transition to the boiling regime, the temporal dynamics of the droplet temperature does not depend on the droplet size. With the empirical normalization of time, the dynamics of the droplet shrinkage and cooling are found to be independent of droplet sizes and peak laser intensities.

42 ENGINEERING↗

Sequential addition of short DNA oligos in DNA-polymerase-based synthesis reactions

A method of preselecting a multiplicity of DNA sequence segments that will comprise the DNA molecule of user-defined sequence, separating the DNA sequence segments temporally, and combining the multiplicity of DNA sequence segments with at least one polymerase enzyme wherein the multiplicity of DNA sequence segments join to produce the DNA molecule of user-defined sequence. Sequence segments may be of length n, where n is an odd integer. In one embodiment the length of desired hybridizing overlap is specified by the user and the sequences and the protocol for combining them are guided by computational (bioinformatics) predictions. In one embodiment sequence segments are combined from multiple reading frames to span the same region of a sequence, so that multiple desired hybridizations may occur with different overlap lengths.

59 BASIC BIOLOGICAL SCIENCES↗

EMAPS: An Efficient Multiscale Approach to Plasma Systems with Non-MHD Scale Effects

Global interactions of energetic ions with magnetoplasmas and neutral gases lie at the core of many space and laboratory plasma phenomena ranging from solar wind entry into and transport within planetary magnetospheres and exospheres to fast-ion driven instabilities in fusion devices to astrophysics-in-lab experiments. The ability of computational models to properly account for physical effects that underlie such interactions, namely ion kinetic, ion cyclotron, Hall, collisional and ionization processes is important for the success and planning of experimental research in plasma physics. Understanding the physics of energetic ions, in particular their nonlinear resonance interactions with Alfvén waves, is central to improving the heating performance of magnetically confined plasmas for future energy generation. Fluid models are not adequate for high-beta plasmas as they cannot fully capture ion kinetic and cyclotron physics (e.g., ion behavior in the presence of magnetic nulls, shock structures, plasma interpenetration, etc.). Recent results from global reconnection simulations show that even in a MHD-like regime there may be significant differences between kinetic and MHD simulations. Therefore, kinetic modeling becomes essential for meeting modern day challenges in plasma physics. The hybrid approximation is an intermediate approximation between the fluid and fully kinetic approximations. It eliminates light waves, removes the electron inertial temporal and spatial scales from the problem and enables full-orbit ion kinetics. As a result, hybrid codes have become effective tools for exploring ion-scale driven phenomena associated with ion beams, shocks, reconnection and turbulence that control the large-scale behavior of laboratory and space magnetoplasmas. A number of numerical issues, however, make three-dimensional (3D) large-scale hybrid simulations of inhomogeneous magnetized plasmas prohibitively expensive or even impossible. To resolve these difficulties we have developed a novel Event-driven Multiscale Asynchronous Parallel Simulation (EMAPS) technology that replaces time stepping with self-adaptive update events. Local calculations are carried out only on an “as needed basis”. EMAPS (i) guarantees accurate and stable processing of physical variables in time accurate simulations, and (ii) eliminates unnecessary computation. Applying EMAPS to the hybrid model has resulted in the development of a unique parallel code, dimension-independent (compile-time-configurable) HYPERS (Hybrid Parallel Event-Resolved Simulator) that scales to hundreds of thousands of parallel processors. HYPERS advances electromagnetic fields and particles asynchronously on time scales determined by local physical laws and mesh properties. To achieve high computational accuracy in complex device geometries, HYPERS employs high-fidelity Cartesian grids with masked conductive cells. The HYPERS model includes multiple ion species, energy and momentum conserving ion-ion collisions, and provides a number of approximations for plasma resistivity and vacuum regions. Both local and periodic boundary conditions are allowed. The HYPERS solver preserves zero divergence of magnetic field. The project has demonstrated HYPERS capabilities on a number of applications of interest to fusion and astrophysical plasma physics applications listed below. 1. Theta-pinch formation of FRCs The formation, spontaneous spin-up, and stability of theta-pinch formed field-reversed configurations have been studied self-consistently in 3D. The end-to-end hybrid simulations reveal poloidal profiles of implosion-driven fast toroidal plasma rotation and demonstrate three discharge regimes as a function of experimental parameters: the decaying stable configuration, the tilt unstable configuration, and the nonlinear evolution of a fast growing tearing mode. 2. FRC collisions with magnetic mirrors Interactions of fast plasma streams and objects with magnetic obstacles (dipoles, mirrors, etc) lie at the core of many space and laboratory plasma phenomena ranging from magnetoshells and solar wind interactions with planetary magnetospheres to compact fusion plasmas. HYPERS simulations are compared with data from the MSX experiment (LANL) that focuses on the physics of magnetized collisionless shocks through the acceleration and subsequent stagnation of FRC plasmoids against a strong magnetic mirrors and flux-conserving boundaries. 3. Exploding magnetoplasmas Results from hybrid simulations of two experiments at the LAPD and Nevada Terawatt Facility are discussed where short-pulse lasers are used to ablate solid targets to produce plasmas that expand across external magnetic fields. The first simulation recreates flutelike density striations observed at the leading edge of a carbon plasma and predicts an early destruction of the magnetic cavity in agreement with experimental evidence. In the second simulation a polyethylene target is ablated into a mixture of protons and carbon ions. A mechanism is demonstrated that allows protons to penetrate the magnetic field in the form of a collimated flow. The results are compared to experimental data and single-fluid MHD simulations. The EMAPS framework has the potential for wide application in many other engineering and scientific fields, such as climate models, biological systems, electronic devices, seismic events, oil reservation simulators that all involve advancing solutions of partial differential equations in time where the rate of activity can be adapted widely over the spatial domain depending on locally space/time phenomena (“events”).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

System and method for computed axial lithography (CAL) for 3D additive manufacturing

A method of forming a three dimensional (3D) object is disclosed. The method may involve providing a volume of photo-curable resin contained within an optically transparent resin container, and simultaneously directing optical projections from an optical subsystem at a plurality of angles θ through the volume of photo-curable resin. The optical beams are directed about a z axis extending through the volume of photo-curable resin. Each of the projections is provided with a calculated 2D spatial intensity function which creates a 3D intensity map. The projections act over a fixed temporal exposure period, during which the net exposure dose is sufficient to cure select portions of the volume of photo-curable resin, and to leave other portions uncured, to form a desired 3D part.

36 MATERIALS SCIENCE↗

Self-consistent integrated modeling of combined hybrid discharge-laser produced plasma devices for extreme ultraviolet metrology

Discharge- and laser-produced plasma (DLPP) devices are being used as light sources for extreme ultraviolet (EUV) generation. A key challenge for both, DPP and LPP, is achieving sufficient brightness to support the throughput requirements of nanometrology tools. To simulate the environment of a hybrid DLPP device and optimize the EUV output, we have developed an integrated HEIGHTS-DLPP computer simulation package. The package integrates simulation of two evolving plasmas (DPP and LPP) and includes modeling of a set of integrated self-consistent processes: external power source and plasma energy balance, plasma resistive magnetohydrodynamics, plasma heat conduction, detailed radiation transport (RT), and laser absorption and refraction. We simulated and optimized DLPP devices using Xe gas as a target material. We synchronized the external circuit parameters, chamber gas parameters, and laser beam temporal and spatial profiles to achieve maximum EUV output. The full 3D Monte Carlo scheme was integrated for detailed RT and EUV output calculations in Xe using more than 3600 spectral groups. The modeling results are in good agreement with Julich Forschungszentrum experimental data. Theoretical models, developed and integrated into the HEIGHTS package, showed wide capabilities and flexibility. In conclusion, the models and package can be used for optimization of the experimental parameters and settings, investigation of DLPP devices with complex design, analyzing the impact of integrated spatial effects and working timeline arrangement on the final EUV output, and EUV source size, shape, and angular distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

First critical repressive H3K27me3 marks in embryonic stem cells identified using designed protein inhibitor

The polycomb repressive complex 2 (PRC2) histone methyltransferase plays a central role in epigenetic regulation in development and in cancer, and hence to interrogate its role in a specific developmental transition, methods are needed for disrupting function of the complex with high temporal and spatial precision. The catalytic and substrate recognition functions of PRC2 are coupled by binding of the N-terminal helix of the Ezh2 methylase to an extended groove on the EED trimethyl lysine binding subunit. Disrupting PRC2 function can in principle be achieved by blocking this single interaction, but there are few approaches for blocking specific protein–protein interactions in living cells and organisms. Here, in this work, we describe the computational design of proteins that bind to the EZH2 interaction site on EED with subnanomolar affinity in vitro and form tight and specific complexes with EED in living cells. Induction of the EED binding proteins abolishes H3K27 methylation in human embryonic stem cells (hESCs) and at all but the earliest stage blocks self-renewal, pinpointing the first critical repressive H3K27me3 marks in development.

60 APPLIED LIFE SCIENCES↗

Radiative signatures of plasmoid-dominated reconnection in blazar jets

The multiwavelength spectral and temporal variability observed in blazars set tight constraints on current theoretical emission models. In this work, we investigate the relativistic magnetic reconnection process as a source of blazar emission in which quasi-spherical plasmoids, containing relativistic particles and magnetic fields, are associated with the emission sites in blazar jets. By coupling recent two-dimensional particle-in-cell simulations of relativistic reconnection with a time-dependent radiative transfer code, we compute the non-thermal emission from a chain of plasmoids formed during a reconnection event. The derived photon spectra display characteristic features observed in both BL Lac sources and flat spectrum radio quasars, with the distinction made by varying the strength of the external photon fields, the jet magnetization, and the number of pairs per proton contained within. Light curves produced from reconnection events are composed of many fast and powerful flares that appear on excess of a slower evolving envelope produced by the cumulative emission of medium-sized plasmoids. The observed variability is highly dependent upon the orientation of the reconnection layer with respect to the blazar jet axis and to the observer. Our model provides a physically motivated framework for explaining the multitime-scale blazar variability across the entire electromagnetic spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗

Photovoltaic Inverter Controllers Seeking AC Optimal Power Flow Solutions

This paper considers future distribution networks featuring inverter-interfaced photovoltaic (PV) systems, and addresses the synthesis of feedback controllers that seek real- and reactive-power inverter setpoints corresponding to AC optimal power flow (OPF) solutions. The objective is to bridge the temporal gap between long-term system optimization and real-time inverter control, and enable seamless PV-owner participation without compromising system efficiency and stability. The design of the controllers is grounded on a dual ..epsilon..-subgradient method, while semidefinite programming relaxations are advocated to bypass the non-convexity of AC OPF formulations. Global convergence of inverter output powers is analytically established for diminishing stepsize rules for cases where: i) computational limits dictate asynchronous updates of the controller signals, and ii) inverter reference inputs may be updated at a faster rate than the power-output settling time.

14 SOLAR ENERGY↗

A Numerical Tool for the Design of Enhanced Geothermal Reservoirs based on Modeling of Thermo-Hydro-Mechanical Processes and Explicit Representation of 3D Discrete Fracture Networks

This project has developed a coupled thermo-hydro-mechanical numerical modeling tool for prediction of energy production from Enhanced Geothermal Reservoirs (EGS). The tool is unique because it can explicitly represent thousands of pre-existing natural fractures. The capabilities developed in this project were built on the already existing expertise of Itasca arising from thirty years of research and development in discrete element modeling of fractured rocks. A thermal module suitable for analysis of different heat transfer mechanisms in fractured rocks percolated by fluids was developed and coupled with the already existing hydro-mechanical calculation in 3DEC, a commercial software for analysis of jointed rock based on the discrete element method (DEM). The heat transfer module simulates heat conduction, heat advection by moving fluid in rock fractures, and convective heat exchange at the fracture walls between the rock and the moving fluid. Techniques for spatial discretization of heat transfer in EGS-type problems were evaluated, and a boundary layer meshing approach was developed. Also, given the significant differences in time scale of physical processes involved, temporal integration schemes for coupled advection-diffusion processes and coupled thermal-hydro-mechanical processes were developed by taking advantage of both implicit and explicit time integration and also optimizing the coupling intervals. These improvements were necessary for modeling EGS reservoirs. Also, the DFN capacities in 3DEC were extended to include a larger number of fractures. Research was carried out on approaches to simplify the DFN so that the model can meet computational demands, while preserving thermo-hydro-mechanical characteristics of the DFN. The developed modules were coupled with the already existing capabilities of 3DEC. The results were presented as a submitted conference paper (Riahi et al., 2018a). A series of benchmark and test examples showed the developed capabilities. Finally, the developed tool was tested for a large-scale reservoir model for longer periods of injection and production. The thermal draw-down curves were generated and presented. The project successfully met all the milestones laid out in the proposal. Results demonstrated the feasibility of developing a fast and reliable software for the EGS community to use for assessment and prediction of reservoir performance. Some of its applications include assessment of stimulated volume and produced temperature and power. It can also be used for improved engineering, design and optimization of EGS reservoirs as well as other unconventional resources such as shale gas. Finally, the 3D analysis presented in this study showed that simulating EGS reservoirs with tens of thousands of fractures is feasible, and confirmed that the developed tool can serve toward meeting the goals and objectives of Geothermal Technologies Office in overcoming technical barriers associated with commercial EGS development.

15 GEOTHERMAL ENERGY↗

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. As a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK —a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.

60 APPLIED LIFE SCIENCES↗

Piano Transcription with Convolutional Sparse Lateral Inhibition

This paper extends our prior work on contextdependent piano transcription to estimate the length of the notes in addition to their pitch and onset. This approach employs convolutional sparse coding along with lateral inhibition constraints to approximate a musical signal as the sum of piano note waveforms (dictionary elements) convolved with their temporal activations. The waveforms are pre-recorded for the specific piano to be transcribed in the specific environment. A dictionary containing multiple waveforms per pitch is generated by truncating a long waveform for each pitch to different lengths. During transcription, the dictionary elements are fixed and their temporal activations are estimated and post-processed to obtain the pitch, onset and note length estimation. A sparsity penalty promotes globally sparse activations of the dictionary elements, and a lateral inhibition term penalizes concurrent activations of different waveforms corresponding to the same pitch within a temporal neighborhood, to achieve note length estimation. Experiments on the MAPS dataset show that the proposed approach significantly outperforms a state-of-the-art music transcription method trained in the same context-dependent setting in transcription accuracy.

97 MATHEMATICS AND COMPUTING↗

Designing and Evaluating Redundancy-Based Soft-Error Masking on a Continuum of Energy versus Robustness

Near-threshold computing is an effective strategy to reduce the power dissipation of deeply-scaled CMOS logic circuits. However, near-threshold strategies exacerbate the impact of delay variations on device performance and increase the susceptibility to soft errors due to narrow voltage margins. The objective of this work is to develop and assess design approaches that leverage tradeoffs between performance and the resilience of fault masking coverage for various soft-error mitigation techniques. The primary insight from this work is identification of redundancy-based hardening techniques that can deliver increased benefits in terms of the fault coverage energy ratio (FCER) for the leveraged tradeoffs within iso-energy constraints at near-threshold voltage (NTV). Simulation results demonstrate that temporal redundancy approaches offer favorable tradeoffs in terms of FCER. They exhibit reduced impact on performance variations and achieve extensive soft fault masking, therefore improving the system robustness within acceptable delay constraints. Meanwhile, it is shown that a hybrid redundancy approach can be used to protect a low-power system to maintain throughput while tolerating soft errors. We demonstrate how the FCER metric can be used as an optimization parameter to guide circuit synthesis to meet performance and robustness goals. Lastly, the impact of design diversity on spatial and hybrid redundancy at NTV is assessed in terms of FCER and delay variation to form overall recommendations regarding soft-error mitigation at NTV.

97 MATHEMATICS AND COMPUTING↗

Orchestrating Spontaneous Emission With Metasurfaces: Recent Advances in Engineering Thermal, Luminescent, and Quantum Emissions

Metasurfaces have emerged as powerful tools for controlling spontaneous emission, offering unprecedented control over light-matter interactions at sub-wavelength scales. While metasurfaces are traditionally utilized for shaping coherent electromagnetic waves, they have recently extended their capabilities to control incoherent or spontaneous emission. This examines review how metasurfaces can enhance and precisely control properties of thermal, luminescent, and quantum emission. In thermal emission, metasurfaces enable control over spatial, temporal, and spin coherence, offering new possibilities for applications such as energy harvesting, radiative cooling and heat assisted ranging and detection. For luminescent emission, metasurfaces significantly improve emission rates, quantum efficiency, and directionality, driving innovations in lighting and display technologies. For controlling quantized spontaneous emission, metasurfaces are instrumental in enhancing single-photon sources and enabling novel functionalities in quantum states through photon-pair generation, which is vital for quantum communication, meteorology, and computing. Here, despite these advancements several challenges to increase the operational bandwidths, accelerate and develop simulation strategies, and fabrication complexities persist. Emerging trends are also discussed, such as dynamic metasurfaces and their integration with nanophotonic platforms, which could further expand the capabilities of light-emitting metasurfaces.

Luminescence↗

Coordinating Garbage Collectionfor Arrays of Solid-State Drives

The primary goal of the extreme-scale plasma turbulence studies described in this article is to gain new insights on confinement scaling in magnetic fusion systems by using powerful, world-class supercomputers to carry out simulations with unprecedented resolution and temporal duration. New insights have been gained on the key question of how the turbulent transport of thermal energy and particles in the plasma and the associated confinement scale from present-generation devices to much larger ITER-size plasmas. In particular, new results from large-scale simulation studies have demonstrated that improvement in confinement as devices grow larger is far more gradual, with significantly lower loss rates than less-powerful computer simulations have indicated in research carried out over the past decade.

Computer Science↗

Nature-GL: A Revolutionary Learning Paradigm Unleashing Nature’s Power in Real-World Spatial-Temporal Graph Learning

Spatial-Temporal Graph Learning (ST-GL) is a prominent research area due to its unique capability to effectively learn real-world graphs. Applications of ST-GL pose stringent and various demands on not only real-time inference with low energy cost and high ac- curacy but also fast training. Unfortunately, as Moore’s Law approaches its limits and ST-GL model complexity drastically grows, the gap between digital hardware’s computational power and ST- GL application demands is widening. In response, this paper introduces Nature-GL, a nature-powered graph learning paradigm that exploits the principle of entropy increase to advance graph learning. In particular, Nature-GL transforms both the training and inference of real-valued ST-GL into electron-speed natural anneal- ing processes of a parameterized dynamical system that represents the target graphs. Experimental results across four real-world ap- plications with six datasets demonstrate that Nature-GL achieves orders-of-magnitude speedups in both training and inference, delivering higher accuracy compared to Graph Neural Networks.

Liu, Chuan [University of Rochester]↗