libEMMIMGFD: A program of marine controlled-source electromagnetic modelling and inversion using frequency-domain multigrid solverWe develop a software package libEMMI\MGFD for 3D frequency-domain marine controlled-source electromagnetic (CSEM) modelling and inversion. It is the first open-source C program tailored for…Pengliang Yang, An Ping·Jul 30, 2024SaveLearn
Dynamic Mode Decomposition Accelerated Forecast and Optimization of Geological CO2 Storage in Deep Saline AquifersData-driven and non-intrusive DMDc and DMDspc models successfully expedite the reconstruction and forecasting of CO2 fluid flow with acceptable accuracy margins, aiding in the rapid optimization of…Dimitrios Voulanas, Eduardo Gildin·Jul 30, 2024SaveLearn
Multi-GPU RI-HF Energies and Analytic Gradients - Towards High Throughput Ab Initio Molecular DynamicsThis article presents an optimized algorithm and implementation for calculating resolution-of-the-identity Hartree-Fock (RI-HF) energies and analytic gradients using multiple Graphics Processing…Ryan Stocks, Elise Palethorpe, Giuseppe M. J. Barca·Jul 29, 2024SaveLearn
Near-Isotropic Sub-ngstrom 3D Resolution Phase Contrast Imaging Achieved by End-to-End Ptychographic Electron TomographyThree-dimensional atomic resolution imaging using transmission electron microscopes is a unique capability that requires challenging experiments. Linear electron tomography methods are limited by the…Shengboy You, Andrey Romanov, Philipp Pelz·Jul 28, 2024SaveLearn
Moment-preserving Monte-Carlo Coulomb collision method for particle codesBinary-pairing Monte-Carlo methods are widely used in particle-in-cell codes to capture effects of small angle Coulomb collisions. These methods preserve momentum and energy exactly when the…Justin Ray Angus, Yichen Fu, Vasily Geyko et al.·Jul 27, 2024SaveLearn
On the relation between the velocity- and position-Verlet integratorsThe difference and similarity between the velocity- and position-Verlet integrators are discussed from the viewpoint of their Hamiltonian representations for both linear and nonlinear systems. For a…Liyan Ni, Zhonghan Hu·Jul 26, 2024SaveLearn
REMIX SPH -- improving mixing in smoothed particle hydrodynamics simulations using a generalised, material-independent approachWe present REMIX, a smoothed particle hydrodynamics (SPH) scheme designed to alleviate effects that typically suppress mixing and instability growth at density discontinuities in SPH simulations. We…Thomas D. Sandnes, Vincent R. Eke, Jacob A. Kegerreis et al.·Jul 26, 2024SaveLearn
Solving physics-based initial value problems with unsupervised machine learningInitial value problems -- a system of ordinary differential equations and corresponding initial conditions -- can be used to describe many physical phenomena including those arise in classical…Jack Griffiths, Steven A. Wrathmall, Simon A. Gardiner·Jul 25, 2024SaveLearn
Inherent structural descriptors via machine learningFinding proper collective variables for complex systems and processes is one of the most challenging tasks in simulations, which limits the interpretation of experimental and simulated data and the…Emanuele Telari, Antonio Tinti, Manoj Settem et al.·Jul 25, 2024SaveLearn
Numerical evaluation of orientation averages and its application to molecular physicsIn molecular physics, it is often necessary to average over the orientation of molecules when calculating observables, in particular when modelling experiments in the liquid or gas phase. Evaluated…Alexander Blech, Raoul M. M. Ebeling, Marec Heger et al.·Jul 24, 2024SaveLearn
Application of Machine Learning and Convex Limiting to Subgrid Flux Modeling in the Shallow-Water EquationsWe propose a combination of machine learning and flux limiting for property-preserving subgrid scale modeling in the context of flux-limited finite volume methods for the one-dimensional…Ilya Timofeyev, Alexey Schwarzmann, Dmitri Kuzmin·Jul 24, 2024SaveLearn
COLOSS: Complex-scaled Optical and couLOmb Scattering SolverWe introduce COLOSS, a program designed to address the scattering problem using a bound-state technique known as complex scaling. In this method, the oscillatory boundary conditions of the wave…Junzhe Liu, Jin Lei, Zhongzhou Ren·Jul 23, 2024SaveLearn
Benchmark: Tao's symplectic integration methodA benchmark test was conducted for a new symplectic integration method originally developed by Molei Tao. The method raises interest due to its explicit evolution equation, with applicability to both…Matheus Lazarotto, Iberê Caldas, Yves Elskens·Jul 22, 2024SaveLearn
Shock Hugoniot calculations using on-the-fly machine learned force fields with ab initio accuracyWe present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model based on the kernel…Shashikant Kumar, John E. Pask, Phanish Suryanarayana·Jul 21, 2024SaveLearn
ELEQTRONeX: A GPU-Accelerated Exascale Framework for Non-Equilibrium Quantum Transport in NanomaterialsNon-equilibrium electronic quantum transport is crucial for the operation of existing and envisioned electronic, optoelectronic, and spintronic devices. The ultimate goal of encompassing atomistic to…Saurabh Sawant, François Léonard, Zhi Yao et al.·Jul 19, 2024SaveLearn
Deep learning density functional theory Hamiltonian in real spaceDeep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in deep-learning density…Zilong Yuan, Zechen Tang, Honggeng Tao et al.·Jul 19, 2024SaveLearn
Evidential Deep Learning for Interatomic PotentialsMachine learning interatomic potentials (MLIPs) have been widely used to facilitate large-scale molecular simulations with accuracy comparable to ab initio methods. In practice, MLIP-based molecular…Han Xu, Taoyong Cui, Chenyu Tang et al.·Jul 19, 2024SaveLearn
Exploring End-to-end Differentiable Neural Charged Particle Tracking -- A Loss Landscape PerspectiveMeasurement and analysis of high energetic particles for scientific, medical or industrial applications is a complex procedure, requiring the design of sophisticated detector and data processing…Tobias Kortus, Ralf Keidel, Nicolas R. Gauger·Jul 18, 2024SaveLearn
Machine Learning for Improved Current Density Reconstruction from 2D Vector Magnetic ImagesThe reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics,…Niko R. Reed, Danyal Bhutto, Matthew J. Turner et al.·Jul 18, 2024SaveLearn
One-dimensional gas-fueled nuclear reactor with thermal feedbackThis study explores a simplified one-dimensional subchannel of a graphite-moderated nuclear reactor operating with a gaseous core in steady-state conditions, reproducing a…Mathis Caprais, Kacim François-Elie, Daniele Tomatis·Jul 17, 2024SaveLearn
Efficient ensemble uncertainty estimation in Gaussian Processes RegressionReliable uncertainty measures are required when using data based machine learning interatomic potentials (MLIPs) for atomistic simulations. In this work, we propose for sparse Gaussian Process…Mads-Peter Verner Christiansen, Nikolaj Rønne, Bjørk Hammer·Jul 17, 2024SaveLearn
Application of a spectral scheme to simulate horizontally slowly varying three-dimensional ocean acoustic propagationThree-dimensional numerical models for underwater sound propagation are popular in computational ocean acoustics. For horizontally slowly varying waveguide environments, an adiabatic mode-parabolic…Houwang Tu, Yongxian Wang, Xiaolan Zhou et al.·Jul 17, 2024SaveLearn
Discrete element method model of soot aggregatesSoot is a component of atmospheric aerosols that affects climate by scattering and absorbing the sunlight. Soot particles are fractal aggregates composed of elemental carbon. In the atmosphere, the…Egor V. Demidov, Gennady Y. Gor, Alexei F. Khalizov·Jul 16, 2024SaveLearn
Thermalized and mixed meanfield ADP potentials for magnesium hydridesWe develop meanfield approximation and numerical quadrature schemes for the evaluation of Angular-Dependent interatomic Potentials (ADPs) for magnesium and magnesium hydrides at finite temperature…M. Molinos, M. Ortiz, M. P. Ariza·Jul 14, 2024SaveLearn
Uncertainty Quantification in Reduced-Order Gas-Phase Atmospheric Chemistry Modeling using Ensemble SINDyUncertainty quantification during atmospheric chemistry modeling is computationally expensive as it typically requires a large number of simulations using complex models. As large-scale modeling is…Lin Guo, Xiaokai Yang, Zhonghua Zheng et al.·Jul 13, 2024SaveLearn