Perfect cycles in the synchronous Heider dynamics in complete networkWe discuss a cellular automaton simulating the process of reaching Heider balance in a fully connected network. The dynamics of the automaton is defined by a deterministic, synchronous and global…Zdzislaw Burda, Malgorzata J. Krawczyk, Krzysztof Kulakowski·Jan 28, 2022SaveLearn
Full Configuration Interaction Excited-State Energies in Large Active Spaces from Subspace Iteration with Repeated Random SparsificationWe present a stable and systematically improvable quantum Monte Carlo (QMC) approach to calculating excited-state energies, which we implement using our fast randomized iteration method for the full…Samuel M. Greene, Robert J. Webber, James E. T. Smith et al.·Jan 28, 2022SaveLearn
Valley Piezoelectric Mechanism for Interpreting and Optimizing Piezoelectricity in Quantum Materials via Anomalous Hall EffectQuantum materials have exhibited attractive electro-mechanical responses, but their piezoelectric coefficients are far from satisfactory due to the lack of fundamental mechanisms to benefit from the…Yilimiranmu Rouzhahong, Chao Liang, Chong Li et al.·Jan 27, 2022SaveLearn
Data-driven and constrained optimization of semi-local exchange and non-local correlation functionals for materials and surface chemistryReliable predictions of surface chemical reaction energetics require an accurate description of both chemisorption and physisorption. Here, we present an empirical approach to simultaneously optimize…Kai Trepte, Johannes Voss·Jan 26, 2022SaveLearn
Voronoi cell analysis: The shapes of particle systemsMany physical systems can be studied as collections of particles embedded in space, evolving through deterministic evolution equations. Natural questions arise concerning how to characterize these…Emanuel A. Lazar, Jiayin Lu, Chris H. Rycroft·Jan 26, 2022SaveLearn
A hybrid adaptive multiresolution approach for the efficient simulation of reactive flowsComputational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This…Brandon Gusto, Tomasz Plewa·Jan 26, 2022SaveLearn
Deep neural networks for the prediction of the optical properties and the free-form inverse design of metamaterialsMany phenomena in physics, including light, water waves, and sound, are described by wave equations. Given their coefficients, wave equations can be solved to high accuracy, but the presence of the…Timo Gahlmann, Philippe Tassin·Jan 25, 2022SaveLearn
Capturing the influence of intermolecular potential in rarefied gas flows by a kinetic model with velocity-dependent collision frequencyA kinetic model called the -model is proposed to replace the complicated Boltzmann collision operator in the simulation of rarefied flows of monatomic gas. The model follows the relaxation-time…Yuan RuiFeng, Wu Lei·Jan 25, 2022SaveLearn
Two-fluid kinetic theory for dilute polymer solutionsWe provide a Boltzmann-type kinetic description for dilute polymer solutions based on two-fluid theory. This Boltzmann-type description uses a quasi-equilibrium based relaxation mechanism to model…Shiwani Singh, Ganesh Subramanian, Santosh Ansumali·Jan 25, 2022SaveLearn
Exploration vs Convergence Speed in Adaptive-bias Enhanced SamplingIn adaptive-bias enhanced sampling methods, a bias potential is added to the system to drive transitions between metastable states. The bias potential is a function of a few collective variables and…Michele Invernizzi, Michele Parrinello·Jan 24, 2022SaveLearn
Many-Body Effects in the X-ray Absorption Spectra of Liquid WaterX-ray absorption spectroscopy (XAS) is a powerful experimental technique to probe the local order in materials with core electron excitations. Experimental interpretation requires supporting…Fujie Tang, Zhenglu Li, Chunyi Zhang et al.·Jan 24, 2022SaveLearn
Training Data Selection for Accuracy and Transferability of Interatomic PotentialsAdvances in machine learning (ML) techniques have enabled the development of interatomic potentials that promise both the accuracy of first principles methods and the low-cost, linear scaling, and…David Montes de Oca Zapiain, Mitchell A. Wood, Nicholas Lubbers et al.·Jan 24, 2022SaveLearn
Fast kinetic simulator for relativistic matterWe present a new family of relativistic lattice kinetic schemes for the efficient simulation of relativistic flows in both strongly-interacting (fluid) and weakly-interacting (rarefied gas) regimes.…Victor Ambrus, Lorenzo Bazzanini, Alessandro Gabbana et al.·Jan 23, 2022SaveLearn
Clapeyron.jl: An extensible, open-source fluid-thermodynamics toolkitThermodynamic models are often vital when characterising complex systems, particularly natural gas, electrolyte, polymer, pharmaceutical and biological systems. However, their implementations have…Pierre J. Walker, Hon-Wa Yew, Andrés Riedemann·Jan 21, 2022SaveLearn
Towards energy discretization for muon scattering tomography in GEANT4 simulations: A discrete probabilistic approachIn this study, by attempting to eliminate the disadvantageous complexity of the existing particle generators, we present a discrete probabilistic scheme adapted for the discrete energy spectra in the…Ahmet Ilker Topuz, Madis Kiisk·Jan 21, 2022SaveLearn
Monte Carlo simulations in anomalous radiative transfer: a tutorialAnomalous radiative transfer (ART) theory is a generalization of classical radiative transfer theory. The present tutorial wants to show how Monte Carlo (MC) codes describing photons transport in…Tiziano Binzoni, Fabizio Martelli·Jan 20, 2022SaveLearn
A unified algorithm for interfacial flows with incompressible and compressible fluidsThe majority of available numerical algorithms for interfacial two-phase flows either treat both fluid phases as incompressible (constant density) or treat both phases as compressible (variable…Fabian Denner, Berend van Wachem·Jan 19, 2022SaveLearn
Particle generation through restrictive planes in GEANT4 simulations for potential applications of cosmic ray muon tomographyIn this study, by attempting to resolve the angular complication during the particle generation for the muon tomography applications in the GEANT4 simulations, we exhibit an unconventional…Ahmet Ilker Topuz, Madis Kiisk, Andrea Giammanco·Jan 18, 2022SaveLearn
The world beyond physics: how big is it?We discuss the possibility that the complexity of biological systems may lie beyond the predictive capabilities of theoretical physics: in Stuart Kauffman's words, there is a World Beyond Physics…Sauro Succi·Jan 18, 2022SaveLearn
Observing how deep neural networks understand physics through the energy spectrum of one-dimensional quantum mechanicsWe investigate how neural networks (NNs) understand physics using 1D quantum mechanics. After training an NN to accurately predict energy eigenvalues from potentials, we used it to confirm the NN's…Kenzo Ogure·Jan 18, 2022SaveLearn
Time-dependent dynamical Bragg diffraction in deformed crystals by beam propagation method (BPM)This paper describes how to efficiently solve time-dependent x-ray dynamic diffraction problems in distorted crystals with an FFT-based beam propagation method (FFT BPM). We show examples of using…Jacek Krzywinski, Aliaksei Halavanau·Jan 17, 2022SaveLearn
Improved three-dimensional thermal multiphase lattice Boltzmann model for liquid-vapor phase changeModeling liquid-vapor phase change using the lattice Boltzmann (LB) method has attracted significant attention in recent years. In this paper, we propose an improved three-dimensional (3D) thermal…Qing Li, Y. Yu, Kai. H. Luo·Jan 16, 2022SaveLearn
Physics-Informed Deep Learning for Solving Phonon Boltzmann Transport Equation with Large Temperature Non-EquilibriumPhonon Boltzmann transport equation (BTE) is a key tool for modeling multiscale phonon transport, which is critical to the thermal management of miniaturized integrated circuits, but assumptions…Ruiyang Li, Jian-Xun Wang, Eungkyu Lee et al.·Jan 12, 2022SaveLearn
GraphVAMPNet, using graph neural networks and variational approach to markov processes for dynamical modeling of biomoleculesFinding low dimensional representation of data from long-timescale trajectories of biomolecular processes such as protein-folding or ligand-receptor binding is of fundamental importance and kinetic…Mahdi Ghorbani, Samarjeet Prasad, Jeffery B. Klauda et al.·Jan 12, 2022SaveLearn
Hyperparameter Search using Genetic Algorithm for Surrogate Modeling of Geophysical FlowsThe computational models for geophysical flows are computationally very expensive to employ in multi-query tasks such as data assimilation, uncertainty quantification, and hence surrogate models…Suraj Pawar, Omer San, Gary G. Yen·Jan 7, 2022SaveLearn