Compression and information entropy of binary strings from the collision history of three hard ballsWe investigate how to measure and define the entropy of a simple chaotic system, three hard spheres on a ring. A novel approach is presented, which does not assume the ergodic hypothesis. It consists…Matej Vedak, Graeme J Ackland·Feb 14, 2023SaveLearn
A unified gas-kinetic particle method for frequency-dependent radiative transfer equations with isotropic scattering process on unstructured meshIn this paper, we extend the unified kinetic particle (UGKP) method to the frequency-dependent radiative transfer equation with both absorption-emission and scattering processes. The extended UGKP…Yuan Hu, Chang Liu·Feb 14, 2023SaveLearn
Code-Verification Techniques for the Method-of-Moments Implementation of the Combined-Field Integral EquationCode verification plays an important role in establishing the credibility of computational simulations by assessing the correctness of the implementation of the underlying numerical methods. In…Brian A. Freno, Neil R. Matula·Feb 13, 2023SaveLearn
Magnetohydrodynamics with Physics Informed Neural OperatorsThe modeling of multi-scale and multi-physics complex systems typically involves the use of scientific software that can optimally leverage extreme scale computing. Despite major developments in…Shawn G. Rosofsky, E. A. Huerta·Feb 13, 2023SaveLearn
An implicit unified gas-kinetic wave-particle method for radiative transport processThe unified gas-kinetic wave-particle method (UGKWP) has been developed for the multiscale gas, plasma, and multiphase flow transport processes for the past years. In this work, we propose an…Chang Liu, Weiming Li, Peng Song et al.·Feb 13, 2023SaveLearn
Meta-GGA density functional calculations on atoms with spherically symmetric densities in the finite element formalismDensity functional calculations on atoms are often used for determining accurate initial guesses as well as generating various types of pseudopotential approximations and efficient atomic-orbital…Susi Lehtola·Feb 13, 2023SaveLearn
Efficient generation of random rotation matrices in four dimensionsMarkov-chain Monte Carlo algorithms rely on trial moves that are either rejected or accepted based on certain criteria. Here, we provide an efficient algorithm to generate random rotation matrices in…Jakob Tómas Bullerjahn, Balázs Fábián, Gerhard Hummer·Feb 13, 2023SaveLearn
Study of chaos in rotating galaxies using extended force-gradient symplectic methodsWe take into account the dynamics of three types of models of rotating galaxies in polar coordinates in a rotating frame. Due to non-axisymmetric potential perturbations, the angular momentum varies…Li-Na Zhang, Wen-Fang Liu, Xin Wu·Feb 13, 2023SaveLearn
Ferroelectric Antiferromagnetic Quantum Anomalous Hall Insulator in TwoDimensional van der Waals MaterialsFerroelectricity, anti-ferromagnetism (AFM) and quantum anomalous Hall effect (QAHE) are three fundamental phenomena in the field of condensed matter physics, which could enable the realization of…Yan Liang, Fulu Zheng, Thomas Frauenheim et al.·Feb 10, 2023SaveLearn
Analysis of dynamical effects in the uniform electron liquids with the self-consistent method of moments complemented by the Shannon information entropy and the path-integral Monte-Carlo simulationsDynamical properties of uniform electron fluids (jellium model) are studied within a novel non-perturbative approach consisting in the combination of the self-consistent version of the method of…A. Filinov, J. Ara, I. M. Tkachenko·Feb 10, 2023SaveLearn
How the exchange energy can affect the power laws used to extrapolate the coupled cluster correlation energy to the thermodynamic limitFinite size error is commonly removed from coupled cluster theory calculations by N-1 extrapolations over correlation energy calculations of different system sizes (N), where the N-1…Tina N. Mihm, Laura Weiler, James J. Shepherd·Feb 10, 2023SaveLearn
Linear-response time-dependent density functional theory approach to warm dense matter with adiabatic exchange--correlation kernelsWe present a new methodology for the linear-response time-dependent density functional theory (LR-TDDFT) calculation of the dynamic density response function of warm dense matter in an adiabatic…Zhandos A. Moldabekov, Michele Pavanello, Maximilian P. Boehme et al.·Feb 9, 2023SaveLearn
Reduction of Autocorrelation Times in Lattice Path Integral Quantum Monte Carlo via Direct Sampling of the Truncated Exponential DistributionIn Monte Carlo simulations, proposed configurations are accepted or rejected according to an acceptance ratio, which depends on an underlying probability distribution and an a priori sampling…Emanuel Casiano-Diaz, Kipton Barros, Ying Wai Li et al.·Feb 8, 2023SaveLearn
Inverse asymptotic treatment: capturing discontinuities in fluid flows via equation modificationA major challenge in developing accurate and robust numerical solutions to multi-physics problems is to correctly model evolving discontinuities in field quantities, which manifest themselves as…Shahab Mirjalili, Søren Taverniers, Henry Collis et al.·Feb 8, 2023SaveLearn
Field emitter electrostatics: efficient improved simulation technique for highly precise calculation of field enhancement factorsWhen solving the Laplace equation numerically via computer simulation, in order to determine the field values at the surface of a shape model that represents a field emitter, it is necessary to…Fernando F. Dall'Agnol, Thiago A. de Assis, Richard G. Forbes·Feb 7, 2023SaveLearn
Molybdenum Carbide MXenes as Efficient Nanosensors Towards Selected Chemical Warfare AgentsThere has been budding demand for the fast, reliable, inexpensive, non-invasive, sensitive, and compact sensors with low power consumption in various fields, such as defence, chemical sensing, health…Puspamitra Panigrahi, Yash Pal, Thanayut Kaewmaraya et al.·Feb 7, 2023SaveLearn
A neural operator-based surrogate solver for free-form electromagnetic inverse designNeural operators have emerged as a powerful tool for solving partial differential equations in the context of scientific machine learning. Here, we implement and train a modified Fourier neural…Yannick Augenstein, Taavi Repän, Carsten Rockstuhl·Feb 4, 2023SaveLearn
Solving two-dimensional quantum eigenvalue problems using physics-informed machine learningA particle confined to an impassable box is a paradigmatic and exactly solvable one-dimensional quantum system modeled by an infinite square well potential. Here we explore some of its infinitely…Elliott G. Holliday, John F. Lindner, William L. Ditto·Feb 2, 2023SaveLearn
High-precision regressors for particle physicsMonte Carlo simulations of physics processes at particle colliders like the Large Hadron Collider at CERN take up a major fraction of the computational budget. For some simulations, a single data…Fady Bishara, Ayan Paul, Jennifer Dy·Feb 2, 2023SaveLearn
On the equivalence of the hybrid particle-field and Gaussian core modelsHybrid particle-field molecular dynamics is a molecular simulation strategy wherein particles couple to a density field instead of through ordinary pair potentials. Traditionally considered a…Morten Ledum, Samiran Sen, Sigbjørn Løland Bore et al.·Feb 2, 2023SaveLearn
Hamiltonian formulation and symplectic split-operator schemes for time-dependent density-functional-theory equations of electron dynamics in moleculesWe revisit Kohn-Sham time-dependent density-functional theory (TDDFT) equations and show that they derive from a canonical Hamiltonian formalism. We use this geometric description of the TDDFT…Francois Mauger, Cristel Chandre, Mette B. Gaarde et al.·Feb 2, 2023SaveLearn
Accelerating the calculation of electron-phonon coupling by machine learning methodsElectron-phonon coupling (EPC) plays an important role in many fundamental physical phenomena, but the high computational cost of the EPC matrix hinders the theoretical research on them. In this…Yang Zhong, Zhiguo Tao, Weibin Chu et al.·Feb 1, 2023SaveLearn
A hybrid immersed boundary method for dense particle-laden flowsA novel smooth immersed boundary method (IBM) based on a direct-forcing formulation is proposed to simulate incompressible dense particle-laden flows. This IBM relies on a regularization of the…Victor Chéron, Fabien Evrard, Berend van Wachem·Jan 31, 2023SaveLearn
A Self-Adaptive Algorithm of the Clean Numerical Simulation (CNS) for ChaosThe background numerical noise 0 is determined by the maximum of truncation error and round-off error. For a chaotic system, the numerical error (t) grows exponentially,…Shijie Qin, Shijun Liao·Jan 31, 2023SaveLearn
Physics-informed machine learning and stray field computation with application to micromagnetic energy minimizationWe study the full 3d static micromagnetic equations via a physics-informed neural network (PINN) ansatz for the continuous magnetization configuration. PINNs are inherently mesh-free and unsupervised…Sebastian Schaffer, Thomas Schrefl, Harald Oezelt et al.·Jan 31, 2023SaveLearn