fPINNs: Fractional Physics-Informed Neural NetworksPhysics-informed neural networks (PINNs) are effective in solving integer-order partial differential equations (PDEs) based on scattered and noisy data. PINNs employ standard feedforward neural…Guofei Pang, Lu Lu, George Em Karniadakis·Nov 20, 2018SaveLearn
Feasibility analysis of ensemble sensitivity computation in turbulent flowsIn chaotic systems, such as turbulent flows, the solutions to tangent and adjoint equations exhibit an unbounded growth in their norms. This behavior renders the instantaneous tangent and adjoint…Nisha Chandramoorthy, Pablo Fernandez, Chaitanya Talnikar et al.·Nov 19, 2018SaveLearn
Updated Core Libraries of the ALPS ProjectThe open source ALPS (Algorithms and Libraries for Physics Simulations) project provides a collection of physics libraries and applications, with a focus on simulations of lattice models and strongly…Markus Wallerberger, Sergei Iskakov, Alexander Gaenko et al.·Nov 19, 2018SaveLearn
Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning ModelWe present the incorporation of a surrogate Gaussian Process Regression (GPR) atomistic model to greatly accelerate the rate of convergence of classical Nudged Elastic Band (NEB) calculations. In our…José A. Garrido Torres, Paul C. Jennings, Martin H. Hansen et al.·Nov 19, 2018SaveLearn
Particle-without-Particle: a practical pseudospectral collocation method for linear partial differential equations with distributional sourcesPartial differential equations with distributional sources---in particular, involving (derivatives of) delta distributions---have become increasingly ubiquitous in numerous areas of physics and…Marius Oltean, Carlos F. Sopuerta, Alessandro D. A. M. Spallicci·Nov 19, 2018SaveLearn
Particle coalescing with angular momentum conservation in SPH simulationsThe present work introduces a simple, yet effective particle coalescing procedure for two-dimensional SPH simulations with spatially varying resolution. In addition to the regular conservation…Balázs Havasi-Tóth·Nov 18, 2018SaveLearn
Constructing high-order discontinuity-capturing schemes with linear-weight polynomials and boundary variation diminishing algorithmIn this study, a new framework of constructing very high order discontinuity-capturing schemes is proposed for finite volume method. These schemes, so-called…Xi Deng, Yuya Shimizu, Feng Xiao·Nov 18, 2018SaveLearn
An Unconditionally Energy-Stable Scheme Based on an Implicit Auxiliary Energy Variable for Incompressible Two-Phase Flows with Different Densities Involving Only Precomputable Coefficient MatricesWe present an energy-stable scheme for numerically approximating the governing equations for incompressible two-phase flows with different densities and dynamic viscosities for the two fluids. The…Z. Yang, S. Dong·Nov 18, 2018SaveLearn
Implicit High-Order Gas Kinetic Scheme for Turbulence SimulationIn recent years, coupled with traditional turbulence models, the second-order gas-kinetic scheme (GKS) has been used in the turbulent flow simulations. At the same time, high-order GKS has been…Guiyu Cao, Hongmin Su, Jinxiu Xu et al.·Nov 16, 2018SaveLearn
Co-located diffuse approximation method for two dimensional incompressible channel flowsThe main contribution of this paper is the formulation of a diffuse approximation method(DAM), for two-dimensional channel flows. The proposed method is based on the vorticity-streamfunction…Christian Prax, Hamou Sadat·Nov 16, 2018SaveLearn
Precise Kohn-Sham total-energy calculations at reduced costThe standard way to calculate the Kohn-Sham orbitals utilizes an approximation of the potential. The approximation consists in a projection of the potential into a finite subspace of basis functions.…Rudolf Zeller·Nov 16, 2018SaveLearn
An Optimizing Symbolic Algebra Approach for Generating Fast Multipole Method OperatorsWe have developed a symbolic algebra approach to automatically produce, verify, and optimize computer code for the Fast Multipole Method (FMM) operators. This approach allows for flexibility in…Jonathan P. Coles, Rebekka Bieri·Nov 15, 2018SaveLearn
Histogram-Free Multicanonical Monte Carlo Sampling to Calculate the Density of StatesWe report a new multicanonical Monte Carlo algorithm to obtain the density of states for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain a…Alfred C. K. Farris, Ying Wai Li, Markus Eisenbach·Nov 15, 2018SaveLearn
Time-Reversible, Symplectic, Angular Velocity Based Integrator for Rigid Linear MoleculesA very simple explicit integrator for the rotational motion of rigid linear molecules is presented which can preserve the rigidity of the molecules without requiring any constraint force. The…Somajit Dey·Nov 15, 2018SaveLearn
Nonlinearly Bandlimited SignalsIn this paper, we study the inverse scattering problem for a class of signals that have a compactly supported reflection coefficient. The problem boils down to the solution of the…Vishal Vaibhav·Nov 15, 2018SaveLearn
Free-stream preserving linear-upwind and WENO schemes on curvilinear gridsApplying high-order finite-difference schemes, like the extensively used linear-upwind or WENO schemes, to curvilinear grids can be problematic. The geometrically induced error from grid Jacobian and…Yujie Zhu, Xiangyu Hu·Nov 15, 2018SaveLearn
Efficient prediction of 3D electron densities using machine learningThe Kohn-Sham scheme of density functional theory is one of the most widely used methods to solve electronic structure problems for a vast variety of atomistic systems across different scientific…Mihail Bogojeski, Felix Brockherde, Leslie Vogt-Maranto et al.·Nov 15, 2018SaveLearn
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materialsWe introduce the use of Crystal Graph Convolutional Neural Networks (CGCNN), Fully Connected Neural Networks (FCNN) and XGBoost to predict thermoelectric properties. The dataset for the CGCNN is…Leo Laugier, Daniil Bash, Jose Recatala et al.·Nov 15, 2018SaveLearn
Symmetries and Local Conservation Laws of Variational Schemes for the Surface Plasmon PolaritonsThe relation between symmetries and local conservation laws, known as Noether's theorem, plays an important role in modern theoretical physics. As a discrete analog of the differentiable physical…Qiang Chen, Xiaojun Hao, Chuanchuan Wang et al.·Nov 14, 2018SaveLearn
On the physical inadmissibility of ILES for simulations of Euler equation turbulenceWe present two main results. The first is a plausible validation argument for the principle of a maximal rate of entropy production for Euler equation turbulence. This principle can be seen as an…James Glimm, Baolian Cheng, David H. Sharp et al.·Nov 14, 2018SaveLearn
Simulating fluids with a computer: Introduction and recent advancesIn this article, I present recent methods for the numerical simulation of fluid dynamics and the associated computational algorithms. The goal of this article is to explain how to model an…Bruno Levy·Nov 14, 2018SaveLearn
Accelerating and parallelizing Lagrangian simulations of mixing-limited reactive transportRecent advances in random-walk particle-tracking have enabled direct simulation of mixing and reactions on particles by allowing the particles to interact with each other using a multi-point mass…Nicholas B. Engdahl, Michael J. Schmidt, David A. Benson·Nov 13, 2018SaveLearn
Hermite integrator for high-order mesh-free schemesIn most of mesh-free methods, the calculation of interactions between sample points or particles is the most time consuming. When we use mesh-free methods with high spatial orders, the order of the…Satoko Yamamoto, Junichiro Makino·Nov 13, 2018SaveLearn
Ultracold Neutron Storage Simulation Using the Kassiopeia Software PackageThe Kassiopeia software package was originally developed to simulate electromagnetic fields and charged particle trajectories for neutrino mass measurement experiments. Recent additions to Kassiopeia…Z Bogorad, P M Murthy, J A Formaggio·Nov 13, 2018SaveLearn
A Load Balance Strategy for Hybrid Particle-Mesh MethodsWe present a load balancing strategy for hybrid particle-mesh methods that is based on domain decomposition and element-local time measurement. This new strategy is compared to our previous approach,…P. Ortwein, T. Binder, S. Copplestone et al.·Nov 13, 2018SaveLearn