Regularized integral equation methods for elastic scattering problems in three dimensionsThis paper presents novel methodologies for the numerical simulation of scattering of elastic waves by both closed and open surfaces in three-dimensional space. The proposed approach utilizes new…Oscar P. Bruno, Tao Yin·Sep 27, 2019SaveLearn
Fermionic neural-network states for ab-initio electronic structureNeural-network quantum states have been successfully used to study a variety of lattice and continuous-space problems. Despite a great deal of general methodological developments, representing…Kenny Choo, Antonio Mezzacapo, Giuseppe Carleo·Sep 27, 2019SaveLearn
Efficient computation of the density matrix with error control on distributed computer systemsThe recursive polynomial expansion for construction of a density matrix approximation with rigorous error control [J. Chem. Phys. 128, 074106 (2008)] is implemented in the quantum chemistry program…Anastasia Kruchinina, Elias Rudberg, Emanuel H. Rubensson·Sep 27, 2019SaveLearn
Deep learning meets nanophotonics: A generalized accurate predictor for near fields and far fields of arbitrary 3D nanostructuresDeep artificial neural networks are powerful tools with many possible applications in nanophotonics. Here, we demonstrate how a deep neural network can be used as a fast, general purpose predictor of…Peter R. Wiecha, Otto L. Muskens·Sep 26, 2019SaveLearn
Boundary-element method to analyze acoustic scattering from a coupled swimbladder-fish body configurationA model for computing acoustic scattering by a swimbladdered fish with coupling to surrounding fish tissue that is assumed to behave as a homogeneous fluid, is presented. Mathematically, this…Juan D. Gonzalez, Edmundo F. Lavia, Silvia Blanc et al.·Sep 25, 2019SaveLearn
Active Learning the Coarse-Grained Energy Landscape For Water Clusters From Sparse Training DataANNs are currently trained by generating large quantities (On the order of 104 or greater) of structural data in hopes that the ANN has adequately sampled the energy landscape both near and…Troy D. Loeffler, Tarak K. Patra, Henry Chan et al.·Sep 25, 2019SaveLearn
A high order continuation method to locate exceptional points and to compute Puiseux series with applications to acoustic waveguidesA numerical algorithm is proposed to explore in a systematic way the trajectories of the eigenvalues of non-Hermitian matrices in the parametric space and exploit this in order to find the locations…Benoit Nennig, Emmanuel Perrey-Debain·Sep 25, 2019SaveLearn
Comparison of the Shakhov and ellipsoidal models for the Boltzmann equation and DSMC for ab initio-based particle interactionsIn this paper, we consider the capabilities of the Boltzmann equation with the Shakhov and ellipsoidal models for the collision term to capture the characteristics of rarefied gas flows. The…Victor E. Ambrus, Felix Sharipov, Victor Sofonea·Sep 25, 2019SaveLearn
Machine Learning Surrogate Models for Landau Fluid ClosureThe first result of applying the machine/deep learning technique to the fluid closure problem is presented in this paper. As a start, three different types of neural networks (multilayer perceptron…Chenhao Ma, Ben Zhu, Xue-qiao Xu et al.·Sep 25, 2019SaveLearn
Temperature expressions and ergodicity of the Nosé-Hoover deterministic schemesThermostats are dynamic equations used to model thermodynamic variables in molecular dynamics. The applicability of thermostats is based on the ergodic hypothesis. The most commonly used thermostats…A. Samoletov, B. Vasiev·Sep 25, 2019SaveLearn
DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal SystemsExtracting actionable insight from complex unlabeled scientific data is an open challenge and key to unlocking data-driven discovery in science. Complementary and alternative to supervised machine…Adam Rupe, Nalini Kumar, Vladislav Epifanov et al.·Sep 25, 2019SaveLearn
Machine learning approaches for analyzing and enhancing molecular dynamics simulationsMolecular dynamics (MD) has become a powerful tool for studying biophysical systems, due to increasing computational power and availability of software. Although MD has made many contributions to…Yihang Wang, Joao Marcelo Lamim Ribeiro, Pratyush Tiwary·Sep 25, 2019SaveLearn
Multiple eigenvectors around the homo-lumo gap as a cheap by-product in linear scaling electronic structure calculationsIn this work we present and evaluate an implementation of the purify-shift-and-project method [J. Chem. Phys. 128, 176101 (2008)] for linear scaling computation of multiple eigenvectors around the…Anastasia Kruchinina·Sep 25, 2019SaveLearn
Enhanced high harmonic generation in semiconductors by the excitation with multi-color pulsesWe investigate high-order harmonic generation in ZnO driven by linearly polarized multi-color pulses. It is shown that the intensities of the harmonics in the plateau region can be enhanced by two to…Xiaohong Song, Shidong Yang, Ruixin Zuo et al.·Sep 25, 2019SaveLearn
rp-adaptation for compressible flowsWe present an rp-adaptation strategy for high-fidelity simulation of compressible inviscid flows with shocks. The mesh resolution in regions of flow discontinuities is increased by using a…Julian Marcon, Giacomo Castiglioni, David Moxey et al.·Sep 24, 2019SaveLearn
Recurrent Neural Network-based Model for Accelerated Trajectory Analysis in AIMD SimulationsThe presented work demonstrates the training of recurrent neural networks (RNNs) from distributions of atom coordinates in solid state structures that were obtained using ab initio molecular dynamics…Mohammad Javad Eslamibidgoli, Mehrdad Mokhtari, Michael H. Eikerling·Sep 23, 2019SaveLearn
Controlling bubble coalescence in metallic foams: A simple phase field-based approachThe phase-field method is used as a basis to develop a strictly mass conserving, yet simple, model for simulation of two-phase flow. The model is aimed to be applied for the study of structure…Samad Vakili, Ingo Steinbach, Fathollah Varnik·Sep 23, 2019SaveLearn
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEsPhysics-informed neural networks (PINNs) encode physical conservation laws and prior physical knowledge into the neural networks, ensuring the correct physics is represented accurately while…Xuhui Meng, Zhen Li, Dongkun Zhang et al.·Sep 23, 2019SaveLearn
Robust Field-Only Surface Integral Equations: Scattering from a Perfect Electric ConductorA robust field-only boundary integral formulation of electromagnetics is derived without the use of surface currents that appear in the Stratton-Chu formulation. For scattering by a perfect…Qiang Sun, Evert Klaseboer, Alex J. Yuffa et al.·Sep 22, 2019SaveLearn
d-SEAMS: Deferred Structural Elucidation Analysis for Molecular SimulationsStructural analyses are an integral part of computational research on nucleation and supercooled water, whose accuracy and efficiency can impact the validity and feasibility of such studies. The…Rohit Goswami, Amrita Goswami, Jayant K. Singh·Sep 21, 2019SaveLearn
Deep Conservation: A latent-dynamics model for exact satisfaction of physical conservation lawsThis work proposes an approach for latent-dynamics learning that exactly enforces physical conservation laws. The method comprises two steps. First, the method computes a low-dimensional embedding of…Kookjin Lee, Kevin Carlberg·Sep 21, 2019SaveLearn
A thermodynamically consistent pseudo-potential lattice Boltzmann model for multi-component, multiphase, partially miscible mixturesCurrent multi-component, multiphase pseudo-potential lattice Boltzmann models have thermodynamic inconsistencies that prevent them to correctly predict the thermodynamic phase behavior of partially…Cheng Peng, Luis F. Ayala, Orlando M. Ayala·Sep 20, 2019SaveLearn
Time-step dependent force interpolation scheme for suppressing numerical Cherenkov instability in relativistic particle-in-cell simulationsThe WT scheme, a piecewise polynomial force interpolation scheme with time-step dependency, is proposed in this paper for relativistic particle-in-cell (PIC) simulations. The WT scheme removes the…Yingchao Lu, Patrick Kilian, Fan Guo et al.·Sep 20, 2019SaveLearn
Computation of the solid-liquid interfacial free energy in hard spheres by means of thermodynamic integrationWe used a thermodynamic integration scheme, which is specifically designed for disordered systems, to compute the interfacial free energy of the solid-liquid interface in the hard-sphere model. We…Moritz Bültmann, Tanja Schilling·Sep 20, 2019SaveLearn
Efficient Simulation of Field/Circuit Coupled Systems with Parallelised Waveform RelaxationThis paper proposes an efficient parallelised computation of field/circuit coupled systems co-simulated with the Waveform Relaxation (WR) technique. The main idea of the introduced approach lies in…Idoia Cortes Garcia, Iryna Kulchytska-Ruchka, Sebastian Schöps·Sep 19, 2019SaveLearn