Electrostatic T-matrix for a torus on bases of toroidal and spherical harmonicsSemi-analytic expressions for the static limit of the T-matrix for electromagnetic scattering are derived for a circular torus, expressed in bases of both toroidal and spherical harmonics. The…Matt Majic·Apr 24, 2019SaveLearn
An efficient numerical framework for the amplitude expansion of the phase-field crystal modelThe study of polycrystalline materials requires theoretical and computational techniques enabling multiscale investigations. The amplitude expansion of the phase field crystal model (APFC) allows for…Simon Praetorius, Marco Salvalaglio, Axel Voigt·Apr 24, 2019SaveLearn
Artificial Neural Networks as Trial Wave Functions for Quantum Monte CarloInspired by the universal approximation theorem and widespread adoption of artificial neural network techniques in a diversity of fields, we propose feed-forward neural networks as a general purpose…Jan Kessler, Francesco Calcavecchia, Thomas D. Kühne·Apr 23, 2019SaveLearn
Entropy: The former trouble with particles (including a new numerical model computational penalty for the Akaike information criterion)Traditional random-walk particle-tracking (PT) models of advection and dispersion do not track entropy, because particle masses remain constant. Newer mass-transfer particle tracking (MTPT) models…David A. Benson, Stephen Pankavich, Michael Schmidt et al.·Apr 23, 2019SaveLearn
Multicomponent Flow on Curved Surfaces: A Vielbein Lattice Boltzmann ApproachWe develop and implement a novel lattice Boltzmann scheme to study multicomponent flows on curved surfaces, coupling the continuity and Navier-Stokes equations with the Cahn-Hilliard equation to…Victor E. Ambruş, Sergiu Busuioc, Alexander J. Wagner et al.·Apr 22, 2019SaveLearn
Making the most of data: Quantum Monte Carlo Post-Analysis RevisitedIn quantum Monte Carlo (QMC) methods, energy estimators are calculated as the statistical average of the Markov chain sampling of energy estimator along with an associated statistical error. This…Tom Ichibha, Kenta Hongo, Ryo Maezono et al.·Apr 22, 2019SaveLearn
A conservative discrete velocity method for the ellipsoidal Fokker-Planck equation in gas-kinetic theoryA conservative discrete velocity method (DVM) is developed for the ellipsoidal Fokker-Planck (ES-FP) equation in prediction of non-equilibrium neutral gas flows in this paper. The ES-FP collision…Sha Liu, Ruifeng Yuan, Usman Javid et al.·Apr 20, 2019SaveLearn
DeepMoD: Deep learning for Model Discovery in noisy dataWe introduce DeepMoD, a Deep learning based Model Discovery algorithm. DeepMoD discovers the partial differential equation underlying a spatio-temporal data set using sparse regression on a library…Gert-Jan Both, Subham Choudhury, Pierre Sens et al.·Apr 20, 2019SaveLearn
Acceleration of the Power Method with Dynamic Mode DecompositionPresented is an algorithm based on dynamic mode decomposition (DMD) for acceleration of the power method (PM). The power method is a simple technique for determining the dominant eigenmode of an…Jeremy A. Roberts, Leidong Xu, Rabab Elzohery et al.·Apr 20, 2019SaveLearn
An energy-conserving and asymptotic-preserving charged-particle orbit implicit time integrator for arbitrary electromagnetic fieldsWe present a new implicit asymptotic preserving time integration scheme for charged-particle orbit computation in arbitrary electromagnetic fields. The scheme is built on the Crank-Nicolson…Lee F. Ricketson, Luis Chacón·Apr 20, 2019SaveLearn
Semi-Lagrangian Exponential Integration with application to the rotating shallow water equationsIn this paper we propose a novel way to integrate time-evolving partial differential equations that contain nonlinear advection and stiff linear operators, combining exponential integration…Pedro da Silva Peixoto, Martin Schreiber·Apr 19, 2019SaveLearn
Spin wave dispersion of 3d ferromagnets based on QSGW calculationsWe calculate transverse spin susceptibility in the linear response method based on the ground states determined in the quasi-particle self-consistent GW (QSGW) method. Then we extract spin wave…Haruki Okumura, Kazunori Sato, Takao Kotani·Apr 19, 2019SaveLearn
Semi-implicit methods for the dynamics of elastic sheetsRecent applications (e.g. active gels and self-assembly of elastic sheets) motivate the need to efficiently simulate the dynamics of thin elastic sheets. We present semi-implicit time stepping…Silas Alben, Alex A. Gorodetsky, Donghak Kim et al.·Apr 19, 2019SaveLearn
Physical Symmetries Embedded in Neural NetworksNeural networks are a central technique in machine learning. Recent years have seen a wave of interest in applying neural networks to physical systems for which the governing dynamics are known and…M. Mattheakis, P. Protopapas, D. Sondak et al.·Apr 18, 2019SaveLearn
Complex time, shredded propagator method for large-scale GW calculationsThe GW method is a many-body electronic structure technique capable of generating accurate quasiparticle properties for realistic systems spanning physics, chemistry, and materials science. Despite…Minjung Kim, Glenn J. Martyna, Sohrab Ismail-Beigi·Apr 18, 2019SaveLearn
Effect of lattice shrinking on the migration of water within zeolite LTAWater adsorption within zeolites of the Linde Type A (LTA) structure plays an important role in processes of water removal from solvents. For this purpose, knowing in which adsorption sites water is…Julio E. Perez-Carbajo, Salvador R. G. Balestra, Sofia Calero et al.·Apr 17, 2019SaveLearn
Dimensionless solutions and general characteristics of bioheat transfer during thermal therapyThe derivation and application of the general characteristics of bioheat transfer for medical applications are shown in this paper. Two general bioheat transfer characteristics are derived from…Junnosuke Okajima, Shigenao Maruyama, Hiroki Takeda et al.·Apr 15, 2019SaveLearn
An a posteriori verification method for generalized real-symmetric eigenvalue problems in large-scale electronic state calculationsAn a posteriori verification method is proposed for the generalized real-symmetric eigenvalue problem and is applied to densely clustered eigenvalue problems in large-scale electronic state…Takeo Hoshi, Takeshi Ogita, Katsuhisa Ozaki et al.·Apr 13, 2019SaveLearn
Deep-learning PDEs with unlabeled data and hardwiring physics lawsProviding fast and accurate solutions to partial differential equations is a problem of continuous interest to the fields of applied mathematics and physics. With the recent advances in machine…S. Mohammad H. Hashemi, Demetri Psaltis·Apr 13, 2019SaveLearn
Quantum Point Contact Parameter Extraction of Carbon-based Resistive Memory using Hybrid Genetic AlgorithmResistive switching phenomenon in carbon film is associated with formation and annihilation of low resistance sp2 nanochannels within the amorphous sp3 matrix. The thinnest point of these graphitic…Ee Wah Lim·Apr 13, 2019SaveLearn
Approximation of tensor fields on surfaces of arbitrary topology based on local Monge parametrizationsWe introduce a new method, the Local Monge Parametrizations (LMP) method, to approximate tensor fields on general surfaces given by a collection of local parametrizations, e.g.~as in finite element…Alejandro Torres-Sánchez, Daniel Santos-Oliván, Marino Arroyo·Apr 12, 2019SaveLearn
NeuDATool: An Open Source Neutron Data Analysis Tools, Supporting GPU Hardware Acceleration, and Across-computer Cluster Nodes ParallelEmpirical potential structure refinement (EPSR) is a neutron scattering data analysis algorithm and a software package. It was developed by the British spallation neutron source (ISIS) Disordered…Changli Ma, He Cheng, Taisen Zuo et al.·Apr 12, 2019SaveLearn
A group theoretical approach to computing phonons and their interactionsHere we present four independent advances which facilitate the computation of phonons and their interactions from first-principles. First, we implement a group-theoretical approach to construct the…Lyuwen Fu, Mordechai Kornbluth, Zhengqian Cheng et al.·Apr 12, 2019SaveLearn
Acoustic cloaking: geometric transform, homogenization and a genetic algorithmA general process is proposed to experimentally design anisotropic inhomogeneous metamaterials obtained through a change of coordinate in the Helmholtz equation. The method is applied to the case of…Lucas Pomot, Cédric Payan, Marcel Remillieux et al.·Apr 12, 2019SaveLearn
Deep learning methods based on cross-section images for predicting effective thermal conductivity of compositesEffective thermal conductivity is an important property of composites for different thermal management applications. Although physics-based methods, such as effective medium theory and solving…Qingyuan Rong, Han Wei, Hua Bao·Apr 12, 2019SaveLearn