Adjoint computations by algorithmic differentiation of a parallel solver for time-dependent PDEsA computational fluid dynamics code is differentiated using algorithmic differentiation (AD) in both tangent and adjoint modes. The two novelties of the present approach are 1) the adjoint code is…J. I. Cardesa, L. Hascoët, C. Airiau·Dec 25, 2019SaveLearn
A re-formulization of the transfer matrix method for calculating wave-functions in higher dimensional disordered open systemsWe present a numerically stable re-formulization of the transfer matrix method (TMM). The iteration form of the traditional TMM is transformed into solving a set of linear equations. Our method gains…Liang Chen, Cheng Lv, Xunya Jiang·Dec 25, 2019SaveLearn
Evaluation of the spectrum of a quantum system using machine learning based on incomplete information about the wavefunctionsWe propose an effective approach to rapid estimation of the energy spectrum of quantum systems with the use of machine learning (ML) algorithm. In the ML approach (back propagation), the wavefunction…Gennadiy Burlak·Dec 24, 2019SaveLearn
Interfacial Atomic Number Contrast in Thick TEM SamplesThe atomic number contrast imaging technique reveals an increase in intensity at interfaces of a high and low-density material in case of relatively thick samples. Elastic scattering factors and…Aniruddha Dutta, Helge Heinrich·Dec 24, 2019SaveLearn
Multi-level Convolutional Autoencoder Networks for Parametric Prediction of Spatio-temporal DynamicsA data-driven framework is proposed towards the end of predictive modeling of complex spatio-temporal dynamics, leveraging nested non-linear manifolds. Three levels of neural networks are used, with…Jiayang Xu, Karthik Duraisamy·Dec 23, 2019SaveLearn
Artificial neural network subgrid models of 2-D compressible magnetohydrodynamic turbulenceWe explore the suitability of deep learning to capture the physics of subgrid-scale ideal magnetohydrodynamics turbulence of 2-D simulations of the magnetized Kelvin-Helmholtz instability. We produce…Shawn G. Rosofsky, E. A. Huerta·Dec 23, 2019SaveLearn
Identification and Resolution of Unphysical Multielectron Excitations in the Real-Time Time-Dependent Kohn-Sham FormulationWe resolve a fundamental issue associated with the conventional Kohn-Sham formulation of real-time time-dependent density functional theory. We show that unphysical multielectron excitations,…Xiaoning Zang, Udo Schwingenschlogl, Mark T. Lusk·Dec 23, 2019SaveLearn
Simulating collective neutrinos oscillations on the Intel Many Integrated Core (MIC) architectureWe evaluate the second-generation Intel Xeon Phi coprocessor based on the Intel Many Integrated Core (MIC) architecture, aka the Knights Landing or KNL, for simulating neutrino oscillations in…Vahid Noormofidi, Susan R. Atlas, Huaiyu Duan·Dec 23, 2019SaveLearn
Extreme acoustic anisotropy in crystals visualized by diffraction tensorAcoustic wave propagation in single crystals, metamaterials and composite structures is a basic mechanism in acoustic, acousto-electronic and acousto-optic devices. Acoustic anisotropy of crystals…Natalya Naumenko, Konstantin Yushkov, Vladimir Molchanov·Dec 21, 2019SaveLearn
Numerical solution of large scale Hartree-Fock-Bogoliubov equationsThe Hartree-Fock-Bogoliubov (HFB) theory is the starting point for treating superconducting systems. However, the computational cost for solving large scale HFB equations can be much larger than that…Lin Lin, Xiaojie Wu·Dec 21, 2019SaveLearn
kramersmoyal: Kramers--Moyal coefficients for stochastic processeskramersmoyal is a python library to extract the Kramers--Moyal coefficients from timeseries of any dimension and to any desired order. This package employs a non-parametric Nadaraya--Watson…Leonardo Rydin Gorjão, Francisco Meirinhos·Dec 20, 2019SaveLearn
Memory-efficient Lattice Boltzmann Method for low Reynolds number flowsThe Lattice Boltzmann Method algorithm is simplified by assuming constant numerical viscosity (the relaxation time is fixed at τ=1). This leads to the removal of the distribution function from the…Maciej Matyka, Michał Dzikowski·Dec 19, 2019SaveLearn
Coupled Elastic-Acoustic Modelling for Quantitative Photoacoustic TomographyQuantitative photoacoustic tomography (qPAT) is an imaging technique aimed at estimating chromophore concentrations inside tissues from photoacoustic images, which are formed by combining optical…Hwan Goh, Timo Lahivaara, Tanja Tarvainen et al.·Dec 19, 2019SaveLearn
Probe Ferroelectricity by X-ray Absorption Spectroscopy in Molecular CrystalWe carry out X-ray absorption spectroscopy experiment at oxygen K-edge in croconic acid (C5H2O5) crystal as a prototype of ferroelectric organic molecular solid, whose electric polarization is…Fujie Tang, Xuanyuan Jiang, Hsin-Yu Ko et al.·Dec 19, 2019SaveLearn
Temporal Normalizing FlowsAnalyzing and interpreting time-dependent stochastic data requires accurate and robust density estimation. In this paper we extend the concept of normalizing flows to so-called temporal Normalizing…Gert-Jan Both, Remy Kusters·Dec 19, 2019SaveLearn
Fast and stable deep-learning predictions of material properties for solid solution alloysWe present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to…Massimiliano Lupo Pasini, Ying Wai Li, Junqi Yin et al.·Dec 18, 2019SaveLearn
CASSCF with Extremely Large Active Spaces using the Adaptive Sampling Configuration Interaction MethodThe complete active space self-consistent field (CASSCF) method is the principal approach employed for studying strongly correlated systems. However, exact CASSCF can only be performed on small…Daniel S. Levine, Diptarka Hait, Norm M. Tubman et al.·Dec 18, 2019SaveLearn
New interaction potentials for borate glasses with mixed network formersWe adapt and apply a recently developed optimization scheme used to obtain effective potentials for aluminosilicate glasses to include the network former boron into the interaction parameter set. As…Siddharth Sundararaman, Liping Huang, Simona Ispas et al.·Dec 18, 2019SaveLearn
M-SPARC: MATLAB-Simulation Package for Ab-initio Real-space CalculationsWe present M-SPARC: MATLAB-Simulation Package for Ab-initio Real-space Calculations. It can perform pseudopotential spin-polarized and unpolarized Kohn-Sham Density Functional Theory (DFT)…Qimen Xu, Abhiraj Sharma, Phanish Suryanarayana·Dec 18, 2019SaveLearn
Formation of normal surface plasmon modes in small sodium nanoparticlesFormation of surface plasmon modes in sodium nanoclusters containing 20-300 atoms was studied using the GW method. It is shown that in the small Na nanoparticles up to 2 nm in size, the loss function…N. L. Matsko·Dec 18, 2019SaveLearn
A mass-preserving level set method for simulating 2D/3D fluid flows with evolving interfaceWithin the context of Eulerian approaches, we aim to develop a new interface-capturing solver to predict two-phase flow in 2D/3D Cartesian meshes. To achieve mass conservation and to capture…Hao-Liang Wen, Ching-Hao Yu, Tony Wen-Hann Sheu·Dec 18, 2019SaveLearn
A multiscale discrete velocity method for model kinetic equationsIn this paper, authors focus effort on improving the conventional discrete velocity method (DVM) into a multiscale scheme in finite volume framework for gas flow in all flow regimes. Unlike the…Ruifeng Yuan, Sha Liu, Chengwen Zhong·Dec 17, 2019SaveLearn
Upper limit to the photovoltaic efficiency of imperfect crystalsThe Shockley-Queisser (SQ) limit provides a convenient metric for predicting light-to-electricity conversion efficiency of a solar cell based on the band gap of the light-absorbing layer. In reality,…Sunghyun Kim, José A. Márquez, Thomas Unold et al.·Dec 17, 2019SaveLearn
Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order ModelsInverse problems are pervasive mathematical methods in inferring knowledge from observational and experimental data by leveraging simulations and models. Unlike direct inference methods, inverse…Sheroze Sheriffdeen, Jean C. Ragusa, Jim E. Morel et al.·Dec 17, 2019SaveLearn
Chaotic dynamics of piezoelectric mems based on maximal Lyapunov exponent and Smaller Alignment Index computationsWe characterize the dynamical states of a piezoelectric microelectromechanical system (MEMS) using several numerical quantifers including the maximal Lyapunov exponent, the Poincare Surface of…M. V. Tchakui, P. Woafo, Ch. Skokos·Dec 17, 2019SaveLearn