On the derivatives of feed-forward neural networksIn this paper we present a C++ implementation of the analytic derivative of a feed-forward neural network with respect to its free parameters for an arbitrary architecture, known as back-propagation.…Rabah Abdul Khalek, Valerio Bertone·May 12, 2020SaveLearn
Towards Exascale Lattice Boltzmann computingWe discuss the state of art of Lattice Boltzmann (LB) computing, with special focus on prospective LB schemes capable of meeting the forthcoming Exascale challenge. After reviewing the basic notions…Sauro Succi, Giorgio Amati, Massimo Bernaschi et al.·May 12, 2020SaveLearn
Energy-momentum conserving integration schemes for molecular dynamicsWe address the formulation and analysis of energy and momentum conserving time integration schemes in the context of particle dynamics, and in particular atomic systems. The article identifies three…Mark Schiebl, Ignacio Romero·May 12, 2020SaveLearn
A deep neural network for molecular wave functions in quasi-atomic minimal basis representationThe emergence of machine learning methods in quantum chemistry provides new methods to revisit an old problem: Can the predictive accuracy of electronic structure calculations be decoupled from their…M. Gastegger, A. McSloy, M. Luya et al.·May 11, 2020SaveLearn
Multi-Fidelity Gaussian Process based Empirical Potential Development for Si:H NanowiresIn material modeling, the calculation speed using the empirical potentials is fast compared to the first principle calculations, but the results are not as accurate as of the first principle…Moonseop Kim, Huayi Yin, Guang Lin·May 11, 2020SaveLearn
Spectral Neural Network Potentials for Binary AlloysIn this work, we present a numerical implementation to compute the atom centered descriptors introduced by Bartok et al (Phys. Rev. B, 87, 184115, 2013) based on the harmonic analysis of the atomic…David Zagaceta, Howard Yanxon, Qiang Zhu·May 9, 2020SaveLearn
Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flowsActive- and transfer-learning are applied to polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic…Lifei Zhao, Zhen Li, Zhicheng Wang et al.·May 9, 2020SaveLearn
Fluid-Structure Interaction Simulation of a Coriolis Mass Flowmeter using a Lattice Boltzmann MethodIn this paper we use a fluid-structure interaction (FSI) approach to simulate a Coriolis mass flowmeter (CMF). The fluid dynamics are calculated by the open source framework OpenLB, based on the…Marc Haussmann, Peter Reinshaus, Stephan Simonis et al.·May 8, 2020SaveLearn
Ab initio Path Integral Monte Carlo Simulations of Quantum Dipole Systems in Traps: Superfluidity, Quantum Statistics, and Structural PropertiesWe present extensive ab initio path integral Monte Carlo (PIMC) simulations of two-dimensional quantum dipole systems in a harmonic confinement, taking into account both Bose- and…Tobias Dornheim·May 8, 2020SaveLearn
openMMF: a library for multimode driven quantum systemsOPENMMF is a numerical library designed to evaluate the Time-Evolution Operator of quantum systems with a discrete spectrum, and driven by an arbitrary combination of harmonic couplings. The…German A. Sinuco-León·May 7, 2020SaveLearn
Diffusion NMR in periodic media: efficient computation and spectral propertiesThe Bloch-Torrey equation governs the evolution of the transverse magnetization in diffusion magnetic resonance imaging, where two mechanisms are at play: diffusion of spins (Laplacian term) and…Nicolas Moutal, Antoine Moutal, Denis S. Grebenkov·May 7, 2020SaveLearn
Wigner-Smith Time Delay Matrix for Electromagnetics: Computational Aspects for Radiation and Scattering AnalysisThe WS time delay matrix relates a lossless and reciprocal system's scattering matrix to its frequency derivative, and enables the synthesis of modes that experience well-defined group delays when…Utkarsh R. Patel, Eric Michielssen·May 7, 2020SaveLearn
Nonlinear model reduction: a comparison between POD-Galerkin and POD-DEIM methodsSeveral nonlinear model reduction techniques are compared for the three cases of the non-parallel version of the Kuramoto-Sivashinsky equation, the transient regime of flow past a cylinder at…Denis Sipp, Miguel Fosas de Pando, Peter J. Schmid·May 6, 2020SaveLearn
Reproducibility of Potential Energy Surfaces of Organic/Metal Interfaces on the Example of PTCDA on Ag(111)Molecular adsorption at organic/metal interfaces depends on a range of mechanisms: covalent bonds, charge transfer, Pauli repulsion and van der Waals (vdW) interactions shape the potential energy…Lukas Hörmann, Andreas Jeindl, Oliver T. Hofmann·May 4, 2020SaveLearn
Iterative solution of the Lippmann-Schwinger equation in strongly scattering acoustic media by randomized construction of preconditionersIn this work the Lippmann-Schwinger equation is used to model seismic waves in strongly scattering acoustic media. We consider the Helmholtz equation, which is the scalar wave equation in the…Kjersti Solberg Eikrem, Geir Nævdal, Morten Jakobsen·May 4, 2020SaveLearn
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel ApproachGradient-domain machine learning (GDML) is an accurate and efficient approach to learn a molecular potential and associated force field based on the kernel ridge regression algorithm. Here, we…Jiang Wang, Stefan Chmiela, Klaus-Robert Müller et al.·May 4, 2020SaveLearn
Dynamic Compressed Sensing for Real-Time Tomographic ReconstructionElectron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal…Jonathan Schwartz, Huihuo Zheng, Marcus Hanwell et al.·May 4, 2020SaveLearn
Off-the-shelf deep learning is not enough: parsimony, Bayes and causalityDeep neural networks ("deep learning") have emerged as a technology of choice to tackle problems in natural language processing, computer vision, speech recognition and gameplay, and in just…Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek et al.·May 4, 2020SaveLearn
GeantV: Results from the prototype of concurrent vector particle transport simulation in HEPFull detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections…G. Amadio, A. Ananya, J. Apostolakis et al.·May 3, 2020SaveLearn
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes EquationsThe goal of this work is to train a neural network which approximates solutions to the Navier-Stokes equations across a region of parameter space, in which the parameters define physical properties…Christopher J Arthurs, Andrew P King·May 2, 2020SaveLearn
Analysis of mathematical techniques for the calculation of the electrostatic field in a dielectric-loaded waveguideThe resolution of the Green's function for obtaining the electrostatic potential generated by the charges located in the dielectric layer of a rectangular waveguide requires efficient integration…A. Berenguer, A. Coves, E. Bronchalo et al.·May 2, 2020SaveLearn
Weyl's problem: A computational approachThe distribution of eigenvalues of the wave equation in a bounded domain is known as Weyl's problem. We describe several computational projects related to the cumulative state number, defined as…Isaac Bowser, Ken Kiers, Erica Mitchell et al.·May 2, 2020SaveLearn
Improved Fast Randomized Iteration Approach to Full Configuration InteractionWe present three modifications to our recently introduced fast randomized iteration method for full configuration interaction (FCI-FRI) and investigate their effects on the method's performance for…Samuel M. Greene, Robert J. Webber, Jonathan Weare et al.·May 1, 2020SaveLearn
Molecular dynamics approach for predicting release temperatures of noble gases in pre-solar nanodiamondsPre-solar meteoritic nanodiamond grains carry an array of isotopically distinct noble gas components and provide information on the history of nucleosynthesis, galactic mixing and the formation of…Alireza Aghajamali, Andrey A. Shiryaev, Nigel A. Marks·May 1, 2020SaveLearn
Pseudospectral time-domain (PSTD) methods for the wave equation: Realising boundary conditions with discrete sine and cosine transformsPseudospectral time domain (PSTD) methods are widely used in many branches of acoustics for the numerical solution of the wave equation, including biomedical ultrasound and seismology. The use of the…E. S. Wise, J. Jaros, B. T. Cox et al.·May 1, 2020SaveLearn