A Role of Symmetries in Evaluation of Fundamental BoundsA problem of the erroneous duality gap caused by the presence of symmetries is solved in this paper utilizing point group theory. The optimization problems are first divided into two classes based on…Miloslav Capek, Lukas Jelinek, Michal Masek·Jun 1, 2020SaveLearn
SIESTA: recent developments and applicationsA review of the present status, recent enhancements, and applicability of the SIESTA program is presented. Since its debut in the mid-nineties, SIESTA's flexibility, efficiency and free…Alberto García, Nick Papior, Arsalan Akhtar et al.·Jun 1, 2020SaveLearn
A method of incorporating rate constants as kinetic constraints in molecular dynamics simulationsFrom the point of view of statistical mechanics, a full characterisation of a molecular system requires the experimental determination of its possible states, their populations and the respective…Z. Faidon Brotzakis, Michele Vendruscolo, Peter. G. Bolhuis·Jun 1, 2020SaveLearn
Hybrid deep neural network based prediction method for unsteady flows with moving boundariesA novel hybrid deep neural network architecture is designed to capture the spatial-temporal features of unsteady flows around moving boundaries directly from high-dimensional unsteady flow fields…Renkun Han, Zhong Zhang, Yixing Wang et al.·Jun 1, 2020SaveLearn
Algorithm for the replica redistribution in the implementation of parallel annealing method on the hybrid supercomputer architectureThe parallel annealing method is one of the promising approaches for large scale simulations as potentially scalable on any parallel architecture. We present an implementation of the algorithm on the…Alexander Russkov, roman Chulkevich, Lev Shchur·May 31, 2020SaveLearn
Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloysWe present a scale-bridging approach based on a multi-fidelity (MF) machine-learning (ML) framework leveraging Gaussian processes (GP) to fuse atomistic computational model predictions across…Anh Tran, Julien Tranchida, Tim Wildey et al.·May 30, 2020SaveLearn
A Windowed Green Function method for elastic scattering problems on a half-spaceThis paper presents a windowed Green function (WGF) method for the numerical solution of problems of elastic scattering by "locally-rough surfaces" (i.e., local perturbations of a half space), under…Oscar P. Bruno, Tao Yin·May 29, 2020SaveLearn
A single-step third-order temporal discretization with Jacobian-free and Hessian-free formulations for finite difference methodsDiscrete updates of numerical partial differential equations (PDEs) rely on two branches of temporal integration. The first branch is the widely-adopted, traditionally popular approach of the…Youngjun Lee, Dongwook Lee·May 29, 2020SaveLearn
LogLatt: A computational library for the calculus and flows on logarithmic latticesModels on logarithmic lattices have recently been proposed as an alternative approach to the study of multi-scale nonlinear physics. Here, we introduce LogLatt, an efficient MATLAB library for the…Ciro S. Campolina·May 29, 2020SaveLearn
Learning and correcting non-Gaussian model errorsAll discretized numerical models contain modelling errors - this reality is amplified when reduced-order models are used. The ability to accurately approximate modelling errors informs statistics on…Danny Smyl, Tyler N. Tallman, Jonathan A. Black et al.·May 29, 2020SaveLearn
Abelian-Higgs cosmic string evolution with multiple GPUsTopological defects form at cosmological phase transitions by the Kibble mechanism. Cosmic strings and superstrings can lead to particularly interesting astrophysical and cosmological consequences,…J. R. C. C. C. Correia, C. J. A. P. Martins·May 29, 2020SaveLearn
Principal component trajectories for modeling spectrally-continuous dynamics as forced linear systemsDelay embeddings of time series data have emerged as a promising coordinate basis for data-driven estimation of the Koopman operator, which seeks a linear representation for observed nonlinear…Daniel Dylewsky, Eurika Kaiser, Steven L. Brunton et al.·May 28, 2020SaveLearn
Machine Learning for Condensed Matter PhysicsCondensed Matter Physics (CMP) seeks to understand the microscopic interactions of matter at the quantum and atomistic levels, and describes how these interactions result in both mesoscopic and…Edwin A. Bedolla-Montiel, Luis Carlos Padierna, Ramón Castañeda-Priego·May 28, 2020SaveLearn
ODEN: A Framework to Solve Ordinary Differential Equations using Artificial Neural NetworksWe explore in detail a method to solve ordinary differential equations using feedforward neural networks. We prove a specific loss function, which does not require knowledge of the exact solution, to…Liam L. H. Lau, Denis Werth·May 28, 2020SaveLearn
Projective Integration Schemes for Hyperbolic Moment EquationsIn this paper, we apply projective integration methods to hyperbolic moment models of the Boltzmann equation and the BGK equation, and investigate the numerical properties of the resulting scheme.…Julian Koellermeier, Giovanni Samaey·May 28, 2020SaveLearn
Physically interpretable machine learning algorithm on multidimensional non-linear fieldsIn an ever-increasing interest for Machine Learning (ML) and a favorable data development context, we here propose an original methodology for data-based prediction of two-dimensional physical…Rem-Sophia Mouradi, Cédric Goeury, Olivier Thual et al.·May 28, 2020SaveLearn
Fully implicit and accurate treatment of jump conditions for two-phase incompressible Navier-Stokes equationWe present a numerical method for two-phase incompressible Navier-Stokes equation with jump discontinuity in the normal component of the stress tensor and in the material properties. Although the…Hyuntae Cho, Myungjooo Kang·May 28, 2020SaveLearn
A simple real-space scheme for periodic Dirac operatorsWe address in this work the question of the discretization of two-dimensional periodic Dirac Hamiltonians. Standard finite differences methods on rectangular grids are plagued with the so-called…H. Chen, O. Pinaud, M. Tahir·May 28, 2020SaveLearn
Scalable neural networks for the efficient learning of disordered quantum systemsSupervised machine learning is emerging as a powerful computational tool to predict the properties of complex quantum systems at a limited computational cost. In this article, we quantify how…N. Saraceni, S. Cantori, S. Pilati·May 28, 2020SaveLearn
A multi-scale kinetic inviscid flux extracted from the gas-kinetic scheme for simulating incompressible and compressible flowsA Kinetic Inviscid Flux (KIF) is proposed for simulating incompressible and compressible flows. It is constructed based on the direct modeling of multi-scale flow behaviors, which is used in the…Sha Liu, Junzhe Cao, Chengwen Zhong·May 28, 2020SaveLearn
Deep Learning on the 2-Dimensional Ising Model to Extract the Crossover Region with a Variational AutoencoderThe 2-dimensional Ising model on a square lattice is investigated with a variational autoencoder in the non-vanishing field case for the purpose of extracting the crossover region between the…Nicholas Walker, Ka-Ming Tam·May 28, 2020SaveLearn
Non-Intrusive Reduced-Order Modeling Using Uncertainty-Aware Deep Neural Networks and Proper Orthogonal Decomposition: Application to Flood ModelingDeep Learning research is advancing at a fantastic rate, and there is much to gain from transferring this knowledge to older fields like Computational Fluid Dynamics in practical engineering…Pierre Jacquier, Azzedine Abdedou, Vincent Delmas et al.·May 27, 2020SaveLearn
Data-Driven Continuum Dynamics via Transport-Teleport DualityIn recent years, machine learning methods have been widely used to study physical systems that are challenging to solve with governing equations. Physicists and engineers are framing the data-driven…Jong-Hoon Ahn·May 27, 2020SaveLearn
Diffusion toward non-overlapping partially reactive spherical traps: fresh insights onto classic problemsSeveral classic problems for particles diffusing outside an arbitrary configuration of non-overlapping partially reactive spherical traps in three dimensions are revisited. For this purpose, we…Denis S. Grebenkov·May 27, 2020SaveLearn
Hashing algorithms, optimized mappings and massive parallelization of multiconfigurational methods for bosonsNumerical routines for Fock states indexing and to handle creation and annihilation operators in the spanned multiconfigurational space are developed. From the combinatorial problem of fitting…Alex Andriati, Arnaldo Gammal·May 27, 2020SaveLearn