Using rectangular collocation with finite difference derivatives to solve electronic Schrodinger equationWe show that a rectangular collocation method, equivalent to evaluating all matrix elements with a quadrature-like scheme and using more points than basis functions, is an effective approach for…Sergei Manzhos, Tucker Carrington·Aug 15, 2018SaveLearn
Anomaly detection in scientific data using joint statistical momentsWe propose an anomaly detection method for multi-variate scientific data based on analysis of high-order joint moments. Using kurtosis as a reliable measure of outliers, we suggest that principal…Konduri Aditya, Hemanth Kolla, W. Philip Kegelmeyer et al.·Aug 14, 2018SaveLearn
A central-moment multiple-relaxation-time collision modelWe propose a multiple relaxation time Boltzmann equation collision model by systematically assigning a separate relaxation time to each of the central moments of the distribution function. The…Xiaowen Shan·Aug 13, 2018SaveLearn
Improving accuracy of interatomic potentials: more physics or more data? A case study of silicaIn this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large volumes of available quantum-mechanical…Ivan S. Novikov, Alexander V. Shapeev·Aug 11, 2018SaveLearn
A Unified Stochastic Particle Bhatnagar-Gross-Krook Method for Multiscale Gas FlowsThe stochastic particle method based on Bhatnagar-Gross-Krook (BGK) or ellipsoidal statistical BGK (ESBGK) model approximates the pairwise collisions in the Boltzmann equation using a relaxation…Fei Fei, Jun Zhang, Jing Li et al.·Aug 11, 2018SaveLearn
Rejection-based sampling of inelastic neutron scatteringDistributions of inelastically scattered neutrons can be quantum dynamically described by a scattering kernel. We present an accurate and computationally efficient rejection method for sampling a…X. X. Cai, T. Kittelmann, E. Klinkby et al.·Aug 8, 2018SaveLearn
Low rank representations for quantum simulation of electronic structureThe quantum simulation of quantum chemistry is a promising application of quantum computers. However, for N molecular orbitals, the O(N4) gate complexity of performing Hamiltonian and…Mario Motta, Erika Ye, Jarrod R. McClean et al.·Aug 8, 2018SaveLearn
Shape Synthesis Based on Topology SensitivityA method evaluating the sensitivity of a given parameter to topological changes is proposed within the method of moments paradigm. The basis functions are used as degrees of freedom which, when…Miloslav Capek, Lukas Jelinek, Mats Gustafsson·Aug 7, 2018SaveLearn
Field-Programmable Gate Arrays and Quantum Monte Carlo: Power Efficient Co-processing for Scalable High-Performance ComputingMassively parallel architectures offer the potential to significantly accelerate an application relative to their serial counterparts. However, not all applications exhibit an adequate level of data…Salvatore Cardamone, Jonathan R. Kimmitt, Hugh G. A. Burton et al.·Aug 7, 2018SaveLearn
Adaptive resolution for multiphase smoothed particle hydrodynamicsThe smoothed particle hydrodynamics (SPH) method has been increasingly used to study fluid problems in recent years; but its computational cost can be high if high resolution is required. In this…Xiufeng Yang, Song-Charng Kong·Aug 6, 2018SaveLearn
Modelling approaches to capture role of gelatinization in texture changes during thermal processing of foodWhile processing at elevated temperatures, starchy food products undergo gelatinization, which leads to softening related changes in textural characteristics. Study of role of gelatinization in…Ankita Sinha, Atul Bhargav·Aug 6, 2018SaveLearn
Machine learning valence force field modelThe valence force field (VFF) model is a concise physical interpretation of the atomic interaction in terms of the bond and angle variations in the explicit quadratic functional form, while the…Jing Wan, Ya-Wen Tan, Jin-Wu Jiang et al.·Aug 6, 2018SaveLearn
A Hybrid Monte Carlo algorithm for sampling rare events in space-time histories of stochastic fieldsWe introduce a variant of the Hybrid Monte Carlo (HMC) algorithm to address large-deviation statistics in stochastic hydrodynamics. Based on the path-integral approach to stochastic (partial)…G. Margazoglou, L. Biferale, R. Grauer et al.·Aug 5, 2018SaveLearn
Pair functions computed recursively in ordered and disordered latticesIn this article I study pairing of two interacting particles in ideal 1D, 2D and Bethe lattices. I employ the method of recursion that has been formulated recently by Berciu et. al. to compute the…Tirthaprasad Chattaraj·Aug 4, 2018SaveLearn
CADISHI: Fast parallel calculation of particle-pair distance histograms on CPUs and GPUsWe report on the design, implementation, optimization, and performance of the CADISHI software package, which calculates histograms of pair-distances of ensembles of particles on CPUs and GPUs. These…Klaus Reuter, Jürgen Köfinger·Aug 4, 2018SaveLearn
GPU parallelization of a hybrid pseudospectral fluid turbulence framework using CUDAAn existing hybrid MPI-OpenMP scheme is augmented with a CUDA-based fine grain parallelization approach for multidimensional distributed Fourier transforms, in a well-characterized pseudospectral…Duane Rosenberg, Pablo D. Mininni, Raghu Reddy et al.·Aug 3, 2018SaveLearn
TRIQS/SOM: Implementation of the Stochastic Optimization Method for Analytic ContinuationWe present the TRIQS/SOM analytic continuation package, an efficient implementation of the Stochastic Optimization Method proposed by A. Mishchenko et al [Phys. Rev. B…Igor Krivenko, Malte Harland·Aug 2, 2018SaveLearn
Discrete-element model for the interaction between ocean waves and sea iceWe present a discrete element method (DEM) model to simulate the mechanical behavior of sea ice in response to ocean waves. The interaction of ocean waves and sea ice can potentially lead to the…Zhijie Xu, Alexandre M. Tartakovsky, Wenxiao Pan·Aug 2, 2018SaveLearn
A dissipative particle dynamics model of biofilm growthA dissipative particle dynamics (DPD) model for the quantitative simulation of biofilm growth controlled by substrate (nutrient) consumption, advective and diffusive substrate transport, and…Zhijie Xu, Paul Meakin, Alexandre Tartakovsky et al.·Aug 2, 2018SaveLearn
A diffuse-interface model for smoothed particle hydrodynamicsDiffuse-interface theory provides a foundation for the modeling and simulation of microstructure evolution in a very wide range of materials, and for the tracking/capturing of dynamic interfaces…Zhijie Xu, Paul Meakin, Alexandre Tartakovsky·Aug 2, 2018SaveLearn
PETGEM: A parallel code for 3D CSEM forward modeling using edge finite elementsWe present the capabilities and results of the Parallel Edge-based Tool for Geophysical Electromagnetic modeling (PETGEM), as well as the physical and numerical foundations upon which it has been…Octavio Castillo-Reyes, Josep de la Puente, José María Cela·Aug 1, 2018SaveLearn
Tunable Half-Metallicity and Edge Magnetism of H-saturated InSe NanoribbonsWe report on a theoretical study of electronic and magnetic properties of hydrogen-saturated InSe nanoribbons (H-ZISNs). Based on hybrid-functional first-principles calculations, we find that H-ZISNs…Weiqing Zhou, Guodong Yu, A. N. Rudenko et al.·Jul 31, 2018SaveLearn
Unsupervised machine learning for detection of phase transitions in off-lattice systems I. FoundationsWe demonstrate the utility of an unsupervised machine learning tool for the detection of phase transitions in off-lattice systems. We focus on the application of principal component analysis (PCA) to…R. B. Jadrich, B. A. Lindquist, T. M. Truskett·Jul 31, 2018SaveLearn
Unsupervised machine learning for detection of phase transitions in off-lattice systems II. ApplicationsWe outline how principal component analysis (PCA) can be applied to particle configuration data to detect a variety of phase transitions in off-lattice systems, both in and out of equilibrium.…R. B. Jadrich, B. A. Lindquist, W. D. Pineros et al.·Jul 31, 2018SaveLearn
Towards the Theory of the Yukawa PotentialUsing three different approaches, Perturbation Theory (PT), the Lagrange Mesh Method (Lag-Mesh) and the Variational Method (VM), we study the low-lying states of the Yukawa potential…J. C. del Valle, D. J. Nader·Jul 31, 2018SaveLearn