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In this work, we developed an interatomic potential for saturated hydrocarbons using the modified embedded-atom method (MEAM), a reactive semi-empirical many-body potential based on density functional theory and pair potentials. We…

Chemical Physics · Physics 2017-09-13 S. Nouranian , M. A. Tschopp , S. R. Gwaltney , M. I. Baskes , M. F. Horstemeyer

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In…

Computational Physics · Physics 2025-04-03 Boqin Zhang , Shikhar Shah , John E. Pask , Edmond Chow , Phanish Suryanarayana

The stochastic density functional theory (DFT) [Phys. Rev. Lett. 111, 106402 (2013)] is a valuable linear scaling approach to Kohn-Sham DFT that does not rely on the sparsity of the density matrix. Linear (and often sub-linear) scaling is…

Chemical Physics · Physics 2019-02-20 Ming Chen , Roi Baer , Daniel Neuhauser , Eran Rabani

Site-occupation embedding theory (SOET) is an in-principle-exact multi-determinantal extension of density-functional theory for model Hamiltonians. Various extensions of recent developments in SOET [Senjean et al., Phys. Rev. B 97, 235105…

Strongly Correlated Electrons · Physics 2019-08-06 Bruno Senjean , Naoki Nakatani , Masahisa Tsuchiizu , Emmanuel Fromager

The finite-amplitude method (FAM) is one of the most promising methods for optimizing the computational performance of the random-phase approximation (RPA) calculations in deformed nuclei. In this report, we will mainly focus on our recent…

Nuclear Theory · Physics 2014-05-16 Haozhao Liang , Takashi Nakatsukasa , Zhongming Niu , Jie Meng

We present an implementation of a fully variational formulation of an immersed method for fluid-structure interaction problems based on the finite element method. While typical implementation of immersed methods are characterized by the use…

Numerical Analysis · Mathematics 2015-04-10 Saswati Roy , Luca Heltai , Francesco Costanzo

The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success of Deep Potential rests on the proper treatment of locality…

Computational Physics · Physics 2019-12-05 Leonardo Zepeda-Núñez , Yixiao Chen , Jiefu Zhang , Weile Jia , Linfeng Zhang , Lin Lin

Kohn-Sham spin-density functional theory provides an efficient and accurate model to study electron-electron interaction effects in quantum dots, but its application to large systems is a challenge. An efficient algorithm for the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Hong Jiang , Harold U. Baranger , Weitao Yang

With the development of low order scaling methods for performing Kohn-Sham Density Functional Theory, it is now possible to perform fully quantum mechanical calculations of systems containing tens of thousands of atoms. However, with an…

Chemical Physics · Physics 2020-04-03 William Dawson , Stephan Mohr , Laura E. Ratcliff , Takahito Nakajima , Luigi Genovese

Accurate modeling in the warm dense matter regime is a persistent challenge with the most detailed models such as quantum molecular dynamics and path integral Monte Carlo being immensely computationally expensive. Density functional theory…

Materials Science · Physics 2024-09-04 Sameen Yunus , David A. Strubbe

In this paper, we extend our Smooth Particle Hydrodynamics (SPH) impact code to include the effect of porosity at a sub-resolution scale by adapting the so-called $P-alpha$ model. Many small bodies in the different populations of asteroids…

Astrophysics · Physics 2009-11-13 M. Jutzi , W. Benz , P. Michel

Simulations in the warm dense matter regime using finite temperature Kohn-Sham density functional theory (FT-KS-DFT), while frequently used, are computationally expensive due to the partial occupation of a very large number of high-energy…

Materials Science · Physics 2018-04-04 Yael Cytter , Eran Rabani , Daniel Neuhauser , Roi Baer

Resonant absorption imaging is a common technique for detecting the two-dimensional column density of ultracold atom systems. In many cases, the system's thickness along the imaging direction greatly exceeds the imaging system's depth of…

Atomic Physics · Physics 2014-01-28 Andika Putra , Daniel L. Campbell , Ryan M. Price , Subhadeep De , I. B. Spielman

We present an efficient and scalable computational approach for conducting projected population analysis from real-space finite-element (FE) based Kohn-Sham density functional theory calculations (DFT-FE). This work provides an important…

Fracture coalescence is a critical phenomenon for creating large fractures from smaller flaws, affecting fracture network flow and seismic energy release potential. In this paper, simulations of fracture coalescence processes in granite…

In this work we give a comprehensive derivation of an exact and numerically feasible method to perform ab-initio calculations of quantum particles interacting with a quantized electromagnetic field. We present a hierachy of…

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham DFT method, the density is an average over multiple stochastic samples, with…

Chemical Physics · Physics 2020-01-08 Wenfei Li , Ming Chen , Eran Rabani , Roi Baer , Daniel Neuhauser

Electron energy-loss spectroscopy (EELS) and cathodoluminescence (CL) are widely used experimental techniques for characterization of nanoparticles. The discrete dipole approximation (DDA) is a numerically exact method for simulating…

Optics · Physics 2023-03-03 Alexander A. Kichigin , Maxim A. Yurkin

Kohn-Sham density functional theory (DFT) is a widely-used electronic structure theory for materials as well as molecules. DFT is needed especially for large systems, ab initio molecular dynamics, and high-throughput searches for functional…

Introducing a reduced particle stiffness in discrete element method (DEM) allows for bigger time steps and therefore fewer total iterations in a simulation. Although this approach works well for dry non-adhesive particles, it has been shown…

Soft Condensed Matter · Physics 2018-10-17 Sheng Chen , Wenwei Liu , Shuiqing Li
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