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相关论文: Diffusion quantum Monte Carlo study of the equatio…

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We review the use of continuum quantum Monte Carlo (QMC) methods for the calculation of energy gaps from first principles, and present a broad set of excited-state calculations carried out with the variational and fixed-node diffusion QMC…

材料科学 · 物理学 2018-08-22 Ryan J. Hunt , Marcin Szyniszewski , Genki I. Prayogo , Ryo Maezono , Neil D. Drummond

Diffusion Monte Carlo (DMC) is one of the most accurate techniques available for calculating the electronic properties of molecules and materials, yet it often remains a challenge to economically compute forces using this technique. As a…

化学物理 · 物理学 2022-11-15 Cancan Huang , Brenda M. Rubenstein

We report results of both Diffusion Quantum Monte Carlo(DMC) method and Reptation Quantum Monte Carlo(RMC) method on the potential energy curve of the helium dimer. We show that it is possible to obtain a highly accurate description of the…

化学物理 · 物理学 2015-05-18 Xuebin Wu , Xianru Hu , Chenlei Du , Yunchuan Dai , Shibin Chu , Leibo Hu , Jianbo Deng , Yuanping Feng

We report all-electron and pseudopotential calculations of the ground-stateenergies of the neutral Ne atom and the Ne+ ion using the variational and diffusion quantum Monte Carlo (DMC) methods. We investigate different levels of…

材料科学 · 物理学 2008-01-03 N. D. Drummond , P. Lopez Rios , A. Ma , J. R. Trail , G. Spink , M. D. Towler , R. J. Needs

The energetics of point defects in oxide materials plays a major role in determining their high-temperature properties, but experimental measurements are difficult, and calculations based on density functional theory (DFT) are not…

材料科学 · 物理学 2016-08-16 D. Alfè , M. J. Gillan

We report variational and diffusion quantum Monte Carlo (VMC and DMC) studies of the binding curve of the ground-state chromium dimer. We employed various single determinant (SD) or multi-determinant (MD) wavefunctions multiplied by a…

化学物理 · 物理学 2012-04-06 Kenta Hongo , Ryo Maezono

Ab initio quantum Monte Carlo (QMC) is a stochastic approach for solving the many-body Schr\"odinger equation without resorting to one-body approximations. QMC algorithms are readily parallelizable via ensembles of $N_w$ walkers, making…

化学物理 · 物理学 2025-08-19 Kousuke Nakano , Sandro Sorella , Michele Casula

Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

While Diffusion Monte Carlo (DMC) is in principle an exact stochastic method for \textit{ab initio} electronic structure calculations, in practice the fermionic sign problem necessitates the use of the fixed-node approximation and trial…

We have used diffusion Monte Carlo (DMC) simulations to calculate the energy barrier for H$_2$ dissociation on the Mg(0001) surface. The calculations employ pseudopotentials and systematically improvable B-spline basis sets to expand the…

材料科学 · 物理学 2009-11-13 M. Pozzo , D. Alfe`

We report results of both the Diffusion Quantum Monte Carlo (DMC) and Reptation Quantum Monte Carlo (RMC) methods on the potential energy curve of the helium dimer. We show that it is possible to obtain a highly accurate description of the…

化学物理 · 物理学 2010-05-07 Xuebin Wu , Chenlei Du , Jianbo Deng

We report diffusion Monte Carlo (DMC) calculations on MgO in the rock-salt and CsCl structures. The calculations are based on Hartree-Fock pseudopotentials, with the single-particle orbitals entering the correlated wave function being…

强关联电子 · 物理学 2016-08-16 D. Alfè , M. Alfredsson , J. Brodholt , M. J. Gillan M. D. Towler , R. J. Needs

We develop a formalism and present an algorithm for optimization of the trial wave-function used in fixed-node diffusion quantum Monte Carlo (DMC) methods. We take advantage of a basic property of the walker configuration distribution…

强关联电子 · 物理学 2015-05-13 Fernando A. Reboredo , Randolph Q. Hood , Paul R. C. Kent

The Diffusion Monte Carlo method with constant number of walkers, also called Stochastic Reconfiguration as well as Sequential Monte Carlo, is a widely used Monte Carlo methodology for computing the ground-state energy and wave function of…

统计理论 · 数学 2024-12-09 Michel Caffarel , Pierre del Moral , Luc de Montella

A many-flavor electron gas (MFEG) in a semiconductor with a valley degeneracy ranging between 6 and 24 was analyzed using diffusion Monte Carlo (DMC) calculations. The DMC results compare well with an analytic expression derived by one of…

强关联电子 · 物理学 2009-11-13 G. J. Conduit , P. D. Haynes

The Diffusion Monte Carlo method is devoted to the computation of electronic ground-state energies of molecules. In this paper, we focus on implementations of this method which consist in exploring the configuration space with a {\bf fixed}…

数值分析 · 数学 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

We report exact expressions for atomic forces in the diffusion Monte Carlo (DMC) method when using nonlocal pseudopotentials. We present approximate schemes for estimating these expressions in both mixed and pure DMC calculations, including…

材料科学 · 物理学 2008-08-15 A. Badinski , R. J. Needs

We calculate the equation of state of neutron matter at zero temperature by means of the auxiliary field diffusion Monte Carlo method (AFDMC) combined with a fixed-phase approximation. The calculation of the energy is carried out by…

核理论 · 物理学 2009-06-30 S. Gandolfi , A. Yu. Illarionov , K. E. Schmidt , F. Pederiva , S. Fantoni

On the base of Diffusion Monte-Carlo method it is developed a new Complex Diffusion Monte-Carlo (CDMC) method allowing to simulate the quantum systems with complex wave function. There are no approximations on the calculation of modulus and…

凝聚态物理 · 物理学 2007-05-23 B. Abdullaev , M. Musakhanov , A. Nakamura

We present two machine learning methodologies that are capable of predicting diffusion Monte Carlo (DMC) energies with small datasets (~60 DMC calculations in total). The first uses voxel deep neural networks (VDNNs) to predict DMC energy…

介观与纳米尺度物理 · 物理学 2022-11-02 Kevin Ryczko , Jaron T. Krogel , Isaac Tamblyn