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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…

Strongly Correlated Electrons · Physics 2015-05-13 Fernando A. Reboredo , Randolph Q. Hood , Paul R. C. Kent

We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on…

Chemical Physics · Physics 2015-08-13 Julien Toulouse , Roland Assaraf , C. J. Umrigar

We evaluated the non-additive contributions of the inter-molecular interactions in B-DNA stacking by using diffusion Monte Carlo methods with fixed node approximations (FNDMC). For some base-pair steps, we found that their non-additive…

Chemical Physics · Physics 2019-11-19 Ken Sinkou Qin , Tom Ichibha , Kenta Hongo , Ryo Maezono

Diffusion Monte Carlo (DMC) calculations are performed on the monocyclic and bicyclic forms of m-benzyne, which are the equilibrium structures at the CCSD(T) and CCSD levels of coupled cluster theory. We employed multi-configuration…

Chemical Physics · Physics 2009-11-13 W. A. Al-Saidi , C. J. Umrigar

The many-body diffusion quantum Monte Carlo (DMC) method with twist-averaged boundary conditions is used to calculate the ground-state equation of state and the energetics of point defects in fcc aluminum using supercells up to 1331 atoms.…

Materials Science · Physics 2012-10-22 Randolph Q. Hood , P. R. C. Kent , Fernando A. Reboredo

We analyze the effect of increasing charge density on the Fixed Node Errors in Diffusion Monte Carlo by comparing FN-DMC calculations of the total ground state energy on a 4 electron system done with a Hartree-Fock based trial wave function…

Chemical Physics · Physics 2013-07-23 Kevin Rasch , Lubos Mitas

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…

Condensed Matter · Physics 2007-05-23 B. Abdullaev , M. Musakhanov , A. Nakamura

Fixed node diffusion Monte Carlo (DMC) has been performed on a test set of forward and reverse barrier heights for 19 non-hydrogen-transfer reactions, and the nodal error has been assessed. The DMC results are robust to changes in the nodal…

Chemical Physics · Physics 2017-04-26 Kittithat Krongchon , Brian Busemeyer , Lucas K. Wagner

The disiloxane molecule is a prime example of silicate compounds containing the Si-O-Si bridge. The molecule is of significant interest within the field of quantum chemistry, owing to the difficulty in theoretically predicting its…

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…

Statistics Theory · Mathematics 2024-12-09 Michel Caffarel , Pierre del Moral , Luc de Montella

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…

Chemical Physics · Physics 2025-08-19 Kousuke Nakano , Sandro Sorella , Michele Casula

Quantum Monte Carlo (QMC) is a stochastic method which has been particularly successful for ground-state electronic structure calculations but mostly unexplored for the computation of excited-state energies. Here, we show that, within a…

Chemical Physics · Physics 2018-08-09 Anthony Scemama , Anouar Benali , Denis Jacquemin , Michel Caffarel , Pierre-François Loos

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}…

Numerical Analysis · Mathematics 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

Accuracy of the fixed-node diffusion Monte Carlo (FN-DMC) depends on the node location of the best available trial state $\Psi_T$. The practical FN-DMC approaches available for large systems rely on compact yet effective $\Psi_T$s…

Chemical Physics · Physics 2017-03-22 Matúš Dubecký

We present an analysis of the polymorphic energy ordering and properties of the rock salt and zincblende structures of manganese oxide using fixed node diffusion Monte Carlo (DMC). Manganese oxide is a correlated, antiferromagnetic material…

Materials Science · Physics 2016-01-06 Joshua A. Schiller , Lucas K. Wagner , Elif Ertekin

Piecewise deterministic Markov process samplers are attractive alternatives to Metropolis--Hastings algorithms. A central design question is how to incorporate partial velocity refreshment to ensure ergodicity without injecting excessive…

Probability · Mathematics 2026-02-20 Hirofumi Shiba , Kengo Kamatani

The small magnitude and long-range character of non-covalent interactions pose a significant challenge for computational quantum chemical and electronic-structure methods alike. State-of-the-art coupled cluster (CC) theory and…

Chemical Physics · Physics 2026-01-22 S. Lambie , P. López-Ríos , D. Kats , Ali Alavi

The self-healing diffusion Monte Carlo algorithm (SHDMC) [Phys. Rev. B {\bf 79}, 195117 (2009), {\it ibid.} {\bf 80}, 125110 (2009)] is shown to be an accurate and robust method for calculating the ground state of atoms and molecules. By…

Strongly Correlated Electrons · Physics 2015-05-14 Michal Bajdich , Murilo L. Tiago , Randolph Q. Hood , Paul R. C. Kent , Fernando A. Reboredo

Direct sampling of multi-dimensional systems with quantum Monte Carlo methods allows exact account of many-body effects or particle correlations. The most straightforward approach to solve the Schr\"odinger equation, Diffusion Monte Carlo,…

Quantum Physics · Physics 2017-09-07 Ilkka Ruokosenmäki , Tapio T. Rantala

We establish a notion of random entropy solution for degenerate fractional conservation laws incorporating randomness in the initial data, convective flux and diffusive flux. In order to quantify the solution uncertainty, we design a…

Numerical Analysis · Mathematics 2020-10-02 Ujjwal Koley , Deep Ray , Tanmay Sarkar