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Quantum Monte Carlo approaches such as the diffusion Monte Carlo (DMC) method are among the most accurate many-body methods for extended systems. Their scaling makes them well suited for defect calculations in solids. We review the various…

Materials Science · Physics 2014-04-23 William D. Parker , John W. Wilkins , Richard G. Hennig

While it is empirically accepted that the fixed-node diffusion Monte-Carlo (FN-DMC) depends only weakly on the size of the one-particle basis sets used to expand its guiding functions, limits of this observation are not settled yet. Our…

Chemical Physics · Physics 2017-02-07 Matúš Dubecký

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

In plasma edge simulations, the behavior of neutral particles is often described by a Boltzmann--BGK equation. Solving this kinetic equation and estimating the moments of its solution are essential tasks, typically carried out using Monte…

Numerical Analysis · Mathematics 2025-12-30 Zhirui Tang , Julian Koellermeier , Emil Løvbak , Giovanni Samaey

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

By incorporating renormalization procedure into Bold Diagrammatic Monte Carlo (BDMC), we propose a method for studying quantum field theories in the strong coupling regime. BDMC essentially samples Feynman diagrams using local…

High Energy Physics - Lattice · Physics 2013-12-13 Ali Davody

Fracture phenomena in soft materials span multiple length- and timescales. This poses a major challenge in computational modeling and predictive materials design. To pass quantitatively from molecular- to continuum scales, a precise…

Soft Condensed Matter · Physics 2023-03-03 Tianchi Li , Eric R. Dufresne , Martin Kröger , Stefanie Heyden

A recent line of research has exploited pre-trained generative diffusion models as priors for solving Bayesian inverse problems. We contribute to this research direction by designing a sequential Monte Carlo method for linear-Gaussian…

Machine Learning · Computer Science 2025-10-13 Filip Ekström Kelvinius , Zheng Zhao , Fredrik Lindsten

Recently Schautz and Flad concluded that the Hellmann-Feynman theorem holds within the fixed-node diffusion quantum Monte Carlo (DMC) method. We show that the Hellmann-Feynman expression is not in general equal to the derivative of the DMC…

Condensed Matter · Physics 2009-10-31 K. C. Huang , R. J. Needs , G. Rajagopal

One of the most significant drawbacks of the all-electron ab initio diffusion Monte Carlo (DMC) is that its computational cost drastically increases with the atomic number ($Z$), which typically scales with $Z^{\sim 6}$. In this study, we…

Computational Physics · Physics 2020-04-15 Kousuke Nakano , Ryo Maezono , Sandro Sorella

We present a novel hybrid computational method to simulate accurately dendritic solidification in the low undercooling limit where the dendrite tip radius is one or more orders of magnitude smaller than the characteristic spatial scale of…

Materials Science · Physics 2009-10-31 Mathis Plapp , Alain Karma

This paper considers the problem of sampling from non-logconcave distribution, based on queries of its unnormalized density. It first describes a framework, Denoising Diffusion Monte Carlo (DDMC), based on the simulation of a denoising…

Machine Learning · Statistics 2024-10-31 Ye He , Kevin Rojas , Molei Tao

Basis set incompleteness error (BSIE) is a common source of error in quantum chemistry (QC) calculations, but it has not been comprehensively studied in fixed-node Diffusion Monte Carlo (FN-DMC) calculations. FN-DMC, being a projection…

Chemical Physics · Physics 2025-09-03 Kousuke Nakano , Benjamin X. Shi , Dario Alfè , Andrea Zen

Ab initio calculation of dielectric response with high-accuracy electronic structure methods is a long-standing problem, for which mean-field approaches are widely used and electron correlations are mostly treated via approximated…

Chemical Physics · Physics 2024-06-25 Xiang Li , Yubing Qian , Ji Chen

Diffusion Monte Carlo (DMC) calculations typically yield highly accurate results in solid-state and quantum-chemical calculations. However, operators that do not commute with the Hamiltonian are at best sampled correctly up to second order…

Other Condensed Matter · Physics 2009-11-13 R. Gaudoin , J. M. Pitarke

Ice is one of the most important and interesting molecular crystals exhibiting a rich and evolving phase diagram. Recent discoveries mean that there are now twenty distinct polymorphs; a structural diversity that arises from a delicate…

Materials Science · Physics 2025-09-09 Flaviano Della Pia , Andrea Zen , Dario Alfè , Angelos Michaelides

To sample from a general target distribution $p_*\propto e^{-f_*}$ beyond the isoperimetric condition, Huang et al. (2023) proposed to perform sampling through reverse diffusion, giving rise to Diffusion-based Monte Carlo (DMC).…

Machine Learning · Statistics 2024-01-15 Xunpeng Huang , Difan Zou , Hanze Dong , Yian Ma , Tong Zhang

In this paper the Diffusion Monte Carlo (DMC) method is applied to the confined hydrogen atom with different confinement geometries. This approach is validated using the much studied spherical and cylindrical confinements and then applied…

Chemical Physics · Physics 2019-03-20 Gaia Micca Longo , Savino Longo , Domenico Giordano

Sequential Monte Carlo (SMC), or particle filtering, is widely used in nonlinear state-space systems, but its performance often suffers from poorly approximated proposal and state-transition distributions. This work introduces a…

Machine Learning · Computer Science 2026-05-14 Wessel L. van Nierop , Nir Shlezinger , Ruud J. G. van Sloun

All-electron Fixed-node Diffusion Monte Carlo (FN-DMC) calculations for the nonrelativistic ground-state energy of the water molecule at equilibrium geometry are presented. The determinantal part of the trial wavefunction is obtained from a…

Chemical Physics · Physics 2016-05-25 Michel Caffarel , Thomas Applencourt , Emmanuel Giner , Anthony Scemama