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We present a Monte Carlo (MC) grid-based model for the drying of drops of a nanoparticle suspension upon a heterogeneous surface. The model consists of a generalised lattice-gas in which the interaction parameters in the Hamiltonian can be…

Soft Condensed Matter · Physics 2017-07-25 C. Chalmers , R. Smith , A. J. Archer

The dissociation energies of four transition metal dimers are determined using diffusion Monte Carlo. The Jastrow, CI, and molecular orbital parameters of the wave function are both partially and fully optimized with respect to the…

Chemical Physics · Physics 2019-09-06 Jil Ludovicy , Kaveh Haghighi Mood , Arne Lüchow

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…

Materials Science · Physics 2009-11-13 M. Pozzo , D. Alfe`

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

Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary state properties. QMC is among the most accurate and…

Materials Science · Physics 2025-01-08 Alfonso Annarelli , Dario Alfè , Andrea Zen

Discrete diffusion models have emerged as powerful frameworks for generating structured categorical data. However, efficiently sampling from reward-tilted distributions remains a fundamental challenge. While Twisted Sequential Monte Carlo…

Machine Learning · Computer Science 2026-05-25 Jaihoon Kim , Taehoon Yoon , Prin Phunyaphibarn , Seungjun Kim , Morteza Mardani , Minhyuk Sung

Optimizing highly complex cost/energy functions over discrete variables is at the heart of many open problems across different scientific disciplines and industries. A major obstacle is the emergence of many-body effects among certain…

The Kinetic Monte Carlo (KMC) method has become an important tool for examination of phenomena like surface diffusion and thin film growth because of its ability to carry out simulations for time scales that are relevant to experiments. But…

Materials Science · Physics 2007-05-23 Talat S. Rahman , Abdelkader Kara , Altaf Karim , Oleg Trushin

We present a quantum Monte Carlo study of the hydrogen-benzene system where binding is very weak. We demonstrate that the binding is well described at both variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) levels by a Jastrow…

Materials Science · Physics 2009-11-13 Todd D. Beaudet , Michele Casula , Jeongnim Kim , Sandro Sorella , Richard M. Martin

The Diffusion Monte Carlo (DMC) method is applied to the water monomer, dimer, and hexamer, using q-TIP4P/F, one of the most simple, empirical water models with flexible monomers. The bias in the time step ($\Delta\tau$) and population size…

Chemical Physics · Physics 2016-09-28 Joel D. Mallory , Sandra E. Brown , Vladimir A. Mandelshtam

The surface integral method for estimating ionic-covalent interactions in diatomic systems been successful in producing cross sections for mutual neutralisation (MN) in reasonable agreement with experimental results for branching fractions…

Atomic Physics · Physics 2021-12-10 Paul S. Barklem

DFT is a valuable tool for calculating adsorption energies toward designing materials for hydrogen storage. However, dispersion forces being absent from the theory, it remains unclear how the consideration of van der Waals (vdW)…

Chemical Physics · Physics 2021-09-16 Genki I. Prayogo , Hyeondeok Shin , Anouar Benali , Ryo Maezono , Kenta Hongo

Fixed-node diffusion Monte Carlo (FNDMC) is a stochastic quantum many-body method that has a great potential in electronic structure theory. We examine how FNDMC satisfies exact constraints, linearity and derivative discontinuity of total…

Chemical Physics · Physics 2019-10-16 Matej Ditte , Matus Dubecky

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…

Chemical Physics · Physics 2022-11-15 Cancan Huang , Brenda M. Rubenstein

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

This paper addresses optimization problems constrained by partial differential equations with uncertain coefficients. In particular, the robust control problem and the average control problem are considered for a tracking type cost…

Optimization and Control · Mathematics 2017-11-08 Andreas Van Barel , Stefan Vandewalle

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

A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed…

Computational Physics · Physics 2020-02-05 Alexander A. Kunitsa , So Hirata

We investigate how the fixed-node diffusion Monte Carlo energy of solids depends on single-particle orbitals used in Slater--Jastrow wave functions. We demonstrate that the dependence can be significant, in particular in the case of 3d…

Materials Science · Physics 2010-09-09 Jindrich Kolorenc , Shuming Hu , Lubos Mitas

The self-healing diffusion Monte Carlo algorithm (SHDMC) [Reboredo, Hood and Kent, Phys. Rev. B {\bf 79}, 195117 (2009); Reboredo, {\it ibid.} {\bf 80}, 125110 (2009)] is extended to study the ground and excited states of magnetic and…

Strongly Correlated Electrons · Physics 2011-06-10 Fernando Agustín Reboredo