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Most solved dynamic structural macrofinance models are non-linear and/or non-Gaussian state-space models with high-dimensional and complex structures. We propose an annealed controlled sequential Monte Carlo method that delivers numerically…

Computation · Statistics 2022-01-05 Andras Fulop , Jeremy Heng , Junye Li

Brittle fracturing of materials is common in natural and industrial processes over a variety of length scales. Knowledge of individual particle dynamics is vital to obtain deeper insight into the atomistic processes governing crack…

Soft Condensed Matter · Physics 2024-04-25 Max Huisman , Axel Huerre , Saikat Saha , John C. Crocker , Valeria Garbin

Many problems require to approximate an expected value by some kind of Monte Carlo (MC) sampling, e.g. molecular dynamics (MD) or simulation of stochastic reaction models (also termed kinetic Monte Carlo (kMC)). Often, we are furthermore…

Numerical Analysis · Mathematics 2019-02-18 Sandra Döpking , Sebastian Matera

This article reviews the basic computational techniques for carrying out multi-scale simulations using statistical methods, with the focus on simulations of epitaxial growth. First, the statistical-physics background behind Monte Carlo…

Materials Science · Physics 2009-04-17 Peter Kratzer

An iterative algorithm based on Monte Carlo method is used to model thin film growth of AB type molecule and crystallization. Primarly, PVD technique is investigated since it is one of the most preferred on thin film growth processes. The…

Materials Science · Physics 2012-10-17 İzzet Paruğ Duru , Şahin Aktaş

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds, that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their…

Numerical Analysis · Mathematics 2020-12-02 Miranda Holmes-Cerfon

Colloids have a striking relevance in a wide spectrum of industrial formulations, spanning from personal care products to protective paints. Their behaviour can be easily influenced by extremely weak forces, which disturb their…

Soft Condensed Matter · Physics 2018-06-14 Daniel Corbett , Alejandro Cuetos , Matthew Dennison , Alessandro Patti

We describe and analyze some Monte Carlo methods for manifolds in Euclidean space defined by equality and inequality constraints. First, we give an MCMC sampler for probability distributions defined by un-normalized densities on such…

Numerical Analysis · Mathematics 2017-09-21 Emilio Zappa , Miranda Holmes-Cerfon , Jonathan Goodman

We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system at finite temperature. This allows arbitrary reduced density matrix elements and expectation values of complicated non-local…

Computational Physics · Physics 2015-06-15 N. S. Blunt , T. W. Rogers , J. S. Spencer , W. M. C. Foulkes

We describe a Monte Carlo procedure which allows sampling of the disjoint configuration spaces associated with crystalline and fluid phases, within a single simulation. The method utilises biased sampling techniques to enhance the…

Statistical Mechanics · Physics 2009-10-31 N. B. Wilding , A. D. Bruce

Sintering is a key step in the processing of high performance ceramics. Both the density and the grain size play a crucial role on the ceramic sintering kinetics and the final material properties. The master sintering curve (MSC) is a…

Materials Science · Physics 2020-11-25 Gabriel Kerbart , Charles Manière , Christelle Harnois , Sylvain Marinel

We present a method that optimizes the aspect ratio of a spatially anisotropic quantum lattice model during the quantum Monte Carlo simulation, and realizes the virtually isotropic lattice automatically. The anisotropy is removed by using…

Statistical Mechanics · Physics 2015-01-22 Shinya Yasuda , Synge Todo

Known method of fibrous oxides production (first of all, V2O5) by intensive stirring in water is treated in the frame of driven systems approach developed in 80s by Georges Martin et al for systems under irradiation or severe plastic…

Materials Science · Physics 2025-08-20 Serhii Abakumov , Eugen Rabkin , Andriy Gusak

The stochastic series expansion quantum Monte Carlo method is used to study thin ferromagnetic films, described by a Heisenberg model including local anisotropies. The magnetization curve is calculated, and the results compared to Schwinger…

Strongly Correlated Electrons · Physics 2009-11-07 P. Henelius , P. Fröbrich , P. J. Kuntz , C. Timm , P. J. Jensen

A fundamental challenge in Bayesian inference is efficient representation of a target distribution. Many non-parametric approaches do so by sampling a large number of points using variants of Markov Chain Monte Carlo (MCMC). We propose an…

Machine Learning · Computer Science 2022-04-25 Cole Hawkins , Alec Koppel , Zheng Zhang

In the last decade, sequential Monte-Carlo methods (SMC) emerged as a key tool in computational statistics. These algorithms approximate a sequence of distributions by a sequence of weighted empirical measures associated to a weighted…

Statistics Theory · Mathematics 2007-06-13 R. Douc , France E. Moulines

Sequential Monte Carlo (SMC) methods, also known as particle filters, are simulation-based recursive algorithms for the approximation of the a posteriori probability measures generated by state-space dynamical models. At any given time $t$,…

Computation · Statistics 2016-11-24 Dan Crisan , Joaquín Míguez

We investigate, using Monte Carlo simulations, the phase diagram of a system of hard rectangles of size $m\times mk$ on a square lattice when the aspect ratio $k$ is a non-integer. The existence of a disordered isotropic phase, a nematic…

Statistical Mechanics · Physics 2015-05-29 Joyjit Kundu , R. Rajesh

We revisit two basic Direct Simulation Monte Carlo Methods to model aggregation kinetics and extend them for aggregation processes with collisional fragmentation (shattering). We test the performance and accuracy of the extended methods and…

Numerical Analysis · Mathematics 2022-07-27 A. Kalinov , A. I. Osinsky , S. A. Matveev , W. Otieno , N. V. Brilliantov

Sintering is an important processing step in both ceramics and metals processing. The microstructure resulting from this process determines many materials properties of interest. Hence the accurate prediction of the microstructure,…

Materials Science · Physics 2024-03-06 Marco Seiz , Henrik Hierl , Britta Nestler , Wolfgang Rheinheimer