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We present a promising coarse-graining strategy for linking micro- and mesoscales of soft matter systems. The approach is based on effective pairwise interaction potentials obtained from detailed atomistic molecular dynamics (MD)…

Soft Condensed Matter · Physics 2007-05-23 A. P. Lyubartsev , M. Karttunen , I. Vattulainen , A. Laaksonen

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

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

Fixed node diffusion quantum Monte Carlo (FN-DMC) is an increasingly used computational approach for investigating the electronic structure of molecules, solids, and surfaces with controllable accuracy. It stands out among equally accurate…

Computational Physics · Physics 2019-10-03 Andrea Zen , Jan Gerit Brandenburg , Angelos Michaelides , Dario Alfè

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

Dynamic Monte Carlo simulations are used to study coupled transport (co-transport) through sub-nanometer-diameter pores. In this classic Hodgkin-Keynes mechanism, an ion species uses the large flux of an abundant ion species to move against…

Soft Condensed Matter · Physics 2013-11-27 Dezső Boda , Éva Csányi , Dirk Gillespie , Tamás Kristóf

We develop exact Markov chain Monte Carlo methods for discretely-sampled, directly and indirectly observed diffusions. The qualification "exact" refers to the fact that the invariant and limiting distribution of the Markov chains is the…

Conventional approaches for simulating steady-state distributions of particles under diffusive and advective transport at high P\'eclet numbers involve solving the diffusion and advection equations in at least two dimensions. Here, we…

We propose a modification, based on the RESTART (repetitive simulation trials after reaching thresholds) and DPR (dynamics probability redistribution) rare event simulation algorithms, of the standard diffusion Monte Carlo (DMC) algorithm.…

Probability · Mathematics 2014-04-10 Martin Hairer , Jonathan Weare

A novel micromixing technique that exploit a thrust of droplets into the mixing interface is developed. The technique enhances the mixing by injecting immiscible droplets in a mixing channel and the methodology enables a control of the…

Fluid Dynamics · Physics 2023-03-28 Ryosuke Sakurai , Ken Yamamoto , Masahiro Motosuke

The direct simulation Monte Carlo (DSMC) method is widely used to describe rarefied gas flows. The DSMC method accounts for the transport and collisions of computational particles, resulting in higher computational costs in the continuum…

Computational Physics · Physics 2025-08-11 Joonbeom Kim , Eunji Jun

Direct numerical simulations of free round jets at a Reynolds number ($Re_{D}$) of $5000$, based on jet diameter ($D$) and jet-exit bulk velocity ($U_{e}$), are performed to study jet turbulence characteristics at supercritical pressures.…

Fluid Dynamics · Physics 2021-08-04 Nek Sharan , Josette Bellan

In this study, we develop vector flow imaging techniques for multi-layered models with a high wavespeed contrast using photoacoustic and ultrasonic imaging. We use refraction-corrected delay-and-sum image reconstruction (RC-DAS), which…

Medical Physics · Physics 2025-12-18 Caitlin Smith , Guillaume Renaud , Kasper van Wijk , Jami Shepherd

We report on a investigation of turbulent bubbly flows. Bubbles of a size larger than the dissipative scale, cannot be treated as point-wise inclusions, and generate important hydrodynamic fields in the carrier fluid when in motion.…

Fluid Dynamics · Physics 2021-12-17 Alessio Innocenti , Alice Jaccod , Stéphane Popinet , Sergio Chibbaro

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

Classical algorithms in numerical analysis for numerical integration (quadrature/cubature) follow the principle of approximate and integrate: the integrand is approximated by a simple function (e.g. a polynomial), which is then integrated…

Numerical Analysis · Mathematics 2018-06-15 Yuji Nakatsukasa

We propose a Monte Carlo sampler from the reverse diffusion process. Unlike the practice of diffusion models, where the intermediary updates -- the score functions -- are learned with a neural network, we transform the score matching…

Machine Learning · Statistics 2024-03-14 Xunpeng Huang , Hanze Dong , Yifan Hao , Yi-An Ma , Tong Zhang

The fixed node diffusion Monte Carlo (DMC) method has attracted interest in recent years as a way to calculate properties of solid materials with high accuracy. However, the framework for the calculation of properties such as total…

Materials Science · Physics 2016-01-20 Jaehyung Yu , Lucas K. Wagner , Elif Ertekin

Significance: Monte Carlo (MC) methods are the gold-standard for modeling light-tissue interactions due to their accuracy. Mesh-based MC (MMC) offers enhanced precision for complex tissue structures using tetrahedral mesh models. Despite…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-01 Shijie Yan , Douglas Dwyer , David R. Kaeli , Qianqian Fang

We investigate the stochastic Direct Simulation Monte Carlo method (DSMC) for numerically solving the collision-term in heavy-ion transport theories of the Boltzmann-Uehling-Uhlenbeck (BUU) type. The first major modification we consider is…

Nuclear Theory · Physics 2009-10-28 G. Kortemeyer , F. Daffin , W. Bauer
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