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This paper introduces a Monte Carlo method for maximum likelihood inference in the context of discretely observed diffusion processes. The method gives unbiased and a.s.\@ continuous estimators of the likelihood function for a family of…

Statistics Theory · Mathematics 2009-03-03 Alexandros Beskos , Omiros Papaspiliopoulos , Gareth Roberts

The statistical mechanics of phase transitions in dense systems of polydisperse particles presents distinctive challenges to computer simulation and analytical theory alike. The core difficulty, namely dealing correctly with particle size…

Soft Condensed Matter · Physics 2013-09-03 Nigel B. Wilding , Peter Sollich

Determinant Quantum Monte Carlo (DQMC) provides numerically exact solutions for strongly correlated fermionic systems but faces significant computational challenges with increasing system size. While submatrix updates were originally…

Strongly Correlated Electrons · Physics 2025-02-19 Fanjie Sun , Xiao Yan Xu

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

Monte Carlo simulations are widely employed to measure the physical properties of glass-forming liquids in thermal equilibrium. Combined with local Monte Carlo moves, the Metropolis algorithm can also be used to simulate the relaxation…

Statistical Mechanics · Physics 2024-09-23 Ludovic Berthier , Federico Ghimenti Frédéric van Wijland

In this comprehensive and detailed study, vacancy-mediated self-diffusion of A- and B-elements in 'triple-defect' B2-ordered ASB(1-S) binaries is simulated by means of a kinetic Monte Carlo (KMC) algorithm involving atomic jumps to…

Materials Science · Physics 2019-10-16 Jan Betlej , Piotr Sowa , Rafal Kozubski , Graeme E. Murch , Irina V. Belova

We use a diffusion Monte Carlo method to solve the many-body Schr\"odinger equation describing fully-heavy tetraquark systems. This approach allows to reduce the uncertainty of the numerical calculation at the percent level, accounts for…

High Energy Physics - Phenomenology · Physics 2020-12-30 M. C. Gordillo , F. De Soto , J. Segovia

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

In this paper a Monte-Carlo method for simulating the motion of fluid flow moving along a solid wall is proposed. The random vortex method in the present paper is established by using the reflection technology and perturbation technique.…

Fluid Dynamics · Physics 2022-08-30 Z. Qian , Y. Qiu , L. Zhao , J. Wu

The Direct Simulation Monte Carlo (DSMC) method was widely used to simulate low density gas flows with large Knudsen numbers. However, DSMC encounters limitations in the regime of lower Knudsen numbers (Kn<0.1). In such cases, approaches…

It is currently difficult to distill discrete diffusion models. In contrast, continuous diffusion literature has many distillation approaches methods that can reduce sampling steps to a handful. Our method, Discrete Moment Matching…

Machine Learning · Computer Science 2026-03-23 Emiel Hoogeboom , David Ruhe , Jonathan Heek , Thomas Mensink , Tim Salimans

We study statistical model checking of continuous-time stochastic hybrid systems. The challenge in applying statistical model checking to these systems is that one cannot simulate such systems exactly. We employ the multilevel Monte Carlo…

Systems and Control · Computer Science 2017-06-27 Sadegh Esmaeil Zadeh Soudjani , Rupak Majumdar , Tigran Nagapetyan

Density matrix quantum Monte Carlo (DMQMC) is a recently-developed method for stochastically sampling the $N$-particle thermal density matrix to obtain exact-on-average energies for model and \emph{ab initio} systems. We report a systematic…

Step distillation has become a leading technique for accelerating diffusion models, among which Distribution Matching Distillation (DMD) and Consistency Distillation are two representative paradigms. While consistency methods enforce…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Tao Liu , Hao Yan , Mengting Chen , Taihang Hu , Zhengrong Yue , Zihao Pan , Jinsong Lan , Xiaoyong Zhu , Ming-Ming Cheng , Bo Zheng , Yaxing Wang

The evolution of interfaces is intrinsic to many physical processes ranging from cavitation in fluids to recrystallization in solids. Computational modeling of interface motion entails a number of challenges, many of which are related to…

Materials Science · Physics 2022-07-26 Erdem Eren , Brandon Runnels , Jeremy Mason

A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in…

Strongly Correlated Electrons · Physics 2016-06-10 Kensaku Takai , Kota Ido , Takahiro Misawa , Youhei Yamaji , Masatoshi Imada

We apply the Direct Simulation Monte Carlo (DSMC) method, developed originally to calculate rarefied gas dynamical problems, to study the gas flow in an accretion disc in a close binary system. The method involves viscosity and thermal…

Astrophysics · Physics 2007-05-23 Takuya Matsuda , Hiromi Mizutani , Henri M. J. Boffin

Radiative transfer describes the propagation of electromagnetic radiation through an interacting medium. This process is often simulated by the use of the Monte Carlo method, which involves the probabilistic determination and tracking of…

Instrumentation and Methods for Astrophysics · Physics 2020-03-31 A. Krieger , S. Wolf

We investigate hydrodynamic noise in a dilute granular gas during the homogeneous cooling state, by means of a proper application of the Direct Simulation Monte Carlo (DSMC) algorithm. The DSMC includes a source of randomization which is…

Soft Condensed Matter · Physics 2010-09-27 Giulio Costantini , Andrea Puglisi

Diffusion quantum Monte Carlo (DMC) and coupled cluster theory [CCSD(T)] are widely-employed benchmark methods for noncovalent interactions (NCIs). However, recent studies have reported notable discrepancies across several hydrogen-bonded…

Chemical Physics · Physics 2026-04-07 Kousuke Nakano , Benjamin X. Shi , Dario Alfè , Andrea Zen