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Advances in techniques for thermal sampling in classical and quantum systems would deepen understanding of the underlying physics. Unfortunately, one often has to rely solely on inexact numerical simulation, due to the intractability of…

Quantum Physics · Physics 2020-04-10 Jeffrey Marshall , Andrea Di Gioacchino , Eleanor G. Rieffel

Machine learning interatomic potentials (MLIPs) are routinely used to model diverse atomistic phenomena, yet parameterizing them to accurately capture solid-state phase transformations remains difficult. We present error metrics and…

Materials Science · Physics 2026-01-21 Lorenzo Piersante , Anirudh Raju Natarajan

Accurate force fields are essential for reliable molecular simulations. These models are refined against quantum mechanical calculations and experimental measurements, which are subject to random and systematic errors. Bayesian Inference of…

Chemical Physics · Physics 2025-11-04 Robert M. Raddi , Vincent A. Voelz

To quantify the progress in development of algorithms and forcefields used in molecular simulations, a method for the assessment of the sampling quality is needed. We propose a general method to assess the sampling quality through the…

Computational Physics · Physics 2010-02-22 Xin Zhang , Divesh Bhatt , Daniel M. Zuckerman

Given a target Gibbs distribution $\pi^0_{\beta} \propto e^{-\beta \mathcal{H}}$ to sample from in the low-temperature regime on $\Sigma_N := \{-1,+1\}^N$, in this paper we propose and analyze Metropolis dynamics that instead target an…

Probability · Mathematics 2022-08-23 Michael C. H. Choi

This paper presents an algorithm for sampling random variables that allows to separation of the sampling process into subproblems by dividing the sample space into overlapping parts. The subproblems can be solved independently of each other…

Computation · Statistics 2016-01-26 Jonas Hallgren , Timo Koski

This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributions each of which has the mixture of…

Methodology · Statistics 2013-08-22 Minh-Ngoc Tran , Michael K. Pitt , Robert Kohn

A binary mixture of particles interacting with spherically-symmetric potentials leading to microsegregation is studied by theory and molecular dynamics (MD) simulations. We consider spherical particles with equal diameters and volume…

Soft Condensed Matter · Physics 2020-11-20 O. Patsahan , M. Litniewski , A. Ciach

In this study, we firstly introduce a method that converts CityGML data into voxels which works efficiently and fast in high resolution for large scale datasets such as cities but by sacrificing some building details to overcome the…

Machine Learning · Computer Science 2025-01-17 Berk Kıvılcım , Patrick Erik Bradley

The process of protein folding from an unfolded state to a biologically active, folded conformation is governed by many parameters e.g the sequence of amino acids, intermolecular interactions, the solvent, temperature and chaperon…

Soft Condensed Matter · Physics 2010-10-19 Pragya Shukla

In this paper we develop a new general Bayesian methodology that simultaneously estimates parameters of interest and the marginal likelihood of the model. The proposed methodology builds on Simulated Tempering, which is a powerful algorithm…

Computation · Statistics 2019-06-03 Biljana Jonoska Stojkova , David A. Campbell

Single-particle imaging with X-ray free-electron lasers depends crucially on algorithms that merge large numbers of weak diffraction patterns despite missing measurements of parameters such as particle orientations. The…

Computational Physics · Physics 2021-08-24 B. R. Mobley , K. E. Schmidt , J. P. Chen , R. A. Kirian

Ensuring a satisfactory statistical convergence of anharmonic thermodynamic properties requires sampling of many atomic configurations, however the methods to obtain those necessarily produce correlated samples, thereby reducing the…

Statistical Mechanics · Physics 2022-06-07 Erki Metsanurk

Recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the…

We propose an algorithm for simulating stochastic relativistic fluid dynamics based on Metropolis updates. Each step of the algorithm begins with an update based on ideal hydrodynamics. This is followed by proposing random (spatial)…

Nuclear Theory · Physics 2025-02-05 Jay Bhambure , Rajeev Singh , Derek Teaney

We present a method to sample reactive pathways via biased molecular dynamics simulations in trajectory space. We show that the use of enhanced sampling techniques enables unconstrained exploration of multiple reaction routes. Time…

Computational Physics · Physics 2020-07-15 Davide Mandelli , Barak Hirshberg , Michele Parrinello

Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an…

Computational Physics · Physics 2019-11-06 Federico Giberti , Bingqing Cheng , Gareth Aneurin Tribello , Michele Ceriotti

We propose an adiabatic reweighting algorithm for computing the free energy along an external parameter from adaptive molecular dynamics simulations. The adaptive bias is estimated using Bayes identity and information from all the sampled…

Statistical Mechanics · Physics 2014-04-08 Lingling Cao , Gabriel Stoltz , Tony Lelièvre , Mihai-Cosmin Marinica , Manuel Athènes

We review uses of the generalized-ensemble algorithms for free-energy calculations in protein folding. Two of the well-known methods are multicanonical algorithm and replica-exchange method; the latter is also referred to as parallel…

Statistical Mechanics · Physics 2007-05-23 Y. Sugita , Y. Okamoto

We introduce an algorithm to systematically improve the efficiency of parallel tempering Monte Carlo simulations by optimizing the simulated temperature set. Our approach is closely related to a recently introduced adaptive algorithm that…

Other Condensed Matter · Physics 2007-05-23 Helmut G. Katzgraber , Simon Trebst , David A. Huse , Matthias Troyer
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