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We propose a free-energy based Monte-Carlo method to measure the volume of potential-energy basins in configuration space. Using this approach we can estimate the number of distinct potential-energy minima, even when this number is much too…

Soft Condensed Matter · Physics 2015-03-18 Ning Xu , Daan Frenkel , Andrea J. Liu

Partition functions of probability distributions are important quantities for model evaluation and comparisons. We present a new method to compute partition functions of complex and multimodal distributions. Such distributions are often…

Machine Learning · Statistics 2016-05-27 David Carlson , Patrick Stinson , Ari Pakman , Liam Paninski

In order to find the equilibrium geometries of molecules and solids and to perform ab initio molecular dynamics, it is necessary to calculate the forces on the nuclei. We present a correlated sampling method to efficiently calculate…

Condensed Matter · Physics 2009-10-31 Claudia Filippi , C. J. Umrigar

Path integral Monte Carlo with Green's function analysis allows the sampling of quantum mechanical properties of molecules at finite temperature. While a high-precision computation of the energy of the Born-Oppenheimer surface from path…

Quantum Physics · Physics 2007-05-23 Daejin Shin , Ming-Chak Ho , J. Shumway

A simple technique is proposed for numerically determining equilibrium ion distribution functions belonging to free energies of the Poisson-Boltzmann type. The central idea is to perform a conventional Monte-Carlo simulation using the free…

Soft Condensed Matter · Physics 2009-10-31 Markus Deserno

The approximate computation of all gravitational forces between $N$ interacting particles via the fast multipole method (FMM) can be made as accurate as direct summation, but requires less than $\mathcal{O}(N)$ operations. FMM groups…

Instrumentation and Methods for Astrophysics · Physics 2014-05-12 Walter Dehnen

We describe an efficient algorithm to compute forces in quantum Monte Carlo using adjoint algorithmic differentiation. This allows us to apply the space warp coordinate transformation in differential form, and compute all the 3M force…

Other Condensed Matter · Physics 2015-05-20 Sandro Sorella , Luca Capriotti

Molecular Density Functional Theory (MDFT) offers an efficient implicit- solvent method to estimate molecule solvation free-energies whereas conserving a fully molecular representation of the solvent. Even within a second order ap-…

Soft Condensed Matter · Physics 2014-06-12 Volodymyr P. Sergiievskyi , Guillaume Jeanmairet , Maximilien Levesque , Daniel Borgis

Probabilistic graphical models have emerged as a powerful modeling tool for several real-world scenarios where one needs to reason under uncertainty. A graphical model's partition function is a central quantity of interest, and its…

Artificial Intelligence · Computer Science 2021-05-25 Durgesh Agrawal , Yash Pote , Kuldeep S Meel

It is known that solutions of Richardson equations can be represented as stationary points of the "energy" of classical free charges on the plane. We suggest to consider "probabilities" of the system of charges to occupy certain states in…

Superconductivity · Physics 2012-02-03 W. V. Pogosov

In plasma edge simulations, kinetic Monte Carlo (MC) is often used to simulate neutral particles and estimate source terms. For large-sized reactors, like ITER and DEMO, high particle collision rates lead to a substantial computational cost…

Computational Engineering, Finance, and Science · Computer Science 2025-09-16 Zhirui Tang , Emil Løvbak , Julian Koellermeier , Giovanni Samaey

In this paper, I investigate more closely the recently proposed Free Energy Monte Carlo algorithm that is devised in particular for calculations where conventional Monte Carlo simulations struggle with ergodicity problems. The simplest…

Condensed Matter · Physics 2007-05-23 M. J. Thill

We study approximations of the partition function of dense graphical models. Partition functions of graphical models play a fundamental role is statistical physics, in statistics and in machine learning. Two of the main methods for…

Machine Learning · Computer Science 2018-02-21 Vishesh Jain , Frederic Koehler , Elchanan Mossel

We investigate Monte Carlo simulation strategies for determining the effective ("depletion") potential between a pair of hard spheres immersed in a dense sea of much smaller hard spheres. Two routes to the depletion potential are…

Soft Condensed Matter · Physics 2015-06-16 D. J. Ashton , V. Sanchez-Gil , N. B. Wilding

We present a Nested Markov chain Monte Carlo (NMC) scheme for building equilibrium averages based on accurate potentials such as density functional theory. Metropolis sampling of a reference system, defined by an inexpensive but approximate…

Chemical Physics · Physics 2015-06-17 Jeff Leiding , Joshua D. Coe

Due to a hard dependency between time steps, large-scale simulations of gas using the Direct Simulation Monte Carlo (DSMC) method proceed at the pace of the slowest processor. Scalability is therefore achievable only by ensuring that the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-19 William McDoniel , Paolo Bientinesi

Pre-calculated libraries of molecular fragment configurations have previously been used as a basis for both equilibrium sampling (via "library-based Monte Carlo") and for obtaining absolute free energies using a polymer-growth formalism.…

Quantitative Methods · Quantitative Biology 2018-12-26 Steven Lettieri , Artem B. Mamonov , Daniel M. Zuckerman

We propose efficient measurement procedures for the self-energy and vertex function of the Anderson impurity model within the hybridization expansion continuous-time quantum Monte Carlo algorithm. The method is based on the measurement of…

Strongly Correlated Electrons · Physics 2012-06-01 Hartmut Hafermann , Kelly R. Patton , Philipp Werner

Ab initio molecular dynamics (AIMD) based on density functional theory (DFT) has become a workhorse for studying the structure, dynamics, and reactions in condensed matter systems. Currently, AIMD simulations are primarily carried out at…

Chemical Physics · Physics 2025-06-10 Ritama Kar , Sagarmoy Mandal , Vaishali Thakkur , Bernd Meyer , Nisanth N. Nair

This work introduces two Monte Carlo (MC)-based sampling methods, known as line sampling and subset simulation, to improve the performance of standard MC analyses in the context of asteroid impact risk assessment. Both techniques sample the…

Earth and Planetary Astrophysics · Physics 2020-09-28 Matteo Romano , Matteo Losacco , Camilla Colombo , Pierluigi Di Lizia