Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo

Christiane Lemieux Monte Carlo and Quasi - Monte Carlo Sampling

Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation.

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also rapidly sample uncorrelated configurations. Here, we introduce a new class of moves based on nonequilibrium dynamics: Candidate configurations are generated th...

Optimization of Variable Area Transect Sampling Using Monte Carlo Simulation

An extensive simulation study was conducted to optimize the number, r, of population members to be encountered from each random starting point in variable area transect (VAT) sampling. The quality of estimation provided by the original calculation formula presented by K. R. Parker in 1979 was compared to another formula that was a Morisita analog intended to reduce bias when sampling aggregated...

Continuous-time quantum Monte Carlo using worm sampling

P. Gunacker,1 M. Wallerberger,1 E. Gull,2 A. Hausoel,3 G. Sangiovanni,3 and K. Held1 1Institute for Solid State Physics, Vienna University of Technology, 1040 Vienna, Austria 2Department of Physics, University of Michigan, Ann Arbor, Michigan 48109, USA 3Institute for Theoretical Physics and Astrophysics, University of Würzburg, Am Hubland 97074 Würzburg, Germany (Received 22 June 2015; publish...

Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics

We present a Monte Carlo sampler using a modified Nosé-Poincaré Hamiltonian along with Riemannian preconditioning. Hamiltonian Monte Carlo samplers allow better exploration of the state space as opposed to random walk-based methods, but, from a molecular dynamics perspective, may not necessarily provide samples from the canonical ensemble. Nosé-Hoover samplers rectify that shortcoming, but the ...