84 citations · 207 across the 6 of their papers we have counts for
7 papers · 1 filter
Advanced simulations with PLUMED: OPES and Machine Learning Collective Variables
Enrico Trizio, Andrea Rizzi, Pablo M. Piaggi +2
Many biological processes occur on time scales longer than those accessible to molecular dynamics simulations. Identifying collective variables (CVs) and introducing an external po…
Exploration vs Convergence Speed in Adaptive-bias Enhanced Sampling
Michele Invernizzi, Michele Parrinello
In adaptive-bias enhanced sampling methods, a bias potential is added to the system to drive transitions between metastable states. The bias potential is a function of a few collec…
OPES: On-the-fly Probability Enhanced Sampling Method
Michele Invernizzi
Molecular simulations are playing an ever increasing role, finding applications in fields as varied as physics, chemistry, biology and material science. However, many phenomena of…
Attenuating the fermion sign problem in path integral Monte Carlo simulations using the Bogoliubov inequality and thermodynamic integration
Tobias Dornheim, Michele Invernizzi, Jan Vorberger +1
Accurate thermodynamic simulations of correlated fermions using path integral Monte Carlo (PIMC) methods are of paramount importance for many applications such as the description o…
A Unified Approach to Enhanced Sampling
Michele Invernizzi, Pablo Miguel Piaggi, Michele Parrinello
The sampling problem lies at the heart of atomistic simulations and over the years many different enhanced sampling methods have been suggested towards its solution. These methods…
Rethinking Metadynamics: from bias potentials to probability distributions
Michele Invernizzi, Michele Parrinello
Metadynamics is an enhanced sampling method of great popularity, based on the on-the-fly construction of a bias potential that is function of a selected number of collective variab…