A Unified Approach to Enhanced Sampling

Abstract

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 are often grouped into two broad families. On the one hand methods such as umbrella sampling and metadynamics that build a bias potential based on few order parameters or collective variables. On the other hand, tempering methods such as replica exchange that combine different thermodynamic ensembles in one single expanded ensemble. We instead adopt a unifying perspective, focusing on the target probability distribution sampled by the different methods. This allows us to introduce a new class of collective-variables-based bias potentials that can be used to sample any of the expanded ensembles normally sampled via replica exchange. We also provide a practical implementation, by properly adapting the iterative scheme of the recently developed on-the-fly probability enhanced sampling method [Invernizzi and Parrinello, J. Phys. Chem. Lett. 11.7 (2020)], which was originally introduced for metadynamics-like sampling. The resulting method is very general and can be used to achieve different types of enhanced sampling. It is also reliable and simple to use, since it presents only few and robust external parameters and has a straightforward reweighting scheme. Furthermore, it can be used with any number of parallel replicas. We show the versatility of our approach with applications to multicanonical and multithermal-multibaric simulations, thermodynamic integration, umbrella sampling, and combinations thereof.

References in corpus (30)

• Canonical sampling through velocity-rescaling
• Escaping free-energy minima
• PLUMED 2: New feathers for an old bird
• Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method
• An efficient, multiple range random walk algorithm to calculate the density of states
• Simulated Tempering: A New Monte Carlo Scheme
• Parallel Tempering: Theory, Applications, and New Perspectives
• Multidimensional replica-exchange method for free-energy calculations
• Enhanced Sampling in Molecular Dynamics Using Metadynamics, Replica-Exchange, and Temperature-Acceleration
• Rethinking Metadynamics: from bias potentials to probability distributions
• A Variational Approach to Enhanced Sampling and Free Energy Calculations
• Enhanced Sampling in the Well-Tempered Ensemble
• Determination of phase diagrams via computer simulation: Methodology and applications to water, electrolytes and proteins
• Hamiltonian replica-exchange in GROMACS: a flexible implementation
• Data-Driven Collective Variables for Enhanced Sampling
• Reconstructing the Density of States by History-Dependent Metadynamics
• Monte Carlo simulation and global optimization without parameters
• Homogeneous nucleation of ice
• Analyzing and biasing simulations with PLUMED
• Calculation of phase diagrams in the multithermal-multibaric ensemble
• Gaussian Mixture Based Enhanced Sampling
• Making the best of a bad situation: a multiscale approach to free energy calculation
• Combining Metadynamics and Integrated Tempering Sampling
• Multithermal-multibaric molecular simulations from a variational principle
• Riemann metric approach to optimal sampling of multidimensional free-energy landscapes
• Metadynamics of paths
• Enhanced sampling of transition states
• Phase equilibrium of liquid water and hexagonal ice from enhanced sampling molecular dynamics simulations
• Infinite Switch Simulated Tempering in Force (FISST)
• Simulated Tempering Method in the Infinite Switch Limit with Adaptive Weight Learning

Cited by in corpus (28)

• Phase equilibrium of water with hexagonal and cubic ice using the SCAN functional
• Liquid-liquid transition in water from first principles
• Rare Event Kinetics from Adaptive Bias Enhanced Sampling
• Universal QM/MM Approaches for General Nanoscale Applications
• Liquid-Liquid Critical Point in Phosphorus
• Attenuating the fermion sign problem in path integral Monte Carlo simulations using the Bogoliubov inequality and thermodynamic integration
• Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications
• Collective Variables for the Study of Crystallization
• Multiscale reweighted stochastic embedding (MRSE): Deep learning of collective variables for enhanced sampling
• Stochastic Resetting for Enhanced Sampling
• Reinforcement learning of rare diffusive dynamics
• Skipping the Replica Exchange Ladder with Normalizing Flows
• Reaction Coordinates for Conformational Transitions using Linear Discriminant Analysis on Positions
• Descriptors-free Collective Variables From Geometric Graph Neural Networks
• Adding alchemical variables to metadynamics to enhance sampling in free energy calculations
• Sparse inference and active learning of stochastic differential equations from data
• Ab Initio Generalized Langevin Equation
• Manifold Learning in Atomistic Simulations: A Conceptual Review
• Deep learning the slow modes for rare events sampling
• Propensity of water self-ions at air(oil)-water interfaces revealed by deep potential molecular dynamics with enhanced sampling
• Atomistic View of Homogeneous Nucleation of Water into Polymorphic Ices
• Melting curves of ice polymorphs in the vicinity of the liquid-liquid critical point
• Multiple Topology Replica Exchange of Expanded Ensembles (MT-REXEE) for Multidimensional Alchemical Calculations
• Exploration vs Convergence Speed in Adaptive-bias Enhanced Sampling
• Ab Initio bulk free energy surface of proper ferroelectrics
• Guiding Peptide Kinetics via Collective-Variable Tuning of Free-Energy Barriers
• Global free energy landscapes as a smoothly joined collection of local maps
• Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials