Determining Pathways of Minimum Work: Simple Examples

Area of Science:

• Computational Chemistry
• Statistical Mechanics
• Physical Chemistry

Background:

• Minimal Work Pathways (MWP) are crucial for efficient free energy calculations.
• MWP are essential for designing advanced sampling methods like Candidate Monte Carlo Moves.
• Efficient sampling of complex energy landscapes is a persistent challenge in molecular simulations.

Purpose of the Study:

• To present a novel grid search approach for identifying minimal work pathways (MWP).
• To demonstrate the applicability of the MWP grid search method across diverse systems.
• To analyze the behavior and characteristics of MWP in different potential energy landscapes.

Main Methods:

• Implementation of a grid search algorithm to systematically explore parameter space for MWP.
• Application of the method to two-dimensional model landscapes to identify MWP.
• Utilizing the method to study MWP during the mutation of a Lennard-Jones sphere.

Main Results:

• Successful identification of minimal work pathways (MWP) in two-dimensional landscape examples at fixed short times.
• Observation of a broad funnel of minimal work pathways in the Lennard-Jones mutation example, lacking a single, distinct MWP.
• Validation of the grid search approach for finding MWP in systems with varying landscape complexities.

Conclusions:

• The grid search approach provides a viable method for calculating minimal work pathways (MWP).
• The presence or absence of a clear MWP depends on the specific characteristics of the energy landscape.
• This method offers insights into the dynamics of systems traversing complex potential energy surfaces.