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Hybrid Monte Carlo metadynamics (hybridMC-MetaD)
Charlotte Shiqi Zhao1, Sun-Ting Tsai1, Sharon C Glotzer1,2
1Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, USA.
The Journal of Chemical Physics
|January 12, 2026
Summary
We introduce hybridMC-MetaD, a novel algorithm combining Hybrid Monte Carlo (hybridMC) and well-tempered metadynamics. This method enables simulations using non-differentiable collective variables, accelerating rare event discovery in molecular dynamics.
Area of Science:
- Computational chemistry and physics
- Statistical mechanics
- Materials science
Background:
- Metadynamics simulations often require differentiable collective variables (CVs), limiting their application.
- Rare events in molecular dynamics (MD) simulations are challenging to study due to their low probability.
Purpose of the Study:
- To develop and demonstrate a new algorithm, hybridMC-MetaD, that integrates Hybrid Monte Carlo (hybridMC) with well-tempered metadynamics.
- To enable the use of non-differentiable CVs in metadynamics simulations for enhanced flexibility and applicability.
- To accelerate the study of rare events and calculate free energy barriers in complex systems.
Main Methods:
- Integration of the Hybrid Monte Carlo (hybridMC) algorithm with well-tempered metadynamics to create the hybridMC-MetaD algorithm.
- Application of hybridMC-MetaD to five rare event examples in MD simulations: model potential system, argon condensation, nearly hard sphere crystallization, nearly hard bipyramid crystallization, and colloidal suspension.
- Utilizing non-differentiable CVs to bias transitions, which is not feasible with conventional MD simulations.
Main Results:
- Successfully demonstrated the application of hybridMC-MetaD to simulate rare events using non-differentiable CVs across all five test cases.
- Observed significant acceleration of phase transitions and calculated free energy barriers using the new method.
- Reported the free energy surface for the crystallization of the nearly hard bipyramid system, driven by entropy, for the first time.
Conclusions:
- The hybridMC-MetaD scheme effectively reduces the complexity and increases the accessibility of metadynamics simulations.
- This novel algorithm broadens the applicability of metadynamics, particularly for systems involving non-differentiable collective variables.
- The hybridMC-MetaD algorithm is expected to foster greater interest and broader applications of metadynamics in scientific research.
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