Free-energy landscapes from adaptively biased methods: application to quantum systems

Area of Science:

• Computational Chemistry
• Statistical Mechanics
• Materials Science

Background:

• Calculating free-energy pathways is crucial for understanding chemical reactions and material properties.
• Complex systems, like the Lennard-Jones cluster, present significant challenges for traditional simulation methods.

Purpose of the Study:

• To evaluate and compare the efficiency of parallel adaptive biasing methods for free-energy calculations.
• To extend adaptively biased molecular-dynamics (ABMD) to quantum systems and assess its performance.

Main Methods:

• Application of parallel adaptive biasing techniques, including Wang-Landau and ABMD, to a 38-atom Lennard-Jones cluster.
• Implementation and testing of a quantum extension of ABMD using path-integral molecular dynamics (PIMD).
• Comparison of the quantum ABMD method against the quantum superposition method for Ne38.

Main Results:

• Wang-Landau and ABMD methods demonstrated efficiency for classical systems when employing multiple walkers and replication/deletion schemes.
• The extended quantum ABMD method, utilizing PIMD, was successfully implemented.
• The quantum ABMD approach showed comparable performance to the quantum superposition method for Ne38.

Conclusions:

• Parallel adaptive biasing methods, particularly Wang-Landau and ABMD with enhancements, are efficient tools for calculating free-energy pathways in complex classical systems.
• The developed quantum ABMD method offers a viable and efficient approach for studying free-energy landscapes in quantum systems.