Detecting reactive islands using Lagrangian descriptors and the relevance to transition path sampling

Area of Science:

• Chemical Dynamics
• Computational Chemistry
• Statistical Mechanics

Background:

• Isomerization reactions are often mediated by phase space structures known as reactive islands (RI).
• Reactive islands offer a pathway to address nonstatistical effects in reaction dynamics.
• Understanding RI is crucial for accurate modeling of chemical reactions and rare event sampling.

Purpose of the Study:

• To map reactive islands in the two-dimensional Müller-Brown model potential.
• To investigate the link between reactive islands and rare event sampling.
• To evaluate the utility of Lagrangian descriptors for identifying reactive island hierarchies, especially in high-dimensional systems.

Main Methods:

• Utilized the two-dimensional Müller-Brown model potential to study reaction dynamics.
• Employed transition path sampling techniques to analyze committor probabilities.
• Applied Lagrangian descriptors to identify and characterize the hierarchical structure of reactive islands.

Main Results:

• Demonstrated a strong connection between reactive islands and the challenges of rare event sampling.
• Established the sensitivity of committor probabilities to the hierarchical structure of reactive islands.
• Successfully employed Lagrangian descriptors to effectively identify the reactive island hierarchy in the model system.

Conclusions:

• Reactive islands play a critical role in the dynamics of isomerization reactions and rare event sampling.
• Lagrangian descriptors provide an effective method for identifying reactive island hierarchies.
• The findings suggest Lagrangian descriptors are a promising tool for analyzing complex, high-dimensional chemical systems.