Two New Methods To Generate Internal Coordinates for Molecular Wave Packet Dynamics in Reduced Dimensions.

Area of Science:

• * Computational Chemistry
• * Quantum Dynamics
• * Chemical Physics

Background:

• * The curse of dimensionality poses a significant challenge in molecular quantum dynamical calculations.
• * Accurate potential landscapes require methods that reduce the configuration space's dimensionality.
• * Current dimensionality reduction often relies on chemical intuition, limiting automation.

Purpose of the Study:

• * To develop automated methods for dimensionality reduction in molecular quantum dynamics.
• * To replace subjective chemical intuition with quantifiable criteria for selecting internal coordinates.
• * To improve the efficiency and accuracy of dynamic calculations by reducing the problem's complexity.

Main Methods:

• * Devised two novel methods for automated dimensionality reduction.
• * Both methods linearly reduce dimensionality using the intrinsic reaction coordinate (IRC) as guidance.
• * Method 1 relies solely on the IRC; Method 2 incorporates semiclassical trajectories to identify key degrees of freedom.

Main Results:

• * The developed methods increase automation in dimensionality reduction.
• * Quantifiable criteria are introduced, moving beyond reliance on chemical intuition.
• * Both approaches effectively reduce the dimensionality of molecular configuration space.

Conclusions:

• * The new methods provide a more objective and automated approach to dimensionality reduction.
• * Utilizing the intrinsic reaction coordinate and semiclassical trajectories enhances the selection of relevant degrees of freedom.
• * These advancements are expected to improve the feasibility and accuracy of molecular quantum dynamical calculations.