MCTDH on-the-fly: Efficient grid-based quantum dynamics without pre-computed potential energy surfaces

Area of Science:

• Quantum Chemistry
• Computational Physics
• Chemical Dynamics

Background:

• Direct quantum dynamics methods are crucial for simulating molecular behavior.
• Representing potential energy surfaces (PES) accurately is computationally intensive.
• Existing grid-based methods face challenges in computational efficiency.

Purpose of the Study:

• To enhance algorithmic efficiency in direct quantum dynamics.
• To accelerate simulations by improving potential energy surface representation.
• To maintain accuracy in quantum dynamics calculations.

Main Methods:

• Developed a novel approach using weighted sums of Gaussian functions for PES representation.
• Implemented singular value decomposition for secondary PES fitting.
• Utilized on-the-fly simulations with standard grid-based methods and multi-configuration time-dependent Hartree (MCTDH).

Main Results:

• Demonstrated significant acceleration of standard grid-based quantum dynamics methods.
• Achieved this acceleration without compromising the accuracy of simulations.
• Successfully applied the method to simulate proton transfer in salicylaldimine and non-adiabatic dynamics in pyrazine.

Conclusions:

• The proposed method offers a computationally efficient alternative for quantum dynamics simulations.
• Gaussian function expansions and SVD fitting are effective for PES representation.
• This advancement facilitates more complex and accurate simulations of chemical dynamics.