Quantum dynamics using path integral coarse-graining.

Area of Science:

• Quantum chemistry
• Computational physics
• Spectroscopy

Background:

• Vibrational spectra are crucial for understanding molecular systems, influenced by quantum effects of light nuclei.
• Current quantum dynamics simulations, like path-integral (PI) methods, are computationally expensive, especially at low temperatures.

Purpose of the Study:

• To develop a computationally efficient and accurate method for simulating quantum dynamics and calculating vibrational spectra.
• To overcome the limitations of traditional path-integral methods regarding computational cost and temperature scaling.

Main Methods:

• Developed a path-integral (PI) method incorporating machine-learned coarse-graining to reduce computational expense.
• Implemented a temperature elevation scheme to mitigate artifacts and unfavorable temperature scaling in PI simulations.
• Applied the method to calculate vibrational spectra of water molecules and bulk water.

Main Results:

• Achieved significant computational savings, comparable to classical simulations.
• Demonstrated dramatically improved accuracy compared to existing expensive reference methods.
• Successfully attenuated artifacts and eliminated unfavorable temperature scaling inherent in standard PI approaches.

Conclusions:

• The developed method offers a simple, efficient, and accurate approach for routine vibrational spectra calculations.
• This method enables explicit treatment of nuclear quantum effects in a wide range of molecular systems.
• The findings have broad implications for computational chemistry and condensed matter physics research.