Cost-Efficient High-Resolution Linear Absorption Spectra through Extrapolating the Dipole Moment from Real-Time...

Area of Science:

• Computational Chemistry
• Quantum Mechanics
• Spectroscopy

Background:

• Real-time electronic structure calculations are crucial for determining electronic absorption spectra.
• Accurate spectral resolution requires long propagation times for the electric dipole moment, leading to high computational costs.
• Discrete Fourier transforms are typically used to analyze the electric dipole moment data.

Purpose of the Study:

• To develop a novel function fitting method for approximating the time-dependent electric dipole moment propagation.
• To reduce the computational cost associated with achieving high spectral resolution in real-time electronic structure calculations.
• To enable arbitrary spectral resolution through extrapolation from shorter dipole moment trajectories.

Main Methods:

• Function fitting applied to shorter trajectories of the time-dependent electric dipole moment.
• Extrapolation techniques to achieve desired spectral resolution.
• Numerical testing and validation against high-resolution spectra obtained from longer calculations.
• Introduction of an error estimation method for assessing fit convergence and spectrum quality.

Main Results:

• The function fitting method successfully reproduces high-resolution electronic absorption spectra using significantly shorter dipole moment trajectories.
• The method demonstrates convergence with trajectories as short as 100 atomic units for certain systems.
• Convergence difficulty correlates with spectral density, indicating system-dependent performance.
• The introduced error estimate reliably assesses the quality of the approximated spectrum.

Conclusions:

• The developed function fitting method offers a computationally efficient approach to obtaining high-resolution electronic absorption spectra.
• This method significantly reduces the computational burden of real-time electronic structure calculations.
• The error estimation provides a crucial tool for validating the accuracy of the approximated spectral data.