PyBERTHART: A Relativistic Real-Time Four-Component TDDFT Implementation Using Prototyping Techniques Based on Python
Authors
Matteo De Santis, Loriano Storchi, Leonardo Belpassi, Harry M. Quiney, Francesco Tarantelli
Abstract
We present a real-time time-dependent four-component Dirac-Kohn-Sham (RT-TDDKS) implementation based on the BERTHA code. This new implementation takes advantage of modern software engineering, including the prototyping techniques. The software design follows a three step approach: i) the prototype implementation of time-propagation algorithm in non-relativistic real-time TDDFT within the Psi4NumPy framework, which provides an easy-to-use environment for the creation of a clear, readable and easy to test reference code in Python, ii) the design of an original Python application programming interface for the relativistic four-component code BERTHA (PyBERTHA), which has an efficient computational kernel for relativistic integrals written in FORTRAN and iii) the porting of the time-propagation scheme eveloped within the Psi4NumPy framework to PyBERTHA. The propagation scheme consequently resides in a single readable Python computer code that is easy to maintain and in which the key quantities, such as the Dirac-Kohn-Sham and dipole matrices, can be accessed directly from the PyBERTHA module. For linear algebra operations (matrix-matrix multiplications and diagonalization) we use the highly optimized procedures implemented in the popular NumPy library. The overhead introduced by the Python interface to BERTHA is almost negligible (less than 1\% evaluated on the SCF procedure) and the inter-operability between different programming languages (FORTRAN, C and Python) does not affect the numerical stability of the time propagation scheme. Our new RT-TDDKS implementation has been employed to investigate the stability of the time propagation procedure in combination with density-fitting algorithm (both for the Coulomb and for the exchange-correlation matrix construction), which are employed in BERTHA to speed-up the Dirac-Kohn-Sham matrix evaluation. On the basis of systematic calculations, employing several density fitting basis sets of increasing accuracy, we showed that quantitative agreement can be achieved in combination with extended fitting basis sets, with an error in the Coulomb energy below 1 μ-hartree. Convergence of the transition energies increasing of quality of the fitting basis sets has been also observed. Our data suggest that the error in the Coulomb energy may also represent a good estimate of the fitting basis set quality for real-time electron dynamic simulations. Further, we study the applicability of the RT-TDDKS method in combination of both weak and extreme strong field regime. Numerical results of excited-state transitions for the Group 12 atoms are reported and compared with a previous real-time Dirac-Kohn-Sham implementation (Repisky et. al. J. Chem. Theory Comp. 2015, 11, 980-991.). Finally, calculations of high harmonic generation in the hydrogen molecule and Au dimer have been also carried out. We were able to generate high harmonics with relatively well-defined peaks up to 21th and 13th order in the case of H2 and Au2, respectively. Our findings show that the four-component structure of the Dirac-Kohn-Sham hamiltonian provides a suitable theoretical framework, with no intrinsic unfavorable features, to study molecules in the strong-field regime.
Citation
- Journal: Journal of Chemical Theory and Computation
- Year: 2020
- Volume: 16
- Issue: 4
- Pages: 2410–2429
- Publisher: American Chemical Society (ACS)
- DOI: 10.1021/acs.jctc.0c00053
BibTeX
@article{De_Santis_2020,
title={{PyBERTHART: A Relativistic Real-Time Four-Component TDDFT Implementation Using Prototyping Techniques Based on Python}},
volume={16},
ISSN={1549-9626},
DOI={10.1021/acs.jctc.0c00053},
number={4},
journal={Journal of Chemical Theory and Computation},
publisher={American Chemical Society (ACS)},
author={De Santis, Matteo and Storchi, Loriano and Belpassi, Leonardo and Quiney, Harry M. and Tarantelli, Francesco},
year={2020},
pages={2410--2429}
}
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