Frozen-Density Embedding for including environmental effects in the Dirac-Kohn-Sham theory: an implementation based on density fitting and prototyping techniques
Matteo De Santis, Diego Sorbelli, Valerie Vallet, Andre' Severo, Pereira Gomes, Loriano Storchi, Leonardo Belpassi

TL;DR
This paper extends the relativistic Dirac-Kohn-Sham method with a frozen density embedding scheme to include environmental effects, demonstrating scalable performance and improved modeling of confined heavy elements within a flexible Python-based framework.
Contribution
The implementation of FDE in the Dirac-Kohn-Sham framework using Python API and density fitting, enabling efficient and realistic modeling of environmental and confinement effects in relativistic quantum chemistry.
Findings
Linear scaling with environment and system size.
Successful modeling of heavy and super-heavy elements in C60 cages.
FDE improves upon simpler confinement models in atomic physics.
Abstract
The Frozen Density Embedding scheme represents an embedding method in which environmental effects onto a given subsystem are included by representing the other subsystems making up the surroundings quantum mechanically, by means of their electron densities. In the present paper, we extend the full 4-component relativistic Dirac-Kohn-Sham method, as implemented in the BERTHA code, to include environmental and confinement effects with the FDE scheme. This implementation has been enormously facilitated by BERTHA's python API (PyBERTHA), which provides a flexible framework of development by using all Python advantages in terms of code re-usability, portability while facilitating the interoperability with other FDE implementations available through the PyADF framework. The computational performance has been evaluated on a series of gold clusters (Au, with n=2,4,8) embedded into an…
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