Description |
Strongly correlated electrons are common in much of excited states in chemical and biological systems. Traditional computational chemistry techniques are quite well developed for ground state systems and therefore, predictive as well as interpretative. However, most of these methods cannot be extended reliably to excited states where the mean field approximations are inadequate. In this talk, I will discuss about the multireference quantum chemical methods that can circumvent these limitations. We will explore the ever growing reference space that is required to quantitatively compute these excited state properties and the variational and machine learning approaches to achieve that goal. Applications on polyaromatic systems and metal clusters will show the usability of these new methods.
Reference:
1. M. Rano, S.K. Ghosh, D. Ghosh, Chemical Science, 10, 9270 (2019).
2. S.K. Ghosh, M. Rano, D. Ghosh, J. Chem. Phys., 154, 094117 (2021).
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