2021
DOI: 10.1021/acs.jctc.0c01293
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Toward an Accurate Ab Initio Description of Low-Lying Singlet Excited States of Polyenes

Abstract: The low-lying excited states of carotenoids play a crucial role in many important biophysical processes such as photosynthesis. Most of these excited states are strongly correlated, which makes them both challenging for a qualitative ab initio description and an engaging model system for trying out emerging multireference methods. Among these methods, driven similarity renormalization group (DSRG) and its perturbative version (DSRG-MRPT2) are especially attractive in terms of both accuracy and moderate numeric… Show more

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Cited by 19 publications
(62 citation statements)
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“…We mainly followed the protocol which has earlier been proposed for unsubstituted polyenes by the same authors 40 . DMRGSCF calculations were carried out in the active space including the entire π-system to avoid an additional bias in its selection.…”
Section: Excitation Energiesmentioning
confidence: 99%
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“…We mainly followed the protocol which has earlier been proposed for unsubstituted polyenes by the same authors 40 . DMRGSCF calculations were carried out in the active space including the entire π-system to avoid an additional bias in its selection.…”
Section: Excitation Energiesmentioning
confidence: 99%
“…Another approach is to replace commonly used perturbation theories such as complete active space second-order perturbation theory (CASPT2) 41 or N-electron valence state second-order perturbation theory (NEVPT2) 6,31,42 by driven similarity renormalization group (DSRG) perturbation theory (DSRG-MRPT2). 40 While DSRG-MRPT2 itself is not capable of completely removing a "poor" reference problem, it produces excitation energies which are closer to the experimental data than the NEVPT2 ones. Moreover, it has a much better computational scaling with respect to the number of active orbitals, therefore, in principle, it could pave the way to "double" active space calculations with post-SCF MRPT2 treatment for long polyenes.…”
Section: Introductionmentioning
confidence: 96%
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