Multireference approaches for excited states of molecules
journal contributionposted on 2018-08-02, 08:56 authored by Hans Lischka, Dana Nachtigallova, Adelia J. A. Aquino, Peter G. Szalay, Felix PlasserFelix Plasser, Francisco B.C. Machado, Mario Barbatti
Understanding the properties of electronically excited states is a challenging task that becomes increasingly important for numerous applications in chemistry, molecular physics, molecular biology, and materials science. A substantial impact is exerted by the fascinating progress in time-resolved spectroscopy, which leads to a strongly growing demand for theoretical methods to describe the characteristic features of excited states accurately. Whereas for electronic ground state problems of stable molecules the quantum chemical methodology is now so well developed that informed nonexperts can use it efficiently, the situation is entirely different concerning the investigation of excited states. This review is devoted to a specific class of approaches, usually denoted as multireference (MR) methods, the generality of which is needed for solving many spectroscopic or photodynamical problems. However, the understanding and proper application of these MR methods is often found to be difficult due to their complexity and their computational cost. The purpose of this review is to provide an overview of the most important facts about the different theoretical approaches available and to present by means of a collection of characteristic examples useful information, which can guide the reader in performing their own applications.
FBCM, AJAA, and HL thank the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)/Tianjin University SPRINT program (Project No. 2017/50157-4) for travel support. AJAA and HL acknowledge financial support from the School of Pharmaceutical Science and Technology, Tianjin University, China. DN acknowledges the supports from research project RVO (61388963) of the IOCB of the CAS and of the Czech Science Foundation (GA16-16959S). Financial support for PGS has been provided by the National Research, Innovation and Development Office (NKFIH) of Hungary, Grant No KH124293. FBCM thanks Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) under grant 2017/07707-3, and Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq) under grants 307052/2016-8, 404337/2016-3. MB work was supported by Excellence Initiative of Aix-Marseille University (A*MIDEX) and the project Equip@Meso (ANR-10-EQPX-29-01), both funded by the French Government “Investissements d’Avenir” program. MB also acknowledges funding from and of the WSPLIT project (ANR-17-CE05-0005-01).