Evaluation and analysis of vibrationally resolved electronic spectra with ab initio semiclassical dynamics

Linear and nonlinear spectroscopy techniques are widely used to study numerous important chemical and physical processes. However, the interpretation of these experimental spectra often becomes very complicated because a particular spectrum constitutes a mere footprint of a host of various, possibly intertwined, effects. In this spirit, calculations in the time-dependent picture provide a useful tool for decoding such spectra. Nevertheless, the ultimate challenge is to devise a theoretical framework that could yield sufficient efficiency as well as accuracy to describe the molecular system of interest in a satisfactory way. The strategy is relatively straightforward for low dimensional systems that are directly tractable, e.g., with exact quantum dynamics performed on an equidistant grid. Despite the formidable overall exponential scaling, these calculations can be significantly accelerated by using higher-order split-operator propagation schemes. In general however, one is forced to seek an affordable balance between physical accuracy on one hand and computational efficiency on the other by employing, for instance, some of the techniques from the broad family of semiclassical methods based on classical trajectories. To this end, the thawed Gaussian approximation (TGA) is combined with an on-the-fly ab initio scheme (OTF-AI). The resulting OTF-AI-TGA algorithm is efficient enough to treat all vibrational degrees of freedom (DOFs) on an equal footing even in case of larger molecules such as pentathiophene (105 DOFs). Moreover, in sharp contrast to popular approaches based on global harmonic approximation, OTF-AI-TGA reproduces almost perfectly the absorption and photoelectron spectra of ammonia, i.e., spectra with strong dependence on large amplitude motions. In addition to the mere reproduction of experimental spectra, a novel systematic approach is introduced to assess the importance and the dynamical couplings of individual vibrational DOFs. This is in turn used to gain a deeper insight into the associated physical and chemical processes by attributing specific spectral features to the underlying molecular motion. Specifically, in the case of oligothiophenes, this approach was used to assign the dynamical interplay between quinoid and aromatic characters of individual rings to particular spectral patterns and, furthermore, to explain the changes in the vibrational line shape with an increasing number of rings. Furthermore, in systems that are too large to be treated with accurate quantum methods, efficient methods such as OTF-AI-TGA are expected to be useful as a preliminary tool for identification of the subspace of the important DOFs. On this subspace, one can then unleash some of the less efficient yet better-suited methods. In summary, OTF-AI-TGA combined with this novel analysis approach is intended to provide the first crucial step in a hierarchical computational protocol for studying large molecules such as dyes.