Gaussian wavepacket methods are an attractive way to solve the time-dependent Schrödinger equation (TDSE). They have an underlying trajectory picture that has a natural connection to semi-classical mechanics, allowing a simple pictorial interpretation of an evolving wavepacket. They also have better scaling with system size compared to conventional grid-based techniques. Here we review the variational multi-configurational Gaussian (vMCG) method. This is a variational solution to the TDSE, with explicit coupling between the Gaussian basis functions, resulting in a favourable convergence on the exact solution. The implementation of the method and its performance will be discussed with examples from non-adiabatic photo-excited dynamics and tunneling to show that it can correctly describe both of these strongly quantum mechanical processes. Particular emphasis is given to the implementation of the direct dynamics variant, DD-vMCG, where the potential surfaces are calculated on-the-fly via an interface to quantum chemistry programs.

An implementation of the full explicitly correlated coupled-cluster singles and doubles model CCSD-F12 using a single Slater-type geminal has been obtained with the aid of automated term generation and evaluation techniques. In contrast to a previously reported computer code [T. Shiozaki et al., J. Chem. Phys. 129, 071101 (2008)], our implementation features a reduced dependence on the auxiliary basis set due to the use of a reformulated evaluation of the so-called Z-intermediate rather than straight forward insertion of an auxiliary basis expansion, which allows an unambiguous comparison to more approximate CCSD-F12 models. First benchmark results for total correlation energies and reaction energies indicate an excellent performance of the much cheaper CCSD(F12) model.

We present significant algorithmic improvements to a recently proposed direct quantum dynamics method, based upon combining well established grid-based quantum dynamics approaches and expansions of the potential energy operator in terms of a weighted sum of Gaussian functions. Specifically, using a sum of low-dimensional Gaussian functions to represent the potential energy surface (PES), combined with a secondary fitting of the PES using singular value decomposition, we show how standard grid-based quantum dynamics methods can be dramatically accelerated without loss of accuracy. This is demonstrated by on-the-fly simulations (using both standard grid-based methods and multi-configuration time-dependent Hartree) of both proton transfer on the electronic ground state of salicylaldimine and the non-adiabatic dynamics of pyrazine.