Abstract

A time dependent quantum mechanical framework is used to examine the dis-sociation dynamics of van der Waals clusters, in particular the Hen-I2 system. The time dependent approach exploits the time scale separation between the He motion and the I2 vibration. The formalism used is the Time Dependent Self Consistent Field (TDSCF). In this picture, in which the He degrees of freedom are moving in the average field of the I2 molecule and vice versa, the equations of motion are solved by the Fourier grid method which calculates the operation of the operators constituting the Hamiltonian locally. The result is a very fast convergence with respect to grid size. The TDSCF approximation is tested for the collinear He—I2 system by comparing to an exact time dependent propagation. Good results were obtained for low vibrational excitation of the I2 bond. For higher excitations the TDSCF approximation could not account for the fast dephasing part of the autocorrelation function, nevertheless the long time behavior responsible for the dissociation was represented well. The TDSCF approach was then applied to calculate the dissociation of T-shaped and X-shaped Hen-I2 clusters. The basis of this approximation is the weak interaction between the He atoms, and the extra averaging due to increase in the number of particles. Results show very small dependence of dissociation rate on cluster size in contrast to. an RRKM picture. The symmetry of the He wavefunction to exchange is investigated. A scheme to incorporate part of the correlations responsible for collective motion which are missing in the simple TDSCF approach is presented. This scheme is based on a projection operator approach and the time dependent variational principle. On the basis of symmetry it is predicted that the dissociation rate of a cluster consisting of He3 will be faster than a cluster of He4.KeywordsAutocorrelation FunctionDissociation RateTime Scale SeparationTime Dependent QuantumDissociation DynamicThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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