Wave operator and artificial intelligence contraction algorithms in quantum dynamics: Application to CD3H and C6H6

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Abstract
We have established in this study the capabilities of the wave operator (WO) algorithm to extract from a huge primitive space a smaller subspace (the active space) containing all of the zero order states which play an active role during the intramolecular vibrational energy redistribution (IVR) from an initial state ‖i≳0. While exact methods such as the recursive residue generation method (RRGM) or the Chebychev algorithms can only be applied in a primitive space containing less than about 200 000 states, the WO algorithm can be used efficiently in ultralarge basis sets containing billions of states. The recursive residue generation method (RRGM) or Chebychev methods can then be applied in this active space which typically contains less than 10 000 states. In order to draw general conclusions on the efficiency of such a method and on the main features of IVR phenomena, we have concurrently studied IVR from the fifth CH overtone in the nine mode CD3H molecule and from the second CH overtone in the 16 mode C6H6 system. We have analyzed the main features of the active space and have shown that the WO algorithm selects the important states. A very broad energy distribution of states in the active space has been obtained for these two systems. We have also shown that C6H6 is a very complex system to study; while only a few hundred states are effectively populated during the IVR from the fifth CH overtone in CD3H, about 8000 states have to be considered in order to accurately study IVR from the second CH overtone in C6H6. However, we have shown that the WO method is able to reproduce correctly both the survival probability of the initial state and the intricate energy flow through the molecule during the first picosecond. Finally, we have shown that the WO algorithm builds a far more efficient active space than a more traditional artificial intelligence (Al) tree pruning procedure.