Combinatorial analysis of the adaptive last particle method

The adaptive last particle method is a simple and interesting alternative in the class of general splitting algorithms for estimating tail distributions. We consider this algorithm in the space of trajectories and for general reaction coordinates. Using a combinatorial approach in discrete state spaces, we demonstrate two new results. First, we are able to give the exact expression of the distribution of the number of iterations in an perfect version of the algorithm where trajectories are i.i.d. This result is an improvement of previous known results when the cumulative distribution function has discontinuities. Second, we show that an effective computational version of the algorithm where trajectories are no more i.i.d. follows the same statistics than the idealized version when the reaction coordinate is the committor function.

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