Weight optimization in multichannel Monte Carlo
R. Kleiss, R. Pittau
Abstract
We discuss the improvement in the accuracy of a Monte Carlo integration that can be obtained by optimization of the `a-priori weights' of the various channels. These channels may be either the strata in a stratified-sampling approach, or the several `approximate' distributions such as are used in event generators for particle phenomenology. The optimization algorithm does not require any initialization, and each Monte Carlo integration point can be used in the evaluation of the integral. We describe our experience with this method in a realistic problem, where an effective increase in program speed by almost an order of magnitude is observed.
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