We present a method which extends Monte Carlo studies to situations that
require a large dynamic range in particle number. The underlying idea is that,
in order to calculate the collisional evolution of a system, some particle
interactions are more important than others and require more resolution, while
the behavior of the less important, usually of smaller mass, particles can be
considered collectively. In this approximation groups of identical particles,
sharing the same mass and structural parameters, operate as one unit. The
amount of grouping is determined by the zoom factor – a free parameter that
determines on which particles the computational effort is focused. Two methods
for choosing the zoom factors are discussed: the equal mass method,' in which the groups trace the mass density of the distribution, and the distribution
method,’ which additionally follows fluctuations in the distribution. Both
methods achieve excellent correspondence with analytic solutions to the
Smoluchowski coagulation equation. The grouping method is furthermore applied
to simulations involving runaway kernels, where the particle interaction rate
is a strong function of particle mass, and to situations that include
catastrophic fragmentation. For the runaway simulations previous predictions
for the decrease of the runaway timescale with the initial number of particles
are reconfirmed, extending to . Astrophysical
applications include modeling of dust coagulation, planetesimal accretion, and
the dynamical evolution of stars in large globular clusters. The proposed
method is a powerful tool to compute the evolution of any system where the
particles interact through discrete events, with the particle properties
characterized by structural parameters.

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