  We revisit the method of cumulants for analysing dynamic light scattering
data in particle sizing applications. Here the data, in the form of the time
correlation function of scattered light, is written as a series involving the
first few cumulants (or moments) of the distribution of particle diffusion
constants. Frisken (2001 Applied Optics 40, 4087) has pointed out that, despite
greater computational complexity, a non-linear, iterative, analysis of the data
has advantages over the linear least-squares analysis used originally. In order
to explore further the potential and limitations of cumulant methods we
analyse, by both linear and non-linear methods, computer-generated data with
realistic `noise', where the parameters of the distribution can be set
explicitly. We find that, with modern computers, non-linear analysis is
straightforward and robust. The mean and variance of the distribution of
diffusion constants can be obtained quite accurately for distributions of width
(standard deviation/mean) up to about 0.6, but there appears to be little
prospect of obtaining meaningful higher moments.
