**Woncheol Jang**

We present a fast clustering algorithm for density countour clusters
(Hartigan, 1975) that is a modified version of the Cuevas, Febrero and
Fraiman (2000) algorithm. By Hartigan's definition, clusters are the
connected components of a level set
where
is the probability density function. We use kernel density
estimators and orthogonal series estimators to estimate and modify
the Cuevas, Febrero and Fraiman (2000) Algorithm to extract the
connected components from level set estimators
. Unlike the original algorithm, our method does
not require an extra smoothing parameter and can use the Fast Fourier
Tranform (FFT) to speed up the calculations. We show the cosmological
definition of clusters of galaxies is equivalent to density contour
clusters and present an application in cosmology.

*Keywords:* Density contour cluster; clustering; Fast Fourier Transform

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