A PARALLEL ALGORITHM FOR STRUCTURE DETECTION BASED ON WAVELET AND SEGMENTATION ANALYSIS

We present a parallel algorithm which allows to recognize rapidly stru ctures in a 3-dimensional set of discrete data points resulting from n umerical experiments, and to study their morphological properties. The algorithm consists of two main steps: (1) wavelet analysis in order t o separate those data points which belong to structures from uniformly distributed background points, and (2) segmentation analysis in order to label individual structures and their corresponding data points. P arameters which characterize the morphology of these structures may th en be extracted easily. The fast parallel implementation on a Connecti on Machine CM-200 makes the algorithm interesting for other areas in c omputational physics which require a method for morphological comparis ons. The algorithm is illustrated by an example in the field of cosmol ogy for studying the formation of the Large Scale Structure in the Uni verse. This analysis allows to distinguish clearly qualitatively as we ll as quantitatively between two models which respectively favour fila mentary or clustered structures.