Physics based algorithms for sparse graph visualization

Graph visualization represents an important computational tool in analysis of complex networks. Recently, variety of network structures in complex dynamical systems have been found which require appropriately adjusted visualization algorithms. We are testing quantitatively performance of two visualization algorithms based on energy minimization principle on variety of complex networks from cell-aggregated planar graphs to highly clustered scale-free networks. We found that fairly large structures with high clustering can be efficiently visualized with spring energy model with truncated interaction.