Before revision:  The resulting QT clustering (QTC) algorithm is shown to outperform the state-of-the-art spectral clustering method on synthetic and real data sets containing complex geometric patterns  .
After revision:  The resulting QT clustering (QTC) algorithm is shown to outperform the state-of-the-art spectral clustering method on synthetic and real data sets containing complex geometric patterns and more robust when clusters show strong density variations or heterogeneity in size .