RESUMEN
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms, such as k-means. However, spectral clustering suffers from a scalability problem in both memory use and computational time when the size of a data set is large. To perform clustering on large data sets, we investigate two representative ways of approximating the dense similarity matrix. We compare one approach by sparsifying the matrix with another by the Nyström method. We then pick the strategy of sparsifying the matrix via retaining nearest neighbors and investigate its parallelization. We parallelize both memory use and computation on distributed computers. Through an empirical study on a document data set of 193,844 instances and a photo data set of 2,121,863, we show that our parallel algorithm can effectively handle large problems.
Asunto(s)
Algoritmos , Inteligencia Artificial , Redes de Comunicación de Computadores/instrumentación , Modelos Estadísticos , Integración de Sistemas , Análisis por Conglomerados , Simulación por Computador , Reconocimiento de Normas Patrones Automatizadas/métodos , Reproducibilidad de los ResultadosRESUMEN
This study investigates the photoluminescence for self-assembled InAs quantum dots embedded in photonic crystal nanocavities as two of the air holes nearest the H1 cavity were shifted. A rapid decrease of resonant wavelength and quality factor for the cavity modes, in which the electric field patterns extended in the shifting direction, were found as the shift increased from 0.2 to 0.4 lattice constants. This phenomenon is interpreted as being caused by the formation of two point defects between the nearest and second nearest air holes.
RESUMEN
This work investigates the single-photon emissions from self-assembled InGaAs quantum dots that are grown on an apex plane of a GaAs pyramid-like multifaceted structure. The number of QDs on a multifaceted structure is estimated by scanning electron microscopy. Single-exciton emissions from individual quantum dots are examined by micro-photoluminescence and by making photon correlation measurements. This experiment demonstrates the improvement of the single-photon extraction efficiency as quantum dots are grown on a reduced apex plane of a multifaceted structure.
RESUMEN
An efficient single-photon source based on low-density InGaAs quantum dots in a photonic-crystal nanocavity is demonstrated. The single-photon source features the effects of a photonic band gap, yielding a single-mode spontaneous emission coupling efficiency as high as beta = 92% and a linear polarization degree up to p = 95%. This appealing performance makes it well suited for practical implementation of polarization-encoded schemes in quantum cryptography.