Supernova Type Ia Diversity: A Study using DBSCAN Algorithm

Malik, Neha

doi:10.30534/ijatcse/2020/140932020

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Another technique commonly used for validation of clusters is silhouette score technique [7,18]. Silhouette Score Coefficient finds how much the data points are integrated in their respective cluster as compared to other clusters.…”

Section: Validation Of Clustering Resultsmentioning

confidence: 99%

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Search for Sub-classes with in Type-Ia Supernovae using Hierarchical Agglomerative Clustering (HAC)

2020

IJETER

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Search of sub-classes within Type Ia Supernovae is a topic of debate in cosmology. Researchers have considered diverse perspectives while searching for sub-classes in various studies. In the present study, SNe Ia have been investigated based on morphology of host galaxy and location of the progenitor within the host galaxy. Hierarchical Agglomerative Clustering technique has been applied on a sample of 43 type Ia Supernovae for the purpose. Our results show that spiral galaxies (Sb, Sc, Sd) favour brighter SNe Ia as compared to S0 and ellipticals. Also, the frequency of occurrence of brighter SNe is less towards the outer regions of the host galaxies. The reason could be the difference in metalicity among the host galaxies as well as the variation in metalicity at different locations within the host galaxy.

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Section: Validation Of Clustering Resultsmentioning

confidence: 99%

“…Repeat steps 1-2 until all data points get clustered into a single cluster. [19,20] and other clustering algorithms [18]. The process followed from data collection to result interpretation is displayed in figure 2.…”

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confidence: 99%