A SEARCH FOR SELF-SIMILARITIES IN BATSE GAMMA-RAY BURST EMISSIONS USING AGGLOMERATIVE CLUSTERING

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dc.contributor.authorCannon, Thomas W
dc.date.accessioned2020-08-24T16:06:20Z
dc.date.available2020-08-24T16:06:20Z
dc.date.updated2020-08-24T16:06:20Z
dc.description.abstractWe present a new method for categorizing Gamma-Ray Burst (GRB) emission episodes with similar light curves from the Burst and Transient Source Experiment (BATSE) onboard NASA’s Compton Gamma-Ray Observatory (CGRO). We compare normalized time-series data from any two respective GRBs’ 64ms light curves using several statistical tests. The comparisons are used in the construction of similarity matrices as input for a hierarchical clustering algorithm. With the new application of this data mining tool, we begin to see similar GRB light curves cluster together by emission properties that exist independent of their amplitude and time scales, leading to a unique understanding of GRB physics.
dc.identifier.urihttp://hdl.handle.net/123456789/3809
dc.language.rfc3066en
dc.titleA SEARCH FOR SELF-SIMILARITIES IN BATSE GAMMA-RAY BURST EMISSIONS USING AGGLOMERATIVE CLUSTERING
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