Confirmation of Binary Clustering in Gamma-Ray Bursts through an Integrated $p$-value from Multiple Nonparametric Tests of Hypotheses
TLDR
This paper confirms binary clustering in gamma-ray bursts using a new nonparametric distance measure and integrated p-value from multiple statistical tests.
Key contributions
- Developed a new nonparametric, interpoint distance-based measure for clustering analysis.
- Confirmed binary clustering (short and long) in gamma-ray bursts, resolving prior conflicts.
- Employed multiple nonparametric statistical tests and an integrated p-value for robust validation.
Why it matters
This research settles a long-standing debate about the fundamental nature of gamma-ray burst populations. By providing robust statistical confirmation of binary clustering, it offers a clearer understanding of these powerful cosmic events, crucial for future astrophysical models and classifications.
Original Abstract
The paper applies a new, nonparametric, interpoint distance-based measure to confirm the inherent groups prevailing in the brightest source of light in the universe: gamma-ray bursts. Our effective metric, in association with clustering methods like Gaussian-mixture model-based and $K$-means algorithms, resolves the conflict regarding the possibility about existence of more than binary clusters in the gamma-ray burst population. Here we carry out multiple nonparametric statistical tests of hypotheses, as many as the number of bursts available from the `BATSE' catalog. An integrated $p$-value achieved from the aforesaid dependent tests solves our concern confirming two groups of short and long bursts.
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