Outliers in spectral time lag selected gamma-ray bursts

TL;DR

This paper identifies outliers in gamma-ray burst data using the PAM method to improve the reliability of spectral time lag correlations for cosmological studies.

Contribution

It introduces an outlier detection approach for gamma-ray bursts using PAM and analyzes the impact on spectral time lag correlations.

Findings

Outliers identified include GRBs 980425B and 030528A.

Linear regression shows limited significance after outlier removal.

Further parameter analysis is needed for better correlations.

Abstract

It is possible that the astrophysical {samples} are polluted by some outliers, which might belong to a different sub-class. By removing the outliers, the underline statistical feature may be revealed. {A more reliable correlation can be used as a standard candle relation for the cosmological study.} We present outlier searching for gamma-ray bursts with Partitioning Around Medoids (PAM) method. In this work, we choose three parameters from the sample, while all of them having rest-frame spectral time lag ($\tau_{\rm lag,i}$). In most cases, the outliers are GRBs 980425B and 030528A. Linear regression is carried out for the sample without the outliers. Some of them have passed hypothesis testing, while others have not. However, even for the passed sample, the correlation is not very significant. More parameter combinations should be considered in the future work.