Detailed Time Resolved Spectral and Temporal Investigations of SGR J1550-5418 Bursts Detected with Fermi/Gamma-ray Burst Monitor

TL;DR

This study performs a detailed time-resolved spectral analysis of SGR J1550-5418 bursts using machine learning and multiple spectral models, revealing consistent spectral properties, correlations, and potential quasiperiodic oscillations.

Contribution

Introduces a novel two-step temporal segmentation method combined with machine learning for spectral analysis of magnetar bursts, providing new insights into their spectral evolution and oscillations.

Findings

Most burst segments fit well with the COMPT model.

Spectral parameters follow Gaussian or skewed Gaussian distributions.

Identified five potential quasiperiodic spectral oscillation candidates.

Abstract

We have conducted a time-resolved spectral analysis of magnetar bursts originating from SGR J1550-5418. Our analysis utilizes a two-step methodology for temporal segmentation of the data. We first generated and fitted overlapping time segments. Subsequently, we obtained non-overlapping time segments with varying lengths based on their spectral evolution patterns, employing a machine learning algorithm called k-means clustering. For the fitting process, we employed three distinct models, namely a modified blackbody (MBB-RCS), a double blackbody (BB+BB), and a power law with an exponential cut-off (COMPT) model. We found that nearly all of the time segments fit well with the COMPT model. Both the average peak energy in the ${\nu}$F${\nu}$ spectra (Epeak) and Photon Index parameters follow a Gaussian distribution with the means ${\sim}$30 keV and -0.5, respectively. Furthermore, there is a strong positive correlation between the cooler and hotter temperature parameters of the BB+BB model, and both two parameters show a Gaussian distribution with peaks ${\sim}$4 keV and 12 keV, respectively. Additionally, we found that the distribution of the temperature parameter of the MBB-RCS model can be fitted with a skewed Gaussian function with a peak ${\sim}$9-10 keV. Lastly, we searched for quasiperiodic spectral oscillations (QPSOs) in the hardness ratio evolution of the bursts. We identified five potential QPSO candidates at frequencies ranging from ${\sim}$15 Hz to ${\sim}$68 Hz. We discuss and compare these results with previous studies.