2025ApJ...988..282D

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 nonoverlapping 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 cutoff (COMPT) model. We found that nearly all of the time segments fit well with the COMPT model. Both the average peak energy in the νF_ν spectra (E_peak) and photon index parameters follow a Gaussian distribution with means ∼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 parameters show a Gaussian distribution with peaks ∼4 and 12 keV, respectively. Additionally, we found that the distribution of the temperature parameter of the MBB-RCS model can be fit with a skewed Gaussian function with a peak ∼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 ∼15 to ∼68 Hz. We discuss and compare these results with previous studies.