tokens: To estimate the effective area correction between the different detectors of Fermi and BAT, we adopted the following methodology (Page et al. 2009 ): (i) To find the best-fitting model: Each of the time-resolved spectra of all detectors (BAT, GBM: n6, n7, n9, and b1) was jointly analysed using different spectral functions such as power law, cutoff-power law, and Band, without including the constant factor correction. In this exercise, the time-averaged and time-resolved spectra were found to be better fitted by cutoff-power-law function. (ii) Finding the normalization-offsets: We then simultaneously fitted the five bright time-resolved spectra with the best-fitting model, cutoff-power law, by multiplying the model by a constant of normalization for each instrument. The constant of BAT data was frozen to unity, while those of the GBM detectors were kept free. In addition, these constants were also tied across the respective data sets of the different time-resolved intervals. The relative normalizations were found as, for n6 detector, for n7 detector, for n9 detector, and for b1 detector. These constant factors are consistent with the expected intercalibration uncertainty of up to and hence were used for the subsequent spectral analyses. 3.2 Parameters evolution For characterizing the spectra, we fit the brightest time intervals in both episodes with several phenomenological models including power law with an exponential cutoff (cutoff-power law), blackbody + cutoff-power law, and traditional Band functions. In Fig. 2 , the reduced χ 2 obtained for the different models in the different time intervals are shown. We note that in the brightest time interval (bin 5) of the first episode, blackbody + cutoff-power law model is statistically favoured (i.e reduced χ 2 ∼ 1). On the addition of blackbody component to the cutoff-power law, we also find an improvement in Akaike Information Criterion (AIC; Akaike 1974 ) and Bayesian Information Criterion (BIC; Schwarz et al. 1978 ) by 15 and 7, respectively (see Appendix B ). At the same time, in all other time intervals, this model is also found to give comparable statistics when compared with other models. The Monte Carlo (MC) simulations for estimating the statistical significance of the additional blackbody component with the cutoff-power-law model are performed for the brightest time interval. The difference of χ 2 -statistics between cutoff-power-law model and blackbody + cutoff-power-law model is found to be 19. Here, we assume cutoff-power-law model as the null hypothesis model and blackbody + cutoff-power-law model as the alternate model and simulations are run for realizations. We find that the probability of observing Δ χ 2 > 19 is 10 −2.52 , which corresponds to ∼3 σ significance level. Thus, by considering the above fit statistics and MC simulations obtained in the brightest time bin, we consider blackbody + cutoff-power-law model to be the best-fitting model for all the time-resolved intervals
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