Investigations On The Light Curve Of Single Pulses In Gamma-Ray Bursts

In the thesis, we firstly review the actuality and progression of the observational and theoretical studies on gamma-ray bursts (GRBs) and their afterglows, which includes their underlying observational properties, primary theoretical models and other correlated phenomenon such as GRB-SN association and GRB cosmology. Subsequently, our investigations on the light curve of single pulses in gamma-ray bursts are summarized and discussed as follows:Firstly, using the Qin pulse model we have interpreted the parameters in KRL function describing the shape of GRB pulses. We find from our analysis that 1) The rise time (t_r) and the decay time (t_d) of pulses are found to be related to the Lorentz factor by a power law, where the power-law for both cases is close to -2; 2) the asymmetry (t_r/t_d) first increases quickly with the comoving pulse width (△τ_θ) and the influence of the comoving pulse shape on the KRL function parameters of the resulting pulses is considerable and can be distinguished by the decay index d when the width is less 2. Once the width exceeds 2 the asymmetry remains nearly invariant with△τ_θand it is very difficult to discern the comoving pulse form from the fitted parameters; and 3) if the value of△τ_θcan be suitably assigned, say 0.1≤△τ_θ≤2, at least some sources in Kocevski sample could be described with Qin pulse model dominated by Doppler effect.By analyzing the relative spectral lags (RSLs) in long bursts between energy channels 1 and 3, we found that the RSLs, "Ï„_rel, 31, are normally distributed and have a mean value of 0.1; that the RSLs are weakly correlated with the FWHM, the asymmetry, peak flux (F_p), peak energy (E_p) and spectral indexesαandβ, while they are uncorrelated with spectral lag (Ï„₃₁), the hardness ratio (HR₃₁) and the peak time (t_m). Our important discovery is that redshift (z) and peak luminosity (L_p) are strongly correlated with the RSL, which can be measured easily and directly, making the RSL a good redshift and peak luminosity or distance indicator.Thirdly, we restudy the spectral lag features of short bright gamma-ray bursts (T₉₀<2.6s) with a BATSE time-tagged event (TTE) sample including 65 single pulse bursts. We conclude that spectral lags of short gamma ray bursts (SGRBs) are normally distributed and concentrated around the value of 0.014, with 40 percent of them having negative lags. With K-S tests, we find the lag distribution is identical with a normal one caused by white noises, which indicates the lags of the vast majority (～94%) of SGRBs are so small that they are negligible or unmeasurable, as Norris & Bonnell have suggested. On the assumption that there is the same relationτ∝±Γ^-η as in long bursts, We interpret the negligible lag in SGRBs as a result of large lorentz factor or large power indexηor both of them.Finally, we have clarified the relations between the observed pulses and their corresponding timescales, such as the angular spreading time, the dynamic time as well as the cooling time. We find that the angular spreading timescale caused by curvature effect of fireball surface only contributes to the falling part of the observed pulses, while the dynamic one in the co-moving frame of the shell merely contributes to the rising portion of pulses provided the radiative time is negligible. In addition, the pulses resulted from the pure radiative cooling time of relativistic electrons exhibit properties of fast rise and slow decay(a quasi-FRED) profile together with smooth peaks. Meanwhile, we find the intrinsic emission time is decided by the ratios of lorentz factors and radii of the shells between short and long bursts. Besides, we interpret the phenomena of wider pulses tending to be more asymmetric to be a consequence of the difference in emission regions. Our results suggest that the long GRB pulses may occur in the regions with larger radius, while the short bursts could locate at the smaller distance from central engine.We here state that the above-mentioned results are more or less constrained by theoretical model or sample size. Therefore, they need to be updated and checked with much more physical model or larger sample, some findings are expected to be verified by new observations in the future.