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Register a new userOn the PDS of GRB light curves
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In spite of the complicated behavior in the time domain, long GRBs show a simpler behavior in the Fourier domain of frequencies, represented by power density spectra, PDS. Recently, there are some relations found between GRBs properties and PDS parameters, modeled by power-laws. Among them, the correlation between peak energy $E_{peak}$ and PDS slope $alpha$ shows a clear evidence. In this work we try to understand the origin of this correlation, making use of synthetic pulses. We find some preliminary evidences that $E_{peak}-alpha$ relation can be seen as a new confirmation of the empiric relations $E_{peak}-L$ and $t_{p}-L$ for GRBs.
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We have collected all of the published photometry for GRB 990123 and GRB 990510, the first two gamma-ray bursts where breaks were seen in the light curves of their optical afterglows, and determined the shapes of their light curves and the break times. These parameters were used to investigate the physical mechanisms responsible for the breaks and the nature of the ambient medium that the bursts occurred in. The light curve for GRB 990123 is best fit by a broken power law with a break 1.68 +/- 0.19 days after the burst, a slope of alpha1 = -1.12 +/- 0.08 before the break, and a slope of alpha2 = -1.69 +/- 0.06 after the break. This is consistent with a collimated outflow with a fixed opening angle (theta0) of approximately five degrees. In this case the break in the light curve is due to the relativistic fireball slowing to a gamma factor of approximately 1 / theta0. The light curve for GRB 990510 is best fit by a continuous function with an early-time slope of alpha1 = -0.54 +/- 0.14, a late-time slope of alpha2 = -1.98 +/- 0.19, and a slow transition between the two regimes approximately one day after the burst. This is consistent with a collimated outflow with an opening angle of approximately five degrees that is initially radiative, but undergoes a sideways expansion that begins approximately one day after the burst. This sideways expansion is responsible for the slow break in the light curve.
We calculate radio-to-X-ray light curves for afterglows caused by non-thermal emission from a highly relativistic blast wave, which is inferred from the gamma-ray flux detected in GRB 980425 and from the very bright radio emission detected in SN 1998bw. We find that the observed gamma-ray and radio light curves are roughly reproduced by the synchrotron emission from a relativistic fireball. The optical flux predicted for the non-thermal emission is well below that of the thermal emission observed for SN 1998bw so that it will not be seen at least for a few years. The model predicts the X-ray flux just above the detection limit of BeppoSAX for the epoch when it was pointed to the field of GRB980425. Therefore, the nondetection of X-ray and optical afterglows is consistent with the model. The models presented here are consistent with the physical association between SN 1998bw and GRB980425, and lend further support to the idea that this object might correspond to an event similar to the ``hypernova or ``collapsar -- events in which the collapse of a massive star forms a rotating black hole surrounded by a disk of the remnant stellar mantle.
Aims: We investigate the behavior of the frequency-centered light curves expected within the standard model of Gamma Ray Bursts allowing the maximum electron energy to be a free parameter permitted to take low values. Methods: We solve the spatially averaged kinetic equations which describe the simultaneous evolution of particles and photons, obtaining the multi-wavelength spectra as a function of time. From these we construct the frequency-centered light curves giving emphasis in the X-ray and optical bands. Results: We show that in cases where the maximum electron energy takes low values, the produced X-ray light curves show a plateau as the synchrotron component gives its place to the Synhro Self-Compton one in the X-ray band.
We use a sample of 19 Gamma Ray Bursts (GRBs) that exhibit single-peaked optical light curves to test the standard fireball model by investigating the relationship between the time of the onset of the afterglow and the temporal rising index. Our sample includes GRBs and X-ray flashes for which we derive a wide range of initial Lorentz factors ($40 < Gamma < 450$). Using plausible model parameters the typical frequency of the forward shock is expected to lie close to the optical band; within this low typical frequency framework, we use the optical data to constrain $epsilon_e$ and show that values derived from the early time light curve properties are consistent with published typical values derived from other afterglow studies. We produce expected radio light curves by predicting the temporal evolution of the expected radio emission from forward and reverse shock components, including synchrotron self-absorption effects at early time. Although a number of the GRBs in this sample do not have published radio measurements, we demonstrate the effectiveness of this method in the case of {it Swift} GRB 090313, for which millimetric and centrimetric observations were available, and conclude that future detections of reverse-shock radio flares with new radio facilities such as the EVLA and ALMA will test the low frequency model and provide constraints on magnetic models.
Within the last years, the classification of variable stars with Machine Learning has become a mainstream area of research. Recently, visualization of time series is attracting more attention in data science as a tool to visually help scientists to recognize significant patterns in complex dynamics. Within the Machine Learning literature, dictionary-based methods have been widely used to encode relevant parts of image data. These methods intrinsically assign a degree of importance to patches in pictures, according to their contribution in the image reconstruction. Inspired by dictionary-based techniques, we present an approach that naturally provides the visualization of salient parts in astronomical light curves, making the analogy between image patches and relevant pieces in time series. Our approach encodes the most meaningful patterns such that we can approximately reconstruct light curves by just using the encoded information. We test our method in light curves from the OGLE-III and StarLight databases. Our results show that the proposed model delivers an automatic and intuitive visualization of relevant light curve parts, such as local peaks and drops in magnitude.
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