Time Profiles Of Gamma-ray Bursts Research Articles

Two Classes of Gamma-ray Bursts Distinguished within the First Second of Their Prompt Emission

Studies of Gamma-Ray Burst (GRB) properties, such as duration and spectral hardness, have found evidence for additional classes, beyond the short/hard and long/soft prototypes, using model-dependent methods. In this paper, a model-independent approach was used to analyse the gamma-ray light curves of large samples of GRBs detected by BATSE, Swift/BAT and Fermi/GBM. All the features were extracted from the GRB time profiles in four energy bands using the Stationary Wavelet Transform and Principal Component Analysis. t-distributed Stochastic Neighbourhood Embedding (t-SNE) visualisation of the features revealed two distinct groups of Swift/BAT bursts using the T100 interval with 64 ms resolution data. When the same analysis was applied to 4 ms resolution data, two groups were seen to emerge within the first second (T1) post-trigger. These two groups primarily consisted of short/hard (Group 1) and long/soft (Group 2) bursts, and were 95% consistent with the groups identified using the T100 64 ms resolution data. Kilonova candidates, arising from compact object mergers, were found to belong to Group 1, while those events with associated supernovae fell into Group 2. Differences in cumulative counts between the two groups in the first second, and in the minimum variability timescale, identifiable only with the 4 ms resolution data, may account for this result. Short GRBs have particular significance for multi-messenger science as a distinctive EM signature of a binary merger, which may be discovered by its gravitational wave emissions. Incorporating the T1 interval into classification algorithms may support the rapid classification of GRBs, allowing for an improved prioritisation of targets for follow-up observations.

Vector Nonlinear Time-Series Analysis of Gamma-Ray Burst Datasets on Heterogeneous Clusters

The simultaneous analysis of a number of related datasets using a single statistical model is an important problem in statistical computing. A parameterized statistical model is to be fitted on multiple datasets and tested for goodness of fit within a fixed analytical framework. Definitive conclusions are hopefully achieved by analyzing the datasets together. This paper proposes a strategy for the efficient execution of this type of analysis on heterogeneous clusters. Based on partitioning processors into groups for efficient communications and a dynamic loop scheduling approach for load balancing, the strategy addresses the variability of the computational loads of the datasets, as well as the unpredictable irregularities of the cluster environment. Results from preliminary tests of using this strategy to fit gamma-ray burst time profiles with vector functional coefficient autoregressive models on 64 processors of a general purpose Linux cluster demonstrate the effectiveness of the strategy.

Statistics of time histories and spectral variability of GRBs

We introduce new parameters for characterizing gamma-ray burst time profiles and energy spectra. Bursts with short and long duration T 90 are compared, and significant differences are found in the number of pulses and equivalent pulse widths. The trend of the average spectral parameters was resolved at the (α,E p) plane. The comparison between bright and dim bursts is done, which manifests the difference in the average emissivity curves and in the average spectral hardness.

Brightness-dependent Properties of Gamma-Ray Bursts

Brightness-dependent correlations have been conclusively detected in the average time profiles of gamma-ray bursts (GRBs). Determining the time constants of the stretched exponential slopes of the average peak-aligned time profile of GRBs as a function of the peak brightness, we find that the postpeak slope shows time dilation when comparing bright and dim bursts, while the prepeak slope hardly changes. Stronger bursts are thus more symmetric than weaker bursts at a high confidence level. The very weakest bursts have a different shape (i.e., a different stretched exponential index) of their average time profile as compared to brighter bursts. This difference is too large to be explained by trigger effects and Poisson noise. We interpret these correlations as being the result of an intrinsic positive correlation between brightness and complexity of GRBs. This interpretation is directly confirmed by simulations as well as by a morphological classification of bursts. The fact that such a correlation can be observed should impose new constraints on the distribution of GRBs over luminosity distance.

Evidence for “Chain Reaction” in the Time Profiles of Gamma-Ray Bursts

Although the time profiles of gamma ray bursts (GRBs) show extremely diverse behavior, their average statistical properties such as the average peak-aligned profile and the auto-correlation function show simple stretched-exponential behavior. This could indicate that the diversity of all bursts is just due to different random realizations of the same simple stochastic process where the process is scale invariant in time. We illustrate how both the diversity of GRB time profiles and some important average statistical properties can be reproduced in this way using a simple toy model for a stochastic pulse avalanche, which behaves as a chain reaction in a near-critical regime. We suggest that one possibility for the underlying physical process for generating GRBs could be a chain detonation in which reconnecting magnetic turbulent features trigger each other.

A Stretched Exponential Law for the Average Time History of Gamma-Ray Bursts and Their Time Dilations

Individual gamma-ray bursts (GRBs) have very diverse time behavior—from a single pulse to a long complex sequence of chaotic pulses of different timescales. I studied time profiles of GRBs using data from the Compton Gamma Ray Observatory's Burst and Transient Source Experiment (BATSE) and found that the postpeak slope of the average peak-aligned time profile of GRBs obeys a unique and simple analytical law, I ~ exp [-(t/t0)1/3], where t is the time measured from the peak of the event and t0 is a constant ranging from 0.3 s for strong bursts to ~1 s for weak bursts. The average peak-aligned time profile follows this law with good accuracy in the whole time range available for analysis (from fractions of a second to ~120 s after the peak). Such a law (a stretched exponential) appears in processes associated with fractals (e.g., turbulence). The same analysis for solar flares gives a different shape for the average time profile. The dependence of t0 on the brightness of GRBs is presented. The time dilation of the dimmest GRBs relative to the brightest GRBs is at least a factor ~2 and possibly ~3. The statistics (600 GRBs), however, still does not allow us to rule out an intrinsic anticorrelation between intensity and duration of GRBs as a possible explanation of the effect. Probably, it is possible to confirm (or disprove) the cosmological origin of GRBs using the total existing statistics of strong bursts.

The Autocorrelation of Gamma-Ray Burst Time Profiles

The autocorrelation of time profiles of emission from gamma-ray bursts has previously been proved to be a valuable diagnostic for the study of the timing behavior of these bursts. In particular, comparative studies benefited from this diagnostic. However, in these previous studies, the particular shape of the autocorrelation function has not been addressed in great detail. In the present paper we try to explain the autocorrelation shape and behavior. We propose an empirical model that aids in the evaluation of uncertainties in autocorrelation analyses of gamma-ray burst time profiles. Our most important conclusions are that analyses based on the autocorrelation function are not dominated by mathematical properties not connected with the gamma-ray burst phenomenon, and that the uncertainty in the relative time stretching between different photon energy ranges found through such an analysis previously from {ital CGRO} BATSE data is less than or equal to 10{percent}. {copyright} {ital 1996 The American Astronomical Society.}

A new variability parameter for gamma-ray burst time profiles

view Abstract Citations (8) References (4) Co-Reads Similar Papers Volume Content Graphics Metrics Export Citation NASA/ADS A New Variability Parameter for Gamma-Ray Burst Time Profiles Lestrade, John Patrick Abstract We present a parameter that measures the structure of gamma-ray burst time profiles. This parameter is based on the statistics of runs and is a good measure of time profile variability. It is shown to be independent of burst duration and less sensitive to burst distance than algorithms that depend directly on the intensity of a burst. Publication: The Astrophysical Journal Pub Date: July 1994 DOI: 10.1086/187400 Bibcode: 1994ApJ...429L...5L Keywords: Gamma Ray Astronomy; Gamma Ray Bursts; Temporal Distribution; Classifications; Parameterization; Statistical Analysis; Variability; Astronomy; GAMMA RAYS: BURSTS full text sources ADS | data products SIMBAD (2) NED (2)