Related papers: Gamma-ray burst light curve reconstruction with pr…
A unified explanation of the variety of long-duration gamma-ray burst (GRB) light curves (LCs) is essential for identifying the dissipation mechanism and possibly the nature of their central engines. In the past, a model was proposed to…
The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift…
Abnormality detection is a challenging task due to the dependence on a specific context and the unconstrained variability of practical scenarios. In recent years, it has benefited from the powerful features learnt by deep neural networks,…
Bidirectional recurrent neural networks (RNN) are trained to predict both in the positive and negative time directions simultaneously. They have not been used commonly in unsupervised tasks, because a probabilistic interpretation of the…
Gamma-ray bursts (GRBs), which have been observed up to redshifts $z \approx 9.5$ can be good probes of the early universe and have the potential of testing cosmological models. The analysis by Dainotti of GRB Swift afterglow lightcurves…
Gamma-ray Bursts (GRBs) are bursts of $\gamma$-rays generated from relativistic jets launched from catastrophic events such as massive star core collapse or binary compact star coalescence. Previous studies suggested that GRB emission is…
This manuscript presents a multilevel analysis of gamma-ray bursts (GRBs). We focus on the plateau phase, which is often observed in the light curves (LCs) of GRBs. We discuss its observational properties and then thoroughly examine…
The TeV observations of GRB~221009A provided us with a unique opportunity to analyze the contemporaneous phase in which both prompt and afterglow emissions are seen simultaneously. To describe this initial phase of Gamma-Ray Burst…
We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated image and utilizes the Recurrent Inference Machine (RIM) to…
Gamma-ray bursts (GRBs) are the most brilliant objects in the Universe but efforts to estimate the total energy released in the explosion -- a crucial physical quantity -- have been stymied by their unknown geometry: spheres or cones. We…
The modelling of gamma-ray burst (GRB) spectra has considerable potential for increasing the understanding of these enigmatic sources. A diversity of ideas and analyses has been generated over the last two decades to explain line features…
The simplest model of the afterglows of the gamma-ray bursts (GRBs) envisions a spherical blast wave with a power-law distribution of electron energy above some cutoff running into a constant density medium. A refinement involves a narrow…
The ultra-relativistic outflows powering gamma-ray bursts (GRBs) acquire angular structure through their interaction with external material. They are often characterized by a compact, nearly uniform narrow core (with half-opening angle…
Gamma-ray burst (GRB) engines are probed most intimately during the prompt gamma-ray luminous phase when the expanding blast wave is closest to the explosion center. Using GRBs 990123 and 940217 as guides, we briefly review observations of…
Graph processes exhibit a temporal structure determined by the sequence index and and a spatial structure determined by the graph support. To learn from graph processes, an information processing architecture must then be able to exploit…
Gamma-ray bursts (GRBs), as a possible probe to extend the Hubble diagram to high redshifts, have attracted much attention recently. In this paper, we select two samples of GRBs that have a plateau phase in X-ray afterglow. One is short…
The diverse and complex light curves of gamma-ray bursts (GRBs) remain an outstanding astrophysical mystery. Here we report the results of 2-1/2-dimensional particle-in-cell (PIC) simulations of the relativistic expansion of magnetized…
Leading models for the "central engine" of long, soft gamma-ray bursts (GRBs) are briefly reviewed with emphasis on the collapsar model. Growing evidence supports the hypothesis that GRBs are a supernova-like phenomenon occurring in star…
Aims. An attempt to classify gamma-ray bursts (GRBs) with a low level of supervision using the state-of-the-start approaches stemming from graph theory was undertaken. Methods. Graph-based classification methods, relying on different…
Internal-Collision-induced Magnetic Reconnection and Turbulence (ICMART) model is a widely accepted model for explaining how high-magnetization jets produce gamma-ray burst (GRB) prompt emissions. In previous works, we show that this model…