Related papers: A Deep Learning Method for AGILE-GRID GRB Detectio…
Detections of very-high-energy (VHE; > 100 GeV) photons from Gamma-ray bursts (GRBs) can provide fundamental information on the involved radiative processes, physical composition of the ejecta and acceleration processes. The High Altitude…
We discuss INTEGRAL's capabilities to detect a high redshift population of Gamma-Ray Bursts (GRBs) in comparison to other high-energy missions. Emphasis is done on the study of the relative capabilities of IBIS on board INTEGRAL with…
Millilensing of Gamma-Ray Bursts (GRBs) is expected to manifest as multiple emission episodes in a single triggered GRB with similar light-curve patterns and similar spectrum properties. Identifying such lensed GRBs could help improve…
The Zir\`e experiment onboard NUSES space mission has several science goals, including the measurements of charged particles and light nuclei from few up to hundreds of MeVs, for the study of low-energy cosmic rays, space weather phenomena,…
The recent advances in Gravitational-wave astronomy have greatly accelerated the study of Multimessenger astrophysics. There is a need for the development of fast and efficient algorithms to detect non-astrophysical transients and noises…
The division of Gamma-ray bursts (GRBs) into different classes, other than the "short" and "long", has been an active field of research. We investigate whether GRBs can be classified based on a broader set of parameters, including prompt…
Detection of spectral line in gamma-ray bursts (GRBs) is importance for studying GRB physics, as it provides insights into the composition and physical conditions of the GRB environment. However, progress in detecting X-ray or gamma-ray…
Gradient-weighted Class Activation Mapping (Grad- CAM), is an example-based explanation method that provides a gradient activation heat map as an explanation for Convolution Neural Network (CNN) models. The drawback of this method is that…
With the discovery of gravitational waves (GWs), Active Galactic Nuclei (AGN) disks have emerged as an interesting environment for hosting a fraction of their sources. AGN disks are conducive to forming both long and short Gamma-Ray Bursts…
Previously we proposed a novel method to inspect the isotropy of the properties of gamma-ray bursts (GRBs) such as their duration, fluences and peak fluxes at various energy bands and different time scales, complementary to existing studies…
Gamma-ray bursts (GRBs) can be probes of the early universe, but currently, only 26% of GRBs observed by the Neil Gehrels Swift Observatory GRBs have known redshifts ($z$) due to observational limitations. To address this, we estimated the…
Fault detection in power distribution grids is critical for ensuring system reliability and preventing costly outages. Moreover, fault detection methodologies should remain robust to evolving grid topologies caused by factors such as…
In this paper, we design Graph Neural Networks (GNNs) with attention mechanisms to tackle an important yet challenging nonlinear regression problem: massive network localization. We first review our previous network localization method…
Although it is generally assumed that there are two dominant classes of gamma-ray bursts (GRB) with different typical durations, it has been difficult to unambiguously classify GRBs as short or long from summary properties such as duration,…
We have performed a systematic study of Gamma-Ray Bursts (GRBs), which have various values in the peak energy of the ${\nu}F_{\nu}$ spectrum of the prompt emission, $E_{{\rm peak}}$, observed by \textsl{Swift}/BAT and \textsl{Fermi}/GBM,…
The Gamma-Ray Burst Monitor (GBM) will significantly augment the science return from the Fermi Observatory in the study of Gamma-Ray Bursts (GRBs). The primary objective of GBM is to extend the energy range over which bursts are observed…
We introduce a new capability of the Neil Gehrels Swift Observatory, dubbed `continuous commanding,' achieving 10 seconds latency response time on-orbit to unscheduled Target of Opportunity requests. This allows Swift to respond to early…
We develop a graph active learning pipeline (GAP) to detect surface water and in-river sediment pixels in satellite images. The active learning approach is applied within the training process to optimally select specific pixels to generate…
Complex organic molecules (COMs) are observed to be abundant in various astrophysical environments, in particular toward star forming regions they are observed both toward protostellar envelopes as well as shocked regions. Emission spectrum…
Gravity inversion is the problem of estimating subsurface density distributions from observed gravitational field data. We consider the two-dimensional (2D) case, in which recovering density models from one-dimensional (1D) measurements…