Related papers: Real-time Likelihood Methods for Improved Gamma-ra…
Transient, star-like point sources that appear and vanish over short timescales are described in astronomical images prior to launch of Sputnik. We have reported that transient numbers diminish significantly in Earth's shadow (shadow…
Detection of short gamma-ray bursts (SGRBs) is critically important for the research of compact object mergers and multi-messenger astrophysics, but a significant part of SGRBs fall below the trigger threshold of GRB detectors, and thus are…
We investigate whether a novel method of quantum machine learning (QML) can identify anomalous events in X-ray light curves as transient events and apply it to detect such events from the XMM-Newton 4XMM-DR14 catalog. The architecture we…
We present an enhanced method for the application of Gaussian Mixture Modelling (GMM) to the coherent WaveBurst (cWB) algorithm in the search for short-duration gravitational wave (GW) transients. The supervised Machine Learning method of…
Gamma-Ray Transient Monitor (GTM) is an all-sky monitor onboard the Distant Retrograde Orbit-A (DRO-A) satellite, with the scientific objective of detecting gamma-ray bursts in the energy range of 20 keV to 1 MeV. GTM is equipped with five…
The first Gamma-Ray Burst (GRB) catalog presented by the Fermi-Large Area Telescope (LAT) collaboration includes 28 GRBs, detected above 100 MeV over the first three years since the launch of the Fermi mission. However, more than 100 GRBs…
This thesis comprises the first three chapters dedicated to providing an overview of Gamma Ray-Bursts (GRBs), their properties, the instrumentation used to detect them, and Artificial Intelligence (AI) applications in the context of GRBs,…
There is significant interest in the models for production of short gamma-ray bursts. Until now, the number of known short gamma-ray bursts with multi-wavelength afterglows has been small. While the {\it Fermi} Gamma-Ray Burst Monitor…
Modern time-domain surveys continuously monitor large swaths of the sky to look for astronomical variability. Astrophysical discovery in such data sets is complicated by the fact that detections of real transient and variable sources are…
This is a follow-up sensitivity study on r-mode gravitational wave signals from newborn neutron stars illustrating the applicability of machine learning algorithms for the detection of long-lived gravitational-wave transients. In this…
To investigate GRBs in depth, it is crucial to develop an effective method for identifying GRBs accurately. Current criteria, e.g., onboard blind search, ground blind search, and target search, are limited by manually set thresholds and…
In this paper, we consider the detection of a small change in the frequency of sinusoidal signals, which arises in various signal processing applications. The generalized likelihood ratio test (GLRT) for this problem uses the maximum…
Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the…
In imaging atmospheric Cherenkov telescope (IACT) arrays, the standard method of statistically inferring the existence of a source is based on the maximum likelihood method of Li&Ma (1983). We present a new statistical approach, also based…
We present detailed, multi-wavelength analysis of GRB 210704A: a Fermi Gamma-ray Burst Monitor discovered and Fermi Large Area Telescope (LAT) detected gamma-ray burst (GRB). The burst is dominated by a short ($\approx 2$ s) pulse followed…
Maximum likelihood (ML) detection is an optimal signal detection scheme, which is often difficult to implement due to its high computational complexity, especially in a multiple-input multiple-output (MIMO) scenario. In a system with $N_t$…
A novel application of machine-learning (ML) based image processing algorithms is proposed to analyze an all-sky map (ASM) obtained using the Fermi Gamma-ray Space Telescope. An attempt was made to simulate a one-year ASM from a…
The Rapid and accurate identification of Gamma-Ray Bursts (GRBs) is crucial for unraveling their origins. However, current burst search algorithms frequently miss low-threshold signals or lack universality for observations. In this study,…
Time domain radio astronomy observing campaigns frequently generate large volumes of data. Our goal is to develop automated methods that can identify events of interest buried within the larger data stream. The V-FASTR fast transient system…
The current data acquisition rate of astronomical transient surveys and the promise for significantly higher rates during in the next decade necessitate the development of novel approaches to analyze astronomical data sets and promptly…