相关论文: Advancing Gamma-Ray Burst Identification through T…

Cosmological gamma ray bursts (GRBs) are the brightest explosions in the Universe. Satellite detectors, such as Beppo-SAX, HETE2 and more recently Swift, have provided a wealth of data, including the localization and redshifts of subsets of…

Gamma-Ray Burst (GRB) explosions from the first generation of stars offer an exciting opportunity to probe the epoch of reionization. Clues about how and when the intergalactic medium was ionized can be read off their UV emission spectrum.…

Context. Gamma-ray bursts can be located via arrival time signal triangulation using gamma-ray detectors in orbit throughout the solar system. The classical approach based on cross-correlations of binned light curves ignores the Poisson…

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…

Convolutional neural networks (CNNs) are widely used for image recognition and text analysis, and have been suggested for application on one-dimensional data as a way to reduce the need for pre-processing steps. Pre-processing is an…

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…

In this study, we present the Graph Sub-Graph Network (GSN), a novel hybrid image classification model merging the strengths of Convolutional Neural Networks (CNNs) for feature extraction and Graph Neural Networks (GNNs) for structural…

The prompt emission mechanism of gamma-ray bursts (GRB) even after several decades remains a mystery. However, it is believed that correlations between observable GRB properties given their huge luminosity/radiated energy and redshift…

Gamma-ray bursts (GRBs) are commonly attributed to the demise of massive stars or the merger of binary compact objects. However, their varied emission characteristics strongly imply the existence of multiple GRB classes based on progenitor…

Gamma-ray bursts (GRBs) are the most luminous electromagnetic explosions in the Universe, which emit up to $8.8\times10^{54}$ erg isotropic equivalent energy in the hard X-ray band. The high luminosity makes them detectable out to the…

Facial Expression Recognition (FER) is vital for understanding interpersonal communication. However, existing classification methods often face challenges such as vulnerability to noise, imbalanced datasets, overfitting, and generalization…

The accurate spatial location of gamma-ray bursts (GRBs) is crucial for both producing a detector response matrix (DRM) and follow-up observations by other instruments. The Fermi Gamma-ray Burst Monitor (GBM) has the largest field of view…

In this paper, we present the development and the results of a new search pipeline for short gamma-ray bursts (sGRBs) in the publicly available data from the Gamma-Ray Burst Monitor (GBM) on board the Fermi satellite. This pipeline uses…

Quality control is a fundamental component of many manufacturing processes, especially those involving casting or welding. However, manual quality control procedures are often time-consuming and error-prone. In order to meet the growing…

Recently, both theoretical arguments and observational evidence suggested that a small fraction of fast radio bursts (FRBs) could be associated with gamma-ray bursts (GRBs). If such FRB/GRB association systems are commonly detected in the…

Giant Star-forming Clumps (GSFCs) are areas of intensive star-formation that are commonly observed in high-redshift (z>1) galaxies but their formation and role in galaxy evolution remain unclear. High-resolution observations of low-redshift…

We construct the Hubble diagram (HD) of Gamma-Ray Bursts (GRBs) with redshifts reaching up to $z \sim 6$, by using five luminosity vs. luminosity indicator relations calibrated with the Cardassian cosmology. This model has a major…

A Hyperspectral image contains much more number of channels as compared to a RGB image, hence containing more information about entities within the image. The convolutional neural network (CNN) and the Multi-Layer Perceptron (MLP) have been…

Graph Neural Networks (GNNs) have achieved tremendous success in graph representation learning. Unfortunately, current GNNs usually rely on loading the entire attributed graph into network for processing. This implicit assumption may not be…

Breast cancer is the most common cancer in the world and the most prevalent cause of death among women worldwide. Nevertheless, it is also one of the most treatable malignancies if detected early. In this paper, a deep convolutional neural…