Conveners
Gamma-ray bursts and AGNs with machine learning: Monday block 1
- Yong-Feng Huang (Nanjing University)
- Gibran Morales (IRyA-UNAM)
- Maria Dainotti (National Astronomical Observatory of Japan)
Gamma-ray bursts and AGNs with machine learning: Monday block 2
- Maria Dainotti (National Astronomical Observatory of Japan)
- Gibran Morales (IRyA-UNAM)
- Yong-Feng Huang (Nanjing University)
Description
Gamma-ray Bursts offer a unique opportunity to look at the early universe and be probes of star formation and population III stars.
However, we need to solve many challenges in this regard: how to increase the number of redshifts and thus infer them, how to reconstruct lightcurves, etc., and machine learning will help with all of these.
We would like to present the state-of-the-art techniques used to tackle these issues by applying machine learning to GRBs and, more generally, high-energy sources, such as Active Galatic Nuclei.
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Aditya Narendra (Jagiellonian University)08/07/2024, 15:00Gamma-ray bursts and AGNs with machine learningInvited talk in a parallel session
Gamma-ray bursts (GRBs), as they are observed at high redshift (z = 9.4), are vital to cosmological studies and investigating Population III stars. To tackle these studies, we need correlations among relevant GRB variables with the requirement of small uncertainties on their variables. Thus, we must have good coverage of GRB light curves (LCs). However, gaps in the LC hinder the precise...
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Shubham Bhardwaj (SOKENDAI/National Astronomical Observatory of Japan)08/07/2024, 15:30Gamma ray bursts relationships in multi-wavenths as cosmological toolsTalk in a parallel session
Gamma-ray bursts (GRBs) have been observed at very high redshifts, up to 9.4, and can be a crucial astrophysical object for studying the evolutionary history of the universe. However, the rapid dimming of their afterglows, combined with the constrained availability of telescope time, poses challenges in promptly observing these events. This difficulty is particularly pronounced for...
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Yong-Feng Huang (Nanjing University)08/07/2024, 16:00Gamma-ray bursts and AGNs with machine learningInvited talk in a parallel session
The X-ray afterglow of many gamma-ray bursts (GRBs) exhibits a plateau phase, which may be related to continued activities of the central engine. It has been found that there exists a so-called L–T–E correlation for these GRBs, which involves three key parameters, i.e., the isotropic gamma-ray energy Eiso of the prompt phase, the end time Ta of the plateau phase, and the corresponding X-ray...
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Aditya Narendra (Jagiellonian University)08/07/2024, 17:00Gamma-ray bursts and AGNs with machine learningInvited talk in a parallel session
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 GRB redshift (distance) via a supervised statistical learning model that uses optical afterglow observed by Swift and ground-based telescopes. The inferred...
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Shubham Bhardwaj (SOKENDAI/National Astronomical Observatory of Japan)08/07/2024, 17:15Gamma ray bursts relationships in multi-wavenths as cosmological toolsTalk in a parallel session
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 and plateau emission ones. Observational evidence suggests the existence of more GRB subclasses, but results so far are either conflicting or not...
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Lisa Ferro (University of Ferrara)08/07/2024, 17:30Gamma-ray bursts and AGNs with machine learningTalk in a parallel session
The light curves (LCs) of long gamma-ray bursts (GRBs) show a wide variety of morphologies, which current LC simulation models based on the internal shock paradigm still fail to fully reproduce. The reason is that, despite the recent significant advance in understanding the energetics and dynamics of long GRBs, the nature of their inner engine, how the relativist outflow is powered, and the...
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Nicolò Parmiggiani (INAF/OAS Bologna)08/07/2024, 17:45Gamma-ray bursts and AGNs with machine learningInvited talk in a parallel session
AGILE is a high-energy astrophysics space mission launched in 2007 which terminated the operations in 2024. Its payload is comprised of the Gamma-Ray Imaging Detector (GRID), the SuperAGILE X-ray detector, the Mini-Calorimeter (MCAL), and an AntiCoincidence System (ACS).
Over the past few years, the AGILE Team has developed deep learning (DL) models to analyze sky maps and time series...
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Mr Liang Li (ICRANet, Piazza della Repubblica 10, I-65122 Pescara, Italy)08/07/2024, 18:00Gamma-ray bursts and AGNs with machine learningInvited talk in a parallel session
Gamma-ray bursts (GRBs) exhibit a diversity of spectra. Several spectral models (e.g., Band, cutoff power-law, and blackbody) and their hybrid versions (e.g., Band+blackbody) have been widely used to fit the observed GRB spectra. Here, we attempt to collect all the bursts detected by {\it Fermi}-GBM with known redshifts from July 2008 to May 2022, motivated to (i) provide a parameter catalog...
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Shu-Xu Yi (Institute of High Energy Physics, Chinese Academy of Sciences)08/07/2024, 18:15Gamma ray bursts relationships in multi-wavenths as cosmological toolsTalk in a parallel session
The second brightest GRB in history, GRB230307A provides an ideal laboratory to study the details of GRB prompt emission thanks to its extraordinarily high photon statistics and its single broad pulse overall shape characterized by an energy-dependent fast-rise-exponential-decay (FRED) profile. Here we demonstrate that its broad pulse is composed of many rapidly variable short pulses, rather...
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