2022
DOI: 10.3847/1538-4357/ac887a
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Variability Signatures of a Burst Process in Flaring Gamma-Ray Blazars

Abstract: Blazars exhibit stochastic flux variability across the electromagnetic spectrum, often exhibiting heavy-tailed flux distributions, commonly modeled as lognormal. However, Tavecchio et al. and Adams et al. found that the high-energy gamma-ray flux distributions of several of the brightest flaring Fermi-LAT flat-spectrum radio quasars (FSRQs) are well modeled by an even heavier-tailed distribution, which we show is the inverse gamma distribution. We propose an autoregressive inverse gamma variability model in wh… Show more

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Cited by 3 publications
(2 citation statements)
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“…Since its public release in December 2021, the community has been using the LCR data to exploit, so far, a number of active galactic nuclei science topics. A recent study [11] used deep learning techniques to investigate the structure in gamma-ray blazars' complex variability patterns that traditional analysis methods may miss. They applied self-supervised deep learning to create a model that encodes a representation of blazar variability.…”
Section: Scientific Impactmentioning
confidence: 99%
“…Since its public release in December 2021, the community has been using the LCR data to exploit, so far, a number of active galactic nuclei science topics. A recent study [11] used deep learning techniques to investigate the structure in gamma-ray blazars' complex variability patterns that traditional analysis methods may miss. They applied self-supervised deep learning to create a model that encodes a representation of blazar variability.…”
Section: Scientific Impactmentioning
confidence: 99%
“…Daylong flux variations have been observed in the Crab Nebula (Abdo et al 2010b;Balbo et al 2011;Striani et al 2011;Tavani et al 2011) as well as in multiple novae (Cheung et al 2016;Li et al 2017b;Franckowiak et al 2018;Nelson et al 2019). Blazars have been observed to emit gamma rays whose emission timescales can vary from days and weeks (Brill 2023;Cutini et al 2023;Dinesh et al 2023;Pittori et al 2023) to months or even years (Abdo et al 2010c;Nolan et al 2012;Collaboration 2015;Abdollahi et al 2020;Peñil et al 2022;Otero-Santos et al 2023).…”
Section: Introductionmentioning
confidence: 99%