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Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks
We focus on characterizing the high-energy emission mechanisms of blazars by analyzing the variability in the radio band of the light curves of more than a thousand sources. We are interested in assigning complexity parameters to these sources, modeling the time series of the light curves with the m...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407290/ https://www.ncbi.nlm.nih.gov/pubmed/36010727 http://dx.doi.org/10.3390/e24081063 |
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author | Acosta-Tripailao, Belén Max-Moerbeck, Walter Pastén, Denisse Moya, Pablo S. |
author_facet | Acosta-Tripailao, Belén Max-Moerbeck, Walter Pastén, Denisse Moya, Pablo S. |
author_sort | Acosta-Tripailao, Belén |
collection | PubMed |
description | We focus on characterizing the high-energy emission mechanisms of blazars by analyzing the variability in the radio band of the light curves of more than a thousand sources. We are interested in assigning complexity parameters to these sources, modeling the time series of the light curves with the method of the Horizontal Visibility Graph (HVG), which allows us to obtain properties from degree distributions, such as a characteristic exponent to describe its stochasticity and the Kullback–Leibler Divergence (KLD), presenting a new perspective to the methods commonly used to study Active Galactic Nuclei (AGN). We contrast these parameters with the excess variance, which is an astronomical measurement of variability in light curves; at the same time, we use the spectral classification of the sources. While it is not possible to find significant correlations with the excess variance, the degree distributions extracted from the network are detecting differences related to the spectral classification of blazars. These differences suggest a chaotic behavior in the time series for the BL Lac sources and a correlated stochastic behavior in the time series for the FSRQ sources. Our results show that complex networks may be a valuable alternative tool to study AGNs according to the variability of their energy output. |
format | Online Article Text |
id | pubmed-9407290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94072902022-08-26 Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks Acosta-Tripailao, Belén Max-Moerbeck, Walter Pastén, Denisse Moya, Pablo S. Entropy (Basel) Article We focus on characterizing the high-energy emission mechanisms of blazars by analyzing the variability in the radio band of the light curves of more than a thousand sources. We are interested in assigning complexity parameters to these sources, modeling the time series of the light curves with the method of the Horizontal Visibility Graph (HVG), which allows us to obtain properties from degree distributions, such as a characteristic exponent to describe its stochasticity and the Kullback–Leibler Divergence (KLD), presenting a new perspective to the methods commonly used to study Active Galactic Nuclei (AGN). We contrast these parameters with the excess variance, which is an astronomical measurement of variability in light curves; at the same time, we use the spectral classification of the sources. While it is not possible to find significant correlations with the excess variance, the degree distributions extracted from the network are detecting differences related to the spectral classification of blazars. These differences suggest a chaotic behavior in the time series for the BL Lac sources and a correlated stochastic behavior in the time series for the FSRQ sources. Our results show that complex networks may be a valuable alternative tool to study AGNs according to the variability of their energy output. MDPI 2022-08-02 /pmc/articles/PMC9407290/ /pubmed/36010727 http://dx.doi.org/10.3390/e24081063 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Acosta-Tripailao, Belén Max-Moerbeck, Walter Pastén, Denisse Moya, Pablo S. Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks |
title | Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks |
title_full | Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks |
title_fullStr | Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks |
title_full_unstemmed | Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks |
title_short | Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks |
title_sort | assigning degrees of stochasticity to blazar light curves in the radio band using complex networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407290/ https://www.ncbi.nlm.nih.gov/pubmed/36010727 http://dx.doi.org/10.3390/e24081063 |
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