Multifractality signatures in quasars time series – I. 3C 273

The presence of multifractality in a time series shows different correlations for different timescales as well as intermittent behaviour that cannot be captured by a single scaling exponent. The identification of a multifractal nature allows for a characterization of the dynamics and of the interm...

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Principais autores: Martins, Bruno Leonardo Canto, Belete, A. Bewketu, Bravo, J. P., Leão, I. C., Araujo, J. M. de, Medeiros, J.R. de
Formato: article
Idioma:English
Publicado em: Oxford University Press (OUP)
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Endereço do item:https://repositorio.ufrn.br/jspui/handle/123456789/29407
http://dx.doi.org/10.1093/mnras/sty1316
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Resumo:The presence of multifractality in a time series shows different correlations for different timescales as well as intermittent behaviour that cannot be captured by a single scaling exponent. The identification of a multifractal nature allows for a characterization of the dynamics and of the intermittency of the fluctuations in non-linear and complex systems. In this study, we search for a possible multifractal structure (multifractality signature) of the flux variability in the quasar 3C 273 time series for all electromagnetic wavebands at different observation points, and the origins for the observed multifractality. This study is intended to highlight how the scaling behaves across the different bands of the selected candidate, which can be used as an additional new technique to group quasars based on the fractal signature observed in their time series and determine whether quasars are non-linear physical systems or not. The multifractal detrended moving average algorithm (MFDMA) has been used to study the scaling in non-linear, complex, and dynamic systems. To achieve this goal, we applied the backward (θ = 0) MFDMA method for one-dimensional signals. We observe weak multifractal (close to monofractal) behaviour in some of the time series of our candidate except in the mm, UV and X-ray bands. The non-linear temporal correlation is the main source of the observed multifractality in the time series whereas the heaviness of the distribution contributes less.