Analysis of the structural complexity of Crab Nebula observed at radio frequency using a multifractal approach

Fuente: arXiv
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Hauptverfasser: Chanu, Athokpam Langlen, Chingangbam, Pravabati, Rahman, Fazlu, Singh, R. K. Brojen, Kharb, Preeti
Format: Preprint
Veröffentlicht: 2022
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author Chanu, Athokpam Langlen
Chingangbam, Pravabati
Rahman, Fazlu
Singh, R. K. Brojen
Kharb, Preeti
author_facet Chanu, Athokpam Langlen
Chingangbam, Pravabati
Rahman, Fazlu
Singh, R. K. Brojen
Kharb, Preeti
contents The Crab Nebula is an astrophysical system that exhibits complex morphological patterns at different observing frequencies. We carry out a systematic investigation of the structural complexity of the nebula using publicly available imaging data at radio frequency. For the analysis, we use the well-known multifractal detrended fluctuation analysis in two dimensions. We find that radio data exhibit long-range correlations, as expected from the underlying physics of the supernova explosion and evolution. The correlations follow a power-law scaling with length scales. The structural complexity is found to be multifractal in nature, as evidenced by the dependence of the generalized Hurst exponent on the order of the moments of the detrended fluctuation function. By repeating the analysis on shuffled data, we further probe the origin of the multifractality in the radio imaging data. For the radio data, we find that the probability density function is close to a Gaussian form. Hence, the multifractal behavior is due to the differing nature of long-range correlations of the large and small detrended fluctuation field values. We investigate the multifractal parameters across different partitions of the radio image and find that the structures across the image are highly heterogeneous, making the Crab Nebula a structurally complex astrophysical system. Our analysis thus provides a fresh perspective on the morphology of the Crab Nebula from a complexity science viewpoint.
format Preprint
id arxiv_https___arxiv_org_abs_2206_04717
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Analysis of the structural complexity of Crab Nebula observed at radio frequency using a multifractal approach
Chanu, Athokpam Langlen
Chingangbam, Pravabati
Rahman, Fazlu
Singh, R. K. Brojen
Kharb, Preeti
Adaptation and Self-Organizing Systems
Astrophysics of Galaxies
Data Analysis, Statistics and Probability
The Crab Nebula is an astrophysical system that exhibits complex morphological patterns at different observing frequencies. We carry out a systematic investigation of the structural complexity of the nebula using publicly available imaging data at radio frequency. For the analysis, we use the well-known multifractal detrended fluctuation analysis in two dimensions. We find that radio data exhibit long-range correlations, as expected from the underlying physics of the supernova explosion and evolution. The correlations follow a power-law scaling with length scales. The structural complexity is found to be multifractal in nature, as evidenced by the dependence of the generalized Hurst exponent on the order of the moments of the detrended fluctuation function. By repeating the analysis on shuffled data, we further probe the origin of the multifractality in the radio imaging data. For the radio data, we find that the probability density function is close to a Gaussian form. Hence, the multifractal behavior is due to the differing nature of long-range correlations of the large and small detrended fluctuation field values. We investigate the multifractal parameters across different partitions of the radio image and find that the structures across the image are highly heterogeneous, making the Crab Nebula a structurally complex astrophysical system. Our analysis thus provides a fresh perspective on the morphology of the Crab Nebula from a complexity science viewpoint.
title Analysis of the structural complexity of Crab Nebula observed at radio frequency using a multifractal approach
topic Adaptation and Self-Organizing Systems
Astrophysics of Galaxies
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2206.04717