Maximum entropy principle for Kaniadakis statistics and networks

In this Letter we investigate a connection between Kaniadakis power-law statistics and networks. By following the maximum entropy principle, we maximize the Kaniadakis entropy and derive the optimal degree distribution of complex networks. We show that the degree distribution follows P(k) =P0 expκ (...

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Principais autores: Moreira, Darlan Araújo, Macedo Filho, Antônio de, Silva Junior, Raimundo, Silva, Luciano Rodrigues da
Formato: article
Idioma:English
Publicado em: Elsevier
Assuntos:
Generalized statistics
Degree distribution
Networks
Endereço do item:https://repositorio.ufrn.br/handle/123456789/30641
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spelling ri-123456789-306412020-11-29T07:45:18Z Maximum entropy principle for Kaniadakis statistics and networks Moreira, Darlan Araújo Macedo Filho, Antônio de Silva Junior, Raimundo Silva, Luciano Rodrigues da Generalized statistics Degree distribution Networks In this Letter we investigate a connection between Kaniadakis power-law statistics and networks. By following the maximum entropy principle, we maximize the Kaniadakis entropy and derive the optimal degree distribution of complex networks. We show that the degree distribution follows P(k) =P0 expκ (−k/ηκ ) with expκ (x) = (√1 + κ2x2 + κx)1/κ , and |κ| < 1. In order to check our approach we study a preferential attachment growth model introduced by Soares et al. [Europhys. Lett. 70 (2005) 70] and a growing random network (GRN) model investigated by Krapivsky et al. [Phys. Rev. Lett. 85 (2000) 4629]. Our results are compared with the ones calculated through the Tsallis statistics 2020-11-23T21:20:26Z 2020-11-23T21:20:26Z 2013-05-03 article MACEDO FILHO, A.; MOREIRA, D.A.; SILVA, R.; SILVA, Luciano R. da. Maximum entropy principle for Kaniadakis statistics and networks. Physics Letters A, [S.L.], v. 377, n. 12, p. 842-846, maio 2013. Disponível em: https://www.sciencedirect.com/science/article/pii/S0375960113000984?via%3Dihub. Acesso em: 08 set. 2020. http://dx.doi.org/10.1016/j.physleta.2013.01.032. 0375-9601 https://repositorio.ufrn.br/handle/123456789/30641 10.1016/j.physleta.2013.01.032 en Attribution 3.0 Brazil http://creativecommons.org/licenses/by/3.0/br/ application/pdf Elsevier
institution Repositório Institucional
collection RI - UFRN
language English
topic Generalized statistics
Degree distribution
Networks
spellingShingle Generalized statistics
Degree distribution
Networks
Moreira, Darlan Araújo
Macedo Filho, Antônio de
Silva Junior, Raimundo
Silva, Luciano Rodrigues da
Maximum entropy principle for Kaniadakis statistics and networks
description In this Letter we investigate a connection between Kaniadakis power-law statistics and networks. By following the maximum entropy principle, we maximize the Kaniadakis entropy and derive the optimal degree distribution of complex networks. We show that the degree distribution follows P(k) =P0 expκ (−k/ηκ ) with expκ (x) = (√1 + κ2x2 + κx)1/κ , and |κ| < 1. In order to check our approach we study a preferential attachment growth model introduced by Soares et al. [Europhys. Lett. 70 (2005) 70] and a growing random network (GRN) model investigated by Krapivsky et al. [Phys. Rev. Lett. 85 (2000) 4629]. Our results are compared with the ones calculated through the Tsallis statistics
format article
author Moreira, Darlan Araújo
Macedo Filho, Antônio de
Silva Junior, Raimundo
Silva, Luciano Rodrigues da
author_facet Moreira, Darlan Araújo
Macedo Filho, Antônio de
Silva Junior, Raimundo
Silva, Luciano Rodrigues da
author_sort Moreira, Darlan Araújo
title Maximum entropy principle for Kaniadakis statistics and networks
title_short Maximum entropy principle for Kaniadakis statistics and networks
title_full Maximum entropy principle for Kaniadakis statistics and networks
title_fullStr Maximum entropy principle for Kaniadakis statistics and networks
title_full_unstemmed Maximum entropy principle for Kaniadakis statistics and networks
title_sort maximum entropy principle for kaniadakis statistics and networks
publisher Elsevier
publishDate 2020
url https://repositorio.ufrn.br/handle/123456789/30641
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AT macedofilhoantoniode maximumentropyprincipleforkaniadakisstatisticsandnetworks
AT silvajuniorraimundo maximumentropyprincipleforkaniadakisstatisticsandnetworks
AT silvalucianorodriguesda maximumentropyprincipleforkaniadakisstatisticsandnetworks
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