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Spatial patterns of the Brusselator model with asymmetric Lévy diffusion |
| Hongwei Yin(尹洪位)1,†, Shangtao Yang(杨尚涛)1, Xiaoqing Wen(文小庆)1, Haohua Wang(王浩华)2, and Shufen Yang(杨淑芬)3 |
1 School of Mathematics and Statistics, Xuzhou University of Technology, Xuzhou 221111, China;
2 School of Mathematics and Statistics, Hainan University, Haikou 570228, China;
3 Jiangxi Institute of Applied Science and Technology, Nanchang 330100, China |
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Abstract The formation of spatial patterns is an important issue in reaction-diffusion systems. Previous studies have mainly focused on the spatial patterns in reaction-diffusion models equipped with symmetric diffusion (such as normal or fractional Laplace diffusion), namely, assuming that spatial environments of the systems are homogeneous. However, the complexity and heterogeneity of spatial environments of biochemical reactions in vivo can lead to asymmetric diffusion of reactants. Naturally, there arises an open question of how the asymmetric diffusion affects dynamical behaviors of biochemical reaction systems. To answer this, we build a general asymmetric Lévy diffusion model based on the theory of a continuous time random walk. In addition, we investigate the two-species Brusselator model with asymmetric Lévy diffusion, and obtain a general condition for the formation of Turing and wave patterns. More interestingly, we find that even though the Brusselator model with symmetric diffusion cannot produce steady spatial patterns for some parameters, the asymmetry of Lévy diffusion for this model can produce wave patterns. This is different from the previous result that wave instability requires at least a three-species model. In addition, the asymmetry of Lévy diffusion can significantly affect the amplitude and frequency of the spatial patterns. Our results enrich our knowledge of the mechanisms of pattern formation.
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Received: 11 June 2024
Revised: 25 August 2024
Accepted manuscript online: 29 August 2024
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PACS:
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02.30.Oz
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(Bifurcation theory)
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45.70.Qj
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(Pattern formation)
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| Fund: This work is supported by the National Natural Science Foundation of China (Grant Nos. 62066026, 62363027, and 12071408), PhD program of Entrepreneurship and Innovation of Jiangsu Province, Jiangsu University ’Blue Project’, the Natural Science Foundation of Jiangxi Province (Grant No. 20224BAB202026), and the Science and Technology Research Project of Jiangxi Provincial Department of Education (Grant No. GJJ2203316). |
Corresponding Authors:
Hongwei Yin
E-mail: hongwei-yin@hotmail.com
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Cite this article:
Hongwei Yin(尹洪位), Shangtao Yang(杨尚涛), Xiaoqing Wen(文小庆), Haohua Wang(王浩华), and Shufen Yang(杨淑芬) Spatial patterns of the Brusselator model with asymmetric Lévy diffusion 2024 Chin. Phys. B 33 110202
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[1] Turing A M 1952 Phil. Tran. Roy. Soc. London B 237 37
[2] Tarnita C E, Bonachela J A, Sheffer E, Guyton J A, Coverdale T C, Long R A and Pringle R M 2017 Nature 541 398
[3] Shoji H and Ohta T 2015 Phys. Rev. E 91 032913
[4] Banerjee M and Banerjee S 2012 Mathematical Biosciences 236 64
[5] Wang Y, Cao J, Sun G Q and Li J 2014 Physica A 412 137
[6] Jacobo A and Hudspeth A J 2014 Proc. Natl. Acad. Sci. USA 111 15444
[7] Korvasová K, Gaffney E A, Maini P K, Ferreira M A and Klika V 2015 Journal of Theoretical Biology 367 286
[8] Hara N and Konishi K 2018 Phys. Rev. E 97 052201
[9] Vetter R and Iber D 2020 Nat. Commun. 13 1145
[10] Henry B I, Langlands T and Wearne S L 2006 Phys. Rev. E 74 031116
[11] Carreras B A, Lynch V E and Del-Castillo-Negrete D 2003 Phys. Rev. Lett. 91 018302
[12] Nec Y, Nepomnyashchy A A and Golovin A A 2008 Europhys. Lett. 82 58003
[13] Golovin A A, Matkowsky B J and Volpert V A 2008 SIAM Journal on Applied Mathematics 69 251
[14] Jia K, Hu L and Nie L 2024 Chin. Phys. B 33 020502
[15] Gao J, Wang X, Liu X and Shen C 2023 Chin. Phys. B 32 070503
[16] Zhang L and Tian C 2014 Phys. Rev. E 90 062915
[17] Metzler R and Klafter J 2020 Physics Reports 339 1
[18] Kutner R and Masoliver J 2017 Euro. Phys. J. B 90 50
[19] Denisov S, Klafter J and Zaburdaev V 2015 Rev. Mod. Phys. 87 483
[20] Yuste S B, Abad E and Lindenberg K 2010 Phys. Rev. E 82 061123
[21] Fedotov S 2010 Phys. Rev. E 81 011117
[22] Lombardo M C, Sammartino M, Sciacca V and Gambino G 2013 Phys. Rev. E 88 042925
[23] Pena B and Pérez-García C 2001 Phys. Rev. E 64 056213
[24] Schmiedeberg M, Stark H and Zaburdaev V 2008 Phys. Rev. E 78 011119
[25] Mainardi F, Luchko Y and Pagnini G 2007 arXiv:cond-mat/0702419 [cond-mat.stat-mech]
[26] Mathai A M, Saxena R K and Haubold H J 2009 The H-Function: Theory and Applications (New York: Springer) p. 79
[27] Villar-Sepúlveda E and Champneys A R 2023 Journal of Mathematical Biology 86 39
[28] Yin H and Wen X 2018 Scientific Reports 8 5070
[29] Guo B 1998 Spectral methods and their applications (Singapore: World Scientific) p. 58 |
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