Infinite series symmetry reduction solutions to the modified KdV--Burgers equation
Yao Ruo-Xia(姚若侠)a)b)c)†, Jiao Xiao-Yu(焦小玉)a), and Lou Sen-Yue(楼森岳)a)c)
a Department of Physics, Shanghai Jiao Tong University, Shanghai 200062, China; b School of Computer Science, Shaanxi Normal University, Xi’an 710062, China; c Department of Physics, Ningbo University, Ningbo 315211, China
Abstract From the point of view of approximate symmetry, the modified Korteweg--de Vries--Burgers (mKdV--Burgers) equation with weak dissipation is investigated. The symmetry of a system of the corresponding partial differential equations which approximate the perturbed mKdV--Burgers equation is constructed and the corresponding general approximate symmetry reduction is derived; thereby infinite series solutions and general formulae can be obtained. The obtained result shows that the zero-order similarity solution to the mKdV--Burgers equation satisfies the Painlevé II equation. Also, at the level of travelling wave reduction, the general solution formulae are given for any travelling wave solution of an unperturbed mKdV equation. As an illustrative example, when the zero-order tanh profile solution is chosen as an initial approximate solution, physically approximate similarity solutions are obtained recursively under the appropriate choice of parameters occurring during computation.
Received: 03 July 2008
Revised: 05 August 2008
Accepted manuscript online:
Fund: Project supported by the National
Natural Science Foundations of China (Grant Nos 10735030, 10475055,
and 90503006), the National Basic Research Program of China (Grant
No 2007CB814800), the Science Foundation for Post Doctorate Research
from the Ministry
Cite this article:
Yao Ruo-Xia(姚若侠), Jiao Xiao-Yu(焦小玉), and Lou Sen-Yue(楼森岳) Infinite series symmetry reduction solutions to the modified KdV--Burgers equation 2009 Chin. Phys. B 18 1821
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.