Nonlinear stability of smooth multi-solitons for the Dullin-Gottwald-Holm equation

被引:3
作者
Wu, Zhi-Jia [1 ]
Tian, Shou-Fu [1 ]
机构
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Peoples R China
基金
中国国家自然科学基金;
关键词
SHALLOW-WATER EQUATION; KORTEWEG-DE-VRIES; INVERSE SCATTERING TRANSFORM; CAMASSA-HOLM; SOLITARY WAVES; WELL-POSEDNESS; GLOBAL EXISTENCE; BREAKING; KDV;
D O I
10.1016/j.jde.2024.08.037
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this work, the stability of exact smooth multi-solitons for the Dullin-Gottwald-Holm (DGH) equation is investigated for the first time. Firstly, through the inverse scattering approach, we derive the conservation laws in terms of scattering data and multi-solitons related to the discrete spectrum based on the Lax pair of the DGH equation. Notably, a new series Hamiltonian derived from bi-Hamilton structure are equivalent to the conservation laws, and can also be expressed in terms of scattering data. Thus we successfully connect scattering data (multi-solitons) to the recursion operator between Hamiltonian, and to the Lyapunov functional constructed from Hamiltonian. With this Lyapunov functional, it is identified that these smooth multi-solitons serve as non-isolated constrained minimizers, adhering to a suitable variational nonlocal elliptic equation. Moreover, the integrable properties of the recursion operator are presented, which is the crucial for spectral analysis in this work. Consequently, the investigation of dynamical stability transforms into a problem on the spectrum of explicit linearized systems. It is worth noting that, compared to previous works on Camassa-Holm equation and KdV-type equations, recursion operator derived from existing Hamiltonian for the DGH equation do not possess good integrable properties. We construct a new series of Hamiltonians with both analysable recursion operator and simple initial variation derivative (8H1/8u = m) to overcome this problem. Furthermore, orbital stability of the smooth double solitons is proved at last of the work. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:408 / 446
页数:39
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