Papers
Topics
Authors
Recent
AI Research Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 81 tok/s
Gemini 2.5 Pro 42 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 103 tok/s Pro
Kimi K2 188 tok/s Pro
GPT OSS 120B 454 tok/s Pro
Claude Sonnet 4 38 tok/s Pro
2000 character limit reached

On the long-time asymptotics of the modified Camassa-Holm equation with step-like initial data (2203.10573v3)

Published 20 Mar 2022 in nlin.SI

Abstract: We study the long time asymptotic behavior for the Cauchy problem of the modified Camassa-Holm (mCH) equation with step-like initial data \begin{align} &m_{t}+\left(m\left(u{2}-u_{x}{2}\right)\right)_{x}=0, \quad m=u-u_{xx}, \nonumber \ &u(x,0)=u_0(x)\to \left{ \begin{array}{ll} A_1, &\ x\to+\infty,\[5pt] A_2, &\ x\to-\infty, \end{array}\right.\nonumber \end{align} where $A_1$ and $A_2$ are two positive constants. Our main technical tool is the representation of the Cauchy problem with an associated matrix Riemann-Hilbert (RH) problem and the consequent asymptotic analysis of this RH problem. Based on the spectral analysis of the Lax pair associated with the mCH equation and scattering matrix, the solution of the step-like initial problem is characterized via the solution of a RH problem in the new scale $(y,t)$. We adopt double coordinates $(\xi, c)$ to divide the half-plane ${ (\xi,c): \xi \in \mathbb{R}, \ c> 0, \ \xi=y/t}$ into four asymptotic regions. Further using the Deift-Zhou steepest descent method, we derive different long time asymptotic expansion of the solution $u(y,t)$ in different space-time regions by the different choice of g-function. The corresponding leading asymptotic approximations are given with the slow/fast decay step-like background wave in genus-0 regions and elliptic waves in genus-2 regions. The second term of the asymptotics is characterized by Airy function or parabolic cylinder model. Their residual error order is $\mathcal{O}(t{-1})$ or $\mathcal{O}(t{-2})$ respectively.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube