Adiabatic approximation for the motion of Ginzburg-Landau vortex filament
Jingxuan Zhang

TL;DR
This paper proves that solutions to the dispersive Ginzburg-Landau equation concentrate near a curve evolving by the binormal curvature flow, under small curvature assumptions, providing a detailed vortex filament description.
Contribution
It offers the first rigorous proof of vortex filament concentration and evolution for the dispersive Ginzburg-Landau equation without symmetry constraints, for fixed small parameters.
Findings
Solutions concentrate near curves evolving by binormal curvature flow.
Results hold for small fixed material parameters, not just zero limit.
The vortex filament structure is precisely described over a finite time interval.
Abstract
In this paper, we consider the concentration property of solutions to the dispersive Ginzburg-Landau (or Gross-Pitaevskii) equation in three dimensions. On a spatial domain, it has long been conjectured that such a solution concentrates near some curve evolving according to the binormal curvature flow, and conversely, that a curve moving this way can be realized in a suitable sense by some solution to the dispersive Ginzburg-Landau equation. Some partial results are known with rather strong symmetry assumptions. Our main theorems here provide affirmative answer to both conjectures under certain small curvature assumption. The results are valid for small but fixed material parameter in the equation, in contrast to the general practice to take this parameter to its zero limit. The advantage is that we can retain precise description of the vortex filament structure. The results hold on a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Mathematical Physics Problems · Nonlinear Photonic Systems · Nonlinear Dynamics and Pattern Formation
