Analysis of gradient flow for computing defocusing action ground states of rotating nonlinear Schr\"odinger equations
Wei Liu, Tingfeng Wang, Yongjun Yuan, Xiaofei Zhao

TL;DR
This paper proves the stability and convergence of a gradient flow method for computing ground states of rotating nonlinear Schrödinger equations, supported by numerical validation.
Contribution
It provides the first rigorous stability and convergence analysis of the direct gradient flow scheme for RNLS ground states, including exponential convergence rates.
Findings
Unconditional stability of the DGF scheme for arbitrary time steps
Global convergence to the ground state under minor assumptions
Numerical experiments confirm theoretical convergence results
Abstract
This work focuses on the numerical computation of defocusing action ground states for rotating nonlinear Schr\"odinger equations (RNLS) using a direct gradient flow (DGF) method. We address theoretical gaps in the existing literature concerning the stability and convergence of this DGF scheme. Firstly, we prove the unconditional stability of the DGF scheme, demonstrating that the action functional is monotonically non-increasing along the discrete flow for arbitrary time step sizes. Secondly, we establish a rigorous convergence analysis, proving global convergence under minor assumptions and local exponential convergence to the action ground state under a reasonable non-degeneracy condition. The analysis relies on the uniform boundedness of sublevel sets of the action functional and introduces a tailored -distance between phase-shift equivalence classes to handle complex-valued…
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