Convergence analysis of $L^{p+1}$-normalized gradient flow for action ground state of nonlinear Schr\"odinger equation
Wei Liu, Tingfeng Wang, Xiaofei Zhao

TL;DR
This paper rigorously analyzes the convergence of an $L^{p+1}$-normalized gradient flow method for computing the action ground state of the nonlinear Schrödinger equation, establishing global and local convergence rates.
Contribution
It provides the first comprehensive convergence analysis of the GFALM method for the $L^{p+1}$-constrained problem, including semi-discrete, fully discrete, and continuous cases.
Findings
Global convergence of the semi-discrete scheme is established.
Local exponential convergence rate is proven under non-degeneracy assumptions.
Extension of analysis to fully discrete Fourier pseudo-spectral discretization.
Abstract
This paper presents a rigorous convergence analysis of the -normalized gradient flow with asymptotic Lagrange multiplier (GFALM) method for computing the action ground state of the nonlinear Schr\"odinger equation in the focusing case. First, a general global convergence theory is established for the semi-discrete GFALM scheme, guaranteeing the existence of an accumulation point and a convergent subsequence. Then, under additional non-degeneracy assumptions, a local exponential convergence rate is rigorously proven. This result is further extended to the fully discrete case using a Fourier pseudo-spectral discretization. The analysis is achieved by characterizing the local geometry of the -constrained manifold near the ground state, establishing a quadratic growth property of the energy functional, and deriving a \L{}ojasiewicz-type gradient inequality. Finally, the…
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Taxonomy
TopicsModel Reduction and Neural Networks · Nonlinear Partial Differential Equations · Numerical methods in inverse problems
