Concentration and Local Uniqueness of Constrained Minimizers for the Kirchhoff Equation With a Trapping Potential

ABSTRACT This paper investigates the ‐normalized minimizers of a Kirchhoff‐type energy functional. We first establish the concentration behavior of minimizers for the case with . Since the explicit form of minimizers is unavailable when the potential vanishes, we derive crucial asymptotic properties to overcome this difficulty. Furthermore, we prove the local uniqueness of minimizers for sufficiently small . In contrast to existing results, our approach introduces novel identities that streamline the classical analysis.

Authors

Institutions

Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2026-02-25
DOI
https://doi.org/10.1002/mma.70630
Primary Topic
Nonlinear Partial Differential Equations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Concentration and Local Uniqueness of Constrained Minimizers for the Kirchhoff Equation With a Trapping Potential

Haolin Liu
Mathematical Methods in the Applied Sciences
Nonlinear Partial Differential Equations
article

Concentration and Local Uniqueness of Constrained Minimizers for the Kirchhoff Equation With a Trapping Potential

Haolin Liu
article en

Abstract

ABSTRACT This paper investigates the ‐normalized minimizers of a Kirchhoff‐type energy functional. We first establish the concentration behavior of minimizers for the case with . Since the explicit form of minimizers is unavailable when the potential vanishes, we derive crucial asymptotic properties to overcome this difficulty. Furthermore, we prove the local uniqueness of minimizers for sufficiently small . In contrast to existing results, our approach introduces novel identities that streamline the classical analysis.

Mathematical Methods in the Applied Sciences
Beijing Institute of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 27%
Nonlinear Partial Differential Equations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.