Searcharxiv⌕ Search

arXiv · 2610.25313

Sharp concentration levels and extremal functions for a planar Choquard-type Trudinger--Moser inequality

Abstract

Let $Ω\subset\mathbb{R}^2$ be a smooth bounded domain and let $0<α<2$. We study the exponential Choquard functional \[ \mathcal{F}_β(u)=\int_Ω\int_Ω \frac{e^{βu^2(x)}e^{βu^2(y)}}{|x-y|^α}d xd y \] on the unit Dirichlet ball of $H_0^1(Ω)$. We establish the sharp boundedness threshold $β_*=(4-α)π$ and prove attainment of the critical supremum. More precisely, we determine the exact concentration level at every point of $\overlineΩ$ in terms of the regular part of the Dirichlet Green function. The concentration upper bound follows from the classical planar Trudinger--Moser concentration formula and the sharp Hardy--Littlewood--Sobolev inequality, after separating the background contribution. A test function obtained by matching a logarithmic profile to the Green function attains this bound asymptotically. Its exact Dirichlet normalization produces a strictly positive lower-order correction, which rules out concentration of maximizing sequences. We also prove the Euler--Lagrange equation, positivity, and regularity of extremals.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jinkai Gao. 2026-10-18. Sharp concentration levels and extremal functions for a planar Choquard-type Trudinger--Moser inequality. https://arxiv.org/abs/2610.25313

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

On the dispersive estimates for the discrete Schrödinger equation on a honeycomb lattice

The discrete Schrödinger equation on a two-dimensional honeycomb lattice is a fundamental tight-binding approximation model that describes the propagation of waves on graphene. For free evolution, we first show that the degenerate frequencies of the dispersion relation are completely characterized by three symmetric periodic curves (Theorem 2.1), and that the three curves meet at Dirac points where conical singularities appear (see Figure 2.1). Based on this observation, we prove the $L^1\to L^\infty$ dispersion estimates for the linear flow depending on the frequency localization (Theorem 2.3). Collecting all, we obtain the dispersion estimate with $O(|t|^{-2/3})$ decay as well as Strichartz estimates. As an application, we prove small data scattering for a nonlinear model (Theorem 2.10). The proof of the key dispersion estimates is based on the associated oscillatory integral estimates with degenerate phases and conical singularities at Dirac points. Our proof is direct and uses only elementary methods.

math.AP↗

Well-posedness and Stability of Thermoelastic Suspension Bridges with Cattaneo Heat Conduction: The Role of Viscoelastic Memory

Thermoelastic suspension bridges operate under strong thermo-mechanical coupling, and the classical Fourier law fails to capture the finite speed of thermal propagation observed in low-conductivity materials such as concrete. This paper investigates a suspension bridge model in which the heat flux is governed by the Cattaneo law with relaxation time $τ$, and in which the bridge deck may or may not possess viscoelastic memory. Using operator semigroup theory, we establish well-posedness and derive sharp decay rates for both regimes. For the memoryless system ($δ=0$), we show that the semigroup is polynomially stable with rate $t^{-1/2}$ when the structural parameters satisfy $\frac{ρ_1}κ = \frac{ρ_2}{b}$, and that the rate deteriorates to $t^{-1/4}$ otherwise; moreover, exponential stability fails whenever $χ_0 \neq 0$, or $χ_0 = 0$ and $χ_1 = 0$, where $χ_0$ and $χ_1$ are parameter-dependent coefficients. In sharp contrast, when viscoelastic memory is present ($δ=1$), the semigroup becomes exponentially stable, regardless of the structural parameter ratio. This reveals a regularizing role of viscoelastic memory: it converts polynomial decay into exponential decay and removes the parameter-ratio obstruction. The results provide a theoretical basis for exploiting inherent viscoelasticity in long-span bridges and for optimizing deck parameters in memoryless structures.

math.AP↗