An independent proof establishes the sharp log-free L^2 to L^{10/3} endpoint estimate for the two-dimensional Hermite operator.
The Endpoint Eigenfunction Bound for the Hermite Operator in Two Dimensions
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abstract
In this paper, we establish the optimal \(L^2(\mathbb{R}^2)\to L^{10/3}(\mathbb{R}^2)\) endpoint estimate for the spectral projection operator associated with the Hermite operator on \(\mathbb{R}^2\). This completes a long-standing line of inquiry into sharp eigenfunction bounds for the Hermite operator, developed through the works of Thangavelu, Karadzhov, Koch--Tataru, and others. In higher dimensions \(d\ge 3\), the corresponding endpoint estimates \[ L^2(\mathbb{R}^d)\to L^{\frac{2(d+3)}{d+1}}(\mathbb{R}^d) \] were recently established by the present authors. Together with these earlier results, the present work fully resolves the problem of optimal \(L^2\to L^q\) eigenfunction bounds for Hermite spectral projections in all dimensions. Although our approach builds on our previous method, we overcome its limitations through a multiscale decomposition in space and time relative to the degeneracy set, combined with an asymmetric refinement on the input side and almost orthogonality.
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Sharp Endpoint Eigenfunction Estimates for the Two-Dimensional Hermite Operator
An independent proof establishes the sharp log-free L^2 to L^{10/3} endpoint estimate for the two-dimensional Hermite operator.