Yau nodal-set conjecture
Canonical statement
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For every closed smooth Riemannian \(n\)-manifold \((M,g)\) there are constants \(c_g,C_g>0\) such that every nonzero real eigenfunction \(\varphi\) satisfying \(-\Delta_g\varphi=\lambda\varphi\), \(\lambda>0\), obeys \[ c_g\sqrt{\lambda}\ \le\ \mathcal H^{n-1}\!\left(\{x\in M:\varphi(x)=0\}\right) \ \le\ C_g\sqrt{\lambda}. \]Notes
In his 1982 problem section Yau conjectured that the nodal set of a Laplace eigenfunction on a closed smooth Riemannian -manifold has -dimensional Hausdorff measure comparable to , where is the eigenvalue: there should be bounds with constants depending only on the manifold [Yau1982ProblemNodalSets]. The heuristic is that an eigenfunction with eigenvalue oscillates on wavelength scale , so its zero set should resemble a hypersurface of total measure of order .
Donnelly and Fefferman proved both bounds in 1988 when the metric is real-analytic [DonnellyFefferman1988NodalSets]. For merely smooth metrics the picture was transformed by Logunov, who proved the sharp lower bound in all dimensions, settling Nadirashvili's conjecture along the way [Logunov2018NodalLowerBound], and established an upper bound of polynomial form for some exponent [Logunov2018NodalHypersurfaces].
What remains is to replace the polynomial upper estimate by the sharp for smooth metrics; this half of the conjecture is still open.
References (4)
- [Yau1982ProblemNodalSets]
Problem section
1982 · misc
- [DonnellyFefferman1988NodalSets]
Nodal sets of eigenfunctions on Riemannian manifolds
Open ↗1988 · misc
- [Logunov2018NodalHypersurfaces]
Nodal sets of Laplace eigenfunctions: polynomial upper estimates of the Hausdorff measure
Open ↗2018 · misc
- [Logunov2018NodalLowerBound]
Nodal sets of Laplace eigenfunctions: proof of Nadirashvili's conjecture and of the lower bound in Yau's conjecture
Open ↗2018 · misc
The boxed statement is the canonical open formulation — not a stronger variant or a related research program. The status reflects the catalog's last review; do your own literature search before investing serious effort.