Spiked matrix model eigenvector fluctuation conjecture

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Let θ>1\theta>1, let d0≥1d_0\geq 1 be fixed, and use the spiked matrix model notation of Theorem~, assuming and. Let R=R(d)∈Rd0×d\bm R=\bm R^{(d)}\in\mathbb{R}^{d_0\times d} satisfy ∥R∥=O(1)\|\bm R\|=O(1), Rv=R(d)v(d)=0\bm R\bm v=\bm R^{(d)}\bm v^{(d)}=\bm 0, and

d⋅RΣR⊤→Γ∈Rsym⁡d0×d0,d\cdot\bm R\bm\Sigma\bm R^{\top}\to\bm\Gamma\in\mathbb{R}^{d_0\times d_0}_{\operatorname{sym}},

where

Σ=S⋆−(1−θ−2)vv⊤.\bm\Sigma=\bm S^{\star}-(1-\theta^{-2})\bm v\bm v^{\top}.

Assume that the dual Lehner formula at A0=θvv⊤\bm A_0=\theta\bm v\bm v^{\top} has a unique optimizer S⋆\bm S^{\star} for every d≥1d\geq 1, and choose v^\widehat{\bm v} so that ⟨v^,v⟩>0\langle\widehat{\bm v},\bm v\rangle>0. Spiked matrix model eigenvector fluctuation conjecture. As d→∞d\to\infty,

Law(d R(v^−1−θ−2 v))→N(0,Γ).\mathsf{Law}\left(\sqrt{d}\,\bm R\left(\widehat{\bm v}-\sqrt{1-\theta^{-2}}\,\bm v\right)\right)\to\mathcal{N}(\bm 0,\bm\Gamma).

The same conclusion with the same limit should hold when Σ\bm\Sigma is replaced by

Σest=Sest−(1−θ−2)vv⊤,\bm\Sigma^{\mathsf{est}}=\bm S^{\mathsf{est}}-(1-\theta^{-2})\bm v\bm v^{\top},

where Sest\bm S^{\mathsf{est}} is from Definition~, provided Proposition~ makes it well-defined. This conjecture proposes Gaussian projected fluctuations for the leading eigenvector, extending the first-order BBP eigenvector limit; its status is unresolved in the supplied source.

References

Primary source

Dmitriy Kunisky, “Lehner's operator norm formulas, semidefinite programming, and spiked matrix models”, arXiv:2606.14687 (2026).

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