Suboptimality of stable algorithms for all p-spin Ising models with p≥3
Determine whether, for the p-spin Ising spin glass model with p≥3, the largest ground-state value achievable by stable (noise-insensitive) polynomial-time algorithms is strictly smaller than the Parisi-optimal value, equivalently whether the extended variational value η_{p,ALG}=inf_{μ∈ℒ}P(μ) remains strictly less than η_{p,OPT}=inf_{μ∈𝒰}P(μ) for all such p.
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On the other hand, when $p\ge 4$ is even, the largest value achievable by stable algorithms is strictly sub-optimal. It is conjectured that this remains the case for all $p\ge 3$ regardless of the parity and has been verified for the case when $p$ is sufficiently large.
For fixed $p$, can a state class with effective profile complexity $O(n2)$, fixed independently of the disorder, outperform product states by $c\sqrt n$ with high probability for some $c>0$? Theorem~\ref{thm:local-profile-complexity-principle}\textup{(ii)} rules out such an advantage at subquadratic complexity, but does not establish that quadratic complexity is sufficient. More generally, what profile complexity is required to approach the unrestricted optimum?