Algorithmic pure states for the negative spherical perceptron
Abstract
We consider the spherical perceptron with Gaussian disorder. This is the set S of points σ ∈ RN on the sphere of radius N satisfying ga , σ N\, for all 1 a M, where (ga)a=1M are independent standard gaussian vectors and ∈ R is fixed. Various characteristics of S such as its surface measure and the largest M for which it is non-empty, were computed heuristically in statistical physics in the asymptotic regime N ∞, M/N α. The case <0 is of special interest as S is conjectured to exhibit a hierarchical tree-like geometry known as "full replica-symmetry breaking" (FRSB) close to the satisfiability threshold αSAT(), and whose characteristics are captured by a Parisi variational principle akin to the one appearing in the Sherrington-Kirkpatrick model. In this paper we design an efficient algorithm which, given oracle access to the solution of the Parisi variational principle, exploits this conjectured FRSB structure for <0 and outputs a vector σ satisfying ga , σ N for all 1 a M and lying on a sphere of non-trivial radius q N, where q ∈ (0,1) is the right-end of the support of the associated Parisi measure. We expect σ to be approximately the barycenter of a pure state of the spherical perceptron. Moreover we expect that q 1 as α αSAT(), so that ga,σ/|σ| ≥ (-o(1))N near criticality.
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