Operator-level quantum acceleration of non-logconcave sampling.

ABSTRACT: Sampling from probability distributions of the form [Formula: see text], where [Formula: see text] is a continuous potential, is a fundamental task across physics, chemistry, biology, computer science, and statistics. However, when [Formula: see text] is nonconvex, the resulting distribution becomes non-logconcave, and classical methods such as Langevin dynamics often exhibit poor performance. We introduce a quantum algorithm that provably accelerates a broad class of continuous-time sampling dynamics. For Langevin dynamics, our method encodes the target Gibbs measure into the amplitudes of a quantum state, identified as the kernel of a block matrix derived from a factorization of the Witten Laplacian operator. This connection enables Gibbs sampling via singular value thresholding and yiel

SUBMITTER: Leng J 

PROVIDER: S-EPMC12933055 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature