High-dimensional asymptotics of Langevin dynamics in spiked matrix models

arxiv(2023)

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摘要
We study Langevin dynamics for recovering the planted signal in the spiked matrix model. We provide a 'path-wise' characterization of the overlap between the output of the Langevin algorithm and the planted signal. This overlap is characterized in terms of a self-consistent system of integro-differential equations, usually referred to as the Crisanti-Horner-Sommers-Cugliandolo-Kurchan equations in the spin glass literature. As a second contribution, we derive an explicit formula for the limiting overlap in terms of the signal-to-noise ratio and the injected noise in the diffusion. This uncovers a sharp phase transition-in one regime, the limiting overlap is strictly positive, while in the other, the injected noise overcomes the signal, and the limiting overlap is zero.
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langevin dynamics,high-dimensional
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