We consider -synchronization on the Euclidean lattice. Every vertex of is assigned an independent symmetric random sign , and for every edge of the lattice, one observes the product flipped independently with probability . The task is to reconstruct products for pairs of vertices and which are arbitrarily far apart. Abb\é, Massouli\é, Montanari, Sly and Srivastava (2018) showed that synchronization is possible if and only if is below a critical threshold , and efficiently so for small enough. We augment this synchronization setting with a model of side information preserving the sign symmetry of , and propose an \emph{efficient} algorithm which synchronizes a randomly chosen pair of far away vertices on average, up to a differently defined critical threshold . We conjecture that for all . Our strategy is to \emph{renormalize} the synchronization model in order to reduce the effective noise parameter, and then apply a variant of the multiscale algorithm of AMMSS. The success of the renormalization procedure is conditional on a plausible but unproved assumption about the regularity of the free energy of an Ising spin glass model on .
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