On Recovery Guarantees for Angular Synchronization

Abstract The angular synchronization problem of estimating a set unknown angles from their known noisy pairwise differences arises in various applications. It can be reformulated as an optimization on graphs involving the graph Laplacian matrix. We consider general, weighted version this problem, where impact noise differs between different pairs entries and some are erased completely; for example ptychography. study two common approaches solving namely eigenvector relaxation semidefinite convex relaxation. Although recovery guarantees available both methods, performance is either unsatisfying or restricted to unweighted graphs. close gap, deriving that completely analogous version.