Deterministic guarantees for $L^1$-reconstruction: A large sieve approach with geometric flexibility

Abstract

We present estimates of the $p$-concentration ratio for various function spaces on different geometries including the line, the sphere, the plane, and the hyperbolic disc, using large sieve methods. Thereby, we focus on $L^1$-estimates which can be used to guarantee the reconstruction from corrupted or partial information.