Classification of joint quantum measurements based on entanglement cost of localization
Jef Pauwels, Alejandro Pozas-Kerstjens, Flavio Del Santo, Nicolas Gisin
TL;DR
The paper develops a finite-resource framework to localize joint quantum measurements using entanglement, building finite versions of teleportation-based schemes and linking localization cost to measurement complexity via the Clifford hierarchy. It analytically classifies all two-qubit measurements localizable with up to three ebits, revealing rich symmetry-connected families such as Bell-state-related bases, the elegant joint measurement, and twisted variants, and proving connections to established structures. It further sketches systematic generalizations to higher levels, higher dimensions, and multipartite settings, supported by numerical explorations that uncover extensive families of localizable measurements. The work provides a principled, representation-theoretic lens on nonlocal measurements and establishes a framework for exploring network nonlocality and resource costs in quantum information protocols.
Abstract
Despite their importance in quantum theory, joint quantum measurements remain poorly understood. An intriguing conceptual and practical question is whether joint quantum measurements on separated systems can be performed without bringing them together. Remarkably, by using shared entanglement, this can be achieved perfectly when disregarding the post-measurement state. However, existing localization protocols typically require unbounded entanglement. In this work, we address the fundamental question: "Which joint measurements can be localized with a finite amount of entanglement?" We develop finite-resource versions of teleportation-based schemes and analytically classify all two-qubit measurements that can be localized in the first steps of these hierarchies. These include several measurements with exceptional properties and symmetries, such as the Bell state measurement and the elegant joint measurement. This leads us to propose a systematic classification of joint measurements based on entanglement cost, which we argue directly connects to the complexity of implementing those measurements. We illustrate how to numerically explore higher levels and construct generalizations to higher dimensions and multipartite settings.
