Quantum Compression for Distributed Entanglement
For quantum communication networks, this work provides theoretical and practical compression schemes to improve entanglement distribution when the receiver partition is unknown.
The paper addresses multipartite entanglement distribution under unknown partitioning, deriving bounds on achievable average entanglement given a rate constraint and proposing practical constructions that approach these bounds.
We study compression strategies for multipartite entanglement distribution under uncertainty in the partitioning of the quantum state. When the partition is not known at the time of state preparation, we show that a joint design of the resource state and a family of compression schemes can increase the entanglement across partitions under a fixed transmission budget. We formulate this as a source coding problem and derive non-asymptotic upper and lower bounds on the achievable average entanglement subject to an average coding rate. We furthermore design an efficient method for jointly optimizing states and lossless compression maps by exploiting the inherent symmetry of weighted Dicke states. In the bipartite case, we propose practical constructions that closely approach the derived upper bound, and more generally we provide practical constructions for multipartite settings.