Quantum Brain
← Back to papers

Efficient Quantum Network Communication Using Optimized Entanglement Swapping Trees

Mohammad Ghaderibaneh, Caitao Zhan, Himanshu Gupta, C. Ramakrishnan·December 21, 2021·DOI: 10.1109/TQE.2022.3168784
Computer SciencePhysics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Quantum network communication is challenging, as the no-cloning theorem in the quantum regime makes many classical techniques inapplicable; in particular, the direct transmission of qubit states over long distances is infeasible due to unrecoverable errors. For the long-distance communication of unknown quantum states, the only viable communication approach (assuming local operations and classical communications) is the teleportation of quantum states, which requires a prior distribution of the entangled pairs (EPs) of qubits. The establishment of EPs across remote nodes can incur significant latency due to the low probability of success of the underlying physical processes. The focus of our work is to develop efficient techniques that minimize EP generation latency. Prior works have focused on selecting entanglement paths; in contrast, we select entanglement swapping trees—a more accurate representation of the entanglement generation structure. We develop a dynamic programming algorithm to select an optimal swapping tree for a single pair of nodes, under the given capacity and fidelity constraints. For the general setting, we develop an efficient iterative algorithm to compute a set of swapping trees. We present simulation results, which show that our solutions outperform the prior approaches by an order of magnitude and are viable for long-distance entanglement generation.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.