Towards a General Framework for Practical Quantum Network Protocols

TL;DR

This paper introduces a mathematical framework for optimizing entanglement distribution in quantum networks using reinforcement learning, aiming to guide the development of scalable quantum internet infrastructure.

Contribution

It develops a comprehensive decision process framework for quantum entanglement distribution and proposes protocols optimized through reinforcement learning for practical quantum networks.

Findings

Framework enables discovering optimal entanglement protocols.

Incorporates practical architectures like ground- and satellite-based networks.

Defines figures of merit to evaluate protocol performance.

Abstract

The quantum internet is one of the frontiers of quantum information science. It will revolutionize the way we communicate and do other tasks, and it will allow for tasks that are not possible using the current, classical internet. The backbone of a quantum internet is entanglement distributed globally in order to allow for such novel applications to be performed over long distances. Experimental progress is currently being made to realize quantum networks on a small scale, but much theoretical work is still needed in order to understand how best to distribute entanglement and to guide the realization of large-scale quantum networks, and eventually the quantum internet, especially with the limitations of near-term quantum technologies. This work provides an initial step towards this goal. The main contribution of this thesis is a mathematical framework for entanglement distribution protocols in a quantum network, which allows for discovering optimal protocols using reinforcement learning. We start with a general development of quantum decision processes, which is the theoretical backdrop of reinforcement learning. Then, we define the general task of entanglement distribution in a quantum network, and we present ground- and satellite-based quantum network architectures that incorporate practical aspects of entanglement distribution. We combine the theory of decision processes and the practical quantum network architectures into an overall entanglement distribution protocol. We also define practical figures of merit to evaluate entanglement distribution protocols, which help to guide experimental implementations.