# FENDI: Toward High-Fidelity Entanglement Distribution in the Quantum Internet

arXiv: https://arxiv.org/abs/2301.08269 · HTML: https://mlsanity.com/paper/2301.08269/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jan 2023.

## Built on by (most cited first, 2 of 2)

- [RELiQ: Scalable Entanglement Routing via Reinforcement Learning in Quantum Networks](https://mlsanity.com/paper/2511.22321/) (2025)
- [SatQNet: Satellite-assisted Quantum Network Entanglement Routing Using Directed Line Graph Neural Networks](https://mlsanity.com/paper/2604.09306/) (2026)

## Abstract (arXiv)

A quantum network distributes quantum entanglements between remote nodes, and is key to many applications in secure communication, quantum sensing and distributed quantum computing. This paper explores the fundamental trade-off between the throughput and the quality of entanglement distribution in a multi-hop quantum repeater network. Compared to existing work which aims to heuristically maximize the entanglement distribution rate (EDR) and/or entanglement fidelity, our goal is to characterize the maximum achievable worst-case fidelity, while satisfying a bound on the maximum achievable expected EDR between an arbitrary pair of quantum nodes. This characterization will provide fundamental bounds on the achievable performance region of a quantum network, which can assist with the design of quantum network topology, protocols and applications. However, the task is highly non-trivial and is NP-hard as we shall prove. Our main contribution is a fully polynomial-time approximation scheme to approximate the achievable worst-case fidelity subject to a strict expected EDR bound, combining an optimal fidelity-agnostic EDR-maximizing formulation and a worst-case isotropic noise model. The EDR and fidelity guarantees can be implemented by a post-selection-and-storage protocol with quantum memories. By developing a discrete-time quantum network simulator, we conduct simulations to show the characterized performance region (the approximate Pareto frontier) of a network, and demonstrate that the designed protocol can achieve the performance region while existing protocols exhibit a substantial gap.