# Learning Quantum Entanglement Distillation with Noisy Classical Communications

arXiv: https://arxiv.org/abs/2205.08561 · HTML: https://mlsanity.com/paper/2205.08561/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 22 references that are in the map.
- First posted on arXiv 17 May 2022.

## Builds on (most cited first, 4 of 4)

- [An Introduction to Quantum Machine Learning for Engineers](https://mlsanity.com/paper/2205.09510/) (2022)
- [Quantum Internet: Networking Challenges in Distributed Quantum Computing](https://mlsanity.com/paper/1810.08421/) (2018)
- [Practical distributed quantum information processing with LOCCNet](https://mlsanity.com/paper/2101.12190/) (2021)
- [Quantum Internet Protocol Stack: a Comprehensive Survey](https://mlsanity.com/paper/2202.10894/) (2022)

## Built on by (most cited first, 1 of 1)

- [Quantum Machine Learning for Distributed Quantum Protocols with Local Operations and Noisy Classical Communications](https://mlsanity.com/paper/2207.11354/) (2022)

## Abstract (arXiv)

Quantum networking relies on the management and exploitation of entanglement. Practical sources of entangled qubits are imperfect, producing mixed quantum state with reduced fidelity with respect to ideal Bell pairs. Therefore, an important primitive for quantum networking is entanglement distillation, whose goal is to enhance the fidelity of entangled qubits through local operations and classical communication (LOCC). Existing distillation protocols assume the availability of ideal, noiseless, communication channels. In this paper, we study the case in which communication takes place over noisy binary symmetric channels. We propose to implement local processing through parameterized quantum circuits (PQCs) that are optimized to maximize the average fidelity, while accounting for communication errors. The introduced approach, Noise Aware-LOCCNet (NA-LOCCNet), is shown to have significant advantages over existing protocols designed for noiseless communications.