This repository contains the source code for reproducing the results of our INFOCOM'24 paper titled LinkSelFiE: Link Selection and Fidelity Estimation in Quantum Networks.
To get started, ensure you have the following packages installed:
NetSquid, scipy, matplotlib
- algorithms: Implementation of various link selection & fidelity estimation algorithms.
- naive_nb.py: The naive algorithm based on network benchmarking.
- online_nb.py: Our proposed LinkSelFiE algorithm.
- succ_elim_nb.py: A successive elimination-based network benchmarking algorithm.
- evaluation.py: Script to visualize evaluation results and generate figures in the paper.
- nb_protocol.py: Implementation of the network benchmarking protocol.
- network.py: Builds the quantum network structure for the experiments.
- utils: A collection of helper functions.
Execute the following command to reproduce all the figures in the paper:
python main.py
See LICENSE