Leiden University Student Repository

Spoor, Lindsay (2024)

Quantum error correction on the toric code using two distinct reinforcement learning game frameworks

Master thesis | Physics (MSc)

This project employs reinforcement learning techniques to explore novel decoding strategies for quantum error correction, particularly focusing on the toric code, to address the challenge of maintaining stable quantum states for fault-tolerant quantum computing. Two game frameworks are established, including a novel dynamic game framework applicable to the training and measuring of RL agents and potential application in multiagent scenarios. The RL agents use Stable Baselines 3’s Proximal Policy Optimization and show to achieve Minimum Weight Perfect Matching performance on 3 × 3 toric code lattices in both the static and dynamic game frameworks.

Quantum Error Correction

Toric Code

Reinforcement Learning

PPO

Quantum Computing

Author

Spoor, Lindsay

Faculty

Faculty of Science

Specialisation

Classical and Quantum Information

Supervisors

Evert van Nieuwenburg

ECTS Credits

36

Language

en