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...Show moreThis 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.Show less
Characterizing quantum states is a central, yet involved, task in quantum information processing. In experiments, the unknown quantum state of interest must be prepared and measured multiple times...Show moreCharacterizing quantum states is a central, yet involved, task in quantum information processing. In experiments, the unknown quantum state of interest must be prepared and measured multiple times to learn its properties. Unfortunately, a full tomographic description is prohibitive by the exponential scaling of the quantum state description with the system size. In practice, only a few quantities are of interest for which protocols involving informationally incomplete measurements are preferable. After studying existing data acquisition protocols, we discuss classical shadow estimation, a particular experimentally feasible method for estimating many system properties. We extend the applicability to quantum many-body systems with higher dimensional subspaces and derive similar performance guarantees to the qubit case. Ultimately we implement the generalized protocol in a modular and economic numerical framework and demonstrate the accuracy along with the favourable scaling of classical shadow estimation in unbiased numerical experiments. In particular, we suggest and discuss the near-term application to 4-photon OAM entangled systems.Show less
Quantum computers can possibly help in the near future to simulate mole-cules and do electronic structure calculations. To work on the near term quantum devices the variational quantum eigensolver ...Show moreQuantum computers can possibly help in the near future to simulate mole-cules and do electronic structure calculations. To work on the near term quantum devices the variational quantum eigensolver (VQE) is an auspicious candidate and particularly the application of the unitary coupled-cluster singles and doubles ansatz. Despite the high accuracy the scaling in the number of terms is unfavourable making the circuit depth too large. In this thesis we look at a possible truncation scheme based on classical quantum chemistry methods to decrease the number of terms while preserving accurate ground state energies. This truncation is shown with numerical results for H$_4$ and N$_2$ giving a significantly reduced number of terms.Show less
