Controlling quantum systems at the pulse level: cavity QED and beyond

Thesis

This thesis addresses challenges in the experimental realisation of optical quantum computing with atom-cavity platforms and develops techniques for experimental quantum control that generalise across a range of quantum modalities. Within the framework of cavity quantum electrodynamics (cQED), methods are developed and numerically validated for fast and precise control of single atoms to generate photonic states of interest. In particular, we consider the generation of high-repetition-rate n-photon bursts and time-bin entangled states. These photonic resources are essential for applications such as boson sampling, multi-photon interference, optical quantum computing, and quantum-enhanced metrology. Experimental improvements in coherent population transfer are demonstrated using adaptive pulse shaping with acousto-optic modulators.

Beyond photon generation, the thesis introduces general-purpose pulse-level techniques, including pulse distortion correction, memory-efficient pulse compression, and machine learning-based optimisation. These methods are shown to be transferable to other platforms, such as neutral atom arrays and superconducting qubits. A particular contribution is the implementation of scalable pulse generation using fixed-point compressed pulse representations on FPGA hardware, achieving substantial memory savings while maintaining high fidelity in simulations of quantum operations. Additionally, reinforcement learning is presented as a powerful tool for optimising complex quantum dynamics, with state-of-the-art results demonstrated across various simulated systems. Throughout the thesis, theoretical developments are supported by numerical simulations and partial experimental validation, providing important insights for the development of future quantum technologies.

Authors: Ernst, JO

• DOI: 10.5287/ora-6qevr5ygx
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: reinforcement learning; acousto-optics; optical computing; single photons; atomic physics; quantum computing; laser physics; quantum optics; quantum information
• Subjects: Quantum computing