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oai:figshare.com:article/32638809 2026-10-01T16:45:10Z portal_1172 item_type_8 month_year_10_2026

Machine learning applications in quantum state engineering Jonathon Patrick Brown (24168213) PUREID: 529267295 Optimal quantum control machine learning reinforcement learning evolutionary strategies open quantum systems quantum information In this thesis we examine the potential of machine learning, and related techniques, for address- ing control problems in quantum systems. Firstly, we implement a classical reinforcement- learning inspired approach to achieve closed loop quantum control of 3-level systems. Our results show that this technique can effectively design optimal control pulses resulting in near- perfect transfer in non-standard but practically relevant operating regimes. Such results are considered in the case of an abstract 3-level system but we discuss a scenario where said control can be used to directly entangle qubits coupled via a common resonator. Following this we employ a genetic-algorithm-based optimization in larger resonator-mediated multi-qubit systems to show that heuristic search techniques can be used to find optimal driving fields in complex, composite quantum systems. This provides flexible alternative to standard techniques. In particular, we achieve control schemes capable of preparing maximally entangled 3- and 4-qubit pure states with high fidelity by affording control over only qubit-resonator coupling and a single resonator driving term, as opposed to individual qubit drives as required in the standard dispersive coupling regime. We finish by investigating the role that automatic differentiation and gradient descent, ubiquitous building blocks for more complex machine learning methods, can play in engineering dissipative quantum dynamics. We provide several proof-of-principle examples, including the preparation of 6-qubit steady state entanglement and GKP states of light. 2026-10-01T16:45:10Z Text Thesis 10.17034/32638809.v1 https://figshare.com/articles/thesis/Machine_learning_applications_in_quantum_state_engineering/32638809 All Rights Reserved