2025 Theses Doctoral

Optimization and Learning Algorithms for Classical and Quantum Signal Processing

Johnston, Jeremy Allen

The scope of this thesis includes optimization and learning algorithms for classical and quantum information processing. Each chapter focuses on a particular application, spanning communication, sensing, and joint communication-sensing algorithms for systems employing either classical signals or quantum states as the information medium. We develop neural network architectures and training techniques that exploit the underlying signal model and domain knowledge as well as draw inspiration from the structure of existing optimization algorithms. This approach yields new signal processing algorithms that exhibit a compelling tradeoff between performance and computational complexity and is therefore promising for real-time applications.