Scalable Control Architectures for Quantum Computing

Abstract

As performance gains in classical CPUs have slowed over time, the field of computinghas looked to accelerators like the GPU as a solution. One such emerging technology is the quantum computer, leveraging the exotic properties of quantum mechani- cal systems to perform calculations that are intractable on any classical hardware. While there is still a long road ahead until some of the most influential algorithms can be realized, small quantum computers are now a reality, with larger systems on the horizon. As these systems scale to larger sizes, the complexity of the classical hardware and software that control them must also scale. This dissertation seeks to address some of engineering challenges of scaling those real-time control systems to keep up with the demand of present and future quantum computers. We show that well-architected control software can improve performance and portability even between distinct quantum hardware systems, allowing faster development of more robust software for the next generation of systems. Due to the extreme precision required for high-fidelity control of quantum systems, routine calibration of the ana- log hardware components is required for the operation of a quantum computer. We present a framework for automating and optimizing that calibration using a graph- based approach. Finally, this dissertation presents progress toward a heterogeneous, system-on-chip based hardware platform for quantum control and its potential sig- nificance for the modular scaling of quantum hardware.