Architecting Emerging Quantum Technologies

Zoom link for remote participants, passcode:  170271

Abstract: Despite its relative infancy, there are a number of emerging quantum technologies for quantum computation, and it is unclear which will be the clear winner. Evaluation of these technologies at the architectural level, far beyond the small-scale prototypes of 1 to 2 qubits, is critical to producing viable systems capable of executing both near and long-term applications effectively. At a high level, we are tasked with asking and answering important sets of questions with each new technology developed. In this talk, I discuss two case studies involving emerging technologies: use of multivalued logic for quantum computation and use of 2.5D quantum architectures with bounded local “memory.” In the first part, we explore the use of a variety of optimization techniques for specialized and general-use of intermediate qudits, temporary occupancy of higher order states, to reduce circuit runtimes and reduce physical device requirements which directly translates into improved output quality. In the second part, we introduce a scalable 2.5D architecture composed of resonant cavities and evaluate its ability to support quantum error correction codes. In particular, we design an architecture which directly matches the requirements of known error correction codes to reduce physical device requirements while accelerating key logical operations. I will conclude with some current and future directions in this area.

Bio: Jonathan Baker is a final-year Ph.D. student in the Department of Computer Science at the University of Chicago, advised by Prof. Fred Chong. His research is focused on interdisciplinary, full-stack optimization and the evaluation of emerging quantum systems. Prior to the University of Chicago, he received degrees in Computer Science, Chemistry, and Mathematics from the University of Notre Dame.