Network Architecture for a Surface Code Quantum Computer in Silicon Presented by Jonathan Baugh

Abstract:
Realizing a large-scale, universal quantum computer would enable major technological advances, yet presents a significant challenge. The standard circuit model for quantum computation requires a staggering error correction overhead to achieve fault tolerance. Topological stabilizer codes acting on two-dimensional qubit arrays, i.e. surface codes, can tolerate relatively high error thresholds and are very promising for scalability. I will present a brief introduction to quantum error correction, targeted to a non-quantum audience, to convey how fault tolerance is achieved in quantum computation. I will then describe our recent proposal for a network-of-nodes architecture that should allow practical scaling for a CMOS electron spin qubit processor.

Bio:
Jonathan Baugh is working toward the physical realization of quantum information processors in the solid-state, using the property of spin to encode and manipulate quantum information. Past work has focused on solid-state electron and nuclear magnetic resonance devices, and more recently on nanoelectronics devices including quantum wires and dots. Prior to joining the Institute for Quantum Computing at the University of Waterloo as a faculty member in 2007, he spent several years as a postdoctoral scholar and one year as a visiting researcher at the University of Tokyo. He received a PhD in Physics in 2001 from the University of North Carolina at Chapel Hill.