Richard L. Greene Dissertation Award in Experimental Condensed Matter or Materials Physics (2020): Beyond-Classical Quantum Computation at Google-AI Quantum

Over the past decade, rapid progress in quantum engineering has allowed full fabrication and control of superconducting quantum processors with over 50 qubits and full planar connectivity, as exemplified by Google’s Sycamore processor. Using random circuits carefully designed to randomly explore the immense Hilbert space with 1016 dimensions, a bit-string sampling task that proves difficult for classical computation has been recently demonstrated on Sycamore. In this presentation, I will first detail the formulation and execution of the original “quantum supremacy” experiment [1]. I will then describe current works being done in our group, with a particular emphasis on the efforts to discover useful quantum computing applications in the Noisy Intermediate-Scale Quantum (NISQ) era. As an example, I will present preliminary experimental results on using Sycamore to study the physics of scrambling and thermalization in quantum circuits that are challenging to analyze or simulate classically [2].


[1] Arute et al., Nature 574, 505–510 (2019).
[2] Work done in collaboration with K. Kechedzhi, P. Roushan, C. Quintana, I. Aleiner, Y. Chen, V. Smelyanskiy and other members of the Google Quantum AI team, as well as S. Mandra and J. Marshall of the Quantum Artificial Intelligence Lab (QuAIL) at NASA Ames Research Center.