Title: "Quantum error correction with superconducting qubits"

Abstract: 

Quantum error correction offers a path to algorithmically-relevant error rates by encoding logical qubits within many physical qubits, where increasing the number of physical qubits enhances protection against physical errors. However, introducing more qubits also increases the number of error sources, so the density of errors must be sufficiently low in order for logical performance to improve with increasing code size. In this talk, we report the measurement of logical qubit performance on distance-3 and distance-5 surface codes on a Sycamore superconducting processor, and demonstrate that our code has sufficient performance to overcome the additional errors from increasing qubit number. We discuss the challenges and outlook towards scaling to a large error-corrected quantum computer.

Bio:

Kevin Satzinger leads the Quantum Error Correction Experiment team at Google Quantum AI in Santa Barbara, California, focusing on bringing quantum error correction to the lab with surface code experiments. He completed his PhD with Andrew Cleland studying quantum surface acoustic waves at UC Santa Barbara and the University of Chicago.