Abstract: Quantum computing has the potential to revolutionize the way we solve many problems, ranging from analyzing chemical reactions to cryptography. However, building these machines in practice is an incredibly challenging engineering exercise, and many organizations are competing in the race toward practical quantum computers. In this talk, I’ll introduce the core operating concepts of a quantum computer and show how we realize them in ion trap hardware. I will then describe how we measure quantum computer performance and what we have done to boost it at IonQ, focusing on both software error mitigation techniques as well as our latest hardware designs.
Bio: John Gamble is Director, System Performance Optimization at IonQ, where he and his team work to model, characterize, and optimize quantum computers. Before joining IonQ, John carried out research and development on topological quantum computing at Microsoft and spin quantum computing at Sandia National Laboratories, first as a Harry S. Truman Fellow and later as technical staff. John received his PhD in physics from the University of Wisconsin-Madison as an NSF Graduate Research Fellow. John’s technical work centers on deploying large-scale computer-aided engineering tools to understand and improve qubits, which draws heavily on techniques from condensed matter physics, electrical engineering, quantum information science, machine learning, and quantum chemistry. Throughout his career, he has worked on a broad cross-section of quantum engineering topics: quantum algorithms, semiconductor quantum dot qubits, semiconductor impurity qubits, topological qubits, trapped ion qubits, quantum characterization, verification, and validation, and the optimization of quantum systems.
This lecture will be over Zoom. https://mines.zoom.us/j/188885471