Julian Kelly
I am Senior Director of Hardware at Google Quantum AI, where I lead the development, integration, and operation of Google's superconducting quantum computers on the path to large-scale, fault-tolerant systems. Throughout my career, my focus has been on a single overarching goal: making fault-tolerant quantum error correction (QEC) a physical reality.
Starting with my PhD at UC Santa Barbara—where we co-developed the planar Xmon transmon architecture, demonstrated the first two-qubit gates at the surface-code fault-tolerance threshold, and realized early repetitive error detection—I joined Google in 2014 as a founding member of the quantum hardware effort.
At Google, I designed the 72-qubit Bristlecone processor, created the Optimus automated calibration framework, helped architect the Quantum AI Hardware Roadmap, and now oversee hardware strategy and execution across the full superconducting technology stack. Along the way, our team has driven a continuous progression of hardware and error-correction milestones:
• Surface-Code Foundations (Nature, 2014, 2015): Demonstrated threshold-level gate fidelities and 9-qubit repetitive error detection in planar superconducting circuits.
• Beyond-Classical Computation (Nature, 2019): Demonstrated high-fidelity control at scale on the Sycamore processor (Milestone 1).
• Scaling a Logical Qubit (Nature, 2021, 2023): Demonstrated exponential error suppression in cyclic error correction and the first error suppression achieved by scaling a surface-code logical qubit (Milestone 2).
• Below-Threshold QEC and Fault-Tolerant Primitives (Nature, 2024; Science, 2026): Overcame a 30-year challenge on the Willow processor by demonstrating exponential error suppression below the surface code threshold, followed by fault-tolerant magic state cultivation.
Today, our focus is delivering long-lived logical qubits (Milestone 3) and scaling hardware systems toward utility-scale, fault-tolerant quantum computers.