Performance optimization for drift-robust fidelity improvement of two-qubit gates
Gregory A. L. White, Charles D. Hill, Lloyd C. L. Hollenberg

TL;DR
This paper introduces POST, a method combining gate set tomography with classical optimization to improve two-qubit gate fidelity efficiently and robustly, even as system parameters drift over time, demonstrated on a superconducting quantum device.
Contribution
The paper presents a novel performance optimization method, POST, that leverages GST and classical optimization for quick, robust gate improvement adaptable to hardware drift.
Findings
Achieved an average 21.1% fidelity increase over six weeks
Demonstrated robustness to parameter drift in quantum gates
Validated on a real superconducting quantum device
Abstract
Quantum system characterization techniques represent the front line in the identification and mitigation of noise in quantum computing, but can be expensive in terms of quantum resources and time to repeatedly employ. Another challenging aspect is that parameters governing the performance of various operations tend to drift over time, and monitoring these is hence a difficult task. One of the most promising characterization techniques, gate set tomography (GST), provides a self-consistent estimate of the completely positive, trace-preserving (CPTP) maps for a complete set of gates, as well as preparation and measurement operators. We develop a method for performance optimization seeded by tomography (POST), which couples the power of GST with a classical optimization routine to achieve a consistent gate improvement in just a short number of steps within a given calibration cycle. By…
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