| Summary: | Over the past two decades, impressive strides have been made in the field of quantum computing. Quantum advantage has been reported, and there is now an ecosystem of cloud-based quantum processors and companies interested in using them. However, high error rates continue to limit circuit depth, such that solving real-world problems with today’s quantum computers remains a challenge. For quantum computing with superconducting qubits, two-qubit gates are a major source of those errors.
In this thesis, we calibrate high-fidelity CZ and CPhase gates for flux-tunable transmon qubits. We develop a new technique for mitigating coherent errors in twoqubit gates called quantum measurement emulation (QME). We use this technique to implement a novel operation called density matrix exponentiation (DME), which has applications in quantum machine learning and universal simulation. These protocols contribute to the understanding and mitigation of errors in two-qubit gates. They are a step towards fault-tolerant universal quantum computing with superconducting circuits.
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