Three-qubit quantum gates are key ingredients for quantum error correction and quantum-information processing. We generate quantum-control procedures to design three types of three-qubit gates, namely Toffoli, controlled-NOT-NOT, and Fredkin gates. The design procedures are applicable to a system comprising three nearest-neighbor-coupled superconducting artificial atoms. For each three-qubit gate, the numerical simulation of the proposed scheme achieves 99.9% fidelity, which is an accepted threshold fidelity for fault-tolerant quantum computing. We test our procedure in the presence of decoherence-induced noise and show its robustness against random external noise generated by the control electronics. The three-qubit gates are designed via the machine-learning algorithm called subspace-selective self-adaptive differential evolution.
['Ehsan Zahedinejad', 'Joydip Ghosh', 'Barry C. Sanders']
Designing high-fidelity single-shot three-qubit gates: A machine learning approach