gates, namely Toffoli, Controlled-Not-Not and Fredkin gates. The design procedures are applicable to an architecture of nearest-neighbor-coupled superconducting artificial atoms. The resultant fidelity for each gate is above 99.9%, which is an accepted threshold fidelity for fault-tolerant quantum computing. We test our policy in the presence of decoherence-induced noise as well as show its robustness against random external noise generated by the control electronics. The three-qubit gates are designed via our machine learning algorithm called Subspace-Selective Self-Adaptive Differential Evolution (SuSSADE).
Designing high-fidelity single-shot three-qubit gates: A machine learning approach
Three-qubit quantum gates are crucial for quantum error correction and quantum information processing. We generate policies for quantum control procedures to design three types of three-qubit