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 as well as 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 (SuSSADE).
@article{arxiv.1511.08862,
title = {Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach},
author = {Ehsan Zahedinejad and Joydip Ghosh and Barry C. Sanders},
journal= {arXiv preprint arXiv:1511.08862},
year = {2016}
}
Comments
18 pages, 13 figures. Accepted for publication in Phys. Rev. Applied