Ji-Hoon Kang: Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea.
Taehyun Yoon: Artificial Intelligence Graduate School, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea.
Chanhui Lee: Department of Artificial Intelligence, Korea University, Seoul, 02841, Republic of Korea.
Sungbin Lim: Department of Statistics, Korea University, Seoul, 02841, Republic of Korea. sungbin@korea.ac.kr.
Hoon Ryu: Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea. elec1020@kisti.re.kr.
Device engineering based on computer-aided simulations is essential to make silicon (Si) quantum bits (qubits) be competitive to commercial platforms based on superconductors and trapped ions. Combining device simulations with the Bayesian optimization (BO), here we propose a systematic design approach that is quite useful to procure fast and precise entangling operations of qubits encoded to electron spins in electrode-driven Si quantum dot (QD) systems. For a target problem of the controlled-X (CNOT) logic operation, we employ BO with the Gaussian process regression to evolve design factors of a Si double QD system to the ones that are optimal in terms of speed and fidelity of a CNOT logic driven by a single microwave pulse. The design framework not only clearly contributes to cost-efficient securing of solutions that enhance performance of the target quantum operation, but can be extended to implement more complicated logics with Si QD structures in experimentally unprecedented ways.
References
Nat Commun. 2017 Dec 15;8(1):1766
[PMID: 29242497]
