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pro vyhledávání: '"Daraeizadeh, Sahar"'
In this paper, we present a machine learning framework to design high-fidelity multi-qubit gates for quantum processors based on quantum dots in silicon, with qubits encoded in the spin of single electrons. In this hardware architecture, the control
Externí odkaz:
http://arxiv.org/abs/2006.08813
Autor:
Daraeizadeh, Sahar, Premaratne, Shavindra P., Song, Xiaoyu, Perkowski, Marek, Matsuura, Anne Y.
Publikováno v:
Phys. Rev. A 102, 012601 (2020)
We use machine learning techniques to design a 50 ns three-qubit flux-tunable controlled-controlled-phase gate with fidelity of >99.99% for nearest-neighbor coupled transmons in circuit quantum electrodynamics architectures. We explain our gate desig
Externí odkaz:
http://arxiv.org/abs/1908.01092
We realize Surface Code quantum memories for nearest-neighbor qubits with always-on Ising interactions. This is done by utilizing multi-qubit gates that mimic the functionality of several gates. The previously proposed Surface Code memories rely on e
Externí odkaz:
http://arxiv.org/abs/1811.09011
Akademický článek
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