Experimental Hamiltonian Learning of an 11-Qubit Solid-State Quantum Spin RegisterSupported by the Frontier Science Center for Quantum Information of the Ministry of Education of China, Tsinghua University Initiative Scientific Research Program, and the National Key Research and Development Program of China (2016YFA0301902)

Learning the Hamiltonian of a quantum system is indispensable for prediction of the system dynamics and realization of high fidelity quantum gates. However, it is a significant challenge to efficiently characterize the Hamiltonian which has a Hilbert space dimension exponentially growing with the sy...

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Bibliographic Details
Published in:	Chinese physics letters 2019-10, Vol.36 (10)
Main Authors:	Hou, P.-Y., He, L., Wang, F., Huang, X.-Z., Zhang, W.-G., Ouyang, X.-L., Wang, X., Lian, W.-Q., Chang, X.-Y., Duan, L.-M.
Format:	Article
Language:	eng
Online Access:	Get full text
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Summary:	Learning the Hamiltonian of a quantum system is indispensable for prediction of the system dynamics and realization of high fidelity quantum gates. However, it is a significant challenge to efficiently characterize the Hamiltonian which has a Hilbert space dimension exponentially growing with the system size. Here, we develop and implement an adaptive method to learn the effective Hamiltonian of an 11-qubit quantum system consisting of one electron spin and ten nuclear spins associated with a single nitrogen-vacancy center in a diamond. We validate the estimated Hamiltonian by designing universal quantum gates based on the learnt Hamiltonian and implementing these gates in the experiment. Our experimental result demonstrates a well-characterized 11-qubit quantum spin register with the ability to test quantum algorithms, and shows our Hamiltonian learning method as a useful tool for characterizing the Hamiltonian of the nodes in a quantum network with solid-state spin qubits.
ISSN:	0256-307X 1741-3540