Kavli Affiliate: Giordano Scappucci
| First 5 Authors: Jaemin Park, Hyeongyu Jang, Hanseo Sohn, Jonginn Yun, Younguk Song
| Summary:
Addressing and mitigating decoherence sources plays an essential role in the
development of a scalable quantum computing system, which requires low gate
errors to be consistently maintained throughout the circuit execution. While
nuclear spin-free materials, such as isotopically purified silicon, exhibit
intrinsically promising coherence properties for electron spin qubits, the
omnipresent charge noise, when converted to magnetic noise under a strong
magnetic field gradient, often hinders stable qubit operation within a time
frame comparable to the data acquisition time. Here, we demonstrate both open-
and closed-loop suppression techniques for the transduced noise in silicon spin
qubits, resulting in a more than two-fold (ten-fold) improvement of the
inhomogeneous coherence time (Rabi oscillation quality) that leads to a
single-qubit gate fidelity of over 99.6% even in the presence of a strong
decoherence field gradient. Utilizing gate set tomography, we show that
adaptive qubit control also reduces the non-Markovian noise in the system,
which validates the stability of the gate fidelity. The technique can be used
to learn multiple Hamiltonian parameters and is useful for the intermittent
calibration of the circuit parameters with affordable experimental overhead,
providing a useful subroutine during the repeated execution of general quantum
circuits.
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