Qubit system in capacitively coupled semiconductor quantum dots

A. A. Setser, J. P. Kestner

E. Vernek, Irisnei L. Ferreira, P. A. Orellana +2 more

Jorge Cayao, Mónica Benito, Guido Burkard

Recent achievements in the field of gate-defined semiconductor quantum dots reinforce the concept of a spin-based quantum computer consisting of nodes of locally connected qubits which communicate with each other via superconducting circuit resonator photons. In this paper, we theoretically demonstrate a versatile set of quantum gates between adjacent spin qubits defined in semiconductor quantum dots situated within the same node of such a spin-based quantum computer. The electric dipole acquired by the spin of an electron that moves across a double quantum dot potential in a magnetic field gradient has enabled strong coupling to resonator photons and low-power spin control. Here we show that this flopping-mode spin qubit also provides the tunability to program multiple two-qubit gates. Since the capacitive coupling between these qubits brings about additional dephasing, we calculate the estimated infidelity of different two-qubit gates in the most immediate possible experimental realizations.

Seigo Tarucha, Michihisa Yamamoto, A. Oiwa +2 more

Joshua Ziegler, Florian Luthi, Mick Ramsey +3 more

Single electrons trapped on semiconductor-defined quantum dots (QDs) are a promising platform for large-scale quantum computing. The authors demonstrate a reliable, automated method to identify the capacitive coupling between QDs. The approach combines machine learning with traditional fitting, to take advantage of the desirable properties of each. Also, analysis of cross capacitance may be used for automatic identification of the spurious QDs that occasionally form during device tuning. These techniques can autonomously flag devices with spurious dots near the operating regime, which is crucial information for reliable tuning for qubit operations.

Daniel Loss