We use machine-learning techniques to design three-qubit entangling gates with fidelities of >99.9% and duration of 50 ns for nearest-neighbor coupled flux-tunable transmons in circuit quantum electrodynamics architectures. The gate design procedure enforces realistic constraints and analyzes the robustness of the new gates under decoherence, distortion, and random noise. The controlled-controlled-phase gate in combination with two single-qubit gates realizes a Toffoli gate which is widely used in quantum circuits, logic synthesis, and quantum error correction. We also introduce a three-qubit entangling Parity Checker gate which has applications in quantum arithmetic circuits and quantum error correction schemes. Using these three-qubit gates, we design a circuit for Shor's nine-qubit quantum error correction code and compare its performance to conventional realizations.

中文翻译：

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基于机器学习的三比特门设计，用于Transmon系统中的Toffoli门和奇偶校验

我们使用机器学习技术为电路量子电动力学架构中的最邻近耦合通量可调谐跨子设计保真度> 99.9％且持续时间为50 ns的三比特纠缠门。门设计程序施加了现实的约束，并分析了新门在去相干，失真和随机噪声下的鲁棒性。受控相控门与两个单量子位门的组合实现了Toffoli门，该门已广泛用于量子电路，逻辑合成和量子误差校正。我们还介绍了一种三量子位纠缠奇偶校验门，它在量子算术电路和量子误差校正方案中都有应用。使用这些三量子位门，我们为Shor'设计了一个电路。