Anne Y. Matsuura

Machine-learning based three-qubit gate for realization of a Toffoli gate with cQED-based transmon systems

  1. Sahar Daraeizadeh,
  2. Shavindra P. Premaratne,
  3. Xiaoyu Song,
  4. Marek Perkowski,
  5. and Anne Y. Matsuura
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 design procedure where we enforce realistic constraints, and analyze the new gate’s robustness under decoherence, distortion, and random noise. Our controlled-controlled-phase gate in combination with two single-qubit gates realizes a Toffoli gate which is widely used in quantum circuits, logic synthesis, quantum error correction, and quantum games.
arxiv pdf