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.

Scalable Realization of Surface Code Quantum Memory by Applying Multi-Qubit Parity Detector Gates

  1. Sahar Daraeizadeh,
  2. Sarah Mostame,
  3. Preethika Kumar Eslami,
  4. Marek Perkowski,
  5. and Xiaoyu Song
We analytically designed the control bias pulses to realize new multi-qubit parity detector gates for 2-Dimensional (2D) array of superconducting flux qubits with non-tunable couplings.
We designed two 5-qubit gates such that the middle qubit is the target qubit and all four coupled neighbors are the control qubits. These new gates detect the parity between two vertically/horizontally coupled neighbor qubits while cancelling out the coupling effect of horizontally/vertically coupled neighbor qubits. For a 3 by 3 array of 9 qubits with non-tunable couplings, we simulated the effect of our new 5-qubit horizontal and vertical parity detector gates. We achieved the intrinsic fidelity of 99.9% for horizontal and vertical parity detector gates. In this paper we realize Surface Code memories based on the multi-qubit parity detector gates for nearest neighbor superconducting flux qubits with and without tunable couplings. However, our scheme is applicable to other superconducting qubits as well. In our proposed memory realization, error correction cycles can be performed in parallel on several logical qubits or even on the entire 2D array of qubits, this makes it a desirable candidate for large scale and longtime quantum computation. In addition to extensive reduction of the number of control parameters in our method, the error correction cycle time is reduced and does not grow by increasing the number of qubits in the logical qubit layout. Another advantage of this approach is that there will not be any dephasing from idle qubits since all the qubits are used in the error correction cycles.