Variational quantum gate optimization on superconducting qubit system

Hybrid quantum-classical (HQC) algorithms aim at realizing the quantum advantage in shallow depth quantum circuits with an aid of classical computation. Recently, HQC algorithms have been extensively studied with the expectation that they may solve practical problems in the near future. However, the quantum gate fidelities directly limit the sizes of executable problems in quantum computers without quantum error correction. While HQC algorithms require fewer quantum gates, the state-of-the-art gate fidelities are still insufficient to deal with practical problems. In this presentation, we propose a gate optimization method, where high-fidelity multi-qubit gates are generated by optimizing parametrized quantum circuits consisting of tunable high-fidelity single-qubit gates and fixed multi-qubit gates with limited controllability. We call the method variational quantum gate optimization (VQGO) and demonstrate it on a superconducting qubit system.