Quantum computing is a novel paradigm for information processing. It holds the promise of solving some computationally hard problems that are otherwise intractable with classical computers. Along with scaling up the size of quantum processors comes formidable engineering challenges, including available wafer size, device yield and crosstalk, all constraining the scalability of monolithic quantum processor designs. The design of modular quantum computing schemes is a potential approach to scaling up to very large qubit numbers. However, the requirement for high quality interconnects that can transfer vulnerable quantum states between separate processors remains an outstanding challenge.
Youpeng Zhong, a researcher at Southern University of Science and Technology, dares to challenge this world-class problem and has achieved a number of important breakthrough results. In 2019, Zhong developed a low-loss coplanar delay line of 0.78 m long for connecting two superconducting qubits, which yielded remote quantum state transfer and entanglement generation with fidelities as high as 95%, laying foundation for remote quantum communication with microwave photons. The results were published in Nature Physics. In 2021, Zhong used superconducting wire bonds directly between a superconducting cable and the qubits to minimize losses and demonstrated multi-qubit entanglement generation and distribution. This research was published in Nature. In 2023, his research team further improved the inter-chip quantum state transfer and entanglement generation fidelity to 99% on a 20-qubit distributed quantum processor, which was published in Nature Electronics. This remarkable advancement is highlighted by Nature and will open a new paradigm for building large scale superconducting quantum processors using modular approaches.
In the future, Zhong plans to carry out systematic research around scalable modular superconducting quantum computers, solve the challenges of integration of superconducting quantum computers, and provide practical solutions for large-scale applications.
