Xiaotong Ni

SuperGrad: a differentiable simulator for superconducting processors

  1. Ziang Wang,
  2. Feng Wu,
  3. Hui-Hai Zhao,
  4. Xin Wan,
  5. and Xiaotong Ni
One significant advantage of superconducting processors is their extensive design flexibility, which encompasses various types of qubits and interactions. Given the large number of
tunable parameters of a processor, the ability to perform gradient optimization would be highly beneficial. Efficient backpropagation for gradient computation requires a tightly integrated software library, for which no open-source implementation is currently available. In this work, we introduce SuperGrad, a simulator that accelerates the design of superconducting quantum processors by incorporating gradient computation capabilities. SuperGrad offers a user-friendly interface for constructing Hamiltonians and computing both static and dynamic properties of composite systems. This differentiable simulation is valuable for a range of applications, including optimal control, design optimization, and experimental data fitting. In this paper, we demonstrate these applications through examples and code snippets.
arxiv pdf

Superconducting processor design optimization for quantum error correction performance

  1. Xiaotong Ni,
  2. Ziang Wang,
  3. Rui Chao,
  4. and Jianxin Chen
In the quest for fault-tolerant quantum computation using superconducting processors, accurate performance assessment and continuous design optimization stands at the forefront. To
facilitate both meticulous simulation and streamlined design optimization, we introduce a multi-level simulation framework that spans both Hamiltonian and quantum error correction levels, and is equipped with the capability to compute gradients efficiently. This toolset aids in design optimization, tailored to specific objectives like quantum memory performance. Within our framework, we investigate the often-neglected spatially correlated unitary errors, highlighting their significant impact on logical error rates. We exemplify our approach through the multi-path coupling scheme of fluxonium qubits.
arxiv pdf

Fluxonium: an alternative qubit platform for high-fidelity operations

  1. Feng Bao,
  2. Hao Deng,
  3. Dawei Ding,
  4. Ran Gao,
  5. Xun Gao,
  6. Cupjin Huang,
  7. Xun Jiang,
  8. Hsiang-Sheng Ku,
  9. Zhisheng Li,
  10. Xizheng Ma,
  11. Xiaotong Ni,
  12. Jin Qin,
  13. Zhijun Song,
  14. Hantao Sun,
  15. Chengchun Tang,
  16. Tenghui Wang,
  17. Feng Wu,
  18. Tian Xia,
  19. Wenlong Yu,
  20. Fang Zhang,
  21. Gengyan Zhang,
  22. Xiaohang Zhang,
  23. Jingwei Zhou,
  24. Xing Zhu,
  25. Yaoyun Shi,
  26. Jianxin Chen,
  27. Hui-Hai Zhao,
  28. and Chunqing Deng
Superconducting qubits provide a promising path toward building large-scale quantum computers. The simple and robust transmon qubit has been the leading platform, achieving multiple
milestones. However, fault-tolerant quantum computing calls for qubit operations at error rates significantly lower than those exhibited in the state of the art. Consequently, alternative superconducting qubits with better error protection have attracted increasing interest. Among them, fluxonium is a particularly promising candidate, featuring large anharmonicity and long coherence times. Here, we engineer a fluxonium-based quantum processor that integrates high qubit-coherence, fast frequency-tunability, and individual-qubit addressability for reset, readout, and gates. With simple and fast gate schemes, we achieve an average single-qubit gate fidelity of 99.97% and a two-qubit gate fidelity of up to 99.72%. This performance is comparable to the highest values reported in the literature of superconducting circuits. Thus our work, for the first time within the realm of superconducting qubits, reveals an approach toward fault-tolerant quantum computing that is alternative and competitive to the transmon system.
arxiv pdf