Zhide Lu (鲁智德)

About Me

I am a Senior Researcher at the Shanghai Qi Zhi Institute. I received my Ph.D. in Physics from the Center for Quantum Information at IIIS, Tsinghua University, advised by Prof. Dong-Ling Deng. My research focuses on quantum error correction, driven by the ultimate goal of realizing practical, large-scale fault-tolerant quantum computation.

Academic Experience

Education

Research Interests

My research focuses on quantum error correction (QEC), driven by the ultimate goal of realizing practical, large-scale fault-tolerant quantum computation. Specific research directions include:

Low-overhead quantum error correction

• Designing low-overhead, high-threshold, hardware-efficient QEC codes
• Developing low-latency, FPGA-based real-time decoders

Fault-tolerant logical operations and quantum compilation

• Designing efficient fault-tolerant logical gates for Cornucopia codes
• Compiling quantum algorithms into resource-efficient, fault-tolerant circuits tailored for high-rate QEC codes

Experimental quantum error correction

• Co-designing quantum chips with experimental superconducting hardware groups to implement high-rate QEC codes, including optimizing layouts and coupler crossings
• Co-designing atom-movement schedules with experimental neutral-atom groups to realize low-overhead error correction

Publications

★: co-first authors; †: corresponding authors.
First- and co-first-author papers appear first; each group is in reverse chronological order.

13. Demonstration of low-overhead quantum error correction codes
    Ke Wang^★, Zhide Lu^★, Chuanyu Zhang^★, …, Zhen Wang^†, Chao Song^†, Haohua Wang, Dong-Ling Deng^†
    Nature Physics 22, 308–314 (2026)
12. Experimental demonstration of quantum continual learning with superconducting qubits
    Chuanyu Zhang^★, Zhide Lu^★, Liangtian Zhao^★, …, Jie Hao^†, Haohua Wang, Dong-Ling Deng^†, Chao Song^†
    npj Quantum Information 12, 28 (2026)
11. Deep quantum neural networks on a superconducting processor
    Xiaoxuan Pan^★, Zhide Lu^★, …, Dong-Ling Deng^†, Luyan Sun^†
    Nature Communications 14, 4006 (2023)
10. Markovian Quantum Neuroevolution for Machine Learning
    Zhide Lu^★, Pei-Xin Shen^★, Dong-Ling Deng^†
    Physical Review Applied 16, 044039 (2021)
9. Topological prethermal strong zero modes on superconducting processors
   Feitong Jin^★, Si Jiang^★, Xuhao Zhu^★, …, Zhide Lu, …, Qiujiang Guo^†, …, Haohua Wang^†, Dong-Ling Deng^†
   Nature 645, 626–632 (2025)
8. Probing many-body Bell correlation depth with superconducting qubits
   Ke Wang^★, Weikang Li^★, Shibo Xu^★, …, Zhide Lu, …, Chao Song^†, Haohua Wang^†, Dong-Ling Deng^†
   Physical Review X 15, 021024 (2025)
7. Experimental demonstration of reconstructing quantum states with generative models
   Xuegang Li^★, Wenjie Jiang^★, Ziyue Hua^★, Weiting Wang^†, Xiaoxuan Pan, Weizhou Cai, Zhide Lu, Jiaxiu Han, Rebing Wu, Chang-Ling Zou, Dong-Ling Deng^†, Luyan Sun^†
   Science Bulletin 70, 1572–1575 (2025)
6. Long-lived topological time-crystalline order on a quantum processor
   Liang Xiang^★, Wenjie Jiang^★, Zehang Bao^★, …, Zhide Lu, …, Qiujiang Guo^†, …, Haohua Wang^†, Dong-Ling Deng^†
   Nature Communications 15, 8963 (2024)
5. Expressibility-induced concentration of quantum neural tangent kernels
   Li-Wei Yu^†, Weikang Li, Qi Ye, Zhide Lu, Zizhao Han, Dong-Ling Deng^†
   Reports on Progress in Physics 87, 110501 (2024)
4. Non-Hermitian Fermi-Dirac Distribution in Persistent Current Transport
   Pei-Xin Shen^†, Zhide Lu, Jose L. Lado, Mircea Trif^†
   Physical Review Letters 133, 086301 (2024)
3. Quantum neural network classifiers: A tutorial
   Weikang Li^†, Zhide Lu, Dong-Ling Deng^†
   SciPost Physics Lecture Notes 61 (2022) [Code]
2. Quantum continual learning overcoming catastrophic forgetting
   Wenjie Jiang, Zhide Lu, Dong-Ling Deng^†
   Chinese Physics Letters 39, 050303 (2022)
1. Adversarial learning in quantum artificial intelligence
   Pei-Xin Shen, Wenjie Jiang, Weikang Li, Zhide Lu, Dong-Ling Deng^†
   Acta Physica Sinica 70, 140302 (2021) (Invited review in Chinese)

Preprints

5. A modular quantum computer based on Cornucopia codes
   Zhide Lu, Weikang Li, Yinghao Ma, Hanyu Yan, Bingrun Wang, Yixuan Ma, Zheng-Zhi Sun, Dong-Ling Deng^†
   arXiv:2610.19073 (2026) [arXiv]
4. Quantum error correction at ultra-low overhead
   Zhide Lu, Weikang Li^†, Dong-Ling Deng^†
   arXiv:2608.02773 (2026) [arXiv]
3. Machine learning the arrow of time in solid-state spins
   Xiang-Qian Meng^★, Zhide Lu^★, Ya-Nan Lu, Xiu-Ying Chang, Yan-Qing Liu, Dong Yuan, Weikang Li, Zheng-Zhi Sun, Pei-Xin Shen, Lu-Ming Duan^†, Dong-Ling Deng^†, Pan-Yu Hou^†
   arXiv:2603.10344 (2026) [arXiv]
2. Improved nonlocality certification via bouncing between Bell operators and inequalities
   Weikang Li^★, Mengyao Hu^★, Ke Wang, Shibo Xu, Zhide Lu, …, Chao Song^†, Haohua Wang, Patrick Emonts^†, Jordi Tura
   arXiv:2407.12347 (2024) [arXiv]
1. Proving olympiad geometry theorems on a superconducting quantum processor
   Ning Wang^★, Zheng-Zhi Sun^★, Zhengyi Cui, …, Zhide Lu, Chao Song^†, …, H. Wang^†, Dong-Ling Deng^†
   arXiv:2609.14533 (2026) [arXiv]

Conferences & Talks

11. Quantum error correction at ultra-low overhead
    奇点科学会议, Dali, Yunnan, 2026 (invited talk)
10. Quantum AI Exploration
    Machine Learning for Science 2025 Conference, Zhejiang, 2025 (invited talk)
9. Theoretical and experimental explorations of quantum low-density parity-check codes
   Chern Institute of Mathematics, Nankai University, Tianjin, 2025 (invited talk)
8. Theoretical and experimental explorations of quantum neural networks
   Department of Computer Science, Sun Yat-sen University, Guangdong, 2025 (invited talk)
7. Theoretical and experimental explorations of quantum neural networks
   Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area, 2025 (invited talk)
6. Deep quantum neural networks equipped with the backpropagation algorithm
   QUANTUMatter 2024, Spain, 2024 (poster)
5. Recent Progress on Deep Quantum Neural Networks
   The 12th International Conference on Computing and Pattern Recognition, Shandong, 2023 (invited talk)
4. Markovian Quantum Neuroevolution for Machine Learning
   APS March Meeting, Virtual, 2023 (contributed talk)
3. Deep Quantum Neural Networks on a Superconducting Processor
   Progress in Electromagnetics Research Symposium, Prague, Czech Republic, 2023 (contributed talk)
2. Deep quantum neural networks on a superconducting processor
   The 2nd International Conference on Emerging Quantum Technology, 2023 (poster)
1. Markovian Quantum Neuroevolution for Machine Learning
   The 6th International Conference on “Quantum Information, Spacetime, and Topological Matter”, Chongqing, 2021 (poster)