I. Team Profile

The team conducts technical research in the field of quantum computing, with distinct characteristics in quantum-classical hybrid algorithms, quantum chip design, and quantum-classical hybrid cloud platforms. In terms of algorithms, the team has designed a high-precision quantum-classical convolutional neural network framework, incorporating quantum computing, ant colony algorithms, quantum LSTM, and Transformer architectures, reducing the time complexity of optimization problems and enabling the practical application of quantum machine learning technologies. The team has implemented a "one-stop," "easy-to-operate," "highly flexible," and "high-efficiency" Quantum Electronic Design Automation (QEDA) platform, allowing users to customize parameters, build frameworks, and perform simulation and analysis within the QEDA platform. The quantum-classical hybrid cloud platform features efficient analysis, visualization of massive data, and includes core functions such as code design and project description visualization. It supports quantum SVM, quantum CNN, and quantum LSTM algorithms, applicable to business scenarios such as industrial internet equipment fault diagnosis and predictive analysis, drug screening, and path planning.

II. Team Members

Team Leader and Profile:

Xu Hua holds a bachelor's degree from the University of Science and Technology of China's Special Class for the Gifted Young, a Ph.D. from the University of Maryland, USA, and was a postdoctoral fellow at the National Institute of Standards and Technology (NIST), USA. He previously served as a Principal Engineer at ASML, and as a Senior Technical Expert and Quantum Scientist at Alibaba. Dedicated to interdisciplinary fields such as quantum computing and artificial intelligence, he has made numerous original and significant contributions, publishing over 20 papers in internationally renowned journals and holding more than 10 patents. He excels at combining technology with applications and possesses strong market development and management capabilities. He was responsible for the establishment of the Alibaba Quantum Laboratory and the integration of Alibaba's AI technology with business, and has undertaken core software system R&D work at ASML.

Team Members and Profile:

Wu Mohan holds a Bachelor of Mathematics from the Hong Kong University of Science and Technology and a Ph.D. in Mathematics from the University of Pittsburgh, USA. He previously served as a Senior Algorithm Engineer at the Communications Artificial Intelligence Laboratory of AsiaInfo Technologies (China) Co., Ltd. His main research interests are computational mathematics and quantum computing. He has published papers in JCR Q1 mathematics journals and is proficient in algorithm-related research and software project implementation.

III. Research Directions

The team conducts technical research in the field of quantum computing, with distinct characteristics in quantum-classical hybrid algorithms, quantum chip design, and quantum-classical hybrid cloud platforms. The team proposed two types of quantum circuits to simulate convolutional operations on RGB images, which is the first work on quantum convolutional circuits capable of effectively processing RGB images. Compared to purely classical Convolutional Neural Networks (CNNs), it achieves higher testing accuracy. The team also investigated the relationship between the scale of the quantum circuit ansatz and the learnability of hybrid quantum-classical convolutional neural networks. Through experiments based on the CIFAR-10 and MNIST datasets, we demonstrated that larger quantum circuit ansatzes lead to better predictive performance in multi-class classification tasks, enhancing the application prospects of quantum algorithms.

IV. Academic Achievements

(I) Representative Achievements

Intelligent Operations and Maintenance & Intelligent IDC / AI Solution design and implementation for resource management optimization of Search-BU and Aliyun-IDC: Conducted in-depth exploratory research on IDC operational intelligence. Participated as a sub-project leader in the application to the Ministry of Science and Technology for the National Key R&D Program project "Key Technologies and Equipment for High-Efficiency Cloud Computing Data Centers," which was approved and established by the Ministry of Science and Technology in September 2017.

(II) Representative Papers and Monographs

1. Y. Jing, X. Li, Y. Yang, C. Wu, W. Fu, W. Hu, Y. Li and H. Xu, "RGB image classification with quantum convolutional ansatz", Quantum Inf Process 21, 101 (2022).

2. W. Hu, Y. Yang, W. Xia, J. Pi, E. Huang, X. Zhang and H. Xu, "Performance of Superconducting Quantum Computing Chips under Different Architecture Design", Quantum Inf Process 21, 237, (2022).

3. Y. Li, L. Song, Q. Sun, H. Xu, X. Li, Z. Fang and W. Yao, "Rolling bearing fault diagnosis based on quantum LS-SVM", EPJ Quantum Technology, 9, 18 (2022).

4. Y. Li, Q. Sun, H. Xu, X. Li, Z. Fang and W. Yao, "Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm", Shock and Vibration, vol. 2022, Article ID 8126464, (2022), doi.org/10.1155/2022/8126464

5. Liang Zhang, Yin Xu, Mohan Wu, Liang Wang, H. Xu, "Quantum Long Short-Term Memory for Drug Discovery", arXiv:2407.19852, (2024)

6. Qian Qiu, Liang Zhang, Mohan Wu, Qichun Sun, Xiaogang Li, Da-Chuang Li, H. Xu, "A practical applicable quantum-classical hybrid ant colony algorithm for the NISQ era", arXiv:2410.17277, (2024)

(III) Representative Patents

1. D. Maurits Van, Y. Zhang, H. Xu, "Alternative target design for metrology using modulation techniques", US10585357B2 / TWI623823B (Granted) / WO 2017114652

2. S. Wang, S. Zhu, F. Lin, M. Sun, L. Yan, H. Xu, C. Yang, T. Li, R. Jin, "Machine learning in message distribution", WO2018103039A1

3. H. Xu, G. Yang, C. Zhang, J. Yin, K. Yang, C. Tian, C. Yang, S. Zhu, R, Jin, " System and method for traffic control in online platform", CN111183621B (Granted) / WO2019006746A1

4. H. Xu, "Qubit detection system and detection method", CN110879105B (Granted) / US20210182727A1 / WO2020048375A1

5. H. Xu, "Device, system, and method for qubit calibration, measurement and control", CN111523671A / US11488048B2 (Granted)

6. Xu Hua, Qin Jin, "Packaging structure, manufacturing method thereof, and quantum processor", CN113675172A / US20210359384A1

7. Xu Hua, Hu Wei, "A quantum chip performance simulation and analysis system based on a cloud platform", CN2020110928248A

8. Jing Yu, Li Xiaogang, Yang Yang, Xu Hua, "A quantum multi-channel circuit classification method, server, storage medium, and system", CN116258886A

9. Xu Hua, "An electromagnetic field spatial distribution measurement method and system", Application No. 202110119865X

10. Sun Qichun, Li Xiaogang, Xu Hua, "Data prediction method, device, storage medium, and electronic device", Application No. CN115618232A

V. Social Service Intentions

The team brings together top talents from various fields including quantum technology, the semiconductor industry, and computer technology. It is committed to building a hybrid cloud platform system that integrates the computing resources and algorithms of both quantum and classical computing, providing users with computing power and algorithm services.

VI. Contact Information

Name: Xu Hua
Email: xuhua123@tust.edu.cn
Team Address: Building 8, School of Artificial Intelligence, Tianjin University of Science and Technology, No. 9, 13th Avenue, Tianjin Economic and Technological Development Area.