2020 Crossed-Seminar on Quantum Physics and Artificial Intelligence Held

The 2020 Crossed-Seminar on Quantum Physics and Artificial Intelligence was held online from November 21 to 22, 2020. Scholars from Tsinghua University, Chinese Academy of Sciences, Huawei and other Organizations made wonderful reports in the seminar. More than 100 scholars from universities, research institutes and well-known enterprises all over China attended the seminar. The seminar was jointly organized by Tianjin University’s College of Intelligence and Computing and Capital Normal University’s Department of Physics, assisted by China Computer Federation Tianjin Branch and Chinese Information Processing Society of China, Youth Working Committee and supported by the Academy for Multidisciplinary Studies of Capital Normal University.

Hua Jianfeng, leader of Tianjin University’s College of Intelligence, and Ji Anchun, head of Capital Normal University’s Department of Physics, addressed in the seminar. Prof. Hu Qinghua, Deputy Dean of Tianjin University’s College of Intelligence and Computing presided over the first session in the seminar. Prof. Su Gang of the Chinese Academy of Sciences University, Professor Xue Peng of the Beijing Computational Science Research Center, Professor Zhai Hui of Tsinghua University’s Institute of Advanced Studies, Prof. Song Dawei of Beijing University of Technology, Prof. Hou Yuexian of Tianjin University and other experts and scholars attended the seminar and made their reports. Liu Qun, Chief phonetic and semantic scientist from Huawei Noah's Ark Laboratory and leaders from Tianjin Municipal Network Information Office were invited to attend the seminar as well.

The seminar kicked off with the introduction of two organizers, Dr. Zhang Peng of Tianjin University and Dr. Ran Shiju of Capital Normal University. The seminar was divided into eight sessions, and the reports covered the application of artificial intelligence in quantum physics, quantum artificial intelligence, quantum machine learning, quantum computation, quantum information retrieval, natural language processing, current quantum technology and artificial intelligence technology.

In terms of quantum artificial intelligence and quantum machine learning, Prof. Su Gang from the University of Chinese Academy of Sciences, systematically elaborated the development of the science of artificial intelligence and its integration with physics, pointing out that the quantum intelligence is becoming an emerging new paradigm in science with some examples and advances in different disciplines.

Xue Peng, professor of Beijing Center for Computing Science, introduced the single photon platform experiment of non-Hermitian quantum walking and non-Hermitian skin effect, and discussed the possible application of non-Hermitian quantum walking and light quantum platform in quantum machine learning.

Prof. Zhai Hui of the Institute of Advanced Studies in Tsinghua University, introduced the work of his team in the scrambling quantum information and quantum neural networks.

Prof. Hou Yuexian of Tianjin University introduced the related work of reconstructing quantum mechanics by information principle.

In terms of quantum information retrieval and natural language processing, Prof. Song Dawei from the Beijing Institute of Technology has systematically introduced the acquisition and retrieval of information from the perspective of quantum cognition.

Prof. Qiu Xipeng of Fudan University, explained the self-attention model in natural language processing and possible scenarios of combining it with quantum computing in details.

Dr. Liu Zhiyuan from Tsinghua University, introduced the latest development and trend of knowledge-based natural language processing.

Dr. Zhang Peng systematically introduced the basic idea of applying quantum theory to artificial intelligence tasks such as information retrieval and natural language processing.

Wen Ying, an assistant professor of Shanghai Jiao Tong University, introduced multi-agent deep reinforcement learning and (quantum) game analysis. The application of quantum theory in NLP was introduced by Dr. Wang Benyou of Padua University, Italy.

In the research of machine learning assisted quantum physics, Prof. Li Xiaopeng of Fudan University introduced the design of automatic quantum adiabatic algorithm combined with reinforcement learning, and elaborated its applicability, transferability and expansibility.

Li Wei, an associate professor of Beihang University, introduced the automatic search of microscopic models of quantum magnets, which are based on experimental data of physical properties to find model descriptions of strongly correlated materials.

Ma Xingyu, a doctoral student at the Chinese Academy of Sciences, reported on the application of machine learning methods in the design of advanced functional materials.

In terms of quantum computing, Lv Dingshun, a senior researcher of Academia Sinica, Huawei 2012 Laboratory, systematically introduced the status of development and existing problems of quantum computing platforms at China and abroad, and introduced HiQ 3.0 quantum computing simulator and developer tools in details.

Dr. Wang Kunkun from Beijing Research Center for Computing Science introduced the quantum classifier of single photon pictures based on the optical quantum computing platform and the recommendation system based on quantum walking.

In the aspect of tensor network, the method of differentiable programming tensor network and its application were introduced in detail by Liao Haijun, an associate professor of Institute of Physics, Chinese Academy of Sciences. Cheng Song, an assistant researcher of Yanqi Lake Institute of Applied Mathematics, Beijing, reported the related research of using matrix product density operator to simulate quantum circuits under noise.

Dr. Liu Ding from Tianjin University of Technology explained the machine learning of hybrid tensor networks.

And then, Dr. Ran Shiju reported the implementation and application of efficient and interpretable probabilistic machine learning based on Bayesian Tensor network. S

un Zhengzhi, a doctoral student of University of Chinese Academy of Sciences, reported on the generative classifier algorithm of tensor networks and the nonlinear visualization method of quantum states.

Finally, Pan Feng, a doctoral student at the Institute of Theoretical Physics of the Chinese Academy of Sciences, reported a new algorithm for shrinking arbitrary tensor networks.

By the College of Intelligence and Computing

Editor: Eva Yin