Huang, Chang JiangMa, HailanYin, QiTang, Jun FengDong, DaoyiChen, ChunlinXiang, Guo YongLi, Chuan FengGuo, Guang Can2025-03-252025-03-25Scopus:85092576756https://dspace-test.anu.edu.au/handle/1885/733737581As a ubiquitous aspect of modern information technology, data compression has a wide range of applications. Therefore, a quantum autoencoder which can compress quantum information into a low-dimensional space is fundamentally important to achieve automatic data compression in the field of quantum information. Such a quantum autoencoder can be implemented through training the parameters of a quantum device using classical optimization algorithms. In this paper, we demonstrate the condition of achieving a perfect quantum autoencoder and theoretically prove that a quantum autoencoder can losslessly compress high-dimensional quantum information into a low-dimensional space (also called latent space) if the number of maximum linearly independent vectors from input states is no more than the dimension of the latent space. Also, we experimentally realize a universal two-qubit unitary gate and design a quantum autoencoder device by applying a machine learning method. Experimental results demonstrate that our quantum autoencoder is able to compress two two-qubit states into two one-qubit states. Besides compressing quantum information, the quantum autoencoder is used to experimentally discriminate two groups of nonorthogonal states.The work at University of Science and Technology of China is supported by the National Natural Science Foundation of China (Grants No. 11574291, No. 11774334, No. 61828303, and No. 11774335), the National Key Research and Development Program of China (Grants No. 2017YFA0304100 and No. 2018YFA0306400), Key Research Program of Frontier Sciences, Chinese Academy of Sciences (Grant No. QYZDY-SSW-SLH003), and Anhui Initiative in Quantum Information Technologies. D.D. also acknowledges the support of the Australian Research Council by Grant No. DP190101566 and the Alexander von Humboldt Foundation of Germany.EnglishPublisher Copyright: © 2020 American Physical Society.202010.1103/PhysRevA.102.032412http://www.scopus.com/inward/record.url?scp=85092576756&partnerID=8YFLogxK