气候变化领域集成服务门户(CCPortal): Reconstruction of quantum channel via convex optimization

CCPortal

DOI	10.1016/j.scib.2019.11.009
	Reconstruction of quantum channel via convex optimization
	Huang X.-L.; Gao J.; Jiao Z.-Q.; Yan Z.-Q.; Zhang Z.-Y.; Chen D.-Y.; Zhang X.; Ji L.; Jin X.-M.
发表日期	2020
ISSN	20959273
起始页码	286
结束页码	292
卷号	65 期号:4
英文摘要	Quantum process tomography is often used to completely characterize an unknown quantum process. However, it may lead to an unphysical process matrix, which will cause the loss of information with respect to the tomography result. Convex optimization, widely used in machine learning, is able to generate a global optimum that best fits the raw data while keeping the process tomography in a legitimate region. Only by correctly revealing the original action of the process can we seek deeper into its properties like its phase transition and its Hamiltonian. Here, we reconstruct the seawater channel using convex optimization and further test it on the seven fundamental gates. We compare our method to the standard-inversion and norm-optimization approaches using the cost function value and our proposed state deviation. The advantages convince that our method enables a more precise and robust estimation of the elements of the process matrix with less demands on preliminary resources. In addition, we examine on a set of non-unitary channels and the reconstructions reach up to 99.5% accuracy. Our method offers a more universal tool for further analyses on the components of the quantum channels and we believe that the crossover between quantum process tomography and convex optimization may help us move forward to machine learning of quantum channels. © 2019 Science China Press
关键词	Convex optimization Quantum channel Quantum information Quantum process tomography
英文关键词	Convex optimization; Cost functions; Machine components; Machine learning; Quantum channel; Quantum communication; Quantum entanglement; Quantum optics; Tomography; Global optimum; Optimization approach; Process matrix; Process tomography; Quantum Information; Quantum process; Quantum process tomography; Robust estimation; Communication channels (information theory)
语种	英语
来源期刊	Science Bulletin
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/207072
作者单位	Center for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, Shanghai, 200240, China; CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, 230026, China
推荐引用方式 GB/T 7714	Huang X.-L.,Gao J.,Jiao Z.-Q.,et al. Reconstruction of quantum channel via convex optimization[J],2020,65(4).
APA	Huang X.-L..,Gao J..,Jiao Z.-Q..,Yan Z.-Q..,Zhang Z.-Y..,...&Jin X.-M..(2020).Reconstruction of quantum channel via convex optimization.Science Bulletin,65(4).
MLA	Huang X.-L.,et al."Reconstruction of quantum channel via convex optimization".Science Bulletin 65.4(2020).