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Quantum spectral clustering algorithm for unsupervised learning

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science China(Information sciences) 2022年第10期65卷 43-52页

作者： Qingyu LI Yuhan HUANG Shan JIN Xiaokai HOU Xiaoting WANG institute of fundamental and frontier sciences University of Electronic Science and Technology of China

Clustering is one of the most crucial problems in unsupervised learning, and the well-known k-means algorithm can be implemented on a quantum computer with a significant speedup. However, for the clustering problems that cannot be solved using the k-means algorithm, a powerful method called spectral clustering is used. In this study, we propose a circuit design to implement spectral clustering on a quantum processor with substantial speedup by initializing the processor into a maximally entangled state and encoding the data information into an efficiently simulatable Hamiltonian. Compared to the established quantum kmeans algorithms, our method does not require a quantum random access memory or a quantum adiabatic process. It relies on an appropriate embedding of quantum phase estimation into Grover's search to gain the quantum speedup. Simulations demonstrate that our method effectively solves clustering problems and is an important supplement to quantum k-means algorithm for unsupervised learning.

关键词： quantum algorithm machine learning spectral clustering quantum phase estimation Grover’s search Hamiltonian simulation

Unlocking the stable interface in aqueous zinc-ion battery with multifunctional xylose-based electrolyte additives

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Journal of Energy Chemistry 2025年第1期 770-778页

作者： Xiaoqin Li Jian Xiang Lu Qiu Xiaohan Chen Yinkun Zhao Yujue Wang Qu Yue Taotao Gao Wenlong Liu Dan Xiao Zhaoyu Jin Panpan Li institute for Advanced Study Chengdu University School of Mechanical Engineering Chengdu University College of Food and Biological Engineering Chengdu University institute of fundamental and frontier sciences University of Electronic Science and Technology of China College of Materials science and Engineering Sichuan University

The growth of dendrites and the side reactions occurring at the Zn anode pose significant challenges to the commercialization of aqueous Zn-ion batteries（AZIBs）. These challenges arise from the inherent conflict between mass transfer and electrochemical kinetics. In this study, we propose the use of a multifunctional electrolyte additive based on the xylose（Xylo） molecule to address these issues by modulating the solvation structure and electrode/electrolyte interface, thereby stabilizing the Zn anode. The introduction of the additive alters the solvation structure, creating steric hindrance that impedes charge transfer and then reduces electrochemical kinetics. Furthermore, in-situ analyses demonstrate that the reconstructed electrode/electrolyte interface facilitates stable and rapid Zn2+ion migration and suppresses corrosion and hydrogen evolution reactions. As a result, symmetric cells incorporating the Xylo additive exhibit significantly enhanced reversibility during the Zn plating/stripping process, with an impressively long lifespan of up to 1986 h, compared to cells using pure ZnSO4electrolyte. When combined with a polyaniline cathode, the full cells demonstrate improved capacity and long-term cyclic stability. This work offers an effective direction for improving the stability of Zn anode via electrolyte design, as well as highperformance AZIBs.

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Rational Design of Colloidal Core/Shell Quantum Dots for Optoelectronic Applications

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Journal of Electronic science and Technology 2020年第2期18卷 105-118页

作者： Xiang-Long Huang Xin Tong Zhiming MWang institute of fundamental and frontier sciences University of Electronic Science and Technology of China

Colloidal core/shell quantum dots(QDs) are promising for solar technologies because of their excellent optoelectronic properties including tunable light absorption/emission spectra, high photoluminescence quantum yield(PLQY), suppressed Auger recombination, efficient charge separation/transfer, and outstanding photo-/thermal-/chemical stability. In this review, engineered core/shell QDs with various types of band structures and corresponding device performance in luminescent solar concentrators(LSCs), light-emitting diodes(LEDs), solar-driven photoelectrochemical(PEC) devices, and QDs-sensitized solar cells(QDSCs) are summarized. In particular, the applications of interfacial layer engineering and eco-friendly, heavy metal-free core/shell QDs in optoelectronic devices are highlighted. Finally, strategies towards the developments and practical perspectives of core/shell QDs are briefly mentioned to offer guidelines for achieving prospective high-efficiency and long-term stable QD devices.

关键词： stability. quantum mentioned

Observation of acoustic hybrid topological phases induced by the p-d orbital interactions

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science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 132-139页

作者： Xiao Xiang Feng Gao Yu-Gui Peng Peng Wu Zong-Lin Li Xue-Feng Zhu School of Physics and Innovation institute Huazhong University of Science and Technology

In spinless systems,growing attention has recently been attracted to synthetic gauge fields,which redefine the fundamental crystal symmetries by utilizing the projective algebraic ***,synthetic gauge fields have been commonly investigated in single orbital systems,and explorations on hybrid orbitals remain elusive in ***,we report the experimental observation of hybrid topological phases induced by hybrid synthetic gauge flux,which is formed by the interaction between p and d orbitals embedded in acoustic *** breaking the translation symmetries of Lxand/or Ly,we unambiguously demonstrate the first-order M?bius edge states and higher-order corner *** work establishes a platform for seeking exotic topological phases induced by hybrid-orbitals interactions and initializing the framework of hybrid-orbitalsrelated topological *** applications can be anticipated in scenarios such as high-quality sensing and robust wave trapping due to the stepwise energy distribution of the hybrid topological phase.

关键词： topological insulator synthetic gauge field projective symmetry corner states

Uncertainty measure in evidence theory

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science China(Information sciences) 2020年第11期63卷 5-23页

作者： Yong DENG School of Education Shannxi Normal University The institute of fundamental and frontier science University of Electronic Science and Technology of China

As an extension of probability theory, evidence theory is able to better handle unknown and imprecise information. Owing to its advantages, evidence theory has more flexibility and effectiveness for modeling and processing uncertain information. Uncertainty measure plays an essential role both in evidence theory and probability theory. In probability theory, Shannon entropy provides a novel perspective for measuring uncertainty. Various entropies exist for measuring the uncertainty of basic probability assignment(BPA) in evidence theory. However, from the standpoint of the requirements of uncertainty measurement and physics, these entropies are controversial. Therefore, the process for measuring BPA uncertainty currently remains an open issue in the literature. Firstly, this paper reviews the measures of uncertainty in evidence theory followed by an analysis of some related controversies. Secondly, we discuss the development of Deng entropy as an effective way to measure uncertainty, including introducing its definition, analyzing its properties, and comparing it to other measures. We also examine the concept of maximum Deng entropy, the pseudo-Pascal triangle of maximum Deng entropy, generalized belief entropy, and measures of divergence. In addition, we conduct an analysis of the application of Deng entropy and further examine the challenges for future studies on uncertainty measurement in evidence theory. Finally, a conclusion is provided to summarize this study.

关键词： evidence theory uncertainty measure Deng entropy Shannon entropy

A duplication-free quantum neural network for universal approximation

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science China(Physics,Mechanics & Astronomy) 2023年第7期66卷 2-16页

作者： Xiaokai Hou Guanyu Zhou Qingyu Li Shan Jin Xiaoting Wang institute of fundamental and frontier sciences University of Electronic Science and Technology of ChinaChengdu 610051China

Different from the concept of universal computation,the universality of a quantum neural network focuses on the ability to approximate arbitrary functions and is an important guarantee for ***,conventional approaches of constructing a universal quantum neural network may result in a huge quantum register that is challenging to implement due to noise on a near-term *** address this,we propose a simple design of a duplication-free quantum neural network whose universality can be rigorously ***,instead of using multiple duplicates of the quantum register,our method relies on a single quantum register combined with multiple activation functions to create nonlinearity and achieve ***,our proposal requires significantly fewer qubits with shallower circuits,and hence substantially reduces the resource overhead and the noise *** addition,simulations demonstrate that our universality design is able to achieve a better learning accuracy in the presence of noise,illustrating a great potential in solving larger-scale learning problems on near-term devices.

关键词： quantum computing quantum machine learning quantum neural network universality

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Engineering tantalum nitride for efficient photoelectrochemical water splitting

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science China Chemistry 2024年第7期67卷 2171-2180页

作者： Beibei Zhang Zeyu Fan Yanbo Li institute of fundamental and frontier sciences University of Electronic Science and Technology of ChinaChengdu 610054China

Photoelectrochemical(PEC)water splitting is a promising energy conversion strategy for directly converting solar energy into green hydrogen *** an efficient PEC device,finding an efficient photoanode material with a suitable band gap and favorable band-edge positions is *** nitride(Ta_(3)N_(5))meets these fundamental requirements,and its theoretical maximum solar-to-hydrogen(STH)conversion efficiency can reach 15.9%.Consequently,it has been widely applied as a photoanode material for the PEC oxygen evolution reaction(OER).However,severe bulk and interface charge recombination,along with sluggish water oxygen kinetics,seriously limits its STH conversion efficiency for PEC water ***,this feature article briefly reviews recent advances by our research group in improving the STH conversion efficiency of the Ta_(3)N_(5)photoanode using various strategies,including defect engineering,construction of a gradient band structure,interface engineering,and surface modification of self-healing OER *** to now,the obtained half-cell STH efficiency has exceeded 4%,providing a solid foundation for the development of tandem PEC devices for unbiased solar-driven overall water splitting toward practical application.

关键词： Photoelectrochemical water splitting tantalum nitride defect engineering interface engineering oxygen evolution cocatalyst

Perovskite Single Crystals: Synthesis, Properties, and Applications

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Journal of Electronic science and Technology 2021年第2期19卷 119-143页

作者： Shan-Shan Rong M.Bilal Faheem Yan-Bo Li institute of fundamental and frontier sciences University of Electronic Science and Technology of ChinaChengdu 610054

Perovskite single crystals have gained enormous attention in recent years due to their facile synthesis and excellent optoelectronic properties including the long carrier diffusion length,high carrier mobility,low trap density,and tunable absorption edge ranging from ultra-violet(UV)to near-infrared(NIR),which offer potential for applications in solar cells,photodetectors(PDs),lasers,*** this review,we summarized the synthesis,properties,and applications of organic-inorganic mixed and all-inorganic perovskite single crystals,particularly those through the solution synthesis *** towards the crystal growth and stability with future perspectives were also briefly described at the end of this paper.

关键词： Laser perovskite photodetector(PD) single crystal solar cell

Feature Selection for Multi-label Classification Using Neighborhood Preservation

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 320-330页

作者： Zhiling Cai William Zhu Laboratory of Granular Computing and AI Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China

Multi-label learning deals with data associated with a set of labels simultaneously. Dimensionality reduction is an important but challenging task in multi-label learning. Feature selection is an efficient technique for dimensionality reduction to search an optimal feature subset preserving the most relevant information. In this paper, we propose an effective feature evaluation criterion for multi-label feature selection, called neighborhood relationship preserving score. This criterion is inspired by similarity preservation, which is widely used in single-label feature selection. It evaluates each feature subset by measuring its capability in preserving neighborhood relationship among samples. Unlike similarity preservation, we address the order of sample similarities which can well express the neighborhood relationship among samples, not just the pairwise sample similarity. With this criterion, we also design one ranking algorithm and one greedy algorithm for feature selection problem. The proposed algorithms are validated in six publicly available data sets from machine learning repository. Experimental results demonstrate their superiorities over the compared state-of-the-art methods.

关键词： Feature selection multi-label learning neighborhood relationship preserving sample similarity