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A fully connected polarization-entangled network via integrated spontaneous four-wave mixing engineering

Science China(Physics,Mechanics & Astronomy) 2025年第6期Mechanics & Astronomy) .卷 76-83页

作者： Pingyu Zhu Yan Wang Yuxing Du Miaomiao Yu Kaikai Zhang Kun Wang Ping Xu Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology Hefei National Laboratory

Quantum communication is rapidly developing and is gradually being commercialized due to its technological maturity. Establishing dense communication links among multiple users in a scalable and efficient way is of great significance for realizing a large-scale quantum communication network. Here, we propose a novel scheme to construct a fully connected polarizationentangled network, utilizing the engineering of spontaneous four-wave mixings(SFWMs) and a path-polarization converter. It does not require active optical switches which limit the communication speed, or trusted nodes which lead to potential security risks. The required frequency channels in the network grow linearly with the number of users. We experimentally demonstrate a six-user fully connected network with on-chip SFWM processes motivated by four pumps. Each user in the network receives a frequency channel, and all fifteen connections between the users are implemented simultaneously. Our work opens up a promising scheme to efficiently construct fully connected large-scale networks.

关键词： quantum network quantum entanglement nonlinear optics integrated optics

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The quantum Ising model for perfect matching and solving it with variational quantum eigensolver

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Science China(Information Sciences) 2024年第9期67卷 306-320页

作者： Qilin ZHENG Pingyu ZHU Chao WU Miaomiao YU Weihong LUO Ping XU Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Hefei National Laboratory

Obtaining all perfect matchings of a graph is a tough problem in graph theory, and its complexity belongs to the #P-Complete class. The problem is closely related to combinatorics, marriage matching problems, dense subgraphs, the Gaussian boson sampling, chemical molecular structures, and dimer *** this paper, we propose a quadratic unconstrained binary optimization formula of the perfect matching problem and translate it into the quantum Ising model. We can obtain all perfect matchings by mapping them to the ground state of the quantum Ising Hamiltonian and solving it with the variational quantum eigensolver. Adjusting the model's parameters can also achieve the maximum or minimum weighted perfect matching. The experimental results on a superconducting quantum computer of the Origin Quantum computing technology Company show that our model can encode 2~n dimensional optimization space with only O（n） qubits consumption and achieve a high success probability of the ground state corresponding to all perfect matchings. In addition, the further simulation results show that the model can support a scale of more than 14 qubits, effectively resist the adverse effects of noise, and obtain a high success probability at a shallow variational depth. This method can be extended to other combinatorial optimization problems.

关键词： perfect matching Ising model quantum Hamiltonian variational quantum eigensolver quadratic unconstrained binary optimization

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Four-wave mixing Bragg scattering for small frequency shift from silicon coupled microrings

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Chinese Physics B 2025年第1期34卷 351-355页

作者： Chang Zhao Chao Wu Pingyu Zhu Yuxing Du Yan Wang Miaomiao Yu Kaikai Zhang Ping Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China

Frequency conversion is pivotal in nonlinear optics and quantum optics for manipulating and translating light signals across different wavelength *** frequency conversion between two light beams with a small frequency interval is a central *** this work,we design a pair of coupled silicon microrings wherein coupled-induced modesplitting exists to achieve a small frequency shift by the process of four-wave mixing Bragg *** an example,the signal can be up or down converted to the idler which is 15.5 GHz spaced when two pumps align with another pair of split *** results unveil the potential of coupled microring resonators for small interval frequency conversion in a high-fidelity,all-optical,and signal processing quantum frequency interface.

关键词： four-wave mixing Bragg scattering silicon coupled microrings

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On-chip quantum NOON state sensing for temperature and humidity

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Chinese Physics B 2024年第10期33卷 15-20页

作者： Weihong Luo Chao Wu Yuxing Du Chang Zhao Miaomiao Yu Pingyu Zhu Kaikai Zhang Ping Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China

A maximal photon number entangled state,namely NOON state,can be adopted for sensing with a quantum *** this work,we designed silicon quantum photonic chips containing two types of Mach-Zehnder interferometerswherein the two-photon NOON state,sensing element for temperature or humidity,is *** with classicallight or single photon case,two-photon NOON state sensing shows a solid enhancement in the sensing resolution *** the first demonstration of on-chip quantum photonic sensing,it reveals the advantages of photonic chips forhigh integration density,small-size,stability for multiple-parameter sensing serviceability.A higher sensing precision isexpected to beat the standard quantum limit with a higher photon number NOON state.

关键词： quantum sensing NOON state photonic chip

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Solving the subset sum problem by the quantum Ising model with variational quantum optimization based on conditional values at risk

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 43-55页

作者： Qilin Zheng Miaomiao Yu Pingyu Zhu Yan Wang Weihong Luo Ping Xu Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China Hefei National Laboratory Hefei 230088China

The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)*** problem is widely used in encryption,planning or scheduling,and integer *** accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical *** effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at *** proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum *** model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum *** investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the ***,we also discuss the performance of the model under different conditional values at *** computer simulation,the scale can reach more than nine *** selecting the noise type,we construct simulators with different QVs and study the performance of the model with *** addition,we deploy the model on a superconducting quantum computer of the Origin Quantum technology Company and successfully solve the subset sum *** model provides a new perspective for solving the subset sum problem.

关键词： subset sum problem quantum Ising model conditional values at risk variational quantum optimization

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An accurate and efficient space-time Galerkin spectral method for the subdiffusion equation

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Science China Mathematics 2024年第10期67卷 2387-2408页

作者： Wei Zeng Chuanju Xu School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing Xiamen UniversityXiamen 361005China

In this paper, we design and analyze a space-time spectral method for the subdiffusion ***, we are facing two difficulties. The first is that the solutions of this equation are usually singular near the initial time. Consequently, traditional high-order numerical methods in time are inefficient. The second obstacle is that the resulting system of the space-time spectral approach is usually large and time-consuming to solve. We aim at overcoming the first difficulty by proposing a novel approach in time, which is based on variable transformation techniques. Suitable ψ-fractional Sobolev spaces and a new variational framework are introduced to establish the well-posedness of the associated variational problem. This allows us to construct our space-time spectral method using a combination of temporal generalized Jacobi polynomials(GJPs) and spatial Legendre polynomials. For the second difficulty, we propose a fast algorithm to effectively solve the resulting linear system. The fast algorithm makes use of a matrix diagonalization in space and QZ decomposition in time. Our analysis and numerical experiments show that the proposed method is exponentially convergent with respect to the polynomial degrees in both space and time directions, even though the exact solution has very limited regularity.

关键词： subdiffusion equations variable transformation Ψ-Sobolev spaces well-posedness space-time Galerkin spectral method error estimate fast algorithm

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HeFormer: A Lightweight Transformer Combining Hash Estimation for Link Prediction 27th

HeFormer: A Lightweight Transformer Combining Hash Estimatio...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Sun, Teng Xiao, Xiaoqiang Zhang, Xu Ning, Weixun School of Computer National University of Defense Technology Changsha China State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9783031783944

Link Prediction(LP) is a fundamental problem in graph machine learning that aims to predict the existence of links between nodes. Most current research on LP adopts Graph Neural Networks (GNNs) to learn the representation of subgraphs, but fails to efficiently capture global topological information in large graphs. In response to this issue, we focus on the global attention mechanism of Transformers. Nevertheless, original Transformers are not inherently suitable for learning graph-structured data, and their deep multi-head attention architecture has been limited by prohibitive compute and memory costs. In this work, we propose a lightweight model: a single-layer, single-head Transformer, which constructs subgraph structural features based on hash estimation. It provides a new perspective for applying Transformers in graph-structured data processing. Firstly, we utilize MinHash and HyperLogLog techniques to estimate the structural information of subgraphs, then fuse subgraph structural features with node features to achieve efficient message passing. In this case, our model does not need to extract or manipulate enclosed subgraphs, and structural features can be preprocessed. Additionally, we design a single-layer, single-head Transformer as the encoder for graph-structured data, utilizing the attention mechanism to capture global effects. Meanwhile, our model does not require extra positional encoding, which significantly reduce computational complexity. Extensive experiments demonstrate that our model achieves optimal prediction accuracy on large-scale datasets with high efficiency. The code is available at https://***/sunteng6/HeFormer. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Graph neural networks

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Simulating a Chern Insulator with C=±2 on Synthetic Floquet Lattice

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Chinese Physics Letters 2024年第9期41卷 1-8页

作者： Ling-Xiao Lei Wei-Chen Wang Guang-Yao Huang Shun Hu Xi Cao Xin-Fang Zhang Ming-Tang Deng Ping-Xing Chen Institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangsha 410073China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China Greatwall Quantum Laboratory Changsha 410006China Hefei National Laboratory Hefei 230088China

The synthetic Floquet lattice,generated by multiple strong drives with mutually incommensurate frequencies,provides a powerful platform for quantum simulation of topological *** this study,we propose a 4-band tight-binding model of the Chern insulator with a Chern number C=±2 by coupling two layers of the half Bernevig–Hughes–Zhang lattice and subsequently mapping it onto the Floquet lattice to simulate its topological *** determine the Chern number of our Floquet-version model,we extend the energy pumping method proposed by Martin et al.[2017 ***.X 7041008]and the topological oscillation method introduced by Boyers et al.[2020 ***.125160505],followed by numerical simulations for both *** simulation results demonstrate the successful extraction of the Chern number using either of these methods,providing an excellent prediction of the phase diagram that closely aligns with the theoretical one derived from the original bilayer half Bernevig–Hughes–Zhang ***,we briefly discuss a potential experimental implementation for our *** work demonstrates significant potential for simulating complex topological matter using quantum computing platforms,thereby paving the way for constructing a more universal simulator for non-interacting topological quantum states and advancing our understanding of these intriguing phenomena.

关键词： properties topological quantum

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Person Re-Identification Based on Multi-Spectrum Information Aggregation Transformers 8

Person Re-Identification Based on Multi-Spectrum Information...

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8th International Conference on Image, Vision and computing, ICIVC 2023

作者： Zhang, Yuxuan Tan, Huibin Lan, Long Ren, Jing Teng, Xiao National University of Defense Technology State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9798350335231

Convolutional Neural Networks (CNNs) have achieved remarkable success in various image-related tasks. However, CNNs' chunking approach of sliding windows over pixels hinders its ability to learn sequential semantic information. To address this issue, researchers have proposed models that integrate Transformers to aggregate features across different resolutions, taking advantage of the Transformer's strengths. Hierarchical Aggregation Transformer (HAT) is one such model that integrates low-level and high-level details, showing a great effect on person re-identification. Based on HAT, we propose the Multi-Spectrum Information Aggregation Transformers (MIAT), which enhances the low-level structural information captured by CNNs through a frequency channel attention module that extracts multi-spectral features. By leveraging discrete cosine transform (DCT), more detailed features can be learned to improve person re-identification, enabling better discernment of distinguishing features between different individuals. Through extensive experimentation, we validate our model's performance on two widely employed person re-identification datasets and demonstrate its superiority over existing advanced methods. © 2023 IEEE.

关键词： Discrete cosine transforms

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Boosting the dimensionality of frequency entanglement using a reconfigurable microring resonator

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Science China(Physics,Mechanics & Astronomy) 2023年第5期66卷 79-88页

作者： Chao Wu Qilin Zheng Yingwen Liu Yang Wang Jiangfang Ding Pingyu Zhu Shichuan Xue Miaomiao Yu Weihong Luo Kaikai Zhang Anqi Huang Mingtang Deng Junjie Wu Ping Xu Institute for Quantum Information State Key Laboratory of High Performance ComputingCollege of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China National Laboratory of Solid State Microstructures School of PhysicsNanjing UniversityNanjing 210093China

Integrated quantum frequency combs(QFCs)based on microring resonators supplies as an essential resource for expanding the Hilbert-space dimensionality for high-dimensional quantum computing and information *** this work,we propose and demonstrate a reconfigurable ring resonator with tunable quality factors to efficiently increase the dimensionality of frequency entanglement,simultaneously,ensuring a high on-chip pair generation rate(PGR)and coincidence-to-accidental ratio(CAR).Our method exploits the asymmetric Mach-Zehnder interferometer instead of the traditional straight waveguide as the coupler of resonators which offer a tunable external coupling coefficient to modulate the quality factor to enlarge the QFCs’bandwidth and thus increase the dimensionality of frequency *** measured the QFCs’joint spectral intensity of 28 frequency pairs under various quality factors ranging from 16.6×10^(4) to 3.4×10^(4).Meanwhile,the measured Schmidt number increased from 11.01 to 24.77,denoting a huge expansion of the Hilbert-space dimensionality from 121 to a record number of 613 dimensions,which agrees well with our theoretical *** addition,the PGR and CAR-another two key parameters for high-quality QFCs-were all measured under different quality factors to verify that our method can significantly increase the Schmidt number and CAR while maintaining a high *** fact,bright QFCs with a total PGR of 4.3 MHz under a 0.48 mW pump power and a mean CAR of 1578 were simultaneously obtained at the highest Schmidt *** method is widely applicable to other material-based ring resonators and can act as a general solution for high-dimensional QFCs.

关键词： reconfigurable resonator quantum frequency comb Hilbert-space dimensionality

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