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arXiv 2024年

作者： Chen, Wei-Kun Liu, Ya-Feng Dai, Yu-Hong Luo, Zhi-Quan The School of Mathematics and Statistics Beijing Key Laboratory on MCAACI Beijing Institute of Technology Beijing100081 China The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China

In this paper, we consider the network slicing (NS) problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and manage network resources to meet diverse quality of service (QoS) requirements. We propose a mixed-integer nonlinear programming (MINLP) formulation for the considered NS problem that can flexibly route the traffic flow of the services on multiple paths and provide end-to-end delay and reliability guarantees for all services. To overcome the computational difficulty due to the intrinsic nonlinearity in the MINLP formulation, we transform the MINLP formulation into an equivalent mixed-integer linear programming (MILP) formulation and further show that their continuous relaxations are equivalent. In sharp contrast to the continuous relaxation of the MINLP formulation which is a nonconvex nonlinear programming problem, the continuous relaxation of the MILP formulation is a polynomial-time solvable linear programming problem, which significantly facilitates the algorithmic design. Based on the newly proposed MILP formulation, we develop a customized column generation (cCG) algorithm for solving the NS problem. The proposed cCG algorithm is a decomposition-based algorithm and is particularly suitable for solving large-scale NS problems. Numerical results demonstrate the efficacy of the proposed formulations and the proposed cCG algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Mixed-integer linear programming

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Asymptotic SEP Analysis and Optimization of Linear-Quantized Precoding in Massive MIMO Systems

arXiv

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arXiv 2023年

作者： Wu, Zheyu Ma, Junjie Liu, Ya-Feng Swindlehurst, A. Lee The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Center for Pervasive Communications and Computing University of California IrvineCA92697 United States

A promising approach to deal with the high hardware cost and energy consumption of massive MIMO transmitters is to use low-resolution digital-to-analog converters (DACs) at each antenna element. This leads to a transmission scheme where the transmitted signals are restricted to a finite set of voltage levels. This paper is concerned with the analysis and optimization of a low-cost quantized precoding strategy, referred to as linear-quantized precoding, for a downlink massive MIMO system under Rayleigh fading. In linear-quantized precoding, the signals are first processed by a linear precoding matrix and subsequently quantized component-wise by the DAC. In this paper, we analyze both the signal-to-interference-plus-noise ratio (SINR) and the symbol error probability (SEP) performances of such linear-quantized precoding schemes in an asymptotic framework where the number of transmit antennas and the number of users grow large with a fixed ratio. Our results provide a rigorous justification for the heuristic arguments based on the Bussgang decomposition that are commonly used in prior works. Based on the asymptotic analysis, we further derive the optimal precoder within a class of linear-quantized precoders that includes several popular precoders as special cases. Our numerical results demonstrate the excellent accuracy of the asymptotic analysis for finite systems and the optimality of the derived precoder. Copyright © 2023, The Authors. All rights reserved.

关键词： MIMO systems

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Riemannian Optimization for Holevo Capacity

arXiv

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arXiv 2025年

作者： Zhu, Chengkai Peng, Renfeng Gao, Bin Wang, Xin Guangzhou China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

computing the classical capacity of a noisy quantum channel is crucial for understanding the limits of communication over quantum channels. However, its evaluation remains challenging due to the difficulty of computing the Holevo capacity and the even greater difficulty of regularization. In this work, we formulate the computation of the Holevo capacity as an optimization problem on a product manifold constructed from probability distributions and their corresponding pure input states for a quantum channel. A Riemannian gradient descent algorithm is proposed to solve the problem, providing lower bounds on the classical capacity of general quantum channels and outperforming existing methods in numerical experiments in both efficiency and scale. © 2025, CC BY.

关键词： Probability distributions

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Plasmon resonance-enhanced graphene nanofilmbased dual-band infrared silicon photodetector

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Photonics Research 2023年第10期11卷 1657-1666页

作者： XINYU LIU SHAOXIONG WU XIAOXUE CAO FENG TIAN SRIKRISHNA CHANAKYA BODEPUDI MUHAMMAD MALIK CHAO GAO LI PENG HUAN HU YANG XU School of Micro-Nano Electronics ZJU-Hangzhou Global Scientific and Technological Innovation CenterState Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang UniversityHangzhou 310027China ZJU-UIUC Institute International CampusZhejiang UniversityHaining 314400China Department of Polymer Science and Engineering MOE Key Laboratory of Macromolecular Synthesis and FunctionalizationKey Laboratory of Adsorption and Separation Materials&Technologies of Zhejiang ProvinceZhejiang UniversityHangzhou 310027China

Graphene-based photodetectors have attracted much attention due to their unique properties,such as high-speed and wide-band detection ***,they suffer from very low external quantum efficiency in the infrared(IR)region and lack spectral ***,we construct a plasmon-enhanced macro-assembled graphene nanofilm(nMAG)based dual-band infrared silicon *** Au plasmonic nanostructures improve the absorption of long-wavelength photons with energy levels below the Schottky barrier(between metal and Si)and enhance the interface transport of *** with the strong photo-thermionic emission(PTI)effect of nMAG,the n MAG–Au–Si heterojunctions show strong dual-band detection capability with responsivities of52.9 mA/W at 1342 nm and 10.72 mA/W at 1850 nm,outperforming IR detectors without plasmonic nanostructures by 58–4562 *** synergy between plasmon–exciton resonance enhancement and the PTI effect opens a new avenue for invisible light detection.

关键词： resonance band dual

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Emerging Clusteroluminescence from Complexes between Carbonyl-Based Polymers and Organic Base

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Chinese Journal of Chemistry 2023年第22期41卷 3012-3018页

作者： Hongwei Lu Yuan Xie Ziteng Zhang Zhiming Zhang Jing ZhiSun Haoke Zhang Ben Zhong Tang MOE Key Laboratory of Macromolecular Synthesis and Function alization Department of Polymer Science and EngineeringZhejiang UniversityHangzhouZhejiang 310058China Zhejiang-srael Joint Laboratory of Self-Assembling Functional Materials ZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiangUniversityHangzhouZhejiang311215China Centreof HealthcareMaterials ShaoxingInstituteZhejiangUniversityShaoxingZhejiang312000China Centerfor AlE Research College of Materials Science and EngineeringShenzhen UniversityShenzhenGuangdong 518061China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)ShenzhenGuangdong518172China

The study of luminescence phenomena in non-conjugated systems,namely clusteroluminescence,has gained significant attention for the development of advanced luminescent *** conventional strategies to manipulate the luminescent performances are based on complicated chemical *** contrast,nature employs complexation to modulate luminescence,inspiring researchers to adopt an engineering approach for the construction of efficient *** this work,we explore the complexationinduced clusteroluminescence of carbonyl-based polymers with nitrogen-containing organic bases,exemplified by polyamide,polyester,polycarbonate,and poly(monothiocarbonate).

关键词： Clusteroluminescence Carbonyl-based polymers Through-space interactions Fluorescence Functional polymers

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Tuning 2D magnetism in Fe3+XGeTe2 films by element doping

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National Science Review 2022年第6期9卷 163-170页

作者： Shanshan Liu Zihan Li Ke Yang Enze Zhang Awadhesh Narayan Xiaoqian Zhang Jiayi Zhu Wenqing Liu Zhiming Liao Masaki Kudo Takaaki Toriyama Yunkun Yang Qiang Li Linfeng Ai Ce Huang Jiabao Sun Xiaojiao Guo Wenzhong Bao Qingsong Deng Yanhui Chen Lifeng Yin Jian Shen Xiaodong Han Syo Matsumura Jin Zou Yongbing Xu Xiaodong Xu Hua Wu Faxian Xiu State Key Laboratory of Surface Physics and Department of Physics Fudan University Institute for Nanoelectronic Devices and Quantum Computing Fudan University College of Science University of Shanghai for Science and Technology Laboratory for Computational Physical Sciences(MOE) Fudan University Solid State and Structural Chemistry Unit Indian Institute of Science School of Electronic Science and Engineering Nanjing University Department of Physics University of Washington Department of Electronic Engineering Royal Holloway University of London Materials Engineering The University of Queensland Beijing Key Laboratory of Microstructure and Property of Advanced Materials Institute of Microstructure and Property of Advanced Materials Beijing University of Technology The Ultramicroscopy Research Center Kyushu University State Key Laboratory of ASIC and System School of Microelectronics Fudan University Collaborative Innovation Center of Advanced Microstructures Department of Applied Quantum Physics and Nuclear Engineering Kyushu University Centre for Microscopy and Microanalysis The University of Queensland Shanghai Research Center for Quantum Sciences

Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enables a boosted Curie temperature（TC） or phase transitions. One of the challenges, however, is the realization of high TC2D magnets that are tunable, robust and suitable for large scale fabrication. Here, we report molecular-beam epitaxy growth of wafer-scale Fe3+XGeTe2films with TCabove room temperature. By controlling the Fe composition in Fe3+XGeTe2, a continuously modulated TCin a broad range of 185–320 K has been achieved. This widely tunable TCis attributed to the doped interlayer Fe that provides a 40% enhancement around the optimal composition X = 2. We further fabricated magnetic tunneling junction device arrays that exhibit clear tunneling signals. Our results show an effective and reliable approach, i.e. element doping, to producing robust and tunable ferromagnetism beyond room temperature in a large-scale 2D Fe3+XGeTe2fashion.

关键词： 2D ferromagnetic material Fe3+XGeTe2 film element doping above room temperature TC tunability

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Covariance-Based Device Activity Detection with Massive MIMO for Near-Field Correlated Channels

arXiv

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arXiv 2024年

作者： Wang, Ziyue Li, Yang Liu, Ya-Feng Ma, Junjie The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Shenzhen Research Institute of Big Data Shenzhen518172 China The School of Science and Engineering The Chinese University of Hong Kong Shenzhen518172 China

This paper studies the device activity detection problem in a massive multiple-input multiple-output (MIMO) system for near-field communications (NFC). In this system, active devices transmit their signature sequences to the base station (BS), which detects the active devices based on the received signal. In this paper, we model the near-field channels as correlated Rician fading channels and formulate the device activity detection problem as a maximum likelihood estimation (MLE) problem. Compared to the traditional uncorrelated channel model, the correlation of channels complicates both algorithm design and theoretical analysis of the MLE problem. On the algorithmic side, we propose two computationally efficient algorithms for solving the MLE problem: an exact coordinate descent (CD) algorithm and an inexact CD algorithm. The exact CD algorithm solves the one-dimensional optimization subproblem exactly using matrix eigenvalue decomposition and polynomial root-finding. By approximating the objective function appropriately, the inexact CD algorithm solves the one-dimensional optimization subproblem inexactly with lower complexity and more robust numerical performance. Additionally, we analyze the detection performance of the MLE problem under correlated channels by comparing it with the case of uncorrelated channels. The analysis shows that when the overall number of devices N is large or the signature sequence length L is small, the detection performance of MLE under correlated channels tends to be better than that under uncorrelated channels. Conversely, when N is small or L is large, MLE performs better under uncorrelated channels than under correlated ones. Simulation results demonstrate the computational efficiency of the proposed algorithms and verify the correctness of the analysis. Copyright © 2024, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Dendritic Integration Inspired Artificial Neural Networks Capture Data Correlation 38

Dendritic Integration Inspired Artificial Neural Networks Ca...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Liu, Chongming Ma, Jingyang Li, Songting Zhou, Douglas School of Mathematical Sciences Shanghai Jiao Tong University Shanghai China Institute of Natural Sciences Shanghai Jiao Tong University Shanghai China Ministry of Education Key Laboratory of Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai China Shanghai Frontier Science Center of Modern Analysis Shanghai Jiao Tong University Shanghai China

Incorporating biological neuronal properties into Artificial Neural Networks (ANNs) to enhance computational capabilities is under active investigation in the field of deep learning. Inspired by recent findings indicating that dendrites adhere to quadratic integration rule for synaptic inputs, this study explores the computational benefits of quadratic neurons. We theoretically demonstrate that quadratic neurons inherently capture correlation within structured data, a feature that grants them superior generalization abilities over traditional neurons. This is substantiated by few-shot learning experiments. Furthermore, we integrate the quadratic rule into Convolutional Neural Networks (CNNs) using a biologically plausible approach, resulting in innovative architectures-Dendritic integration inspired CNNs (Dit-CNNs). Our Dit-CNNs compete favorably with state-of-the-art models across multiple classification benchmarks, e.g., ImageNet-1K, while retaining the simplicity and efficiency of traditional CNNs. All source code are available at https://***/liuchongming1999/Dendritic-integration-inspired-CNN-NeurIPS-2024. © 2024 Neural information processing systems foundation. All rights reserved.

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Genetic and phenotypic relationships between coronary atherosclerotic heart disease and electrocardiographic traits

Genetic and phenotypic relationships between coronary athero...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Wang, Xinfeng Zhang, Haoyang Xiu, Xuehao Qi, Mengling Yang, Yuedong Zhao, Huiying Sun Yat-sen University Key Laboratory of Machine Intelligence and Advanced Computing of Moe School of Computer Science and Engineering Guangzhou China Sun Yat-sen Memorial Hospital Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Department of Medical Research Center Guangzhou China

ISBN: (纸本)9781665468190

Observational studies have revealed that Coronary Atherosclerotic Heart Disease (CAHD) is associated with abnormal electrocardiogram (ECG) traits. However, it remains unclear whether there are genetic correlations between ECG and CAHD. Here, we explored genetic correlations and putative causal relationships between CAHD and ECG by performing Mendelian randomization (MR) and Polygenic risk score (PRS) analyses on the summary statistics from a large-scale genome-wide association study (GWAS) for CAHD (FinnGen: Ncase 23363, Ncontrol 187840) and ECG traits (UK Biobank: Ncase=1137, Ncontrol=40823). Results showed a causal genetic relationship between CAHD and six ECG traits in the lead V6. These ECG traits combining with age and gender have predicted CAHD risk with an AUC of 0.76. Further summary data-based Mendelian randomization (SMR) analysis identified 11 risk genes associated with the causality between CAHD and ECG. Thus, the revealed putative causal effects of CAHD on ECG traits provide genetic evidence to support the importance of monitoring CAHD risk through the ECG. © 2022 IEEE.

关键词： Electrocardiograms

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Projected gradient descent algorithm for ab initio crystal structure relaxation under a fixed unit cell volume

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Physical Review B 2024年第22期109卷 224108-224108页

作者： Yukuan Hu Junlei Yin Xingyu Gao Xin Liu Haifeng Song Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences Innovation Center NPU Chongqing Chongqing 401135 China National Key Laboratory of Computational Physics

This paper is concerned with ab initio crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and forms the basis of thermodynamic property calculations for materials. The task can be formulated as an energy minimization with a determinant constraint. Widely used line minimization-based methods (e.g., conjugate gradient method) lack both efficiency and convergence guarantees due to the nonconvex nature of the determinant constraint as well as the significant differences in the curvatures of the potential energy surface with respect to atomic and lattice components. To this end, we propose a projected gradient descent algorithm named PANBB. It is equipped with (i) search direction projections for lattice vectors, (ii) distinct curvature-aware initial trial step sizes for atomic and lattice updates, and (iii) a nonrestrictive line minimization criterion as the stopping rule for the inner loop. It can be proved that PANBB favors theoretical convergence to equilibrium states. Across a benchmark set containing 223 structures from various categories, PANBB achieves average speedup factors of approximately 1.41 and 1.45 over the conjugate gradient method and direct inversion in the iterative subspace implemented in off-the-shelf simulation software, respectively. Moreover, it normally converges on all the systems, manifesting its robustness. As an application, we calculate the static equations of state for the high-entropy alloy AlCoCrFeNi, which remains elusive owing to 160 atoms representing both chemical and magnetic disorder and the strong local lattice distortion. The results are consistent with the previous calculations and are further validated by experimental thermodynamic data.

关键词： Crystal structure Structural properties Density functional theory

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