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Thickness dependence of superconductivity in layered GeP_(5)

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Rare Metals 2024年第3期43卷 1323-1328页

作者： Lin Wu Ke-Meng Yang Wei Gan Rui-Chun Xiao Ya-Jie Dai Xi Tang Hong Lin Hui Han Hui Li information Materials and intelligent Sensing Laboratory of Anhui Province Institute of Physical Science and Information TechnologyAnhui UniversityHefei230601China

Understanding the relationship between dimensionality and superconductivity has attracted substantial research *** this work,we report the effective modulation of superconductivity in GeP_(5)through *** superconducting phase transition temperature improves by~10%as the thickness of GeP_(5)decreases from bulk to~96 nm,behaving as a unique negative relationship between the superconducting phase transition temperatureand thickness.

关键词： superconductivity dimensionality

Adaptive interaction driven by the learning effect in the spatial prisoner's dilemma

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Chinese Physics B 2024年第3期33卷 160-169页

作者：李佳奇张建磊刘群 institute of intelligent information Hexi UniversityGansu 734000China College of Artificial Intelligence Nankai UniversityTianjin 300350China

We propose a computing model in which individuals can automatically adjust their interaction intensity with their mentor according to the learning *** model is designed to investigate the cooperative dynamics of the spatial prisoner's *** specifically,when the cumulative payoff of a learner is more than his reference earning,he will strengthen his interaction with his mentor;otherwise,he will reduce *** experimental results indicate that this mechanism can improve the emergence of cooperation in a networked population and that the driving coefficient of interaction intensity plays an important role in promoting ***,under a certain social dilemma condition,there exists a minimal driving coefficient that leads to optimal *** occurs due to a positive feedback effect between the individual's satisfaction frequency and the number of effective ***,we find that the experimental results are in accord with theoretical predictions obtained from an extension of the classical pair-approximation *** conclusions obtained by considering relationships with mentors can provide a new perspective for future investigations into the dynamics of evolutionary games within structured populations.

关键词： self-adapting interaction evolutionary game mentor spatial prisoner's dilemma

Multi-sensor multispectral reconstruction framework based on projection and reconstruction

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Science China(information Sciences) 2024年第3期67卷 246-262页

作者： Tianshuai LI Tianzhu LIU Xian LI Yanfeng GU Yukun WANG Yushi CHEN School of Electronics and information Engineering Harbin Institute of Technology Heilongjiang Province Key Laboratory of Space-Air-Ground Integrated intelligent Remote Sensing

The scarcity and low spatial resolution of hyperspectral images(HSIs) have become a major problem limiting the application of the images. In recent years, spectral reconstruction(SR) has been applied to convert multispectral images(MSIs) with abundant quantities and high spatial resolution into HSIs. With the launch of several new multispectral(MS) satellites with a short repeat period, the simultaneous acquisition of images from multiple MS sensors in the same area is gradually becoming feasible. Unfortunately, existing SR methods only consider the reconstruction of the MSIs of a single sensor without considering using MSIs from different MS sensors to obtain a better construction effect through their complementary bands. However,multi-sensor SR is characterized by two problems: inconsistency in the amplitude information of real multisensor imaging and difficulty in the extraction of the complex correlations of bands from different *** solve these problems, this paper proposes a multi-sensor SR framework based on a two-step approach in which the problems of amplitude inconsistency and band information extraction are solved using an ideal projection network and an ideal multi-sensor SR network, respectively. The effectiveness of the proposed method is verified by experiments on three datasets.

关键词： spectral reconstruction spectral superresolution hyperspectral image multispectral image neural networks multi-sensor

Learning Scalable Task Assignment with Imperative-Priori Conflict Resolution in Multi-UAV Adversarial Swarm Defense Problem

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Journal of Systems Science & Complexity 2024年第1期37卷 369-388页

作者： ZHAO Zhixin CHEN Jie XIN Bin LI Li JIAO Keming ZHENG Yifan School of Electronics and information Engineering Tongji UniversityShanghai 201804China Shanghai institute of intelligent Science and Technology Tongji UniversityShanghai 201804China School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous intelligent Unmanned Systems Beijing 100081China Shanghai institute of intelligent Science and Technology Tongji UniversityShanghai 201804China.

The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV *** the problem into task assignment and low-level interception strategies is a widely used ***-based approaches for task assignment are a promising *** studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict *** contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to *** achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is ***,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free ***,the IPCR mechanism is parallelized to enable efficient *** validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various *** experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.

关键词： Conflict resolution reinforcement learning scalability task assignment.

An anti-aliasing filtering of quantum images in spatial domain using a pyramid structure

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Chinese Physics B 2024年第5期33卷 223-237页

作者：吴凯周日贵罗佳 College of information Engineering Shanghai Maritime UniversityShanghai 201306China Research Center of intelligent information Processing and Quantum intelligent Computing Shanghai 201306China School of Mathematics and Computational Science Shangrao Normal UniversityShangrao 334001China

As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum ***-pass filtering can effectively achieve anti-aliasing effects on ***,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum *** paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial *** achieves the effect of anti-aliasing filtering on quantum images during the scaling ***,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical *** aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of ***,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing *** constructed pyramid model is then used to select an appropriate image for upscaling to the original image ***,the complexity of the circuit is *** to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer ***,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.

关键词： quantum color image processing anti-aliasing filtering algorithm quantum multiplier pyramid model

Model architecture level privacy leakage in neural networks

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Science China(information Sciences) 2024年第3期67卷 20-32页

作者： Yan LI Hongyang YAN Teng HUANG Zijie PAN Jiewei LAI Xiaoxue ZHANG Kongyang CHEN Jin LI institute of Artificial intelligent and Blockchain Guangzhou University Pazhou Lab

Privacy leakage is one of the most critical issues in machine learning and has attracted growing interest for tasks such as demonstrating potential threats in model attacks and creating model *** recent years, numerous studies have revealed various privacy leakage risks(e.g., data reconstruction attack, membership inference attack, backdoor attack, and adversarial attack) and several targeted defense approaches(e.g., data denoising, differential privacy, and data encryption). However, existing solutions generally focus on model parameter levels to disclose(or repair) privacy threats during the model training and/or model interference process, which are rarely applied at the model architecture level. Thus, in this paper, we aim to exploit the potential privacy leakage at the model architecture level through a pioneer study on neural architecture search(NAS) paradigms which serves as a powerful tool to automate a neural network *** investigating the NAS procedure, we discover two attack threats in the model architecture level called the architectural dataset reconstruction attack and the architectural membership inference attack. Our theoretical analysis and experimental evaluation reveal that an attacker may leverage the output architecture of an ongoing NAS paradigm to reconstruct its original training set, or accurately infer the memberships of its training set simply from the model architecture. In this work, we also propose several defense approaches related to these model architecture attacks. We hope our work can highlight the need for greater attention to privacy protection in model architecture levels(e.g., NAS paradigms).

关键词： neural architecture search data reconstruction attack membership inference attack

High synchronization absolute distance measurement using a heterodyne and superheterodyne combined interferometer

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Chinese Optics Letters 2024年第1期22卷 47-51页

作者：殷子淇李芳妃孙云科邹运王彦杨宏兴胡鹏程付海金谭久彬 Center of Ultra-precision Optoelectronic Instrument Harbin Institute of TechnologyHarbin 150080China Key Laboratory of Ultra-precision intelligent Instrumentation(Harbin institute of Technology) Ministry of Industry and Information TechnologyHarbin 150080China

We propose an absolute distance measurement method that employs heterodyne and superheterodyne combined interferometers to achieve synchronous detection and demodulation of *** and fine synthetic wavelengths are generated by a dual-longitudinal-mode He-Ne laser and four acoustic optical frequency ***,to improve phase synchronization measurement for multiwavelengths,we analyze the demodulation characteristics of coarse and fine measurement signals and adopt a demodulation method suitable for both *** results demonstrate that the proposed method can achieve high-precision synchronous demodulation of multiwavelengths,and standard deviation is 1.7×10^(-5)m in a range of 2 m.

关键词： multiwavelength absolute distance superheterodyne interferometry phase synchronization

Power output correction model of narrow linewidth ring fiber laser filtered with whispering gallery mode resonator

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Chinese Optics Letters 2024年第3期22卷 60-64页

作者：王子云徐在斌崔继文谭久彬 Center of Ultra-precision Optoelectronic Instrument Harbin Institute of TechnologyHarbin 150080China Key Laboratory of Ultra-precision intelligent Instrumentation Ministry of Industry and Information TechnologyHarbin Institute of TechnologyHarbin 150080China

A whispering gallery mode resonator(WGMR)filter can narrow laser linewidth while significantly changing the output power characteristics of fiber laser *** is found that traditional laser output power model is *** report a correction model of a narrow linewidth fiber laser filtered with a WGMR to analyze its *** believe that the loss of the laser system and the threshold gain increase caused by the WGMR filter lead to the predominate amplified spontaneous emission during the original laser *** to that,we assume the correction coefficient is an exponential decay related to the Er-doped fiber length in the large loss situation,and we verify it *** a result,the correction model is valid for WGMR-filtered fiber laser.

关键词： whispering gallery resonator filter narrow linewidth fiber laser power output correction model

CPT: a pre-trained unbalanced transformer for both Chinese language understanding and generation

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Science China(information Sciences) 2024年第5期67卷 43-55页

作者： Yunfan SHAO Zhichao GENG Yitao LIU Junqi DAI Hang YAN Fei YANG Zhe LI Hujun BAO Xipeng QIU School of Computer Science Fudan University Shanghai Key Laboratory of intelligent information Processing Fudan University Zhejiang Lab

In this paper, we take the advantage of previous pre-trained models(PTMs) and propose a novel Chinese pre-trained unbalanced transformer(CPT). Different from previous Chinese PTMs, CPT is designed to utilize the shared knowledge between natural language understanding(NLU) and natural language generation(NLG) to boost the performance. CPT consists of three parts: a shared encoder, an understanding decoder, and a generation decoder. Two specific decoders with a shared encoder are pretrained with masked language modeling(MLM) and denoising auto-encoding(DAE) tasks, *** the partially shared architecture and multi-task pre-training, CPT can(1) learn specific knowledge of both NLU or NLG tasks with two decoders and(2) be fine-tuned flexibly that fully exploits the potential of the model. Moreover, the unbalanced transformer saves the computational and storage cost, which makes CPT competitive and greatly accelerates the inference of text generation. Experimental results on a wide range of Chinese NLU and NLG tasks show the effectiveness of CPT.

关键词： pre-trained model transformer language model generation unified model