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The detection,extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 82-92页

作者： Qianyun Yun Wen-Biao Han Yi-Yang Guo He Wang minghui du Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310124China Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai 200030China School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 100049China Taiji Laboratory for Gravitational Wave Universe(Beijing/Hangzhou) University of Chinese Academy of SciencesBeijing 100049China Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu ProvinceKey Laboratory of Quantum Theory and Applications of MoELanzhou UniversityLanzhou 730000China Institute of Theoretical Physics&Research Center of Gravitation Lanzhou UniversityLanzhou 730000China International Centre for Theoretical Physics Asia-Pacific(ICTP-AP) University of Chinese Academy of Sciences(UCAS)Beijing 100049China Center for Gravitational Wave Experiment National Microgravity LaboratoryInstitute of MechanicsChinese Academy of SciencesBeijing 100190China

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EM-RIs).This task is particularly challenging because EMRI signals are complex,lengthy,and *** this work,we introduce a 2-layer convolutional neural network(CNN)approach to detect EMRI signals for space-borne detectors,achieving a true positive rate(TPR)of 96.9%at a 1%false positive rate(FPR)for signal-to-noise ratio(SNR)from 50 to ***,the key intrinsic parameters of EMRIs such as the mass,spin of the supermassive black hole(SMBH)and the initial eccentricity of the orbit can also be inferred directly by employing a neural *** mass and spin of the SMBH can be determined at 99%and 92%*** will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform *** study underscores the potential of deep learning methods in EMRI data analysis,enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

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How will our knowledge of short gamma-ray bursts affect the distance measurement of binary neutron stars?

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Science China(Physics,Mechanics & Astronomy) 2022年第1期65卷 103-118页

作者： minghui du Lixin Xu Institute of Theoretical Physics School of PhysicsDalian University of TechnologyDalian 116024China

Gravitational waves from binary neutron stars associated with short gamma-ray bursts have drawn considerable attention due to their prospect in *** such events,the sky locations of sources can be pinpointed with techniques such as identifying the host ***,the cosmological applications of these events still suffer from the problem of degeneracy between luminosity distance and inclination *** address this issue,a technique was proposed in previous study,i.e.,using the collimation property of short gamma-ray *** on the observations,we assume that the cosine of inclination follows a Gaussian distribution,which may act as a prior in the Bayes analysis to break the *** paper investigates the effects of different Gaussian priors and detector configurations on distance measurement and cosmological *** first derive a simplified Fisher information matrix for demonstration,and then conduct quantitative analyses via *** varying the number of third-generation detectors and the scale of prior,we generate four catalogs of 1000 *** is shown that,in the same detecting period,a network of detectors can recognize more and farther events than a single ***,adopting tighter prior and employing multiple detectors both decrease the error of luminosity *** considered is the performance of a widely adopted formula in the error budget,which turns out to be a conservative choice in each *** for cosmological applications,for theΛCDM model,500,200,600,and 300 events are required for the four configurations to achieve 1%H;*** all 1000 events in each catalog,H;and?;can be constrained to(0.66%,0.37%,0.76%,0.49%),and(0.010,0.006,0.013,0.010),*** results of the Gaussian process also show that the gravitational wave standard siren can serve as a probe of cosmology at high redshifts.

关键词： gravitational wave binary neutron star short gamma-ray burst cosmology

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SlBON1调控番茄植株营养生长机制的研究

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园艺学报 2025年第1期52卷 73-87页

作者：李芮王稳杜明辉刘根忠马方放包志龙山东农业大学园艺科学与工程学院作物生物学国家重点实验室山东泰安271018

BONZAI1(BON1)是高度保守的钙依赖膜结合蛋白Copine家族成员,具有调控生长发育的重要作用。番茄SlBON1与拟南芥BON1的蛋白序列相似度为66.84%。通过CRISPR-Cas9技术获得两个番茄SlBON1敲除突变体cr6和cr8,分别为61个碱基缺失突变和1个... 详细信息

BONZAI1(BON1)是高度保守的钙依赖膜结合蛋白Copine家族成员,具有调控生长发育的重要作用。番茄SlBON1与拟南芥BON1的蛋白序列相似度为66.84%。通过CRISPR-Cas9技术获得两个番茄SlBON1敲除突变体cr6和cr8,分别为61个碱基缺失突变和1个碱基插入突变。与野生型相比,SlBON1敲除突变体的地上和地下部生长均受到显著抑制,下胚轴中核内周期下降,叶片光合速率显著下降,淀粉含量升高。转录组分析显示SlBON1敲除突变体中激素信号转导信号通路、MAPK信号通路以及细胞周期的差异基因富集度较高。推测SlBON1通过调控植物激素代谢、细胞周期及光合作用等促进了番茄植株的营养生长。

关键词：番茄 SlBON1 敲除营养生长转录组分析

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A New Multi-Resource Allocation Mechanism： A Tradeoff between Fairness and Efficiency in Cloud Computing

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China Communications 2018年第3期15卷 57-77页

作者： Lihua Zhao minghui du Lin Chen School of Electronic and Information Engineering South China University of Technology Guangzhou 510641 China Lab. Recherche Informatique (LRI-CNRS UMR 8623)Univ. Paris-Sud Orsay 91405 France

This paper addresses multi-resource fair allocation: a fundamental research topic in cloud computing. To improve resource utilization under well-studied fairness constraints, we propose a new allocation mechanism called Dominant Resource with Bottlenecked Fairness(DRBF), which generalizes Bottleneck-aware Allocation(BAA) to the settings of Dominant Resource Fairness(DRF). We classify users into different queues by their dominant resources. The goals are to ensure that users in the same queue receive allocations in proportion to their fair shares while users in different queues receive allocations that maximize resource utilization subject to well-studied fairness properties such as those in DRF. Under DRBF, no user 1) is worse off sharing resources than dividing resources equally among all users; 2) prefers the allocation of another user; 3) can improve their own allocation without reducing other users' allocations; and(4) can benefit by misreporting their resource demands. Experiments demonstrate that the proposed allocation policy performs better in terms of high resource utilization than does DRF.

关键词： multi-resource fairness allocation cloud computing resource utilization

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Advancing space-based gravitational wave astronomy: Rapid parameter estimation via normalizing flows

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Science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 20-33页

作者： minghui du Bo Liang He Wang Peng Xu Ziren Luo Yueliang Wu Center for Gravitational Wave Experiment National Microgravity LaboratoryInstitute of MechanicsChinese Academy of SciencesBeijing 100190China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of SciencesShanghai 201800China International Centre for Theoretical Physics Asia-Pacific University of Chinese Academy of SciencesBeijing 100049China Taiji Laboratory for Gravitational Wave Universe(Beijing/Hangzhou) University of Chinese Academy of SciencesBeijing 100049China Lanzhou Center of Theoretical Physics Lanzhou UniversityLanzhou 730000China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310024China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China

Gravitational wave(GW) astronomy is witnessing a transformative shift from terrestrial to space-based detection, with missions like Taiji at the forefront. While the transition brings unprecedented opportunities for exploring massive black hole binaries(MBHBs), it also imposes complex challenges in data analysis, particularly in parameter estimation amidst confusion *** this gap, we utilize scalable normalizing flow models to achieve rapid and accurate inference within the Taiji environment. Innovatively, our approach simplifies the data's complexity, employs a transformation mapping to overcome the year-period time-dependent response function, and unveils additional multimodality in the arrival time parameter. Our method estimates MBHBs several orders of magnitude faster than conventional techniques, maintaining high accuracy even in complex backgrounds. These findings significantly enhance the efficiency of GW data analysis, paving the way for rapid detection and alerting systems and enriching our ability to explore the universe through space-based GW observation.

关键词： Taiji program gravitational wave detection parameter estimation machine learning

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Super‑elastic Scintillating Fibers and Fabrics for Efficient and Visual Radiation Detection

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Advanced Fiber Materials 2023年第4期5卷 1493-1504页

作者： minghui du Jin Wang Sijia Xu Hongwei Li Zhihao Zhang Yankun Qi Shichao Lv Jianrong Qiu Yurong Yan Shifeng Zhou State Key Laboratory of Luminescent Materials and Devices School of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510641China Institute of Photonics Technology Jinan UniversityGuangzhou 510632China National Engineering Research Center of Novel Equipment for Polymer Processing School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhou 510641China Key Lab Guangdong High Property&Functional Polymer Materials School of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510641China Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques Guangdong Engineering Technology Research and Development Center of Special Optical Fiber Materials and DevicesGuangzhou 510641China College of Optical Science and Engineering State Key Laboratory of Modern Optical InstrumentationZhejiang UniversityHangzhou 310027China

The fabrication of advanced radiation detectors is an important subject due to the wide use of radiation sources in scientific instruments,medical services,security check,non-destructive inspection,and nuclear ***,the manufacture of flexible and stretchable radiation detectors remains a ***,we report the scalable fabrication of super-elastic scintillating fibers and fabrics for visual radiation detection by thermal drawing and melt-spinning methods using styrene-b-(ethylene-co-butylene)-b-styrene,and scintillating Gd_(2)O_(2)S:Tb(GOS).Microstructure evolution,rheological properties,and radiation-composite interaction are studied to reveal the excellent processability,elasticity,and radiation detection ability of the fabricated *** from the physical crosslinking structural features of the polymer matrix and the excellent radiation absorption capacities of GOS,the resulting fiber can sustain high strains of 765%with a high content of GOS dopants(2 wt.%)and has excellent X-ray detection performance with the limit down to 53 nGy_(air)s^(-1).Furthermore,stretchable fabrics are constructed,and their applications in various fields,such as radiation warning,and X-ray imaging,are *** work not only provides a new type of super-elastic scintillating fibers and fabrics for smart textiles but also demonstrates their potential applications in the nuclear field.

关键词： Elastic fiber Radiation detection Optical materials X-ray imaging

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Carbon emissions in China’s steel industry from a life cycle perspective:Carbon footprint insights

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Journal of Environmental Sciences 2025年第2期148卷 650-664页

作者： Xiaocong Song Shuai du Chenning Deng Peng Shen minghui Xie Ci Zhao Chen Chen Xiaoyu Liu State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing 100012China Beijing Key Laboratory of Water Resources&Environmental Engineering China University of Geosciences(Beijing)Beijing 100083China Chinese Research Academy of Environmental Sciences Environmental Technology&Engineering Co.Ltd. Beijing 100012China

China is the most important steel producer in the world,and its steel industry is one of themost carbon-intensive industries in ***,research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development *** constructed a carbon dioxide(CO_(2))emission model for China’s iron and steel industry froma life cycle perspective,conducted an empirical analysis based on data from2019,and calculated the CO_(2)emissions of the industry throughout its life *** emission reduction factors were identified using sensitivity *** results demonstrated that the CO_(2)emission intensity of the steel industry was 2.33 ton CO_(2)/ton,and the production and manufacturing stages were the main sources of CO_(2)emissions,accounting for 89.84%of the total steel life-cycle ***,fossil fuel combustion had the highest sensitivity to steel CO_(2)emissions,with a sensitivity coefficient of 0.68,reducing the amount of fossil fuel combustion by 20%and carbon emissions by 13.60%.The sensitivities of power structure optimization and scrap consumption were similar,while that of the transportation structure adjustment was the lowest,with a sensitivity coefficient of less than *** the current strategic goals of peak carbon and carbon neutrality,it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies,increase the ratio of scrap steel to steelmaking,and build a new power system.

关键词： Iron and steel industry Life cycle Carbon dioxide(CO_(2))emissions Carbon footprint China

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Evaluating Facial Attractiveness： An Gabor Feature Approach

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通讯和计算机（中英文版） 2011年第8期8卷 674-679页

作者： Huiyun Mao Yili Chen Lianwen Jin minghui du School of Electronic and Information Engineering South China University of Technology Guangzhou 510640 China

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交联型特辛基酚醛树脂酚羟基间位的溴化改性

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化工进展 2022年第S01期41卷 382-388页

作者：刘大晨杜明慧王衡沈阳化工大学材料科学与工程学院辽宁沈阳110142 辽宁顺风新材料科技有限公司沈阳先进涂层材料产业技术研究院辽宁沈阳110031

以交联型特辛基酚醛树脂为原料进行改性,得到了一种交联型酚羟基间位溴化特辛基酚醛树脂,采用红外光谱(FTIR)、核磁碳谱(NMR)对树脂的结构进行了表征,结果表明成功地在酚羟基的间位上取代上了溴。采用莫尔法滴定反应测定剩余溴含量,计... 详细信息

以交联型特辛基酚醛树脂为原料进行改性,得到了一种交联型酚羟基间位溴化特辛基酚醛树脂,采用红外光谱(FTIR)、核磁碳谱(NMR)对树脂的结构进行了表征,结果表明成功地在酚羟基的间位上取代上了溴。采用莫尔法滴定反应测定剩余溴含量,计算得到苯环上的溴化率为84.7%。采用凝胶渗透色谱(GPC)对改性前后的酚醛树脂进行表征,结果表明经过溴化改性的酚醛树脂的数均分子量、重均分子量有所降低,分子量分布变窄。根据交联型特辛基酚醛树脂的交联机理,分别对交联型特辛基酚醛树脂、交联型链端溴化特辛基酚醛树脂树脂和交联型酚羟基间位溴化特辛基酚醛树脂交联橡胶的硫化历程和物理力学性能进行测试,结果表明改性后的酚羟基间位溴化特辛基酚醛树脂交联橡胶的硫化程度、硫化速度、力学性能都有明显提升。

关键词：交联型特辛基酚醛树脂酚羟基间位溴化交联机理力学性能

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小样本条件下采用Gabor特征的人脸识别

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计算机辅助设计与图形学学报 2005年第2期17卷 197-201页

作者：万峰杜明辉华南理工大学电子与通信工程系广州510640

人脸表征和特征提取是人脸识别中的关键问题针对Gabor特征的识别能力问题 ,利用点分布模型和类别可分离性判据研究了人脸不同位置和不同Gabor展开系数的分类能力实验结果表明 ,合理地构造Gabor特征和选择特征点位置 ,能够提高识别率... 详细信息

人脸表征和特征提取是人脸识别中的关键问题针对Gabor特征的识别能力问题 ,利用点分布模型和类别可分离性判据研究了人脸不同位置和不同Gabor展开系数的分类能力实验结果表明 ,合理地构造Gabor特征和选择特征点位置 ,能够提高识别率和减少特征数量在此基础上。

关键词：人脸识别 Gabor变换点分布模型主动形状模型

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