检索结果-内蒙古大学图书馆

A comparative study on different background estimation methods for extensive air shower arrays

学校读者我要写书评

暂无评论

A comparative study on different background estimation metho...

作者： Wang, Yan-Jin Zha, Min Hu, Shi-Cong Gao, Chuan-Dong Zhang, Jian-Li Zhang, Xin College of Sciences Northeastern University Shenyang110819 China Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Institute of Frontier and Interdisciplinary Science Shandong University Qingdao266237 China University of Chinese Academy of Sciences Beijing10049 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang110819 China National AFrontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

Background estimation is essential when studying TeV γ-ray astronomy for extensive air shower arrays. In this work, by applying four different methods including equi-zenith angle method, surrounding window method, direct integration method, and time-swapping method, the number of the background events is calculated. Based on simulation samples, the statistical significance of the excess signal from different background estimation methods is determined. Following this, we discuss the limitations and the applicability of the four methods under different conditions. Under the detector stability assumption with signals, the results from the above four methods are consistent at the 1σ level. In the no signal condition, when the acceptance of the detector changes with both space and time, the surrounding window method is the most stable and hardly affected. In this acceptance assumption, we find that the background estimation in the direct integration and time-swapping methods are sensitive to the selection of time window, and the shorter time window can reduce the impact on the background estimation to some extent. © 2022 IOP Publishing Ltd and Sissa Medialab.

关键词： Gamma rays

Cosmological Parameter Estimation Using Current and Future Observations of Strong Gravitational Lensing

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Qi, Jing-Zhao Hu, Wei-Hong Cui, Yu Zhang, Jing-Fei Zhang, Xin Department of Physics College of Sciences Northeastern University Shenyang110819 China Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry [Northeastern University Ministry of Education China

Remarkable development of cosmology is benefited from the increasingly improved measurements of cosmic distances including absolute distances and relative distances. In recent years, however, the emerged cosmological tensions motivate us to explore the independent and precise late-universe probes. The two observational effects of strong gravitational lensing (SGL), the velocity dispersions of lens galaxies and the time delays between multiple images, can provide measurements of relative and absolute distances respectively, and their combination is possible to break the degeneracies between cosmological parameters and enable tight constraints on cosmological parameters. In this paper, we combine the observed 130 SGL systems with velocity-dispersion measurements and 7 SGL systems with time-delay measurements to constrain dark-energy cosmological models. It is found that the combination of the two effects does not significantly break the degeneracies between cosmological parameters as expected. However, with the simulations of 8000 SGL systems with well-measured velocity dispersions and 55 SGL systems with well-measured time delays based on the forthcoming LSST survey, we find that the combination of two effects can significantly break the parameter degeneracies, and make the constraint precision of cosmological parameters meet the standard of precision cosmology. We conclude that the observations of SGL will become a useful late-universe probe for precisely measuring cosmological parameters. © 2022, CC BY.

关键词： Timing circuits

How to Perform Energy-Balanced Underwater data Collection in AUV-Aided UASNs: A Social Welfare-Based Node Clustering Approach

学校读者我要写书评

暂无评论

IEEE Transactions on Computational Social Systems 2024年

作者： Lin, Chuan Han, Guangjie Lu, Chang Hussain Shah, Syed Bilal Zhang, Yu Wang, Feng Northeastern University Software College Shenyang110819 China Hohai University Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Nanjing210013 China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education Nanjing210013 China Dalian University of Technology School of Software Dalian116024 China Dar Al-Hekma University School of Engineering Computing and Informatics Jeddah21589 Saudi Arabia Suzhou Vocational University School of Engineering Suzhou215004 China

The rapid evolution of the Internet of Underwater Things (IoUT) has led to the widespread adoption of autonomous underwater vehicle (AUV)-assisted underwater acoustic sensor networks (UASNs) for various applications such as marine environment monitoring and resource exploration. This article introduces an energy-balanced data collection scheme tailored for AUV-supported UASNs. The proposed scheme combines a node clustering method based on a social welfare function and an intelligent path planning strategy for the AUV. The node clustering approach integrates canopy and K-means algorithms for initial node clustering, followed by reclustering using an enhanced hierarchical clustering algorithm. To balance energy distribution, Atkinson's social welfare function is employed to select and rotate cluster heads (CHs) within each cluster. To address limited CH memory constraints, a lossless compression technique is introduced to reduce data storage requirements at the CHs. Moreover, the article introduces the use of the deep Q-network (DQN) technique for AUV path planning, considering multiple pertinent factors simultaneously. Simulation results demonstrate that the proposed data collection scheme effectively reduces energy consumption, prolongs network lifespan, and enhances data collection efficiency when compared to recent research endeavors. © 2014 IEEE.

关键词： Marine applications

Dark energy and matter interacting scenario to relieve H_(0) and S_(8) tensions

学校读者我要写书评

暂无评论

Chinese Physics C 2024年第5期48卷 1-7页

作者：高立场薛社生张鑫 Key Laboratory of Cosmology and Astrophysics(Liaoning Province)&Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Kapteyn Astronomical Institute University of GroningenP.O.Box 8009700 AV Groningenthe Netherlands ICRANet Piazzale della Repubblica10-65122PescaraItaly ICTP-AP University of Chinese Academy of SciencesBeijing 100049China Physics Department Sapienza University of RomeP.le A.Moro 500185RomeItaly INFN Sezione di PerugiaVia A.PascoliI-06123PerugiaItaly Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China

We consider a new cosmological model(calledΛCDM),in which the vacuum energy interacts with matter and radiation,and test this model using the current cosmological *** the CMB+BAO+SN(CBS)dataset to constrain the model,we find that H_(0) and S_(8) tensions are relieved to 2.87σand 2.77σ,***,in this case,theΛCDM model is not favored by the data,compared withΛ*** find that when the H_(0) and S_(8) data are added to the data combination,the situation is significantly *** the CBS+H_(0) case,the model relieves the H_(0) tension to 0.47σ,and the model is favored overΛ*** the CBS+H_(0)+S_(8) case,we obtain a synthetically best situation,in which the H_(0) and S_(8) tensions are relieved to 0.72σand 2.11σ,*** this case,the model is most favored by the ***,this cosmological model can greatly relieve the H_(0) tension and simultaneously effectively alleviate the S_(8) tension.

关键词： dark energy interacting dark energy model the Hubble constant Hubble tension cosmological constraint

Decomposition is All You Need: Single-Objective to Multi-Objective optimization Towards Responsible Artificial General Intelligence

学校读者我要写书评

暂无评论

SSRN

SSRN 2024年

作者： Wendi, Xu Yuemao, Zhao Ming, Zhang College of Energy and Mining Engineering Shandong University of Science and Technology Qingdao266590 China National Frontier Sciences Center for Industrial Intelligence and Systems Optimization Ministry of Education China College of Information Science and Engineering Northeastern University United States Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education China Xinjiang Astronomical Observatory Chinese Academy of Sciences China Key Laboratory for Radio Astronomy Chinese Academy of Sciences Nanjing China University of Chinese Academy of Sciences China Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines Shenyang110819 China

Responsible artificial general intelligence (AGI) is deeply connected with both explainable artificial intelligence and interpretable artificial intelligence. In frontier science of evolutionary transfer optimization (ETO) towards responsible AGI, transfer core (TC) is both explainable and responsible for single-objective to multi-objective optimization (SMO) that can harness comprehensive intelligent models for complex task-solving. From both theoretical and practical sides, we get the work of "HMeets" (this paper) for SMO on TC in both production and logistic systems. In HMeets, TC is further confirmed its role or responsibility for selection pressure, which performs general-purpose problem-solving abilities. We tend to believe that TC or SMO maybe serves as a fundamental concept and common tool like what happens in ResNets, Transformers and WARSHIP (our visual AGI) for wildly applications beyond manufacturing here in the future. © 2024, The Authors. All rights reserved.

关键词： Multiobjective optimization

Eliminating polarization leakage effect for neutral hydrogen intensity mapping with deep learning

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Gao, Li-Yang Li, Yichao Ni, Shulei Zhang, Xin College of Sciences Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

The neutral hydrogen (HI) intensity mapping (IM) survey is regarded as a promising approach for cosmic large-scale structure studies. A major issue for the HI IM survey is to remove the bright foreground contamination. A key to successfully removing the bright foreground is to well control or eliminate the instrumental effects. In this work, we consider the instrumental effects of polarization leakage and use the U-Net approach, a deep learning-based foreground removal technique, to eliminate the polarization leakage effect. The thermal noise is assumed to be a subdominant factor compared with the polarization leakage for future HI IM surveys and ignored in this analysis. In this method, the principal component analysis (PCA) foreground subtraction is used as a preprocessing step for the U-Net foreground subtraction. Our results show that the additional U-Net processing could either remove the foreground residual after the conservative PCA subtraction or compensate for the signal loss caused by the aggressive PCA preprocessing. Finally, we test the robustness of the U-Net foreground subtraction technique and show that it is still reliable in the case of existing constraint error on HI fluctuation amplitude. Copyright © 2022, The Authors. All rights reserved.

关键词： Polarization

Detecting stochastic gravitational wave background from cosmic strings with next-generation detector networks: Component separation based on a multi-source astrophysical foreground noise model

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Wang, Geng-Chen Jin, Hong-Bo Zhang, Xin Liaoning Key Laboratory of Cosmology and Astrophysics College of Sciences Northeastern University Shenyang110819 China Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University Beijing China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China The International Centre for Theoretical Physics Asia-Pacific University of Chinese Academy of Sciences Beijing100190 China MOE Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

Detecting stochastic gravitational wave background (SGWB) from cosmic strings is crucial for unveiling the evolutionary laws of the early universe and validating non-standard cosmological models. This study presents the first systematic evaluation of the detection capabilities of next-generation ground-based gravitational wave detector networks for cosmic strings. By constructing a hybrid signal model incorporating multi-source astrophysical foreground noise, including compact binary coalescences (CBCs) and compact binary hyperbolic encounters (CBHEs), we propose an innovative parameter estimation methodology based on multi-component signal separation. Numerical simulations using one-year observational data reveal three key findings: (1) The CE4020ET network, comprising the Einstein Telescope (ET-10 km) and the Cosmic Explorer (CE-40 km and CE-20 km), achieves nearly one order of magnitude improvement in constraining the cosmic string tension Gµ compared to individual detectors, reaching a relative uncertainty ∆Gµ/Gµ 3.5×10−15 under standard cosmological framework;(2) The network demonstrates enhanced parameter resolution in non-standard cosmological scenarios, providing a novel approach to probe pre-Big Bang Nucleosynthesis cosmic evolution;(3) Enhanced detector sensitivity amplifies CBHE foreground interference in parameter estimation, while precise modeling of such signals could further refine Gµ constraints by 1 − 2 orders of magnitude. This research not only quantifies the detection potential of third-generation detector networks for cosmic string models but also elucidates the intrinsic connection between foreground modeling precision and cosmological parameter estimation accuracy, offering theoretical foundations for optimizing scientific objectives of next-generation gravitational wave observatories. Copyright © 2025, The Authors. All rights reserved.

关键词： Cosmology

An Adaptive Cost-Sensitive Learning and Recursive Denoising Framework for Imbalanced SVM Classification

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Jiang, Lu Wang, Qi Chang, Yuhang Song, Jianing Fu, Haoyue Yang, Xiaochun College of Sciences Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China Software College Northeastern University Shenyang110819 China School of Computer Science and Engineering Northeastern University Shenyang110819 China

Category imbalance is one of the most popular and important issues in the domain of classification. Emotion classification model trained on imbalanced datasets easily leads to unreliable prediction. The traditional machine learning method tends to favor the majority class, which leads to the lack of minority class information in the model. Moreover, most existing models will produce abnormal sensitivity issues or performance degradation. We propose a robust learning algorithm based on adaptive cost-sensitivity and recursive denoising, which is a generalized framework and can be incorporated into most stochastic optimization algorithms. The proposed method uses the dynamic kernel distance optimization model between the sample and the decision boundary, which makes full use of the sample’s prior information. In addition, we also put forward an effective method to filter noise, the main idea of which is to judge the noise by finding the nearest neighbors of the minority class. In order to evaluate the strength of the proposed method, we not only carry out experiments on standard datasets but also apply it to emotional classification problems with different imbalance rates (IR). Experimental results show that the proposed general framework is superior to traditional methods in Accuracy, G-mean, Recall and F1-score. Copyright © 2024, The Authors. All rights reserved.

关键词： Adversarial machine learning

Impacts of gravitational-wave standard siren observations from Einstein Telescope and Cosmic Explorer on weighing neutrinos in interacting dark energy models

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Jin, Shang-Jie Zhu, Rui-Qi Wang, Ling-Feng Li, Hai-Li Zhang, Jing-Fei Zhang, Xin Department of Physics College of Sciences Northeastern University Shenyang110819 China Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang110819 China

Multi-messenger gravitational-wave (GW) observation for binary neutron star merger events could provide a rather useful tool to explore the evolution of the universe. In particular, for the third-generation GW detectors, i.e., the Einstein Telescope (ET) and the Cosmic Explorer (CE), proposed to be built in Europe and the U.S., respectively, lots of GW standard sirens with known redshifts could be obtained, which would exert great impacts on the cosmological parameter estimation. The total neutrino mass could be measured by cosmological observations, but such a measurement is model-dependent and currently only gives an upper limit. In this work, we wish to investigate whether the GW standard sirens observed by ET and CE could help improve the constraint on the neutrino mass, in particular in the interacting dark energy (IDE) models. We find that the GW standard siren observations from ET and CE can only slightly improve the constraint on the neutrino mass in the IDE models, compared to the current limit. The improvements in the IDE models are weaker than those in the standard cosmological model. Although the limit on neutrino mass can only be slightly updated, the constraints on other cosmological parameters can be significantly improved by using the GW observations. Copyright © 2022, The Authors. All rights reserved.

关键词： Gravity waves