检索结果-内蒙古大学图书馆

Signal-to-noise ratio of Raman signal measured by multichannel detectors

Chinese Physics B 2021年第9期30卷 31-44页

作者： Xue-Lu Liu Yu-Chen Leng Miao-Ling Lin Xin Cong Ping-Heng Tan State Key Laboratory of Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China Center of Materials Science and Optoelectronics Engineering&CAS Center of Excellence in Topological Quantum Computation University of Chinese Academy of SciencesBeijing 100049China

Raman spectroscopy has been widely used to characterize the physical properties of two-dimensional materials(2DMs).The signal-to-noise ratio(SNR or S/N ratio)of Raman signal usually serves as an important indicator to evaluate the instrumental performance rather than Raman intensity *** detectors with outstanding sensitivity,rapid acquisition speed and low noise level have been widely equipped in Raman instruments for the measurement of Raman *** this mini-review,we first introduce the recent advances of Raman spectroscopy of *** we take the most commonly used CCD detector and IGA array detector as examples to overview the various noise sources in Raman measurements and analyze their potential influences on SNR of Raman signal in *** overview can contribute to a better understanding on the SNR of Raman signal and the performance of multichannel detector for numerous researchers and instrumental design for industry,as well as offer practical strategies for improving spectral quality in routine measurement.

关键词： multichannel detectors signal-to-noise ratio dark noise shot noise

来源：评论

学校读者我要写书评

暂无评论

Designing a minimal Landau model to stabilize desired quasicrystals

引用

Physical Review Research 2025年第2期7卷 023021-023021页

作者： Wei Si Shifeng Li Pingwen Zhang An-Chang Shi Kai Jiang School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan 411105 China School of Mathematics and Statistics Wuhan University Wuhan 430072 China LMAM CAPT and School of Mathematical Sciences Peking University Beijing 100871 China Department of Physics and Astronomy McMaster University Hamilton L8S 4M1 Canada

Interparticle interactions with multiple length scales play a pivotal role in the formation and stability of quasicrystals. Choosing a minimal set of length scales to stabilize a given quasicrystal is a challenging problem. To address this challenge, we propose a symmetry-preserving screening method (SPSM) to design a Landau theory with a minimal number of length scales—referred to as the minimal Landau theory—that includes only the essential length scales necessary to stabilize quasicrystals. Based on a generalized multiple-length-scale Landau theory, SPSM first evaluates various spectral configurations of candidate structures under a hard constraint. It then identifies the configuration with the lowest free energy. Using this optimal configuration, SPSM calculates phase diagrams to explore the thermodynamic stability of desired quasicrystals. SPSM can design a minimal Landau theory capable of stabilizing the desired quasicrystals by incrementally increasing the number of length scales. Our application of SPSM has not only confirmed known behaviors in 10- and 12-fold quasicrystals but also led to a significant prediction that quasicrystals with 8-, 14-, 16-, and 18-fold symmetry could be stable within three-length-scale Landau models.

关键词： Quasicrystals

来源：评论

学校读者我要写书评

暂无评论

Amplitude Expansion Phase Field Crystal (APFC) Modeling based Efficient Dislocation simulations using Fourier Pseudospectral Method

arXiv

引用

arXiv 2024年

作者： Wei, Xinyi Wang, Yangshuai Jiang, Kai Zhang, Lei School of Mathematical Sciences Institute of Natural Sciences and MOE-LSC Shanghai Jiao Tong University Shanghai200240 China Department of Mathematics Faculty of Science National University of Singapore 10 Lower Kent Ridge Road Singapore Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

Crystalline defects play a critical role in determining the properties of crystalline solids, underscoring the need for accurate computational methods to study them. Lattice deformation in dislocation simulations, which involves changes in atomic positions, can be described either microscopically by specific atomic configurations or macroscopically by continuum elasticity, each with inherent limitations. The complex amplitude expansion of the phase field crystal (APFC) model provides a mesoscopic approach that bridges these scales. In this paper, we introduce a Fourier pseudospectral method for efficiently solving the APFC model in the context of crystalline defect simulations. This study marks the first application of the Fourier pseudospectral method to the APFC model. The method fully exploits the system’s periodicity and facilitates the implementation of periodic boundary conditions, thanks to its high accuracy and computational efficiency. Numerical experiments conducted on two-dimensional triangular lattices and three-dimensional body-centered cubic lattices for edge dislocation geometry optimization have produced strain field images that align well with by continuum elasticity predictions. The findings demonstrate the potential of the APFC model to accurately capture the complex strain fields associated with dislocations at the mesoscopic scales, a key step toward modeling more intricate crystalline defect structures and dynamics. © 2024, CC BY.

关键词： Edge dislocations

来源：评论

学校读者我要写书评

暂无评论

An Accurate, Robust and Efficient Convection-Pressure Flux Splitting Scheme for Compressible Euler Flows

SSRN

引用

SSRN 2023年

作者： Hu, Lijun Tan, Shide Li, Long Yuan, Haizhuan School of Mathematics and Statistics Hengyang Normal University Hunan Hengyang421002 China School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan Xiangtan411105 China

The Roe's flux difference splitting scheme has been a popular shock-capturing method in computational fluid dynamics due to its high resolution for various discontinuities. However, it fails to satisfy the entropy condition and will encounter different forms of instability while calculating shock wave problems, such as the occurrence of post-shock oscillation in simulations of slowly moving shock waves and the carbuncle phenomenon in simulations of multidimensional strong shock waves. A simple flux difference splitting scheme based on the idea of convection-pressure splitting is proposed in the present work. The flux of the 3D Euler equations is split into the convection part and the pressure part with application of the Toro-Vazquez splitting procedure. The pressure subsystem has a complete set of linearly independent eigenvectors and thus it is solved by the conventional flux difference splitting method which is based on the eigenstructure of the system. The weakly hyperbolic convection subsystem, however, does not have a complete set of linearly independent eigenvectors and it is solved by the flux difference splitting scheme based on the generalized eigenvectors. In order to improve the resolution for contact discontinuities, a strategy combining the THINC reconstruction with the BVD algorithm is employed to minimize the density difference in the numerical dissipation term of the convection flux. Results of stability analysis show that the proposed scheme can effectively attenuate the numerical error and thus suppress the multidimensional shock instability. A comprehensive range of numerical simulations for classical 1D, 2D and 3D benchmark test problems demonstrate that the proposed scheme satisfies the entropy condition and positivity-preserving, possesses high resolution for contact discontinuities, and, more importantly, is free from the post-shock oscillation of slowly moving shock waves and the instability of multidimensional strong shock waves. © 2023, Th

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

A Sparse Optical Flow Method for Camera Tracking under Fisheye Camera Models

A Sparse Optical Flow Method for Camera Tracking under Fishe...

引用

Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Zuoming Zhang Xin Wang College of Computer Science and Technology Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education College of Computer Science and Technology Jilin China

In computer image processing, optical flow is a classic task used to track the motion of pixels. In the field of robotics, methods like SLAM extensively employ sparse optical flow as a substitute for time-consuming feature point matching methods, enabling rapid and stable camera tracking. However, the widespread use of fisheye cameras introduces distortion issues in practical applications. Traditional sparse optical flow struggles to accurately track pixel positions in such scenarios, affecting the precision of camera pose tracking. Therefore, we introduce a sparse optical flow method designed for fisheye camera models, which correctly utilizes prior information obtained during camera tracking to enhance the accuracy of sparse optical flow. Finally, we propose a scheme for constructing a semi-distortion lookup table to accelerate distortion operations and reduce memory requirements. We conducted extensive testing on simulated datasets with various camera motion scenarios, and the experimental results demonstrate that our method outperforms OpenCV in terms of accuracy and versatility.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Learning Interpretable Network Dynamics via Universal Neural Symbolic Regression

arXiv

引用

arXiv 2024年

作者： Hu, Jiao Cui, Jiaxu Yang, Bo College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

Discovering governing equations of complex network dynamics is a fundamental challenge in contemporary science with rich data, which can uncover the mysterious patterns and mechanisms of the formation and evolution of complex phenomena in various fields and assist in decision-making. In this work, we develop a universal computational tool that can automatically, efficiently, and accurately learn the symbolic changing patterns of complex system states by combining the excellent fitting ability from deep learning and the equation inference ability from pre-trained symbolic regression. We conduct intensive experimental verifications on more than ten representative scenarios from physics, biochemistry, ecology, epidemiology, etc. Results demonstrate the outstanding effectiveness and efficiency of our tool by comparing with the state-of-the-art symbolic regression techniques for network dynamics. The application to real-world systems including global epidemic transmission and pedestrian movements has verified its practical applicability. We believe that our tool can serve as a universal solution to dispel the fog of hidden mechanisms of changes in complex phenomena, advance toward interpretability, and inspire more scientific discoveries. Copyright © 2024, The Authors. All rights reserved.

关键词： Economic and social effects

来源：评论

学校读者我要写书评

暂无评论

Nano-sized Ag rather than single-atom Ag determines CO oxidation activity and stability

引用

Nano Research 2022年第1期15卷 452-456页

作者： Fei Wang Zhao Li Honghong Wang Min Chen Changbin Zhang Ping Ning Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Faculty of Environmental Science and Engineering Kunming University of Science and TechnologyKunming 650500China Center for Excellence in Regional Atmospheric Environment Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China University of Chinese Academy of Sciences Beijing 100049China

Single-atom catalysis recently attracts great attentions,however,whether single atom or their nanoparticle(NP)has the advantage in its intrinsic activity remains under heated ***/Al_(2)O_(3) is a widely used catalyst for many catalytic reactions,while the effect of Ag particle size on the actity is seldom investigated due to the great difficulty in synthesizing single atom Ag and Ag clusters/particles with different ***,we firstly prepared an atomically dispersed Ag/Al_(2)O_(3) catalyst using a nano-sized y-Al_(2)O_(3) as the support,subsequently obtained a series of Ag/Al_(2)O_(3) catalysts with different Ag particle sizes by H_(2) reducing single-atom Ag/Al_(2)O_(3) catalyst at various *** Ag/Al_(2)O_(3) treated at 600℃demonstrated superior CO oxidation performance over single-atom Ag/Al_(2)O_(3) and the Ag/Al_(2)O_(3) treated at 400 and 800℃.Based on experimental data and dpnsity functional theory(DFT)calculation results,we reveal that the larger Ag°particle is beneficial to oxygen activation and improves the valence stability during oxidation reaction,while the aggregation of Ag°particle also accordingly decreases the concentration of surface active sites,hence,there is an optimum Ag0 particle *** findings clearly confirm that Ag0nanoparticle has the advantage over single-atom Ag species in its intrinsic activity for CO oxidation.

关键词： Reduction after anchoring Ag clusters single atom catalyst CO oxidation

来源：评论

学校读者我要写书评

暂无评论

An A-D-A′-D-A type unfused nonfullerene acceptor for organic solar cells with approaching 14%efficiency

引用

science China Chemistry 2021年第2期64卷 228-231页

作者： Xingzheng Liu Yanan Wei Xin Zhang Linqing Qin Zhixiang Wei Hui Huang College of Materials Science and Opto-Electronic Technology Center of Materials Science and Optoelectronics EngineeringCAS Center for Excellence in Topological Quantum ComputationCAS Key Laboratory of Vacuum PhysicUniversity of Chinese Academy of SciencesBeijing 100049China CAS Key Laboratory of Nanosystem and Hierarchical Fabrication CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing 100190China

In recent years,power conversion efficiency(PCE)of organic solar cells(OSCs)has made significant improvement.A large number of studies were reported to achieve high PCEs through exploring new active layer materials,especially the high efficiency fused ring acceptors(FRAs).Compared with FRAs,another type of so-called unfused-ring acceptors(UFAs),possessing some advantages such as simple synthesis and low cost,have attracted a lot of ***,a new UFA BTzO-4F,incorporating with a benzotriazole moiety and S···O intramolecular noncovalent interactions,has been successfully *** photovoltaic device based on PBDB-T:BTzO-4F achieved a record PCE of 13.8%for UFAs,which indicates that introducing the benzotriazole moiety is an effective strategy for high quality ***,these findings of this work demonstrate the great potential of UFAs for high performance OSCs.

关键词： organic solar cells unfused nonfullerene acceptor benzotriazole moiety

来源：评论

学校读者我要写书评

暂无评论

OCET: One-Dimensional Convolution Embedding Transformer for Stock Trend Prediction 1

引用

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Yang, Peng Fu, Lang Zhang, Jian Li, Guiying Department of Statistics and Data Science Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen518055 China Shenzhen Securities Information Co. Ltd. Shenzhen China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Due to the strong data fitting ability of deep learning, the use of deep learning for quantitative trading has gradually sprung up in recent years. As a classical problem of quantitative trading, Stock Trend Prediction (STP) mainly predicts the movement of stock price in the future through the historical price information to better guide quantitative trading. In recent years, some deep learning work has made great progress in STP by effectively grasping long-term timing information. However, as a kind of real-time series data, short-term timing information is also very important, because stock trading is high-frequency and price fluctuates violently. And with the popularity of Transformer, there is a lack of an effective combination of feature extraction and Transformer in STP tasks. To make better use of short term information, we propose One-dimensional Convolution Embedding (OCE). Simultaneously, we introduce effective feature extraction with Transformer into STP problem to extract feature information and capture long-term timing information. By combining OCE and Transformer organically, we propose a noval STP prediction model, One-dimensional Convolution Embedding Transformer (OCET), to capture long-term and short-term time series information. Finally, OCET achieves a highest accuracy up to 0.927 in public benchmark FI-2010 When reasoning speed is twice that of SOTA models and a highest accuracy of 0.426 in HKGSAS-2020. Empirical results on these two datasets show that our OCET is significantly superior than other algorithms in STP tasks. Code are available at https://***/langgege-cqu/OCET. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

BA-LORA: BIAS-ALLEVIATING LOW-RANK ADAPTATION TO MITIGATE CATASTROPHIC INHERITANCE IN LARGE LANGUAGE MODELS

arXiv

引用

arXiv 2024年

作者： Chang, Yupeng Chang, Yi Wu, Yuan School of Artificial Intelligence Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University China International Center of Future Science Jilin University China

Large language models (LLMs) have demonstrated remarkable proficiency across various natural language processing (NLP) tasks. However, adapting LLMs to downstream applications requires computationally intensive and memory-demanding fine-tuning procedures. To alleviate these burdens, parameter-efficient fine-tuning (PEFT) techniques have emerged as a promising approach to tailor LLMs with minimal computational overhead. While PEFT methods offer substantial advantages, they do not fully address the pervasive issue of bias propagation from pre-training data. This work introduces Bias-Alleviating Low-Rank Adaptation (BA-LoRA), a novel PEFT method designed to counteract bias inheritance. BA-LoRA incorporates three distinct regularization terms: (1) a consistency regularizer, (2) a diversity regularizer, and (3) a singular value decomposition regularizer. These regularizers aim to enhance the models’ consistency, diversity, and generalization capabilities during fine-tuning. We conduct extensive experiments on natural language understanding (NLU) and natural language generation (NLG) tasks using prominent LLMs such as LLaMA, Mistral, and Gemma. The results demonstrate that BA-LoRA outperforms LoRA and its state-of-the-art variants. Moreover, the extended experiments demonstrate that our method effectively mitigates the adverse effects of pre-training bias, leading to more reliable and robust model outputs. The code is available at https://***/cyp-jlu-ai/BA-LoRA. Copyright © 2024, The Authors. All rights reserved.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：