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Circular Polarization of Simulated Images of Black Holes

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arXiv 2024年

作者： Joshi, Abhishek V. Prather, Ben S. Chan, Chi-Kwan Wielgus, Maciek Gammie, Charles F. Department of Physics University of Illinois 1110 West Green Street UrbanaIL61801 United States Illinois Center for Advanced Study of the Universe 1110 West Green Street UrbanaIL61801 United States Los Alamos National Lab Los AlamosNM87545 United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Department of Astronomy University of Illinois 1002 West Green Street UrbanaIL61801 United States National Center for Supercomputing Applications 605 East Springfield Avenue ChampaignIL61820 United States

Models of the resolved Event Horizon Telescope (EHT) sources Sgr A* and M87* are constrained by observations at multiple wavelengths, resolutions, polarizations, and time cadences. In this paper we compare unresolved circular polarization (CP) measurements to a library of models, where each model is characterized by a distribution of CP over time. In the library we vary the spin of the black hole, the magnetic field strength at the horizon (i.e. both SANE and MAD models), the observer inclination, a parameter for the maximum ion-electron temperature ratio assuming a thermal plasma, and the direction of the magnetic field dipole moment. We find that ALMA observations of Sgr A* are inconsistent with all edge-on (i = 90◦) models. Restricting attention to the magnetically arrested disk (MAD) models favored by earlier EHT studies of Sgr A*, we find that only models with magnetic dipole moment pointing away from the observer are consistent with ALMA data. We also note that in 26 of the 27 passing MAD models the accretion flow rotates clockwise on the sky. We provide a table of the mean and standard deviation of the CP distributions for all model parameters along with their trends. © 2024, CC BY.

关键词： Stars

Correction to: Finite dimensional state representation of physiologically structured populations

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Journal of mathematical biology 2020年第3期81卷 905-906页

作者： Odo Diekmann Mats Gyllenberg Johan A J Metz Department of Mathematics University of Utrecht P.O. Box 80010 3508 TA Utrecht The Netherlands. Department of Mathematics and Statistics University of Helsinki P.O. Box 68 00014 Helsinki Finland. mats.gyllenberg@helsinki.fi. Mathematical Institute and Institute of Biology Leiden University 2333 CA Leiden The Netherlands. Evolution and Ecology Program International Institute of Applied Systems Analysis 2361 Laxenburg Austria.

In the original publication of the article, the Subsection 2.1.2 was published incorrectly.

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Limiting regimes of turbulent horizontal convection. Part I: Intermediate and low Prandtl numbers

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arXiv 2020年

作者： Passaggia, Pierre-Yves Scotti, Alberto White, Brian L. University of Orléans INSA-CVL PRISME EA 4229 Orléans45072 France Carolina Center for Interdisciplinary Applied Mathematics Dept. of Mathematics University of North Carolina Chapel HillNC27599 United States Department of Marine Sciences University of North Carolina Chapel HillNC27599 United States Department of Marine Sciences University of North Carolina Chapel HillNC27599 United States

We report the existence of two new limiting turbulent regimes in horizontal convection (HC) using direct numerical simulations at intermediate to low Prandtl numbers. The flow driven by a horizontal gradient along a horizontal surface, perpendicular to the acceleration of gravity is shown to transition to turbulence in the plume and the core, modifying the rate of heat and momentum transport. These transitions set a sequence of scaling laws blending the theoretical arguments from both the Shishkina, Grossmann & Lohse (SGL) theory [38] with the Hughes, Griffiths & Mullarney (HGM) regime [13]. These results embed the HGM model in the SGL theory, agree, and extend the known regime diagram of horizontal convection [12] at high Rayleigh numbers. In particular, we show that HC and Rayleigh-Bénard share similar turbulent characteristics at low-Prandtl numbers, where HC is shown for the first time to be ruled by its core dynamics and turbulent boundary layers. This new scenario confirms that fully turbulent HC enhances the transport of heat and momentum with respect to previously reported regimes at high Rayleigh numbers. This work provides new insights on the applicability of horizontal convection for geophysical flows such as overturning circulations found in the atmosphere, the oceans, and flows near the earth’s inner core. Copyright © 2020, The Authors. All rights reserved.

关键词： Boundary layers

DeePMD-kit v2: A software package for Deep Potential models

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

Enhanced MPPT efficiency in photovoltaic systems with a new artificial protozoa optimizer method

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Journal of Engineering Research

Journal of Engineering Research 2025年

作者： Abdelkarim Ballouti Mohamed Chouiekh Hatim Ameziane Alia Zakriti Youness El Mourabit Hicham Karmouni S.S. Askar Mohamed Abouhawwash Abdelmalek Essaadi University National School of Applied Sciences Tetouan Morocco Science and Technology for the Engineer Laboratory (LaSTI) National School of Applied Sciences (ENSA) Khouribga Morocco Sultan Moulay Slimane University National School of Applied Sciences Cadi Ayyad University Marrakech Morocco Department of Statistics and Operations Research College of Science King Saud University P.O. Box 2455 Riyadh 11451 Saudi Arabia Department of Computational Mathematics Science and Engineering (CMSE) College of Engineering Michigan State University East Lansing MI 48824 USA Department of Industrial and Systems Engineering Interdisciplinary Research Center of Smart Mobility and Logistics (IRC-SML) King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia

Renewable energy systems have become indispensable in the pursuit of sustainable development, with photovoltaic (PV) technologies emerging as one of the most accessible and scalable solutions. In this context, the present work introduces a new metaheuristic optimization algorithm, known as the Artificial Protozoa Optimizer (APO), which is tailored to improve maximum power point tracking (MPPT) in PV *** to established techniques such as Perturb and Observe (P&O), Particle Swarm Optimization (PSO), and Fuzzy Logic Control (FLC), APO has shown notable improvements in terms of efficiency, reaching values as high as 99 % in simulation *** algorithm is specifically designed to minimize power fluctuations and energy losses, which translates into enhanced system stability and energy *** extensive simulations, APO has demonstrated its capacity to overcome common MPPT challenges, such as slow convergence, sensitivity to rapid environmental variations, and oscillations near the optimal *** simulated setup includes a buck converter interfaced with a battery, enabling an effective energy storage mechanism. All scenarios were tested using MATLAB/Simulink, under both uniform and non-uniform irradiation profiles to assess the algorithm’s robustness in dynamic conditions.

关键词： Photovoltaic-generator MPPT DC/DC Converter Artificial protozoa optimizer Particle swarm optimization Fuzzy logic controller Perturb and observe Partial shading

Distributing pairs of vertices on Hamiltonian cycles

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Science China mathematics 2018年第5期61卷 955-972页

作者： Weihua He Hao Li Qiang Sun Department of Applied Mathematics Guangdong University of Technology Laboratoire de Recherche en Informatique CNRS-Université Paris-Sud Institute for Interdisciplinary Research Jianghan University School of Mathematical Science Yangzhou University

Let G be a graph of order n with minimum degree δ(G)≥n/2+1. Faudree and Li(2012) conjectured that for any pair of vertices x and y in G and any integer 2≤k≤n/2, there exists a Hamiltonian cycle C such that the distance between x and y on C is k. In this paper, we prove that this conjecture is true for graphs of sufficiently large order. The main tools of our proof are the regularity lemma of Szemer′edi and the blow-up lemma of Koml′os et al.(1997).

关键词： Hamiltonian cycle Faudree-Li conjecture regularity lemma blow-up lemma

The split common fixed point problem for infinite families of demicontractive mappings

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Fixed Point Theory and Applications 2018年第1期2018卷 1-21页

作者： Hanjing, Adisak Suantai, Suthep Ph.D. Degree Program in Mathematics Faculty of Science Chiang Mai University Chiang Mai Thailand Center of Excellence in Mathematics and Applied Mathematics Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai Thailand Center of Excellence in Mathematics CHE Bangkok Thailand

In this paper, we propose a new algorithm for solving the split common fixed point problem for infinite families of demicontractive mappings. Strong convergence of the proposed method is established under suitable control conditions. We apply our main results to study the split common null point problem, the split variational inequality problem, and the split equilibrium problem in the framework of a real Hilbert space. A numerical example supporting our main result is also given. © 2018, The Author(s).

关键词： Demicontractive mappings Equilibrium problem Fixed point problem Null point problem Variational inequality problem

Fuzzy sentiment analysis using convolutional neural network

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AIP Conference Proceedings 2021年第1期2329卷

作者： Sugiyarto Joko Eliyanto Nursyiva Irsalinda Meita Fitrianawati 1Mathematics Department Faculty of Applied Science and Technology Universitas Ahmad Dahlan Indonesia 2Mathematics Education Department Postgraduate Program Universitas Ahmad Dahlan Indonesia 3Elementary School Teacher Study Program Faculty of Teacher Training and Education Universitas Ahmad Dahlan Indonesia

Sentiment analysis is one part of natural language processing. Sentiment analysis can be done by lexicon based, or machine learning based. Sentiment analysis based on machine learning has advantage of dynamism to meet with new language datasets or new vocabulary. Sentiment analysis seeks to understand the sentiments contained in a sentence. A sentence can be positive, neutral or negative, based on its sentiments. A sentence can have positive, neutral or negative sentiments. However, the fact is each sentence does not always have positive, negative or neutral sentiment clearly. We try to develop a sentiment analysis method that can show the sentiment degree of a sentence. Fuzzy sentiment analysis using convolutional neural network are introduced in this paper to produce more accurate sentiment analysis results. Convolutional neural networks are a popular machine learning method for sentiment analysis. The concept of fuzzy sets is used to express the sentiment degree of a sentence. Euclidean distance analysis to determine the proximity of two vectors is used to show that this method is better than the standard method. The method we propose successfully produces a value that indicates the degree of sentiment of a sentence. Comparison of the euclid distance between the results of the standard sentiment analysis and our method shows that the results of the fuzzy sentiment analysis using convolutional neural network have a distance that is relatively close to the true sentiment value. Fuzzy convolutional neural network analysis sentiment is proven to be able to produce better and smoother sentiment analysis results than standard methods.

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Convergence acceleration of ensemble Kalman inversion in nonlinear settings

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arXiv 2019年

作者： Chada, Neil K. Tong, Xin T. Applied Mathematics and Computational Science Program King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Department of Mathematics National University of Singapore 119077 Singapore

Many data-science problems can be formulated as an inverse problem, where the parameters are estimated by minimizing a proper loss function. When complicated black-box models are involved, derivative-free optimization tools are often needed. The ensemble Kalman filter (EnKF) is a particle-based derivative-free Bayesian algorithm originally designed for data assimilation. Recently, it has been applied to inverse problems for computational efficiency. The resulting algorithm, known as ensemble Kalman inversion (EKI), involves running an ensemble of particles with EnKF update rules so they can converge to a minimizer. In this article, we investigate EKI convergence in general nonlinear settings. To improve convergence speed and stability, we consider applying EKI with non-constant step-sizes and covariance inflation. We prove that EKI can hit critical points with finite steps in non-convex settings. We further prove that EKI converges to the global minimizer polynomially fast if the loss function is strongly convex. We verify the analysis presented with numerical experiments on two inverse problems. Copyright © 2019, The Authors. All rights reserved.

关键词： Inverse problems